ASSESSMENT OF MARKETING NODES AND STRUCTURE FOR … · Oluwaseun, Olaoluwa and Olutosin for their...

ASSESSMENT OF MARKETING NODES AND STRUCTURE FOR

FISH TRADE ALONG NIGERIA-CAMEROON-CHAD BORDER

BY

OJO, DEBORAH OLUFUNKE

MATRICULATION NUMBER: 187167

A PROJECT REPORT SUBMITTED IN PARTIAL FULFILMENT

FOR THE AWARD OF MASTER OF SCIENCE DEGREE IN THE

DEPARTMENT OF AQUACULTURE AND FISHERIES

MANAGEMENT, FACULTY OF AGRICULTURE AND FORESTRY,

UNIVERSITY OF IBADAN

OCTOBER, 2016

ii

ABSTRACT

Better integration of intra-regional fish trade into nation-state policy agenda is reported as a tool

for improving food and nutritional security; and poverty reduction in Africa. However, critical

information on market structure and value of intra-regional fish trade needed to ensure food

security in the West African corridor are very limited. This study therefore investigated the

marketing nodes and structure for fish trade along Nigeria-Cameroon-Chad border.

Akwa Ibom, Cross River, Benue, Taraba, Adamawa and Borno States along Nigeria-Cameroon-

Chad border were selected for this study. Snowball sampling technique was employed for data

collection. The selection of respondents was based on their involvement in fishing and fish

marketing activities and their acceptance to provide the primary data for this research. Structured

questionnaires were administered to 900 respondents comprising 300 producers, 300 processors

and 300 marketers. The questionnaire was used to obtain data on socio-economic characteristics,

marketing operations, market structure, fish distribution and cross border trade in the study area.

Data were analysed using descriptive statistics, budgetary analysis, Herfindahl index, Gini

coefficient, stochastic production frontier model, linear regression analysis and ANOVA at α0.05.

The results of the study revealed that the production node was dominated by males 93.3%, while

the processing (55.0%) and marketing (56.0%) nodes were dominated by females. Majority of the

producers (34.3%), processors (34.0%) and marketers (39.7%) were within the age bracket of 41-

50 years. Majority of the respondents were married; 87.7%, 88.3% and 85.3% and secondary

school leavers; 31.7%, 40.7% and 43.7% and they Majority of the respondents were members of

marketers’ associations; 51.3%, 65.7% and 67.7% with marketing experiences (> 15 years for

producers, 11-15 years for processors and 6-10 years for marketers). The empirical findings on

Gini coefficients for actors in fresh fish production node (0.63, 0.53) and marketing node (0.43,

0.43); smoked fish processing node (0.68) and marketing node (0.46, 0.39); dried fish processing

node (0.69) and marketing node (0.51, 0.34) and frozen fish marketing node (0.36, 0.25) revealed

an imperfect competitive market structure. Herfindahl index was highest for fresh (0.72), smoked

(0.80) and dried (0.99) fish markets in Borno, Cross River and Adamawa States, respectively and

frozen (1.00) fish markets in Akwa Ibom, Cross River and Borno States. Linear regression

coefficient was positive in majority of the fish markets assessed. Processing node had the highest

gross margin (₦371559.91±282965.56) and marketing margin (₦405394.09±392255.64), and

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marketing node had the highest marketing efficiency of 87.69±84.86. Fresh fish

(564.13±552.27kg) was the highest volume of fish sold in intra-State marketing. The bulk of inter-

State and intra-regional inflow and outflow trade came from the quantity of fresh

(1250.64±703.53kg and 1719.44±638.63kg, respectively) and dried (2098.00±306.88kg and

2205.11±987.43kg, respectively) fish products traded.

The processing node is the most profitable and the marketing node is the most efficient of the fish

marketing nodes identified and the marketing participants in the various nodes exhibited partial

inequality and equality in the share of their monthly revenue. Hence, people should be encouraged

to go into fish marketing as a source of livelihood being an efficient business venture.

Key words: Marketing Nodes, Fish Trade, Profitability, Gini coefficient and Herfindahl index.

iv

DEDICATION

This project is dedicated to God Almighty for His endless love and favour upon my life. I will

forever adore Him.

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ACKNOWLEDGEMENTS

My utmost and heart-felt appreciation goes to God Almighty, the Alpha and Omega for helping

me ‘take the leap of faith’ to commence and complete this programme. He has been forever

faithful, His love does not fail and so I give Him all the glory, honour and adoration.

My profound and sincere gratitude goes to WorldFish Centre, New Partnership for Africa’s

Development (NEPAD) and African Union Inter-African Bureau for Animal Resources (AU-

IBAR), for sponsoring this research.

My heartfelt gratitude goes to my amiable Head of Department and supervisor Prof. Emmanuel

Kolawole Ajani for giving me the opportunity to be a part of this research. Words are hardly

enough to acknowledge his endurance, understanding and commitment to this research. His

intellectual and technical guidance has aided the completion of this work. I am grateful sir and

God bless you. Special thanks to Professors A.E. Falaye, B.O. Omitoyin and O.B. Oyesola for

their fatherly guidance, patience and support throughout the period of this research. Thank you

and God bless you sirs. I am grateful to Professors Adekoya, T. Fregene, Drs. S.A. Omitoyin, and

O. Oyebola for their immense contributions toward the success of this research. I also thank my

other lecturers and non-academic staff of the Department of Aquaculture and Fisheries

Management, University of Ibadan for their collaborative guidance and endless efforts towards my

academic pursuit. I also acknowledge with thanks the field officers in the State and Federal

Department of Fisheries for their help and support in the field survey of this research. God bless

you all.

I have the greatest pleasure of honouring my parents Mr. M.O. and Mrs. T.A Ojo and my siblings

Oluwaseun, Olaoluwa and Olutosin for their nurture, encouraging love, care, prayers and financial

support. God bless you all richly and make you enjoy the reward of your labour in good health. I

love you all to the moon and back. I specially thank Dr. P.E. Ndimele for his encouragements and

academic mentoring.

I thank my esteemed friends whose efforts went a long way towards the completion of this project;

not limited to Busayo, Edowaye, Deborah, Jennifer, Ibukun, Katherine and Bisoye.

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CERTIFICATION

I certify that this work was carried out by OJO, DEBORAH OLUFUNKE in the Department of

Aquaculture and Fisheries Management, Faculty of Agriculture and Forestry, University of

Ibadan, Ibadan, Oyo State, Nigeria.

______________________ _______________________

Supervisor Date

Professor E.K. Ajani

Department of Aquaculture and Fisheries Management,

University of Ibadan.

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TABLE OF CONTENTS

TITLE PAGE

Abstract ii

Dedication iv

Acknowledgement v

Certification vi

Table of Contents vii

List of Tables xi

List of Figures xx

List of Plates xxii

List of Appendices xxiii

List of Acronyms xxiv

CHAPTER ONE

1.0 Introduction 1

1.1 Background of Study 1

1.2 Justification of Study 2

1.3 General Objective 4

1.4 Specific Objectives 4

1.5 Hypotheses 4

CHAPTER TWO

2.0 Literature Review 5

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2.1 Theoretical Framework 5

2.2 Nutritional Benefits of Fish 8

2.3 The Fishery Sector in Nigeria 9

2.4 Fish Production in Nigeria 10

2.5 Demand and Supply of Fish in Nigeria 14

2.6 Fish Consumption in Nigeria 16

2.7 Relevance of Fisheries to Nigerian Economy 18

2.8 Nigeria and Her Borders 19

2.9 Fish Trade 20

2.10 Informal Cross Border Trade 28

2.11 Fish Marketing System 29

2.12 Fisheries Value Chain 30

2.13 Fish Marketing Nodes 31

2.14 Fish Marketing Channel 33

2.15 Fish Preservation, Processing and Packaging 35

2.16 Theoretical Market Models 36

2.17 Analysing Fish Market Structure 37

2.18 Pricing 40

2.19 Analysis on Costs and Earnings 41

2.20 Market Integration 41

2.21 Fish Marketing Margin 42

2.22 Marketing Efficiency 42

2.23 Conceptual Framework 43

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CHAPTER THREE

3.0 Methodology 45

3.1 Study Area 45

3.2 Data Source 47

3.3 Sampling Procedure and Sample Size 47

3.4 Questionnaire Design 49

3.5 Measurement of Variables 50

3.6 Data Analysis 51

3.7 Test of Hypothesis 54

CHAPTER FOUR

4.0 Results 57

4.1 Socio-economic characteristics of respondents in the marketing nodes 57

4.2 Socio-economic characteristics of respondents across the geopolitical zones 66

4.3 Socio-economic characteristics of respondents in each of the sampled State 70

4.4 Marketing Nodes 80

4.5 Profile of fish species produced and traded 80

4.6 Analysis of fish market structure 86

4.7 Quantities, Costs, Profitability Indices and Marketing Efficiency of

Fish Products 135

4.8 Stochastic Production Frontier Model and Technical Inefficiency 157

4.9 Trade Flow of Fish Products 163

4.10 Trade Flow (Inflow) of fish products according to States along Nigeria-

Cameroon-Chad border 191

x

4.11 Trade Flow (Outflow) of fish products according to States along Nigeria-


CHAPTER FIVE

5.0 Discussions 228

5.1 Socio-economic characteristics of respondents across the marketing nodes 228

5.2 Socio-economic characteristics of respondents across the geopolitical zones 232

5.3 Socio-economic characteristics of fish marketing actors in each of the

sampled State 235

5.4 Marketing Nodes 238

5.5 Profile of fish traded in the study area 239

5.6 Fish market structure 239

5.7 Quantities, Costs, Profitability Indices and Marketing Efficiency of

Fish Products 249

5.8 Stochastic Production Frontier Model and Technical Inefficiency 253

5.9 Trade Flow of Fish Products 253

5.10 Pattern of fish trade 254

5.11 Test of Hypotheses 255

CHAPTER SIX

6.0 Summary, Conclusion and Recommendations 258

REFERENCES 261

APPENDICES 276

xi

LIST OF TABLES

TITLE PAGE

Table 2.1: Major Inland water resources of Nigeria 12

Table 2.2: Nigeria Fish Production in tonnes by sectors (2000-2013) 15

Table 2.3: Nigeria fish demand- supply matrix, 1997-2014 17

Table 4.1: Socio-economic characteristics of respondents in the marketing nodes 58

Table 4.2: Socio-economic characteristics of the respondents across the

Geopolitical Zones 68

Table 4.3a: Socio-economic characteristics of the respondents in the States along

Nigeria-Cameroon-Chad border 71

Table 4.3b: Socio-economic characteristics of the respondents across the

sampled States (continued) 72

Table 4.4: Profile of fish species produced and traded in the study area 84

Table 4.4 cont’d: Profile of fish species produced and traded in the study area 85

Table 4.5: Distribution of total monthly revenue of fresh fish Producers (Culture)

in Nigeria-Cameroon-Chad border region 93

Table 4.6: Distribution of total monthly revenue of fresh fish Producers (Capture)


Table 4.7: Distribution of total monthly revenue of fresh fish Wholesalers


Table 4.8: Distribution of total monthly revenue of fresh fish Retailers


Table 4.9: Distribution of total monthly revenue of smoked fish Processors


Table 4.10: Distribution of total monthly revenue of smoked fish Wholesalers

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Table 4.11: Distribution of total monthly revenue of smoked fish Retailers


Table 4.12: Distribution of total monthly revenue of dried fish Processors


Table 4.13: Distribution of total monthly revenue of dried fish Wholesalers


Table 4.14: Distribution of total monthly revenue of dried fish Retailers


Table 4.15: Distribution of total monthly revenue of frozen fish Wholesalers


Table 4.16: Distribution of total monthly revenue of frozen fish Retailers


Table 4.17: Computation of Gini-coefficient of fresh fish markets along


Table 4.18: Computation of Gini-coefficient of smoked fish markets along


Table 4.19: Computation of Gini-coefficient of dried fish markets along


Table 4.20: Computation of Gini-coefficient of frozen fish markets along


Table 4.21: Computations of Herfindahl index for fresh fish markets


Table 4.22: Computations of Herfindahl index for smoked fish markets


Table 4.23: Computations of Herfindahl index for dried fish markets


xiii

Table 4.24: Computations of Herfindahl index for frozen fish markets


Table 4.25: Herfindahl index of the forms of fish marketed in the States

along Nigeria-Cameroon-Chad border 122

Table 4.26: Linear regression estimates showing the relationship between

quantities sold (kg) and total marketing cost (₦) of major forms

of fish marketed in Akwa Ibom State 129


quantities sold (kg) and total marketing cost (₦) of the forms of

fish marketed in Cross River State 130



fish marketed in Benue State 132



fish marketed in Taraba State 133



fish marketed in Adamawa State 134


quantities sold (kg) and total marketing cost (₦) of the major forms

of fish marketed in Borno State 136

Table 4.32: Average monthly quantities, profitability and marketing efficiency

indices of the forms of fish marketed in Nigeria-Cameroon-Chad

border region 137

Table 4.33: Average monthly quantities of fish products in fish markets in the

States along Nigeria-Cameroon-Chad border 139

Table 4.34: Average monthly quantities, profitability indices and marketing

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efficiency of fresh fish marketed in the States along


Table 4.34 cont’d: Average monthly quantities, profitability indices and

marketing efficiency of fresh fish marketed in the States along



efficiency of smoked fish marketed in the States along Nigeria-



marketing efficiency of smoked fish marketed in the States along



efficiency of dried fish marketed in the States along Nigeria-



marketing efficiency of dried fish marketed in the States along



efficiency of frozen fish marketed in the States along Nigeria-


Table 4.38: Economic characteristics, profitability indices and marketing

efficiency at fish marketing node in the study area 151


efficiency of actors in fresh fish marketing nodes 153


efficiency of actors in smoked fish marketing nodes 155


xv

efficiency of actors in dried fish marketing node 156


efficiency of actors in frozen fish marketing node 158

Table 4.43: Estimated maximum likelihood parameters of the Stochastic

production Function 160


socio-economic characteristics and profitability of producers 161


socio-economic characteristics and profitability of processors 162


socio-economic characteristics and profitability of marketers 163

Table 4.47: Average monthly quantities and percentage of forms of fish

entering fish markets along Nigeria-Cameroon-Chad border

through inter-State, intra-State and intra-regional fish trade 165

Table 4.48: Average monthly revenue from sales of fish entering fish

markets along Nigeria-Cameroon-Chad border through inter-

State, intra-State and intra-regional fish trade 166

Table 4.49: Average monthly quantities and percentage of forms of fish

sold from the fish markets along Nigeria-Cameroon-Chad border

through inter-State, intra-State and intra-regional fish trade 168

Table 4.50: Average monthly revenue from forms of fish sold from the fish

markets along Nigeria-Cameroon-Chad border through inter-State,

intra-State and intra-regional fish trade 169

Table 4.51: Profitability and efficiency of the marketing nodes and actors

involved in intra-State trading of fresh fish in fish markets in

Nigeria-Cameroon-Chad border region 170

Table 4.52: Profitability and efficiency of the marketing nodes and actors

xvi

involved in inter-State trading of supplied (inflow) fresh fish into

fish markets in Nigeria-Cameroon-Chad border region 172

Table 4.53: Profitability and efficiency of the marketing node and actors involved

in intra-regional trading of supplied (inflow) fresh fish along Nigeria-


Table 4.54: Profitability and efficiency of the marketing nodes and actors involved

in inter-State trading (outflow) of fresh fish from fish markets in

Nigeria-Cameroon-Chad border region 175

Table 4.55: Profitability and efficiency of the actors involved in intra-regional

trading (outflow) of fresh fish along Nigeria-Cameroon-Chad border 176


in intra-State trading of smoked fish in fish markets in Nigeria-Cameroon-

Chad border region 178


in inter-State trading of supplied (inflow) smoked fish into fish markets


Table 4.58: Profitability and efficiency of actors involved in intra-regional trading of

supplied (inflow) smoked fish into fish markets along Nigeria-Cameroon-

Chad border 180


in inter-State trading (outflow) of smoked fish from fish markets



in intra-regional trading (outflow) of smoked fish from fish markets along



in intra-State trading of dried fish in fish markets in Nigeria-Cameroon-


xvii

Table 4.62: Profitability and efficiency of actors involved in inter-State trading of

supplied (inflow) dried fish into fish markets in Nigeria-Cameroon-


Table 4.63: Profitability and efficiency of actors involved in intra-regional trading of

supplied (inflow) dried fish into fish markets along Nigeria-Cameroon-

Chad border 187


in inter-State trading (outflow) of dried fish from fish markets in Nigeria-

Cameroon-Chad border region 188

Table 4.65: Profitability and efficiency of actors involved in intra-regional trading

(outflow) of dried fish from fish markets along Nigeria-Cameroon-

Chad border 190

Table 4.66: Profitability and efficiency of the marketing node and actors involved

in intra-State trading of frozen fish in fish markets in Nigeria-Cameroon-


Table 4.67: Average monthly quantities, prices, profitability and marketing efficiency

of the forms of fish in Intra-State trade (inflow) in Akwa Ibom State 193


of fresh fish in Inter-State trade (inflow) in Akwa Ibom State 194


of the forms of fish traded (Intra-State Trade) in Cross River State 196


of fresh fish traded (Inter-State Trade) in Cross River State 197


of the forms of fish traded (Intra-Regional Trade) in Cross River State 199


of the forms of fish traded (Intra-State Trade) in Benue State 200

xviii


of the forms of fish traded (Inter-State Trade) in Benue State 202


of the forms of fish traded (Intra-Regional Trade) in Benue State 203


of the forms of fish traded (Intra-State Trade) in Taraba State 205


of the forms of fish traded (Inter-State Trade) in Taraba State 206


of the forms of fish traded (Intra-State Trade) in Adamawa State 208


of the forms of fish traded (Inter-State Trade) in Adamawa State 209


of smoked fish traded (Intra-Regional Trade) in Adamawa State 210


of the forms of fish traded (Intra-State Trade) in Borno State 212


of the smoked fish traded (Intra-Regional Trade) in Borno State 213


of the forms of fish traded (Inter-State Outflow Trade) in Akwa Ibom State 214


of the forms of fish traded (Inter-State Outflow Trade) in Cross River State 216


of fresh fish traded (Cross-border Outflow Trade) in Cross River State 217


of the forms of fish traded (Inter-State Outflow Trade) in Benue State 218

xix


of the forms of fish traded (Intra-Regional Outflow Trade) in Benue State 220


of the forms of fish traded (Inter-State Outflow Trade) in Taraba State 221


of the forms of fish traded (Inter-State Outflow Trade) in Adamawa State 223


of the forms of fish traded (Intra-Regional Outflow Trade) in

Adamawa State 224


of the forms of fish traded (Inter-State Outflow Trade) in Borno State 225


of the forms of fish traded (Intra-Regional Outflow Trade) in Borno State 227

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LIST OF FIGURES

TITLE PAGE

Figure 2.1: Trade balance in fish and fishery products (tonnes) in Africa 22

Figure 2.2: Fishery products trade balance of selected African countries

(average 2006-2011) 23

Figure 2.3: Marketing channel for fresh and dried fish in Maiduguri Metropolis

of Borno State, Nigeria. 34

Figure 2.4: Conceptual Framework for the study 44

Figure 3.1: Map of Study area showing the Local Government Areas 48

Figure 4.1: Schematic view of fish marketing chain along Nigeria-Cameroon-Chad

border 61

Figure 4.2: Chart showing the primary sources of fund for the respondents 62

Figure 4.3: Chart showing percentages of Producers and their primary sources of fund 63

Figure 4.4: Chart showing percentages of Processors and their primary sources of fund 64

Figure 4.5: Chart showing percentages of Marketers and their primary sources of fund 65

Figure 4.6: Bar Chart showing the secondary sources of fund for the respondents 67

Figure 4.7: Chart showing respondents other sources of income 73

Figure 4.8: Sex distribution of respondents in the sampled States 74

Figure 4.9: Bar chart showing the age distribution of respondents 76

Figure 4.10: Bar chart illustrating the marital status of respondents 77

Figure 4.11: Bar chart showing the religion distribution of respondents 79

Figure 4.12: Bar chart showing the household sizes of respondents 81

xxi

Figure 4.13: Bar Chart showing the respondents’ highest level of Education 82

Figure 4.14: Distribution of respondents’ marketing experiences in years 83

Figure 4.15: Percentage of forms of fish marketed in Nigeria-Cameroon-Chad

border region 87

Figure 4.16: Percentage of forms of fish marketed in States along


Figure 4.17: Fish pricing mechanism in the study area 91

Figure 4.18: Lorenz curve for fresh fish markets in Nigeria-Cameroon-Chad

border region 109

Figure 4.19: Lorenz curve for smoked fish markets in Nigeria-Cameroon-Chad

border region 111

Figure 4.20: Lorenz curve for dried fish markets in Nigeria-Cameroon-Chad

border region 114

Figure 4.21: Lorenz curve of frozen fish markets in Nigeria-Cameroon-Chad

border region 116

Figure 4.22: Relationship between total marketing cost and total monthly quantity

of fresh fish sold 124


of smoked fish sold 125


of dried fish sold 126


of frozen fish sold 128

Figure 4.26: Average monthly quantities of forms of fish sold in fish markets

in the States along Nigeria-Cameroon-Chad border 140

xxii

LIST OF PLATES

TITLE PAGE

Plate 1: Picture showing the sales of fresh fish in Wadata fish market,

Benue State, Nigeria 89

Plate 2: Picture showing processed fish retailers in Mayogwoi fish market,

Taraba State, Nigeria 90

xxiii

LIST OF APPENDICES

TITLE PAGE

Appendix 1: Fish Trade Research Questionnaire 276

Appendix 2: Fishermen sorting their harvest of crayfish at Iwuo Okpom landing site

in Ibeno fishing settlement, Akwa Ibom State 290

Appendix 3: Group photograph with fishermen and members of the Artisanal

Fishermen Association of Nigeria (ARFAN) in Akwa Ibom State 291

Appendix 4: Fish marketers in Gurin market, Adamawa State 292

Appendix 5: Fishermen and fish buyers in Bakassi, Cross River State 293

xxiv

LIST OF ACRONYMS

AEC African Economic Community

AFESUN Association of Fish Suppliers of Nigeria

APEC Asian-Pacific Economic Cooperation

AU-IBAR African Union Inter-African Bureau for Animal Resources

FAO Food and Agricultural Organisation

FDF Federal Department of Fisheries

FMARD Federal Ministry of Agriculture and Rural Development

GoN Government of Nigeria

IUU Illegal Unreported and Unregulated

MIP Minimum Integration Program

NEPAD New Partnership for Africa’s Development

OECD Organisation for Economic Co-operation and Development

PIDA Program Infrastructure Development for Africa

REC Regional Economic Communities

RTA Regional Trade Agreement

UNCTAD United Nations Conference on Trade and Development

USAID United States Agency for International Development

1

CHAPTER ONE

1.0 INTRODUCTION

1.1 BACKGROUND OF STUDY

Fish is economically, socially and culturally important as a global dietary aspect of sustainable

food security (Odebiyi et al., 2013). Fisheries and related activities (processing and marketing)

represent the main source of income for coastal fishing communities (United Nations, 2014). An

important discourse among scholars is the marketing of fish and fish products due to its provision

of more than 40% of animal protein consumed by average Nigerian, its contribution to the

economy in terms of Gross National Product and its generation of income along its production,

processing, preservation and marketing chains (Agbebi, 2010a; Agbebi, 2010b).

Fish products are highly traded and global fish trade has been increasing very rapidly in recent

decades with an estimated 45% of the world catch now traded internationally (The FishSite, 2015).

West Africa has a huge potential for trade in intra-regional terms (Torres and Van Seters, 2016)

and vibrant markets for fish and fish products in Nigeria, Ghana and the Ivory Coast being the

three major importers of fish products in the region (Ndiaye, 2013). Nigeria has a staggering

demand-supply gap of about 1.8 million tonnes of fish, from an annual fish demand of about 2.66

million tonnes and a paltry domestic production of about 780,000 tonnes (Oyinbo and Rekwot,

2013). This large deficit between the demand and supply of fish is augmented by massive

importation of frozen fish (Federal Department of Fisheries, 2008).

Africa’s participation in the global fish trade has been limited, providing only about 4.9% of the

total value traded (Worldfish, 2015a). The continent’s share in global export and imports continues

to be minor with Europe (70%) being the number one market for the top ten African exporters of

fish products (The FishSite, 2015). Though Nigeria imports between $400 and $600 million worth

of fish and fish products each year (Federal Ministry of Agriculture and Rural Development,

2016). It is worthy of note that the top suppliers of fishery products into Nigeria are United States

and Chile followed by Europe (18%), and Asia (10%); meanwhile, African suppliers provide 7%

(Food and Agriculture Organisation, 2016a). International trade has not served as an effective tool

for the achievement of sustainable economic growth and development for many African countries,

2

however, promotion of intra-regional trade will contribute to enhancing African countries’

capacity and getting them ready to compete more effectively on international markets (FAO,

2016a).

Intra-regional fish trade in Africa is constrained by inadequate market information, trade

infrastructure, deficient policy and institutional frameworks which have prevented Africa from

optimizing the social and economic benefits available from fish trade (Lokuruka, 2016). The

malfunctioning of the marketing chain of major food leads to high rate of spoilage, constant food

shortage, rising farm products prices and huge importation costs (Ayinde et al., 2009). Research

development and investment efforts have often been focused primarily on production.

Consequently, production increase without a well-developed marketing system lead to all possible

gains from the production effort going into the drains of post-harvest losses (Esiobu and

Onubuogu, 2014). Further enhancement of intra-regional trade is believed to be key for sustainable

development and food security and it creates opportunities for economies of scale and allows food

to flow from food abundant to food deficit areas (Torres and van Seters, 2016). Hence, strong

reasons exist to bring a more strategic focus on promoting regional trade in fisheries by integrating

intra-regional fish trade into nation-state policy agenda.

1.2 JUSTIFICATION OF STUDY

West African region is among the best-endowed fishing grounds in the world, largely due to

upwelling along the coast of Senegal and Mauritania and the Gulf of Guinea. The region benefits

from the nutritional and economic advantages of its fisheries, yet the sector still faces many

challenges ranging from poor exploitation of resources to marketing problems (Ndaiye, 2013). In

an effort to resolve the challenge of marketing problems, development practitioners have focused

attentions on targeting agricultural value chains and fisheries by extension, to improve smallholder

participation in markets (Rota and Sperandini, 2010). The African Union Policy Framework and

Reform Strategy for Fisheries and Aquaculture in Africa, which prioritizes fish trade and aims to

promote responsible and equitable fish trade and marketing has led to the European Union funded

“Fish Trade for a Better Future” project that is focused on conducting research to generate data

that will inform crucial policy decisions towards improving food security and reduction of poverty

through intra-regional fish trade in sub-Saharan Africa (WorldFish, 2015b). One of the policy

3

thrust to improving marketing and trade in the recent Agriculture Promotion Policy (APP) in

Nigeria is enhancing access to market information (process, opportunities etc.) by facilitating the

establishment of national agricultural information system that provides easy access to information

on markets, regulations, price discovery, etc (FMARD, 2016).

Provision of valuable marketing information is of utmost importance since markets determine

marketing policies (Gordon et al., 2013). Various researches have given credence to the

importance of adequate marketing system in the domestic fish markets in Nigeria. Bassey et al.

(2015) studied the determinants of fresh fish marketing and the profitability among fish traders in

Akwa Ibom State. Agom et al. (2012) examined the structure of frozen fish market at the wholesale

level in Calabar, Cross River State. Madugu and Edward (2011) investigated the relationship

between quantity of processed fish distributed and marketing costs in Adamawa State, Nigeria.

Iliyasu et al. (2011) further assessed the economics of smoked and dried fish marketing in

Adamawa State. Ismail et al. (2014) examined the market structure of dried fish in Borno State.

However, there is paucity of information on the market structure and value of intra-regional fish

trade needed to ensure food security in the West African corridor. Therefore, it becomes imperative

to study fish marketing system in Nigeria and trade flow with other African countries.

The following research questions therefore arises:

1. What are the socio-economic characteristics of the marketing actors involved in fish trade

along Nigeria-Cameroon-Chad border?

2. What are the marketing nodes for fish trade and species of fish produced and traded along

Nigeria-Cameroon-Chad border?

3. What is the structure of fish (fresh, smoked, dried and frozen) marketing along these

borders?

4. What is the performance of fish marketing actors at each of the marketing nodes identified?

Based on the aforementioned- research questions, this research was conceptualized to address this

data gap and assess the marketing nodes and structure for fish trade in the States along Nigeria-

Cameroon-Chad border. The profitability and efficiency of the actors involved in fish trade from

those States to other countries was also examined in order to provide a framework for the

development of recommendations for stakeholders and to be able to aid policy makers to develop

sound and sustainable fishery marketing strategies with realizable objectives that would improve

4

fish marketing system in Nigeria and on the long run enhance regional fish trade in Africa. It will

also serve as a tool for investment decisions for fish marketers in the study area.

1.3 GENERAL OBJECTIVE

The aim of this research is to assess the marketing nodes and structure for fish trade along Nigeria-

Cameroon-Chad border.

1.4 SPECIFIC OBJECTIVES

The scope of this research to be carried out along the Nigeria-Cameroon-Chad border aims to:

Determine the socio-economic characteristics of the actors operating along the fish trade

routes;

Identify the marketing nodes for fish (frozen, dried, smoked and fresh) trade and profile

fish species produced and traded;

Describe the structure of fish marketing and

Estimate the profitability and efficiency of the actors involved in fish trade

and trade flow.

1.5 HYPOTHESES

The hypotheses of the study tested in the null forms (H0) were:

I. The socio-economic characteristics of the marketing actors have no effect on their technical

efficiency (productivity).

II. There is no significant difference in the profitability and efficiency of fish marketing across

the marketing nodes for fish trade along Nigeria-Cameroon-Chad border.

III. There is inequality in the share of monthly income among the actors in the various nodes

for fish trade identified in the fish (fresh, smoked, dried and frozen) markets.

IV. There is no significant difference in the profitability and efficiency of fish marketing

among the actors in the forms of fish (fresh, smoked, dried and frozen) markets in Nigeria-

Cameroon-Chad border region.

5

CHAPTER TWO

2.0 LITERATURE REVIEW

2.1 THEORETICAL FRAMEWORK

2.1.1 Market participation

The theory of market participation has developed many different perspectives, including asset-

based approaches and agricultural developmental theory approaches (Onoja et al., 2012).

Recognition of the potential of markets as engines of economic development and structural

transformation gave rise to a market-led paradigm of agricultural development during the 1980’s

(Reardon and Timmer, 2007) in which market liberalization policy agendas were widely promoted

in Sub-Saharan Africa (SSA) and other low-income regions. Furthermore, as households’

disposable income increases, so does demand for variety in goods and services, thereby increasing

demand-side market participation, which further increased the demand for cash and thus supply-

side market participation. The standard process of agrarian and rural transformation therefore

involves households’ transition from a model of subsistence, in which most inputs are provided

for and most outputs consumed internally, to a market engagement mode, with inputs and products

increasingly purchased and sold off the farm (Timmer, 1988; Staatz, 1994). The asset-based theory

was summarized by Omiti et al (2009), who held that as the market share of agricultural output

increases, input utilization decisions and output combinations are progressively guided by profit

maximization objectives. This process leads to the systematic substitution of non-traded inputs

with purchased inputs, the gradual decline of integrated farming systems, and the emergence of

specialized high-value farm enterprises (Onoja et al., 2012).

2.1.2 Market Structure, Conduct and Performance

Market structure conduct and performance (S-C-P) framework was derived from the neo-classical

analysis of markets (Edwards et al., 2005). The structure, conduct and performance (S-C-P) are

differentiated terms yet interrelated. The S-C-P paradigm is mainly focused on analyzing

competitive conditions of the prevailing market framework (Onyango, 2013). As a branch of

6

applied price theory, the basic paradigm of Industrial organization (IO) which was popularized by

Bain in late 1950s, holds that market structure influence the competitive conduct of firms in the

market, which in turn influences market performance. Therefore, structure, conduct and

performance (SCP) is the basic framework of analysis in the theory of Industrial organization

Gichangi, 2010). The industrial organizational approach emerged in the developed country context

where industries, often dominated by a few very large firms, represent a prominent sector of the

economy (Bain, 1968). Its applicability to the more atomistic situation typical of most agricultural

factor and product markets in developing countries has been questioned. In addition, Smith (1972)

believes that the structure-conduct-performance framework has limited transferability to the

developing country scene because of underdeveloped infrastructure, inter-sectoral relations, and

development objectives, as well as the unique social and political structures found in the Third

World. Smith proceeds to develop several performance criteria that he considers more relevant to

developing countries, although the issue of evaluating departures from the perfectly competitive

model remain. Smith, however, states that he sees the necessity for revising only performance

dimensions of the industrial organizational approach through price efficiency analysis, while

leaving structural and conduct dimensions as described by Bain basically intact (Smith, 1972).

There are two competing hypotheses in the S-C-P paradigm: the traditional “structure performance

hypothesis” and “efficient structure hypothesis”. The structure performance hypothesis states that

the degree of market concentration is inversely related to the degree of competition. This is because

market concentration encourages firms to collude. More specifically, the standard S-C-P paradigm

asserts that there is a direct relationship between the degree of market concentration and the degree

of competition among firms. This hypothesis will be supported if positive relationship between

market concentration (measured by concentration ratio) and performance (measured by profits)

exist, regardless of efficiency of the firm (measured by market share). Thus, firms in more

concentrated industries will earn higher profits than firms operating in less concentrated industries,

irrespective of their efficiency. The efficiency structure hypothesis states that performance of the

firm is positively related to its efficiency. This is because market concentration emerges from

competition where firms with low cost structure increase profits by reducing prices and expanding

market share. A positive relationship between firm profits and market structure is attributed to the

gains made in market share by more efficient firms. In turn these gains lead to increased market

concentration. That is, increased profits are assumed to accrue to more efficient firms because they

7

are more efficient and not because of collusive activities as the traditional S-C-P paradigm would

suggest (Molyneux and Forbes, 1995).

Basically, the participants of the market are evaluated based on the extent at which they affect

performance and conduct of the market. According to APEC (2008), the relationship of the market

players affects the conduct (either negatively or positively) and consequently affects the market

performance and vice versa. The model in which the three market characteristics (S-C-P) affects

one another is an interactive system and therefore discussing the measuring criteria includes a deep

understanding of the market participant behaviors as well as the external environment that may

contribute to certain peculiar outcomes (Onyango, 2013).

Market structure relates to how market participants are organized in terms of the size and number

of individual players in the market. In some cases, it denotes the institutional barriers to new

entrants. It refers to certain characteristics of the market, which are believed to influence its nature

of competition and the process of price formation. Characteristics such as the degree of product

differentiation, market integration, concentration (number and size of buyers and sellers). Market

conduct refers to certain behaviours of firms in the market. Market conduct is more or less

influenced by market structure (Onyango, 2013). According to World Food Programme (2011),

level of competition in the market is critical: how prices are determined, whether or not actors

collude or price discriminate, and how far the prices of goods are above their production costs.

Competitiveness of market actors, particularly traders (wholesalers and retailers), can be

particularly important in the context of how they would likely respond to changes in market supply

(e.g. an increase due to food aid) or household demand (e.g. an increase due to non-food transfers,

thus increasing liquidity and purchasing power).

Market performance is the ultimate result derived from the market and it encompasses the outcome

from various market activities (Onyango, 2013). To measure the market performance, an

evaluation of the contribution of marketing to the overall economic welfare in terms of efficiency

remains a key focus. It is the assessment of how well the process of marketing is carried out and

how successfully its aims are accomplished. The elements traditionally classified under

performance are profits, operational efficiency, pricing efficiency and stability and

progressiveness, price stabilization of information, cost of sales promotion. The structure-conduct-

8

performance (SCP) approach is often used in the investigation of agricultural subsectors

(Suleiman, 2007).

2.1.3 Theory of Demand and Supply

The theory of demand and supply plays very vital role in the marketing of fish. The level of

marketing activity going on in a market is determined primarily by the interplay of the forces of

demand and supply. In a perfectly competitive market, where there are many consumers (buyers)

and farmers (producers), the price mechanism is fully operational. In other words, the prices of

goods and services are determined by the forces of demand and supply. Put differently, prices

guide consumers in the choice of goods and services, and the quantities of such goods and services

that they buy (Umoinyang, 2014). Demand is often times differentiated from effective demand.

While demand refers to willingness to buy, effective demand entails willingness backed with the

ability to pay. As such, demand is described as the quantities of goods and services that consumers

are willing and able to buy at various prices. Demand is a function of several variables, i.e., the

quantities of goods and services demanded at any given point in time is a function of several

factors. Four of such factors are often pronounced. These are the price of the good (service), the

price of substitutes and complements, income of consumers, and tastes or preferences

(Umoinyang, 2014).

2.2 NUTRITIONAL BENEFITS OF FISH

Fish and fish products are known worldwide as a very important diet because of their high nutritive

quality and significance in improving human health. Fish plays a vital role in feeding the world’s

population and contributing significantly to the dietary protein intake of billions of people

(Adeosun and Adebukola, 2012). Fish is the most important animal protein food available in the

tropics (Ali et al., 2008). The nutritional benefits derived from consuming fish are as follows:

Fish is the cheapest animal’s protein source in Nigeria, and as a food plays an important

role in our diet. And the human body utilizes protein from fish better than the protein from

milk, beef, pork, chicken etc (Dambatta et al., 2016).

9

It has well-balanced concentrations of all the essential amino acids with a particularly high

concentration of lysine. Fresh fish contains higher proportions of protein, around 14-20

g/100 g raw, edible parts, than plant-source foods. Therefore, adding fish to a plant-based

diet increases the total protein intake as well as enhances protein absorption due to the

lysine content in the fish (Kawarazuka, 2010).

Fish is an integral component of a balanced diet, providing a healthy source of dietary high-

quality protein, minerals and trace elements, fat-soluble vitamins and essential fatty acids

(FAO/WHO, 2011).

It has essential long-chain omega-3 fatty acid docosahexaenoic acid (DHA) that is

important for optimal brain and neurodevelopment in children and eicosapentaenoic acid

(EPA) that improves cardio-vascular health (Thilsted et al., 2014).

There is strong evidence that fish, in particular oily fish, lowers the risk of coronary heart

disease (CHD) mortality by up to 36 percent due to a combination of EPA and DHA

(FAO/WHO 2011).

It has high content of Polyunsaturated (Omega III) fatty acids, which are important in

lowering blood cholesterol level and high blood pressure (Coaster and Otufale, 2010).

Fisheries products are important sources of micronutrients such as vitamins and minerals.

This is in particularly true for small sized species consumed whole with heads and bones,

which can be an excellent source of many essential minerals such as iodine, selenium, zinc,

iron, calcium, phosphorus, potassium, vitamins A and D, and several B vitamins (Thilsted

et al., 2014).

Due to the nutritional importance of fish, venturing into its enterprise holistically holds promising

potentials to investors (Osarenren and Ojor, 2014). Apart from these benefits derived from human

consumption, fish is important for animal feed, a source of raw materials in allied industries and a

source of employment for many Nigerians (Esu et al., 2009).

2.3 THE FISHERY SECTOR IN NIGERIA

Nigeria has a land area of 923,768km2 with a continental shelf area of 37,934km2, a length of

coastline of 853km and Exclusive Economic Zone (EEZ) of 210,900km2 (FDF, 2008). The

10

geography and biodiversity of Nigeria supports fishing activities. Nigerian coastal fishery sector

is characterized by a rich resource base with a water area of 140,000km2 and about 42,000km2

continental shelf areas, adjacent to the country’s 853km coastline (FAO, 2007). The huge Niger

Delta inland waters associated with River Niger and River Benue, their tributaries and flood plains,

natural lakes and wetlands, reservoirs and purpose-built ponds, constitute the total water area in

the country. Furthermore, one quarter of Nigerian States are located at the coastal zone, including

Akwa Ibom. The other states include Lagos, Ogun, Ondo, Delta, Edo, Bayelsa, Rivers and Cross

River state (Bako et al., 2008). Fisheries and aquaculture in Nigeria is a vibrant and dynamic

commercial sector, ripe with investment and employment opportunities. According to FAO (2014)

Nigeria has more than 1 million processors. With an estimated 10 million Nigerians actively

engaged in the upstream and downstream areas of fisheries operations in Nigeria, the contribution

of the fisheries sub-sector to the nation’s economy is significant, ranging from employment

creation to the provision of raw materials for the animal feed industry (Osagie, 2012). Fish and

fish products contributed 6% to the gross domestic product (GDP) of the country in 2006 (Kainga

and Adeyemo, 2012). Fisheries development depends on improved production, processing,

packaging and storage technology, and also on effective marketing system.

The current policy thrust of the Federal Government is aimed at ensuring sustainable development

of Nigerian fisheries for national food security, self-sufficiency in fish production, optimum

resource utilization and conservation (Vincent-Akpu, 2013). The policy focuses on employment

generation, wealth creation, poverty alleviation and reduction in rural-urban migration, among

others. Specific objectives which are expected to be private-sector driven include the following:

achievement of self-sufficiency in fish production; development and modernization of the means

of production, processing, storage, marketing and resources conservation; ensuring total

compliance with the FAO's Code of Conduct for Responsible Fisheries (CCRF), amongst others

(Vincent-Akpu, 2013).

2.4 FISH PRODUCTION IN NIGERIA

Nigeria lies between longitudes 2049’E and 14016’N and 13052’ North of the equator. The climate

is tropical characterized by high temperatures and humidity as well as marked dry and wet seasons,

though there are significant variations between South and North. Total rainfall decreases from the

11

coast northwards. The South (below latitude 80N) has an annual rainfall ranging between 1,500

and 4,000 mm and the extreme North between 500 and 1000 mm. Nigeria is blessed with a vast

expanse of inland freshwater and brackish ecosystems which are contained within 320 nautical

miles (667 km). The country has an extensive mangrove ecosystem of which a great proportion

lies within the Niger Delta and are also found mostly in Rivers, Delta, Cross River, Akwa Ibom,

Lagos and Ondo States. They lie between latitudes 30 and 701’ north and are estimated to cover

between 500,000 and 885,000 ha. Freshwaters start at the Northern limit of the mangrove

ecosystems and extend to the Sahelian region (Sotolu, 2011).

The approximate extent of the major inland water systems is shown in table 2.1. The major rivers,

estimated at about 10,812,400 ha, make up about 11.5% of the total surface area of Nigeria which

is estimated to be approximately 94,185,000 ha. Thirteen lakes and reservoirs with a surface area

of between 4,000 and 550,000 ha have a total surface area of 853,600 ha and represent about 1%

of the total area of Nigeria (Sotolu, 2011). Apart from the major rivers and lakes shown in table

2.1, there are other small lakes and perennial streams around in the country among which are

Asejire dam and Eleyele Lake in Ibadan (South-West Nigeria) (Fapohunda and Godstates, 2007)

and Doma dam and Hunki Lake (North-Central Nigeria). These water bodies are invariably richer

in diversity of both shell and fin fish species. Constant and regular fishing activities of shell and

fin fish (pelagic and off-shore pelagic, demersal) and crustaceans are going on around existing

water bodies in Nigeria. However, since the 1980’s, production trend in the sector has been very

unstable particularly, in the coastal/brackish water artisanal sector which provides the bulk of the

domestic production (Oparinde and Ojo, 2014). Fish production in Nigeria comes from three

sources; artisanal (inland rivers, lakes, costal and brackish water), industrial fishing and

aquaculture (Otubusin, 2011).

2.4.1 ARTISANAL FISHERIES

Artisanal fisheries are traditional fisheries involving fishing households (as opposed to commercial

companies), using relatively small amount of capital and energy, relatively small fishing vessels

(if any), making short fishing trips, close to shore, mainly for local consumption (The Fish Project,

2015). This fishery is composed largely of traditional fishermen who are about half a million in

number scattered all over the country (Kareem et al., 2012).

http://www.scialert.net/fulltext/?doi=jfas.2014.501.505&org=10#71509_an

12

Table 2.1: Major Inland water resources of Nigeria

Types of water bodies Approximate surface area (ha)

Major Rivers

Anambra river 1,401,000

Benue river 129,000

Cross river 3,900,000

Imo river 910,000

Kwa Iboe river 500,200

Niger river (less Kainji and Jebba) 169,800

Ogun river 2,237,000

Oshun river 1,565,400

Sub-total 10,812,400

Major lakes and reservoirs

Lake Chad (Natural) 550,000

Kainji lake (Man-made) 127,000

Jebba lake (Man-made) 35,000

Shiroro lake (Man-made) 31,200

Goronyo lake (Man-made) 20,000

Tiga lake (Man-made) 17,800

Chalawa Gorge (Man-made) 10,100

Dadin Kowa (Man-made) 29,000

Kiri (Man-made) 11,500

Bakolori (Man-made) 8,000

Lower Anambra (Man-made) 5,000

Zobe (Man-made) 5,000

Oyan (Man-made) 4,000

Sub-total 853,600

Total 11,666,000

Source: Adapted from Sotolu, 2011

13

It may be native fisheries for sustenance or commercial fishing using indigenous or small scale

fishing gear like nets, traps and also using motorized or non-motorized fishing boat during fishing

activities (Mustapha, 2013) although planked and dug-out canoes (3 to 13 m long) powered by

outboard engines ranging from 15 horse power (hp) to 25 hp are increasingly common (Etim et

al., 2015). This fishing activities are mostly in the shallow continental shelf (coastline), lagoons,

creeks, rivers, lakes, lagoons, dams, reservoirs as well as the floodplains of the Niger Delta and

other major rivers (Inoni and Oyaide, 2007). On a comparative basis, artisanal fishing is labour

intensive, time consuming and requires low technology application and relatively low capital

investment.

Artisanal fisheries play the role of food supplier, employment provider and income earner in the

Nigerian economy. Faturoti (2010a) reported that artisanal fisheries in Nigeria provides more than

82% of the domestic fish supply, giving livelihoods to one million fishermen and up to 5.8 million

fisher folks in the secondary sector. In fishing communities, during the off-fishing season, which

is usually in the rainy season fish catch is low. This is because of the increased level of turbid

water and strong wind, which hinder the fishermen without outboard engine from going far out to

the sea.

2.4.2 INDUSTRIAL FISHERIES

Industrial fishery involves the use of large boats (trawlers) because operations are in the distant

water (that is, mostly marine and deep sea). These distant water vessels are generally expensive

and require high level organization with efficient shore-based facilities (such as berths for the

trawlers and cold rooms for storage of products). Consequently, industrial fishery tends to be

capital intensive (Kareem et al., 2012). According to Etim et al. (2015) the inshore industrial

fishery operates from about 5 nautical miles off the coast to the edge of the continental shelf. This

industry employs bottom or mid-water trawlers to catch and land a variety of species including

croakers (Pseudotolithus spp.), soles (Cynoglossus spp.), groupers (Epinephelus spp.), snappers

(Lutjanus spp.), bigeyes (Brachydeuterus spp.), threadfins (Polydactilus spp.), baraccudas

(Sphyraena spp.), jacks (Caranx spp.), horse mackerels (Trachurus spp.) and cutlass fishes

(Trichiurus spp.; Etim et al., 2015).

14

2.4.3 AQUACULTURE

Fish farming or aquaculture has the potential to help expand the resource base for food production

and reduce the pressure on conventional sources of fish which are harvested faster than they can

be regenerated. Aquaculture, according to the World Fish Center (2009), is the world’s fastest

growing food production subsector. For developing countries like Nigeria where the economy is

largely agrarian, fish farming can generate significant employment, enhance the socio-economic

status of the farmer as well as generate foreign exchange. Fish farming also has enormous

potentials of improving the nutritional standard of masses of people (Oluwemimo and Damilola,

2013). The production from aquaculture has been growing at a remarkable rate, thereby making it

a promising sector to offset the declining catch from capture fisheries. Table 2.2 shows the

production of fish in the fishery sectors in Nigeria.

The contribution of domestic fish production to the country’s fisheries sector cannot be over

emphasized. Aquaculture has the potential of contributing to domestic fish production and

reducing the amount of money spent on fish importation (Ibok et al., 2013). It has been considered

as a solution to augmenting fish supply in Sub-Saharan Africa and has received considerable

attention from development agencies, yet it remains in the potential stage (Gordon et al., 2013).

High cost of production, especially cost of feeding has been reducing aquaculture’s potential to

compete with capture fisheries. High-level policy support should be directed towards aquaculture

development and the marketing of its products. The major compelling factor for the development

of the sector is the huge domestic market.

2.5 DEMAND AND SUPPLY OF FISH IN NIGERIA

Fish supply in Nigeria is either through capture fisheries, fish farming or by importation (Anene

et al., 2010), but half of the fish consumed in Nigeria is imported (Dauda et al., 2016). According

to Dauda et al. (2016) Nigeria requires about 2.66 million mt of fish annually to satisfy the dietary

requirement of its citizens (160 million). With a paltry domestic production of about 780,000

tonnes, fish demand-supply gap stands at a staggering 1.8 million tonnes (Oyinbo and Rekwot,

2013).

15

Table 2.2: Nigeria Fish Production in tonnes by sectors (2000-2013)

NA means not available

Source: Federal Ministry of Agriculture and Rural Development, Fisheries Department, 2014

SECTORS/YEAR 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

ARTISANAL-:

SUB-TOTAL 418,069 433,537

450,965 446,203 434,830 490,594 518,537 504,226 511,382 598,211 616,981 638,486 668,754 744,930

Coastal & Brackish

Water 236,801 239,311

253,063 241,823 227,523 259,831 269,878 260,098 264,988 309,981 328,332 346,381 370,918 418,537

Inland Rivers and

Lakes 181,268 194,226

197,902 204,380 207,307 230,763 248,659 244,128 246,394 288,230 288,649 292,105 297,836 326,393

AQUACULTURE

(Fish Farm) 25,720 24,398

30,664 30,677 43,950 56,355 84,533 85,087 143,207 152,796 200,535 221,128 253,898 278,706

INDUSTRIAL

(Commercial

Trawlers) 23,308 28,378

30,091 33,882 30,421 32,595 33,778 26,193 29,986 29,698 31,510 33,485 45,631 59,871

Fish (Inshore) 13,877 15,792

16,065 17,542 16,063 19,724 19,129 18,040 18,585 18,820 19,261 19,736 27,977 37,652

Shrimp (inshore) 8,056 12,380

12,797 11,416 12,469 10,946 13,767 5,995 9,881 10,878 12,249 13,749 17,654 22,219

EEZ 1,375 206

1,229 4,924 1,889 1,925 882 2,158 1,520

NA NA

NA

NA

NA

GRAND-TOTAL 467,098 486,313

511,720 510,762 509,201 579,544 636,848 615,507 684,575 780,705 849,026 893,099 968,283 1,083,507

GRAND-TOTAL 467,098 486,313

511,720 510,762 509,201 579,544 636,848 615,507 684,575 780,705 849,026 893,099 968,283 1,083,507

16

The Niger Delta contributes more than 50% of the entire domestic Nigerian fish supply, being

blessed with abundance of both fresh, brackish and marine water bodies that are inhabited by a

wide array of both fin fish and non-fish fauna that supports artisanal fisheries (Akankali and

Jamabo, 2011). Despite this considerably high potential of fish production in Nigeria, local fish

production has failed to meet the country’s domestic demand. Presently, Nigeria spends N100

billion on fish importation annually and the current consumption demand in the country stands at

over 2.6 million tons per annum while importation rate is over 750,000 metric tons (Bassey et al.,

2015).

Table 2.3 below shows the projected population, fish demand and supply matrix in Nigeria

between 2000-2015. It reveals that the annual fish demand exceed supply and the wide gap

between fish demand and supply is on the rise as a result of population explosion in the country in

recent years (Falaye and Jenyo-Oni, 2009). Bassey et al. (2013a) also attributed this increase in

fish demand to the relative decline in the supply of animal protein from other sources, increasing

population, and decline in captured fishes due to pollution and over-fishing, as well as rampant

deforestation of mangrove trees which serve as natural habitats for fishes.

2.6 FISH CONSUMPTION IN NIGERIA

The population of Nigeria according to World Bank (2014) estimate is 168.8 million. In Nigeria,

almost 50% of the total animal protein intake is from fish, it occupies this unique position being

the cheapest source of animal protein (FDF, 2009). Protein is an essential part of human diet and

it is sourced from either plant or animal. Food and Agriculture Organization recommended that a

person takes 35 grams per caput of animal protein per day for sustainable growth and development

(Tanko et al., 2014). Most households consume minimum level of calorie but unable to satisfy the

protein requirements (Dauda et al., 2016). Average fish consumption in Nigeria is 9.8 kg/caput

(USAID, 2010). According to Onyeneke and Nwaiwu (2012), food is not distributed equally

among the households in Nigeria and this may be attributed to high level of poverty in some region

of the country. In addition, fish consumption is also affected by location, seasonality, time and

household socio-economic status (Lem et al., 2014). Seasonal fluctuation in food availability and

household responses to this insecurity has been observed to influence individual consumption

patterns (Fregene and Bolorunduro, 2009).

17

Table 2.3: Projected Human Population, Fish demand and supply in Nigeria (2000-2015)

Year Projected

population

(million)

Projected demand

(tonnes)

Projected

domestic fish

supply (tonnes)

Deficit (tonnes)

2000 114.4 1,430,000.00 467,098.00 962, 902.00

2001 117.6 1,470,000.00 480,163.60 984,836.40

2002 121.0 1,412,500.00 507,928.20 1,004,572.00

2003 124.4 1,555,000.00 522,627.10 1,063,082.60

2004 128.0 1,600,000.00 536,917.60 1,063,072.40

2005 131.5 1,643,750.00 552,433.10 1,091,317.00

2006 135.3 1,691,250.00 567,948.60 1,123,301.40

2007 139.1 1,732,750.00 583,872.40 1,154,873.00

2008 143.0 1,782,300.00 600,612.80 1,186,887.20

2009 147.1 1,838,750.00 617,353.20 1,221,397.00

2010 151.2 1,810,000.00 634,500.20 1,255,440.00

2011 155.5 1,943,750.00 652,606.60 1,291,143.00

2012 160.0 2,000,000.00 689,958.00 1,328,508.00

2013 164.0 2,113,750.00 709,683.10 1,365,042.00

2014 169.1 2,175,000.00 730,248.00 1,404,067.10

2015 174.0 2,055,000.00 671,492.30 1,444,752.10

Source: Federal Department of Fisheries (2008)

18

Fish is known to be an efficient converter of food for human consumption and saving children

from kwashiorkor due to low protein intake and unbalanced diet and there is little or no religious

restriction on its consumption (Dauda and Yakubu, 2013). Fish is an important source of essential

nutrients which includes: protein, lipids, vitamins and minerals (Tsado et al., 2012). In addition to

this beneficial contribution to dietary intake, fish is sold, contributing to household food security

indirectly through increasing household income which can be utilised to purchase other food

commodities, including lower cost staple foods (Bene et al., 2007; Aiga et al., 2009). Apart from

human consumption, fish is important for animal feed, a source of raw materials in allied industries

and a source of employment for many Nigerians (Esu et al., 2009).

2.7 RELEVANCE OF FISHERIES TO NIGERIAN ECONOMY

Fisheries occupy a unique position in the agricultural sector of the Nigerian economy. In terms of

Gross Domestic Product (GDP), the fishery sub-sector has recorded the fastest growth rate in

agriculture to the GDP (Ideba et al., 2013). The fishery sector occupies a significant position in

the economy of Nigeria contributing 4% to agricultural GDP (Lawal et al., 2016). Faturoti (2010b)

put the total contribution of fisheries to the Nigerian economy at N126, 417 billion gross output

with a capitalization of N78, 530 billion. Fish trade is also an important source of foreign exchange.

The fishery sector is crucial to alleviating poverty and ensuring food security. FAO estimates that

fish provides 22 percent of the protein intake in Sub-Saharan Africa; this figure increases to 40%

in Nigeria and to as high as 80% in coastal and riverine communities. (Areola, 2007). In fact,

fishing provides 6 and 9 million full and part-time jobs, respectively, the income from which

supports 30.45 million people. FAO (2007) indicated that fish marketing was providing increased

income to the many Nigerians who distribute fresh and processed fish throughout the country. It

is not uncommon to find markets for smoked fish products along inter-city highways and in

Onitsha, Lokoja, Jebba, Makurdi, Aba, Port Harcourt, etc. For the consumers, fish is an important

part of their nutrition, accounting for a large percentage of their animal protein, since it is often

the most affordable source. Thus, the fish market contributes to the food security drive of the

country. Fisheries can therefore play a role in eradicating extreme poverty and hunger (Kingdom

and Alfred-Ockiya, 2009). Recent poverty analysis confirmed that households that produce fish

for the market are generally better off than those producing for self-consumption (International

19

Fund for Agricultural Development, IFAD, 2010). Marketing of Fish and fish products should be

encouraged since it is consumed in all parts of the country and has a good market price (Esiobu

and Onubuogu, 2014).

2.8 NIGERIA AND HER BORDERS

The Federal Republic of Nigeria shares boundaries with five countries of which three namely

Benin, Cameroon and Equatorial Guinea are coastal. The international boundaries vary in length,

from the shortest (Nigeria-Chad) of 75 km to the longest (Nigeria-Cameroon) of 1,700 km. They

also vary both within and between in terms of the terrain and other aspects of physical geography,

and the details of their history (Bonchuk, 2014).

2.8.1 Nigeria-Cameroon Border

Cameroon and Nigeria share a common border of nearly 1,700km and both countries have strong

historical and cultural ties (World Bank, 2013). Nigeria’s boundary with Cameroon (its longest

international border) traverses a strategic waterway that controls access to the Calabar Port, which

is used by commercial shippers and is the site of the Nigerian Eastern Naval Command. The

observed trade flows are the result of the distribution of population and agricultural production

centers, road networks (accessibility), long-established trading relationships, issues surrounding

comparative advantage, and man-made policy distortions on either side of the border. As both

countries continue to industrialize and integrate into global supply chains, factors determining the

cost of access to primary and intermediate inputs, other costs of production, economies of scale,

and specialization in certain products will continue to impact production, and consequently trade

patterns (World Bank, 2013).

The composition of ethnic groups on both sides of the border varies strongly between the northern

and southern parts of the border. In the south, the main ethnic groups engaged in cross-border trade

are Nigerian traders and a smaller group of Cameroonians. In particular, the Nigerian Igbo ethnic

groups, who predominantly reside in Nigeria but also have a sizable presence in Cameroon, are

the most visible traders in the area. The settlement of many Igbo from densely populated areas of

Nigeria in the western part of Cameroon has created natural trading networks with Nigeria, which

20

tend to increase the volume of trade between these two countries in comparison to trade with other

countries. In the north, there are two main ethnic groups involved in trade, namely the Fulbe and

the Hausa (World Bank, 2013).

2.8.2 Nigeria-Chad Border

Nigeria boundary with Chad is the shortest reaching up to 75 km (Bonchuk, 2014). The South-

western part of Chad however shares boundary with Cameroon and Nigeria and Lake Chad, after

which the country is named, is the largest wetland in Chad and the second-largest in Africa.

(Wikipedia, 2016).

2.9 FISH TRADE

World trade in fish and fishery products has expanded significantly in recent decades, rising by

more than 245 percent in terms of quantity (live weight equivalent) from 1976 to 2014, and by

515 percent if one considers just trade in fish for human consumption (FAO, 2016b), and

developing countries are among the most important exporters (Gordon et al., 2013). The

considerable growth in fish trade in recent decades has been fueled by expanding fishery

production and driven by high demand, with the fisheries sector operating in an increasingly

globalized environment. Fish can be produced in one country, processed in a second and consumed

in a third (FAO, 2016b).

2.9.1 Fish Trade in Africa

Global fish trade has been increasing very rapidly in recent decades. The widespread use of

refrigeration, and improved transportation and communications has facilitated this vast expansion

of trade, which is an important engine of economic growth and development. Imports of dried,

salted and smoked fish remained low, even though they are widely consumed in Africa. The

demand is likely met through domestic production which is processed and consumed locally,

and/or fresh fish which is imported for processing into dried, salted or smoked products. The value

of exports and imports indicate that Africa has been a net exporting continent ever since 1985

https://en.wikipedia.org/wiki/Lake_Chad

https://en.wikipedia.org/wiki/Wetland

21

(figure 2.1). However, in terms of volume, imports exceed exports, being composed of low value

small pelagic fish (horse mackerel, mackerel and sardinellas) (The Fish Site, 2015).

The trade balance of selected countries is presented in figure 2.2. As indicated, Morocco has by

far the largest trade surplus, followed by Namibia (US$ 500 million), Senegal (US$ 300 million)

and South Africa (US$ 299 million). Seychelles (because of tuna imports), Kenya and Tunisia

have individually less than US$ 200 million. Angola, Democratic Republic of Congo, Cameroon,

Ghana, Côte d’Ivoire, Egypt and Nigeria are fish and fishery products trade deficit countries. In

2011, Nigeria alone imported around US$ 1 245 394 while the trade deficit was higher than

US$750 million (The Fish Site, 2015).

2.9.2 Promoting African Intra-Regional Trade in Fisheries

Although the African economy is characterised by a relatively high degree of openness, trade in

general and international trade in particular, has so far not served as an effective tool for the

achievement of rapid and sustainable economic growth and development for many of the countries

of the continent. Africa has already taken different initiatives to scale up cross- border trade. Intra-

regional trade stands only at around 12 percent compared to 60 per cent, 40 per cent, and are poorly

produced and packed and raise concerns about quality and safety (The Fish Site, 2015).

Africa has some of the most difficult terrains in the world, with a total number of fifteen landlocked

African countries, representing about one-third of Africa’s population. (Ancharaz et al., 2011).

Inadequate infrastructure remains one of the principal obstacles to intra-African trade, in addition

to the following factors remaining obstacles for fish trade: inefficient cross- border procedures;

Rules of Origin; catch certificates; quality and safety issues; Illegal Unreported and Unregulated

(IUU) fishing aspects and eco-labelling; and investment and private-sector development (The Fish

Site, 2015). Africa’s policy towards regional integration and intra-Africa trade needs to consider

fish trade diversification as one of the central issues, since the lack of export-import similarity is a

principal hindrance to intra-Africa trade and regional integration. A fundamental challenge is

therefore to address supply chain constraints, value addition, value chains to render African fishery

products more competitive in regional and international markets; and boosting intra-African trade

to create diversification and competitiveness (The Fish Site, 2015).

22

Figure 2.1: Trade balance in fish and fishery products (tonnes) in Africa

Source: The Fish Site, 2015

23

Figure 2.2: Fishery products trade balance of selected African countries (average 2006-2011)

Source: The Fish Site, 2015

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According to Rubiato (2013), most African countries have, in recent years, considered trade

facilitation as a priority issue, and, accordingly, increasingly used financial assistance to modernize

customs and promote other reforms. More generally most trade facilitation related reforms have

empirically had a direct positive impact on development. Along trade corridors in Africa, where

more trade is formally recorded, it has increased the revenue for governments; lower waiting times

at borders have led to a lower incidence of HIV; and, if it is easier for traders to engage in formal

trade, this reduces the volume of informal cross-border transactions. In particular, women are often

engaged in this informal cross-border trade, and facilitating formalities would allow them to enter

the formal economy more easily (Rubiato, 2013).

One intended effect of a regional trade agreement (RTA) is, through the reduction and removal of

tariffs, to enable more efficient producers in a region expand production (and reap economies of

scale and scope) to the advantage of consumers and the detriment of less competitive producers.

However, this potential may be limited unless other barriers to trade are also addressed, and

harmonized. The process of fostering closer regional integration means developing new policy

tools (Keane et al., 2010). Also of importance are policies which create an environment for trade

facilitation in which there are efficient core services such as finance, telecommunication services,

energy and adequate transportation networks. Thus, the following are important to achieve

deepened regional integration and intra-regional trade (The Fish Site, 2015):

1. Improving infrastructure in Africa, addressing the missing links, implementing the New

Partnership for Africa’s Development (NEPAD), and more recently, the Program

Infrastructure Development for Africa (PIDA);

2. Linking landlocked countries via several initiatives including the Almaty Program of

Action, and those of RECs and corridor management institutions;

3. Simplifying and harmonizing documentation, rules and procedures, and customs

formalities as embodied in Regional Economic Communities’ (RECs’) protocols on trade

liberalization;

4. Including national trade policies and facilitation signed at RECs levels;

5. Establishing Free Trade Areas and Customs Unions;

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6. Removing trade facilitation bottlenecks in particular including dealing decisively with rent-

seeking practices and malpractices at border multiple checkpoints, and roadblocks;

7. Establishing one-stop border posts (One Stop Border Trade Posts);

8. Improving payment systems and promoting currency convertibility (an old story);

9. Investing in economic diversification (also an old story); and more recently

10. Implementing the Minimum Integration Program (MIP), which is a major continental

framework aimed at enhancing coordination, convergence and collaboration among RECs

to achieve the ultimate goal of the African Economic Community.

The African Economic Community (AEC) – an integral part of the African Union – sets out the

continental framework for economic integration. It recognizes that the process of fostering

economic integration at the continental, regional and sub-regional levels requires the

rationalization and harmonization of RECs (United Nations Conference on Trade and

Development, UNCTAD, 2009). In addition to reductions in tariffs this includes due consideration

of ‘soft’ infrastructure related to the governance of intra-regional trade, such as rules of origin,

product standards and accreditation systems, the harmonization of which may help to reduce costs

for business and therefore facilitate increases in intra-regional trade (Keane et al., 2010).

In conclusion, Africa cannot do without trading with the outside world but it can reduce its

vulnerability to external shocks by boosting intra-regional trade and furthering market integration.

Such a promotion of intra-regional trade constitutes an imperative response to challenges facing

Africa and will contribute to enhancing the countries’ capacity and getting them ready to compete

more effectively on international markets (The Fish Site, 2015).

2.9.3 Fish Trade in Nigeria

Rondon and Nzeka (2010) report Nigeria importing 800,000 metric tons of frozen fish in 2009,

mostly mackerel, herring, and croaker. Nigeria also imports 160,000 metric tons of higher-value

frozen stockfish, mostly from Norway. Nigeria’s informal imports of fish products are almost

exclusively smoked or dried, contrasting with officially recorded imports of low-value frozen

pelagics from Mauritania, Namibia, and non-African suppliers, though there are imports of (dried

26

and/or salted) stockfish from some European countries (Rondon and Nzeka 2010). Official FAO

data attest to Nigerian imports of dried and smoked products from Mali, Niger, and Senegal;

imports that enter via inland borders are, in particular, likely to be higher than those officially

reported (Gordon et al., 2013).

2.9.3.1 New Trade Import Policy in Nigeria

The aim of the new import quota regime for fish in Nigeria is to stimulate the country to become

self-sufficient in fish production over the next four years through a 25 percent annual fish import

cut. An annual baseline fish import figure has been set at 700,000 tons for 2014 which reduces the

allowable quantity of imported fish to 500,000 tons for the year. Except for fish species farmed in

the country (catfish, tilapia and croaker) which are now strictly regulated and under prohibition

from being imported without control, other fish species are free for entry within the set quota

(Nzeka, 2014).

In October 2013, Nigeria’s Minister of Agriculture Adesina announced that the Government of

Nigeria (GoN) would ban fish imports over four years, and raise the import duty up from 10 per

cent to 50 per cent, and possibly as high as 100 per cent beginning January 1, 2014. The report

also stated that the GoN would compel fish importers to start operating domestic fish farms. The

aim is to replace imports with domestic production. However, GoN replaced that policy proposal

with the current import quota version. Nigeria’s Director of Nigeria’s Federal Department of

Fisheries (FDF) Folake Areola, confirmed that GoN has begun the implementation of the new

import quota policy for fish. At this initial stage, the quota system aims at reducing Nigeria’s

frozen fish import by 25 percent and stopping the import of fish species (such as catfish, tilapia

and croaker) that are produced in Nigeria through local aquaculture and capture fisheries (Nzeka,

2014).

Director Areola also stated that the GON did not propose an import ban as widely published by

local media late last year and may consider importers’ request for a review to free croaker for entry

as the croaker fish species is not farmed in Nigeria and its local capture is very limited. GoN had

consulted with the Association of Fish Suppliers of Nigeria (AFISUN) members to work out a

revised quota. The fish to be imported could be any species other than those (catfish and tilapia)

indicated earlier as not permitted for imports. Reports from AFISUN sources indicate that the GoN

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and importers have settled on an annual baseline fish import figure to be at 700,000 tons and to set

the quota for 2014 at 500,000 tons, representing a 25 percent reduction against the new baseline

figure. A majority of the importers were reported to show satisfaction with the new quota policy,

indicating that it would assist with minimizing sharp marketplace practices which had provided

advantages to a few larger controlling importers (Nzeka, 2014).

2.9.4 Fish Trade and Food Security

The important contribution of fisheries to human well-being is frequently underestimated. Not

only do fisheries generate employment for millions, but fish provides vital nutrition to billions and

is often essential to the diet of the poor (World Bank, 2012). FAO states that “food security exists

when all people, at all times, have physical, social and economic access to sufficient, safe and

nutritious food that meets their dietary needs and food preferences for an active and healthy life”

(FAO, 2012). Food insecurity can cause under nutrition, which results in mortality, morbidity,

stunting and wasting but can also cause micronutrient deficiencies, which result in impaired

immune functions, cognitive development, growth, reproductive performance and work

productivity. The distinction between under nutrition and micronutrient deficiencies is important

because while undernourishment can be improved by increasing energy intake, the problem of

micronutrient deficiencies is of a different nature as it results from an inadequate quality and

diversity in diet (FAO, 2013).

Direct consumption of fish for food provides a vital source of protein and a variety of essential

fatty acids and micronutrients, such as iron, zinc, vitamin A and others. These micronutrients are

particularly rich in smaller sized fish that are often more readily available to low income, at risk

populations due to cheap cost and abundant availability. Fish are an especially important source

of food and nutrients due to the fact their seasonal availability is often different from crops,

meaning that fish can help to reduce seasonal vulnerability, particularly in rural communities

(Kawarazuka, 2010).

The issue of trade’s contribution to food security is clearly a complex one, with numerous studies

attempting to explore the pathways between the economic driver of trade to its impact on food

security and undernourishment in local communities. Indirectly, domestic and international fish

trade can increase food security through employment and income generation, which can be utilized

28

to purchase food commodities, including lower cost staple foods. Domestic trade also makes fish

much more available and accessible to local populations for consumption. In terms of international

trade, it is known that fish exports are a major source of income for developing countries. These

exports can generate foreign exchange as well as create employment and income in the primary

and secondary sectors. Imports of fish will tend to increase domestic food supply and, if anything,

keep prices down (FAO, 2013).

2.10 INFORMAL CROSS BORDER TRADE (ICBT)

Informal cross-border trade (ICBT) is generally defined as the illegal transport of goods and/or

persons in or out of a country to avoid taxation (Njoku 2010) and is thriving almost everywhere in

Africa, including in West Africa (Golub, 2015). This trade cuts across all ages, religion, ethnic

groups and gender and it involves both formal and informal trade. Informal trade is an integral,

but unrecognized component of Africa’s economy (Jawando et al. 2012). Intra-regional informal

trade is mainly conducted by individual traders (a large proportion of which are women) and micro,

small and medium-sized enterprises and often consists of small consignments. Some of these

traders operate entirely outside the formal economy; others are registered domestically yet escape

fully or partially trade-related regulations and duties. They avoid official border posts or pass

through such posts yet resort to illegal practices such as under-invoicing, misclassification of

goods and mis-declaration of country of origin (OECD, 2009).

ICBT developed in the aftermath of the 1980’s economic crisis in Africa. It has been ongoing for

several years and is an important cash-earning activity (Njikam and Tchouassi, 2011). The current

economic and socio-political environment of sub-Saharan Africa has forced an increasing

percentage of sub-Saharan African’s to seek alternative livelihood strategies, some of which

include high-risk activities, often time these alternatives include cross-border trading and

migration to neighbouring states for trading activities (IOM Southern Africa Newsletter, 2010).

2.10.1 Opportunities offered through Informal Cross Border Trade

The opportunities offered through Informal Cross Border Trade were related to regional

integration, income and employment opportunities. By contributing to the exchange of regional

29

produced goods, ICBT contributes immensely to the process of regional integration (Njikam and

Tchouassi, 2011). ICBT as a form of employment plays a vital role in alleviating poverty. It is a

vital source of livelihood for the poor and an important component of Africa’s economy

contributing immensely to the economy of Africa, Particularly in terms of economic upliftment of

women, food security, regional economic trade and social integration (Matsuyama, 2011). Others

include generation of government revenue through payment of duty, license fees; passport fees

and supports road transport industry. Informal cross-border traders make an important contribution

to economic growth.

2.11 FISH MARKETING SYSTEM

Fish marketing describes all various activities that ensures the movement of fish from the point of

catching/harvesting, to processing and ultimately to the point of final consumption. It is important

to evaluate marketing systems of fish because they indicate how the various market participants

are organized to accomplish the movement of the commodity from the producer to the ultimate

consumer (Olukosi et al., 2007). The movement of fish from the point of production either capture

or culture to the final consumer requires an effective and profitable marketing system. This is

important to ensure that fish in all its forms get to the consumers at the right place and best possible

time. Agricultural production and fish marketing must develop hand in hand because they are

partners in a progressive system (Iliyasu et al., 2011).

Nigerian fish market is characterized by indigenous mechanism depending on season, fish species,

ability of buyers to bargain and of course the concept of demand and supply. It is important to

know how the market is sustained and describe the socio-economic characteristics of participants

to be able to aid policy makers in their management decisions (Kainga and Adeyemo, 2012). The

role of fish marketing in developing countries changes with its economic development and as a

country develops, the structure of its urban fish marketing evolves (Agbebi and Fagbote, 2012).

About 90% of fish produced in Nigeria is sold in the local market as a cheap source of protein to

the growing population and fish is made up 40% of dietary protein consumption in the country

(Kainga and Adeyemo, 2012).

30

Research development and investment effort have often been focused primarily on production.

Production increase without a well-developed marketing system lead to all possible gains from the

production effort going into the drains of post-harvest losses. Often times, marketers are compelled

if not forced to sell their product at a very low price to avoid huge wastage or total loss and this

reduces their marketing margins and marketing efficiency (Esiobu and Onubuogu, 2014). Hence,

it becomes imperative to determine the structure, effectiveness and efficiency in the marketing

system of fish.

2.12 FISHERIES VALUE CHAIN

The concept of Value Chain when applied to fisheries and aquaculture simply refers to all the

activities and services- from input supply to production (capture fisheries and aquaculture

farming), processing, wholesaling and finally retailing. It is so called because value is being added

to the product or service at each step (Parke, 2014). Value chain actors are those who deal directly

with the production, processing, packaging, trading etc. of a product. Usually they own the product

for a certain time as it travels along the chain (CYE Consult, 2009). Some of the objectives of fish

value chain studies include: identifying the various actors, their functions and existing linkages;

determining value-increasing opportunities; assessing the input-output structure and the

distribution of margins and return on investment along the chain; and analyzing the constraints

and opportunities in the value chain including the role of different socioeconomic groups such as

women and the poor (Shamsuddoha, 2007; Ardjosoediro and Neven, 2008; Dubay et al., 2010;

Gordon et al., 2011).

Value chain analysis is a means of appraising a market structure by describing the full range of

activities required to bring a product or service from conception, through the intermediary phases

of production (involving a combination of physical transformation or value addition) to delivery

of the product to the final consumer (Christensen et al., 2011). There are many ways to analyze or

evaluate a value chain. Analysis can stem from research of secondary information such as

government or industry data, to interviews with industry participants. It can also be derived from

participatory market assessments and market observations (Weber & Labaste, 2009). The post-

harvest handling of agricultural produce is an important component of value chain development,

and a catalyst for progressive and sustainable expansion of agribusiness, investment and agro-

31

processing activities, thereby eradicating waste and ensuring import substitution, food security,

wealth creation, employment generation, human capital development and security of human life

and property (FMARD, 2016).

2.13 FISH MARKETING NODES

Marketing of fish passes through various market participants and exchange points before they

reach the final consumers (Ali et al., 2008). The marketing system operates through a set of

intermediaries performing useful commercial functions in a chain formation all the way from the

producers to the final consumers. A value chain node is a point in the value chain where a product

is exchanged or goes through major transformation while a market segment is a “vertical chunk”

of value chain between two nodes (Bolwig et al., 2010). There exists a great potential of fish

resources in Nigeria whose distribution and value chain needs to be strengthened and developed

to bridge the gap between demand and supply of fish in Nigeria.

A study carried out by Phiri et al. (2013) to examine the nodes that are along Oreochromis species

(Chambo) value chain revealed a typical Chambo value chain nodes of production, wholesaling,

retailing and consumption. Odebiyi et al. (2013) in their study to evaluate the coastal fisheries

value chain identified three major marketing nodes including: fishermen, fish processors and the

fish marketers, along the coastal area of Ogun Waterside Local Government Area (LGA), Nigeria.

2.13.1 Production

Fish production involves the harvesting of fish from water bodies and fish farms by capture

fishermen and fish farmers (fish producers). The markets in this tier are located near the water

bodies where the fish (product) comes from. For instance, commercial fishing companies maintain

markets at wharfs and other facilities near the shoreline. The purpose of maintaining such locations

that are close to the shoreline is to ensure ease and convenience of transporting the fish, shellfish

and seafood from the shipping vessels to the place where buyers from the next tier typically go.

Fish farmers typically use ponds, tanks and other artificial means of containing fish. The markets

of fish farmers can have various locations including suburbs or even the city center. These markets

are concerned mainly with the sale of fish in large amounts per buyer (Thompson, 2015).

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2.13.2 Processing

Fish processing provides diversified employment opportunities in fishing communities. Lem et al.

(2014) asserted that processing is done either at the small-scale level using traditional techniques

(usually only in developing countries) or at the industrial level as factory workers (common in

both developing and developed countries). Fish are not normally consumed the way they are

produced. Their original forms are changed to forms which can give maximum satisfaction to

different classes of consumers (Umoinyang, 2014). In Nigeria, smoked fish products are the

commonest form of fish products for consumption. Out of the total 194,000 metric tons of dry fish

produced in Nigeria, about 61% of it was smoked (Adeyeye et al., 2015).

The processing node in the value chain therefore consists of farmers who integrate processing as

part of the farm setup, retailers especially women who process fish using the traditional methods

of smoking fish which not only preserves the shelf life of the fish but also attracts better price and

farmers who specifically operate processing plants to process fish that are sold at the local markets

and to restaurants. In this regard, processed fish could be frozen, smoked, dried, and spiced

(Omonona and Ajani, 2014). In general, majority of women take part in the processing and

marketing nodes of the fishery value chain owing largely to social and cultural norms, which have

generally reduced women’s access to resources and their decision-making power (Lem et al.,

2014).

2.13.3 Marketing

Marketing is the management process responsible for identifying, anticipating and satisfying

customer requirements profitably (Chartered Institute of Marketing, 2015). Marketing of fish could

be regarded as the performance of all business activities involved in the flow of fish from the point

of production (fisherman or fish farmer) to the final consumer (Olukosi et al., 2007). The fish

marketing node in the value chain comprises those who sell fish at both retailing and wholesaling

modes to the final consumers (Omonona and Ajani, 2014). These wholesalers/retailers either

collect fish directly from landing points themselves or are supplied by other distributors. The use

of wholesalers and retailers (intermediaries) between producers and consumers tremendously

improve the marketing and distribution of agricultural products. The function of wholesalers and

retailers is very crucial to efficient fish marketing. As asserted by Enete (2008), the efficiency of

33

marketing system gets better as the number of intermediaries increases and vertically differentiate

with specialized functions like wholesale and retail.

2.14 FISH MARKETING CHANNEL

Marketing channel is simply the path of a commodity from its raw form to the finished product or

the path of a product as it moves from the production to consumption. Assessment of fish

marketing channels is important in evaluating fish marketing system because they indicate how

the various market participants are organized to accomplish the movement of a fish and fish

products from the producer to the final consumers. Marketing channel is not only instrumental in

facilitating the physical flow of goods, but it is also the structure through which much marketing

effort is channeled to buyers (Ismail et al, 2014). Fish being a highly perishable substance needs

to be transported to the consumer or final user in time (Ali et al, 2008) through a coordinated

marketing channel to avoid post-harvest spoilage.

Marketing channels are classified as either centralized or decentralized. A centralized marketing

channel is one in which commodities are assembled in large central terminal market where they

are purchased by wholesalers or processed or from farmer agent, while decentralized channel does

not have such large assembly-marketing facilities and traders buy directly from farmer. Centralized

channels deals with agents who serve as middleman between producers and consumers while

decentralized is a kind of channel where both consumers and agents can buy, directly from the

producers (Madugu and Edward, 2011). According to Adeosun and Adebukola (2012) marketing

channels can be identified using the respondents and the route through which fish was transferred

from producers or wholesalers to consumers. According to Ismail et al. (2014), analysis of

marketing channel provides a systematic knowledge of the flow of goods and services from their

origin (producer) to the final destination (consumer). Along the channel are agents who perform

physical functions in order to obtain economic benefit.

Figure 2.3 shows the marketing channel for fresh and dried fish in Maiduguri Metropolis of Borno

State, Nigeria. The channel is divided into two parts for fresh and processed fish (Ismail et al.,

2014).

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Figure 2.3: Marketing channel for fresh and dried fish in Maiduguri Metropolis of Borno

State, Nigeria.

Source: Ismail et al. (2014)

35

Wholesalers and retailers of fresh fish are located on the upper part of the channel followed by

fresh fish processors who also sell the processed fish. The raw/fresh fish processors buy from the

wholesalers and sell through commission agents or directly to wholesaler of already dried fish,

who then sell to the retailers and consumers. There are also retailers of raw fish who buy raw fish

from producers and wholesalers, processed it through fish processors, before selling to the

consumers. On the lower part of the channel are wholesalers of dried fish who use the services of

commission agents to buy from fish processors who are wholesalers of processed dried fish or buy

directly from the processors and sell to retailers and consumers (Ismail et al., 2014).

2.15 FISH PRESERVATION, PROCESSING AND PACKAGING

One of the greatest problem affecting the fishing industry all over the world is fish spoilage.

Attempts have been made to reduce fish spoilage to the minimum through improved preservation

techniques. Preservation and processing methods explore ways by which spoilage are stopped or

slowed down to give the product a longer shelf life (Adeyeye et al., 2015). According to Akegbejo

(2007) fish preservation is a method of keeping fish from changes in texture, taste and appearance.

A study conducted in Niger Republic revealed that salting and smoking of fish were the popular

fish preservation and processing techniques (Kassali et al., 2011). Similar studies also showed that

salting, smoking, refrigeration and sun-drying were among the major fish processing measures

(Nwabueze and Nwabueze, 2010; Akankali and Jamabo, 2011; Madugu and Edward, 2011).

Further studies showed that in Liverpool market of Lagos State, smoked fish was the sole

processed fish marketed constituting about 65% of all fish marketed both fresh and processed

(Ayo-Olalusi, et. al, 2010). Kainga and Adeyemo (2012) reported from their study in Bayelsa State

that smoking, refrigeration and salting were major methods of fish processing and preservation.

Packaging forms an important part of food processing and marketing because it facilitates handling

during storage and distribution within the value chain. Effective packaging will prolong the onset

of spoilage in processed fish products. Jute bags, sacks, paper cartons, wooden rackets and bamboo

baskets, polythene bags are commonly used as packaging containers. Means of transportation

ranges from wheel barrows, motorcycles, taxis, jeeps, pick-up vehicles, buses, trucks, lorries etc

(Abolagba and Nuntah, 2011).

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2.16 THEORETICAL MARKET MODELS

In analysing market structure, three theoretical market models are often used. These are the

perfectly competitive market, oligopolistic market and monopolistic market (Suleiman, 2007).

Markets may exhibit a free entry and exit characteristics; hence referred to as perfect market

structure. Perfect competition is an economic model of a market possessing the following

characteristics: each economic agent acts as if prices are given, that is, each acts as a price taker.

In other words, no large firm or group of firms dominates buying and selling. The product being

sold is considered a homogenous good. Product differentiation does not exist. There is free

mobility of all resources, including free entry and exit of business firms (Suleiman, 2007). In this

scenario, market demand and supply side remain the key determinants of the market outcome in

terms of pricing, product quality, variety and functional characteristic. On the other hand, the

market may exhibit purely monopolistic structure where supply side enjoys the majority command

to production and supply of products in the entire market niche (Onyango, 2013).

As opposed to a competitive market structure where all market players are presumed to operate

and grow in an environment with unconditional freedom, monopoly structure has a conditional

institutional framework that in many cases does not favor majority of the market players (Onyango,

2013). Pure monopoly exists when there is only one seller (producer) in the market. There are no

direct competitors or rivals in either the popular or technical sense. Barriers to entry prevent other

potential competitors from selling in this market. However, pure monopoly is undermined if the

policies of a monopolist are constrained by the indirect competition of all commodities for the

consumer's money and of reasonably adequate substitute goods, and by the threat of potential

competition if market entry is possible (Suleiman, 2007). The deviation of market structure from

the perfect competitive framework may result to a decline in market inefficiency; given that at

society level, market are key platforms for ‘creation of wealth.’ This is because, monopoly reduces

competition and the entire market remains a ‘one-man show’ where created wealth does not flow

to all the beneficiaries in equitable ration (Onyango, 2013).

Oligopoly is said to exist when more than one seller is in the market but when the number is not

so large as to render negligible the contribution of each. A typical oligopoly exists when, for

example, three firms control over 50% of all sales of a particular good in a particular market and

certain barriers prevent potential competitors from entering the market (Suleiman, 2007).

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2.17 ANALYSING FISH MARKET STRUCTURE

Market structure analysis emphasizes the nature of market competition and attempt to relate the

variables of market performance to types of market structure and conduct. Market structure is a

description of the number and nature of participants in a market. If the structure of a market is that

of monopoly rather than pure competition, then one could expect poor market performance (Garba

et al., 2015). The set-up of the market consists of the degree of concentration of buyers and sellers’

integration, product differentiation and the degree of competition between buyers and sellers

(Ismail et al, 2014). The salient aspects of market structure include the degree of seller and buyer

concentration and competition, the degree of product differentiation, and the conditions of entry.

These elements measure the extent of deviations from the perfectly competitive norm. The larger

the deviation, the more imperfectly competitive is the market, that is, an extreme case would be

monopoly (Suleiman, 2007).

2.17.1 Market Concentration

The degree of concentration of buyers and sellers’ integration is an aspect of market set-up (Ismail

et al, 2014), hence an important variable in market structure analysis. Concentration of

establishment in the hands of a few firms in an industry is generally criticized on the grounds of

competition loss (APEC, 2008). A market is said to be more concentrated when there are fewer

number of firms in production or the more unequal the distribution of market share. The higher

the concentration level in an industry, the higher would be the degree of monopoly and absence of

competition. Nonetheless, high concentration brings greater innovation and technological change

and thus the benefits associated with it may perhaps be sufficient to offset the adverse monopoly

effects of high concentration (APEC, 2008).

Gini coefficient and the Herfindahl index are concentration indices that are used to analyse market

structure. Both utilize market shares to determine the extent of market concentration. According

to Garba et al. (2015), Gini coefficient is a measure of statistical dispersion. It measures the

inequality among values of a frequency distribution. A Gini coefficient of zero expresses perfect

equality where all values are the same (for example equal possession of share of a particular

product). Gini coefficient of one (100 on the percentile scale) expresses maximal inequality among

values (for example where only one person has the entire product to be measured). In practice,

38

both extreme values are not quite reached. A low Gini coefficient indicates a more equal

distribution, with 0 corresponding to complete equality, while higher Gini coefficients indicate

more unequal distribution, with 1 corresponding to complete inequality (Garba et al., 2015). The

Gini coefficient summarizes the Lorenz curve which compares the cumulative shares of the

product ordered from small range to the large shares of the product that would accrue to the sellers

and the producers under perfect equality (the diagonal) and the total area under the line of perfect

equality (Enibe et al., 2008).

Agom et al. (2012) in their study carried out to evaluate wholesale frozen fish market in Calabar,

Cross River state, Nigeria used herfindahl index to measure the concentration of the market. The

result showed that wholesale frozen fish market structure is perfectly competitive with Herfindahl

index of 0.211. The value of the Herfindahl index estimated was 0.05 in the study carried out by

Oparinde and Ojo (2014) in Ondo state, which implies some degree of concentration in the

artisanal fish market. Higher Gini coefficient means higher level of concentration and

consequently, high inefficiency in the market structure (Adeleke and Afolabi, 2012). Adeleke and

Afolabi (2012) further indicated Gini coefficient value of 0.5292 for fresh fish market in Ondo

State, Nigeria, which shows high level of concentration and consequently high inefficiency in the

Ondo State fish market structure. In the analysis of the market structure of dried fish in Maiduguri

metropolis, Borno state, Nigeria, Ismail et al. (2014) reported Gini coefficient of 0.5478 and

0.5252 for wholesalers and retailers, respectively. Oparinde and Ojo (2014) determined an

estimated value of Gini coefficient as 0.64, indicating the presence of inequality in the share of the

artisanal fish market in Ondo state.

2.17.2 Product Differentiation

Product differentiation refers to goods of the various sellers in a market whether heterogeneous or

homogenous. It could be differentiated in terms of appearance and/or name. The product

differences may exist in terms of flavour, taste and preparation methods. Fish is available in the

market in different forms like fresh, frozen, canned, smoked or dried form (Mshelia et al., 2007).

Differentiation strategy would provide greater scope for these organizations to produce products

with more valued, desirable features as a means of coping with demands (Dirisu et al., 2013).

39

2.17.3 Barriers to Entry

According to World Food Programme (WFP, 2011) barriers to entry and exit prevent the rapid

turn-over of actors in a given activity. For example, high interest rates resulting in expensive

capital may pose a barrier to entry for potential commodity processors, while anaemic wage labour

markets might pose a barrier to exit for poor smallholder farmers who wish to stop producing low-

margin staple crops but have few alternative income opportunities.

Barriers to entry are used by existing firms as an advantage over new entrants that might potentially

produce in a given market. For example, the production cost which must be borne by the potential

entrant into the given market and not by existing firms. According to Suleiman (2007), potential

entry barriers exist due to demand conditions, including product differentiation and price elasticity;

control over input supplies; legal and institutional factors; scale economies; capital requirements;

and technological factors. Two barriers to entry that are often of critical importance in developing

countries-given relative factor endowments developing versus developed countries are capital

costs and scale economies.

2.17.3.1 Capital costs

Capital requirements serve as an entry barrier because only those who can afford such a monetary

outlay can enter the market. In fish marketing, initial capital costs include equipment (the type of

which may vary from one fishery to another, daily operating capital, and loanable funds. Initial

investment costs can be compared to average disposable incomes from other sources of livelihood;

that is, fishing, farming, processing, to determine the prospects of attracting potential entrants

(cited in Suleiman, 2007). Initial capital costs of investment could pose a restrictive entry

especially for small-scale businesses.

2.17.3.2 Scale economies

A useful measure for explaining concentration is scale economies. The existence of economies of

scale is a condition permitting relatively large firms to market their products at considerably lower

average costs than smaller firms. Simply stated that a firm will attempt to expand its operations in

order to lower average unit costs and increase profits. To the extent that unit costs are lower for

larger firms, economies of scale are said to prevail. Other firms cannot compete because they are

40

not sufficiently large to capture these economies. It is possible beyond some scale that further firm

size brings no additional unit cost savings (Suleiman, 2007). Marketing costs are the embodiment

of barriers to access to market participation by resource poor smallholder (Gichangi, 2010).

2.18 PRICING

Application of various pricing criteria on sales of fish depend on efficiency with which the

marketing system transmits information among the fish mongers or marketers and consequently,

prices of fish changers as it passes through middlemen such that by the time it reaches consumers,

it becomes expensive (Dolapo, 2011). The price efficiency is concerned with improving the

operation of buying, selling and other connected aspects of marketing process so that it will remain

responsive to consumer direction (Ali et al., 2008). Fish pricing is basically guided by bargaining.

The status of the buyer in terms of appearance and dress may also influence the price of fish.

Price has an important bearing on household purchasing behavior, whether in relation to own-price

elasticity or cross-price elasticity (Gordon et al., 2013). Change in price and income affects

demand on food. If the price elasticity of demand is between zero and -1, demand is considered

inelastic as a price change has little impact on quantity demanded. If, on the other hand, the price

elasticity of demand is less than -1 (greater than 1, in absolute value), demand is said to be elastic.

A price elasticity of demand of -1 is a focal point. A good with constant budget share and no

substitutes will have a price elasticity of demand of -1, so that a 1 percent increase in the price will

lead to a 1 percent reduction in the quantity demanded and vice versa. The value of a market in

terms of total revenue is at its highest when the price elasticity is -1. If the supplied quantity

increases above the level that gives a price elasticity of demand of -1, the value of the market will

fall. Finally, the more elastic the demand for the good, the greater substitution possibilities there

will be and therefore the keener the competition (Lem et al., 2014). Marketing is value-adding

activity that provides place, time and form utilities. The final delivered price of a product will

almost often depend on the cost of the marketing functions performed in getting the product across

to end-users from the producers.

41

2.19 ANALYSIS ON COSTS AND EARNINGS

Costs are classified into variable or fixed costs. Variable costs are costs that vary in proportion

with level of output. On the other hand, fixed costs are costs that are independent on the level of

output. And by comparing revenues with costs, the analysis reveals how much different actors earn

from their businesses (Bui Nguyen, 2011). Total cost of the final product sold to the final customer

is constituted of added costs incurred by different chain actors. Added costs are computed by

extracting from the total cost the purchasing price paid from the previous level in the value chain.

Added costs reflect efforts of different chain actors in adding values to the final product (Bui

Nguyen, 2011). Marketing costs represent the cost of performing various marketing functions

which are needed to transfer a commodity from the place of production to the final consumers,

such as cost of labour, storage, preservation, etc. Transport costs are incurred by farmers when

they take their produce to the market and by traders as they move the produce down the marketing

chain to the consumer (Shepherd, 2007).

The revenue (or retail price) is made up of marketing margins belonging to different actors in the

value chain. Marketing margin is the difference between selling price paid by the next stage and

purchasing price paid to the previous stage. Therefore, the marketing margin reflects the

distribution of revenue to different chain actors. Finally, profit from selling the final product to the

final customer comprises of profits accruing to different chain actors (Bui Nguyen, 2011).

2.20 MARKET INTEGRATION

One of the most technically complex yet broadly applicable areas of investigation for market

analysis is the study of market integration, often reduced to price integration. When markets are

integrated, two conditions exist: prices are correlated, i.e. they move in tandem with one another,

but at different levels that are determined by transaction costs (necessary yet insufficient condition

of market integration); commodities flow between markets, i.e. markets are integrated through

trade, which triggers price transmission from one market to another (necessary and sufficient

condition of market integration). Even though prices may be correlated, this does not necessarily

mean that markets are integrated, because of unobserved factors that may be driving the

relationship (World Food Programme, 2011).

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2.21 FISH MARKETING MARGIN

A marketing margin is the percentage of the final weighted average selling price taken by each

stage of the marketing chain. The margin must cover the costs involved in transferring produce

from one stage to the next and provide a reasonable return to those doing the marketing. “Margins”

are often used in the analysis of the efficiency of marketing systems (Shepherd, 2007). As fish,

like any other production moves closer and closer to the ultimate consumer, the selling price

increases since the margins of the various intermediaries and functionaries are added to it. These

market intermediaries are the wholesalers and retailers. Both play important roles in the marketing

system. Market margin if not perfect and static is also measure of market performance. Marketing

margin is the difference between buying and selling prices (Suleiman, 2007). In competitive

markets, the margin achieved should be commensurate with the cost of services rendered

(Suleiman, 2007). Every category of middlemen in fisheries value chain earns a sort of margin for

the duties performed in the marketing channel.

According to Madugu and Edward (2011) marketing margin depicts the ratio that determines the

gap between producer and consumer prices. In their study of the marketing and distribution

channel of processed fish in Adamawa state, Nigeria, the market margin was found to be 39.8%.

This margin is high, thus they concluded that marketers in the study area are making profit. Iliyasu

et al. (2011) reported a market margin of 40%, which could be attributed to less marketing

functions performed when they investigated the economics of smoked and dried fish marketing in

Yola North and South Local Government areas of Adamawa State, Nigeria. Offor et al. (2013)

budgetary analysis for fresh fish marketers in Port Harcourt Municipal, Rivers State, Nigeria

revealed that the weekly average profit made from fresh fish marketing was ₦11,053.00 and

marketing margin was 28.6%.

2.22 MARKETING EFFICIENCY

Marketing efficiency may be defined as the degree of market performance (Bagchi and Raha

(2011). The market mechanisms have to be efficient to be able to play the role of propelling yield.

An efficient market system is one that provides satisfactory and cheap services to consumers or

one that maximize the ratio of input and output of marketing (Esiobu and Onubuogu, 2014). An

43

efficient marketing system apart from stimulating production also accelerates the pace of economic

development and is an important way of raising farmers‟ income levels as well as consumers‟

satisfaction levels (Bagchi and Raha, 2011). Increasing productivity and efficiency within the sub-

sector of agriculture particularly among small-scale fish producers requires a good knowledge of

the current efficiency or inefficiency inherent in the sector as well as factors responsible for this

level of efficiency or inefficiency (Agom et al., 2012).

Nwaru et al. (2011) stated that an efficient marketing system ensures that goods which are seasonal

will be available all year round, with little variation in prices, which can be attributed to cost of

marketing functions like storage, processing, transportation, etc. They further posited that the

effectiveness of the marketing process is assessed by the ability of the market to add value to the

marketed products by creating time, form, place and possession utility. Bassey et al. (2015)

reported marketing efficiency of 674.14% and 787.78% for wholesalers and retailers respectively

in their study of fresh fish marketing and profitability in Akwa Ibom state.

2.23 CONCEPTUAL FRAMEWORK

Figure 2.4 indicates a flow diagram of the conceptual framework for this study. This framework

is a modified structure, conduct and performance framework which provides a visual view of

interactions between fish market participants and the external environmental factors within the fish

marketing chain. At the onset of this framework, the characteristics of the marketing actors such

as sex, religion, age, education level, household size and the structure for fish trade (market

structure, concentration of sellers, pricing method, product differentiation, and pattern for fish

trade) influence the marketing system. Government policies (intervening variable) have a direct

impact on fish market structure, conduct and performance. Positive interaction between

intervening variables and the characteristics of fisheries value chain actors positively dictates

profitability and performance.

44

Dependent Variable Independent Variables

Conduct & Performance

Pricing

Product differentiation

Gross margin

Net returns

Marketing margin

Marketing efficiency

Intervening Variables

Government Policies

Cross border trade

Marketers’ associations

Socio-economic

characteristics

Sex

Age

Household size

Religion

Marital status

Marketing experience

Marketing Nodes

Production

Processing

Marketing

Marketing Participants

Producer

Processor

Wholesaler

Retailer

Market Structure

Concentration

Product

differentiation

Pricing

Barriers to entry

Figure 2.4: Conceptual Framework for the study

45

CHAPTER THREE

3.0 METHODOLOGY

3.1 STUDY AREA

This study was conducted in three geopolitical zones in Nigeria: South-South, North-Central and

North-East. Data were collected from the States along the Nigeria-Cameroon-Chad border area

comprising Akwa-Ibom, Cross-river, Benue, Taraba, Adamawa and Borno states.

Akwa Ibom State occupies part of the South- South region of Nigeria. It has a population of

3,920,208 and a total land mass of 6,900sq km (NPC, 2006). It is located between latitude 4º31’

and 5º53’ North and longitude 7º25’and 8º25’ East of the Greenwich meridian and comprises of

31 Local Government with Uyo as the State capital. The major occupation of the people is fishing,

farming and trading. Akwa Ibom State has a coastline of 129 km, is one of the six maritime states

in Nigeria. The state has a total effective shelf area of 8,005 km and a generous supply of rivers

and floodplains, estuaries, creeks, and mangrove swamps (Essen, 1990). There are many inland

and coastal rivers and deltas together with its southern part being bounded by the Atlantic Ocean,

a region often referred to as the Bight of Benin. The major rivers in the state are lower Cross, Qua

Iboe and Imo Rivers (Ekpo and Essien-Ibok, 2013).

Cross River is a coastal state named after the Cross River, which passes through the state. It is

located on Latitude 5o250N and longitude 25000E. Cross River State is bounded on the North by

Benue State, South by Bight of Bonny and in the East by Ebonyi and Abia States, while in the

West by Republic of Cameroun (Menakaya and Floyd, 1978). Cross River State has the largest

rainforest covering about 7, 290 square kilometers. It is described as one of Africa’s largest

remaining virgin forest harboring as many as five million species of animals, including insects and

plants. The state is located within the evergreen rainforest zone. There are two distinct climate

seasons in the area, rainy season, from March to October and dry season from November to

February. The annual rainfall varies from 2, 942mm to 3, 424mm. The average temperature is

about 28oC. Cross River State is characterized by the presence of numerous ecological and zoo-

geographically important high gradient streams, rapids and waterfalls. Fishing and subsistence

46

agriculture are the main occupations of the people. Crops grown in the locality include rice, maize,

yam, cassava, pineapple, plantain, banana, oil palm, rubber and cocoa among others (Agbor, 2007).

Benue state lies between latitudes 6-8/N of the equator and longitudes 6-10/E of the Greenwich

meridian. The state is bounded in the north by Nasarrawa State, in the south by Cross River and

Enugu States, and in the east and west by Taraba and Kogi states respectively. The state is

acclaimed as “Nigeria’s food basket,” because of its rich and diverse agricultural produce and

supplies which include: yams, rice, cassava, sorghum, etc. The state also accounts for over 70% of

Nigeria’s soybean production. Benue state has about 67,740 sq km with population of about

4,219,444 persons (NPC, 2006). River Benue is the most important geographical feature

promoting fishing activities. The river has an approximate surface area of 129,000 ha and an

estimated length of 1.4×103 km with flood plains surface area of about 181,000 ha. It has a drainage

area with annual rainfall that varies from 120 in the upper reaches of the Katsina-Ala River to 35

in the middle course of the Adamawa River (Ogbeba, 2009). Annual rainfall ranges between 150-

189 mm with its peak in May/June and September. The temperature ranges between 35 and 21°C

(Ezihe, 2013).

Taraba state is situated in the North-Eastern part of Nigeria and occupies 54,473 square kilometers.

The state is bounded in the West by Plateau, Nassarawa and Benue states, on the eastern border

by Adamawa state and the Republic of Cameroon, and on the northern border by Gombo state.

Rivers Benue, Donga, Taraba and Ibi are the main rivers and rise from the Cameroon Mountains,

straining almost the entire length of the state in the North and South direction to link up with the

River Niger. The major occupation of the people of Taraba state is agriculture. Communities living

on the banks of River Benue, river Taraba, river Donga and Ibi engage in fishing all year round

(NigeriaGalleria, 2015).

Adamawa State has a land area of 38.741km2 lying roughly between latitudes 7o and 11o North

and between longitudes 11o and 14o East of the Greenwich meridian (Adebayo, 1999). It has an

annual rainfall that ranges from 700mm to 1600mm with a mean monthly temperature range of

26.7oc to 27.8oc. The Major occupations of the inhabitants includes fishing, processed fish is a

major economic activity in the area. Rivers and lakes found in the state include river Benue,

Gongola, Chochi and Njuwa Lake (Madugu and Edward, 2011).

47

Borno State located in the North-eastern part of Nigeria. It lies between latitudes 12o00N and

14o00N and longitudes 10o00E and 14o00E. Within the north-east, the State shares borders with

Adamawa State to the south, Yobe State to the west, and Gombe State to the southwest. It also

shares International borders with the Republic of Niger to the north, Chad to the north-east and

Cameroon to the East. The state has an area of 75,540 km2 and 27 Local Government Areas spread

over four major agro-ecological zones. Agriculture is the main stay of the State’s economy (Ahmed

et al., 2015). The map of the study area is shown in figure 3.1.

3.2 DATA SOURCE

Primary data were collected with the use of a structured questionnaires and interviews with the

assistance of enumerators that are fluent in the local dialect of the respondents. The population of

the study includes producers, marketers and processors in the States along the Nigeria-Cameroon-

Chad border. Secondary data were sourced through comprehensive desk review of documents and

facts papers on fish trade activities, trade records and other documents useful for this study.

3.3 SAMPLING PROCEDURE AND SAMPLE SIZE

Snow ball sampling technique was adopted to select a sizeable number of producers, wholesalers,

retailers and processors of fish and fishery products from each of these boundary states. The

selection of the communities was based on fishing and fish marketing intensity and communities’

acceptance for the research to be conducted. Field observation and direct oral interviews were also

conducted to supplement the data collected in the questionnaires. The thirty-three (33) Local

Government Areas (LGA) selected for this study are: Ikot Ekpene, Eket, Uyo, Nsit Ibom, Obot

Akara, Ikot Abasi, Ibesikpo, Mbo, Itu and Ibeno in Akwa Ibom State; Calabar municipal,

Odukpani, Akpabuyo, Bakassi and Calabar South in Cross River State; Makurdi, Guma, Gboko

and Kwande in Benue State; Ibi, Lau and Jalingo in Taraba State; Demsa, Yola Vorth, Fufore,

Girei, Yola South and Shelleng in Adamawa State; Abadam, Kukawa, Jere, Maiduguri metropolis

and Ngala in Borno State.

48

Figure 3.1: Map of Study area showing the Local Government Areas

49

The sample size from each of the sampled State was 150 respondents comprising 50 producers

(both capture and culture), 50 processors and 50 marketers, making a total of 900 respondents from

the six States along Nigeria-Cameroon-Chad border.

3.4 QUESTIONNAIRE DESIGN

The instrument used to collect the primary data for this research from fish producers, processors

and marketers in the study area is a structured questionnaire categorized into eight sections as

revealed in appendix 1.

Section A covered the demographics and socio-economic characteristics of the respondents

such as age, sex, marital status, religion, household size, highest education, major

occupation of the respondent and their other sources of income;

Section B comprised of information on the respondent’s location in terms of country,

geopolitical zone, agricultural development project (ADP) zone, and village;

Section C collected data on fishermen and fish farmer operation;

Section D dealt with the market structure- the forms of fish sold, the class of market in

which the respondent operates, the business process operated by the respondent, the

duration of marketing experience, price mechanism and its determinants, and membership

in market association;

Section E contained data on fish marketing nodes, modules used to sell fish, and the

quantity of fish bought at each marketing node;

Section F entailed the aspects of distribution and marketing, the species and forms of fish

purchased and sold by the respondent including the fixed and operational costs incurred in

the business operation and the revenue accrued in a month;

Section G comprised of data on informal cross border trade and Section H collected

information on other marketing costs.

3.4.1 Validation of Questionnaire

The questionnaire was reviewed by face validity. The statements in the instrument were

thoroughly examined by lecturers of the department of aquaculture and fisheries management and

department of agricultural extension and rural development. Field officers in the State Department

50

of fisheries in the study area were trained and mobilized as enumerators to administer the

questionnaires.

3.5 MEASUREMENT OF VARIABLES

3.5.1 Independent Variables

The socio-economic characteristics of the actors operating along the fish trade routes, the

marketing nodes for fish trade and the structure of fish marketing in the States along Nigeria-

Cameron-Chad border and cross-border trade made up the independent variables of this study.

3.5.1.1 Socioeconomics Characteristics of actors in the marketing nodes

Sex: Male or Female (Nominal level)

Age: Actual age in years (Interval level)

Marital Status: Single, Married, Divorced, Widowed (Nominal level)

Religion: Christianity, Muslim and Traditionalist (Nominal level)

Household head: Yes or No (Nominal level)

Household size: The number of persons, both male and female, living under the care of the

respondents as at the time of field survey (Interval level)

Highest Education: Primary, Secondary, Tertiary, Qu’ranic and Informal education

(Ordinal level)

Main Occupation: Producer, Processor and Marketer (Nominal level)

Years of marketing experience: Range of years spent in fish marketing opertaions; less than

1 year, 1-5 years, 6-10 years, 11-15 years and more than 15 years.

Membership of marketers’ association: Yes or No (Nominal level)

3.5.1.2 Marketing nodes

The marketing nodes for fish trade in the study area was determined from field observation of fish

marketing activities. Each node was identified a point in the value chain where a product is

exchanged or goes through major transformation (Bolwig et al., 2010).

51

3.5.1.3 Market structure

The structure of fish markets in the study area was described based on findings on concentration,

product differentiation, market knowledge and ease of/or barrier to entry or exist (Suleiman, 2007).

3.5.2 Dependent Variable

3.5.2.1 Profitability and Efficiency of the actors in the marketing nodes

Actual values for quantity sold, quantity bought, transportation cost, cost of preservation and

storage, operational cost, capital cost, and revenue were collected (Interval level).

3.6 DATA ANALYSIS

Data collected from the survey were analysed using statistical and budgetary analysis. Quantitative

data was analysed using computer software such as Statistical Package for Social Scientist (SPSS)

to come up with both descriptive and inferential statistics.

3.6.1 Socio-economic characteristics of respondents

Descriptive statistics including tables, charts, and percentages were used to describe the socio-

economic characteristics of actors at each marketing node.

3.6.2 Marketing nodes

The marketing nodes for fish trade along Nigeria-Cameroon-Chad border was described using

charts and tables.

3.6.3 Market structure

3.6.3.1 Concentration

Herfindahl Index (HI) was used to measure the concentration of the market which is one of the

variables of the market structure (Agom et al., 2012). According to Oparinde and Ojo (2014), the

formula for herfindahl index is given thus:

52

Where,

i= 1, 2, 3,… , n

n=number of respondents,

S= share of firm in the industry.

In addition, Gini Coefficient was computed to determine the degree of market inequality or

equality. According to Okereke and Anthonio (1988), Gini coefficient is more precise than Lorenz

Curve. But other researchers like Pomeroy (1989) suggested Lorenz Curve to be as precise as Gini

coefficient. Therefore, Gini coefficient and Lorenz curve were used to have a better assessment of

the structure of fish markets in the study area. The Gini coefficients were computed by using the

following formula according to Okereke and Anthonio (1988):

G = 1 − Ʃ𝑥𝑦

Where,

G = Gini coefficient.

x = Percentage share of each class of seller.

y = Cumulative percentage of the sales.

Gona et al., (2004) showed that the degree of concentration of marketers is indicated by the value

of Gini coefficient. The Gini coefficient value ranges from zero to one. A perfect equality in

concentration (low) of sellers is expected if Gini coefficient tends towards zero, while perfect

inequality in concentration (high) of sellers is expected if Gini coefficient tends towards one. That

is, if Gini coefficient = 1 market is imperfect, and if Gini coefficient = 0 market is perfect and

competitive.

Lorenz curve measures the degree of inequality that exists in the share of the industry’s market

size by its firms and the curve bows outwards towards the southeast when there is inequality in the

market share of the firms (Oparinde and Ojo, 2014). In graphical terms, the Gini index is the ratio

of the area between the Lorenz curve and the line of perfect equality (Garba et al., 2015).

53

3.6.3.2 Product Differentiation

Descriptive statistics using simple percentages were used to analyse the different forms of fish sold

in the markets.

3.6.3.3 Ease of/or Barrier to Entry or Exit

In a perfect competitive market, there is ease of entry or exit by sellers. The market

becomes imperfect when seller’s concentration is not even (imbalance). Scale economies is the

measure that was used to determine entry and exit conditions in the market. It is a measure that

examines the average cost function associated with the sellers’ marketing activities. This was

computed using least square regression of the form (Pomeroy, 1989):

𝑦 = 𝑏0 + 𝑏𝑖𝑥𝑖 + 𝑒

Where,

y = Total cost of marketing per class of seller per month (N)

xi = Number of fish (kg) sold per month

bi = Coefficient of explanatory variables

bo = Intercept

e = Error term

If the coefficient of bi is negative, it means as quantity increases, cost decrease. This increase in

cost could form barrier to entry especially by sellers that are not financially sound.

3.6.4 Profitability and Efficiency of the actors in the marketing nodes

Budgetary analytical tools were employed to analyse the profitability and efficiency of the actors

involved in fish trade in the study area.

3.6.4.1 Gross Margin

It is computed as the difference between the total revenue and total variable cost (Oparinde and

Ojo, 2014).

𝐺𝑟𝑜𝑠𝑠 𝑀𝑎𝑟𝑔𝑖𝑛 = 𝑇𝑅 − 𝑇𝑉𝐶

54

Where,

TR = Total Revenue in naira and

TVC = Total Variable Cost in naira

3.6.4.2 Marketing Margin (M.M.)

This is the difference between the total revenue and purchase cost (Omonona and Udoh, 1999).

𝑀𝑎𝑟𝑘𝑒𝑡𝑖𝑛𝑔 𝑀𝑎𝑟𝑔𝑖𝑛 = 𝑇𝑅 − 𝑃𝐶

Where,

TR = Total Revenue in naira

PC = Purchase Cost in naira

3.6.4.3 Marketing Efficiency (M.E.)

Marketing efficiency is defined as the maximization of the ratio of output to input in marketing

(Olukosi et al., 2005). According to Omonona and Udoh (1999) the efficiency of each market in

performing their functions was given as:

𝑀𝑎𝑟𝑘𝑒𝑡𝑖𝑛𝑔 𝐸𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦 = 𝑇𝑅

𝑇𝐶

Where,

TR = Total Revenue in naira

TC = Total Marketing Cost in naira

3.7 TEST OF HYPOTHESES

3.7.1 Hypothesis I

This study made use of Cobb-Douglas production functional form of the stochastic frontier

production function to analyse the collected data. Battese and Coelli (1995) proposed a Stochastic

Frontier Production Function which has firm effects assumed to be distributed as a truncated

normal random variable, in which the inefficiency effects are directly influenced by a number of

55

variables. This was achieved by using the Frontier 4.1 statistical package. The Cobb-Douglas

functional form was assumed for the operation of the respondents and the empirical stochastic

frontier production model is expressed as (Itam et al., 2014):

𝐿𝑛 𝑌 = 𝐿𝑛𝛽0 + 𝛽1𝐿𝑛𝑋1𝑖 + 𝛽2𝐿𝑛𝑋2𝑖 + 𝛽3𝐿𝑛𝑋3𝑖 + 𝛽4𝐿𝑛𝑋4𝑖 + 𝑉𝑖 − 𝑈𝑖

Where,

Y = Output of respondents in terms of total revenue (N)

X1 = Total purchase cost (N)

X2 = Total marketing cost (N)

X3 = Other operational cost (N)

X4 = Fixed cost (depreciated (N))

Vi = Error factor assumed to be independently and identically distributed

Ui = Technical inefficiency effects

Ln = Natural logarithm

The intercept (β0) and the coefficients of the independent variables which range from β1 to β4 are

parameters to be estimated. The inefficiency effects (Ui) are assumed to be non-negative, half

normal distribution N (0, δ2 u).

The influence of socio-economic factors on the monthly revenue of the marketing actors was

assessed by the Technical Inefficiency model outlined as (Omobepade et al., 2014; Itam et al.,

2014):

𝑈𝑖 = 𝛿0 + 𝛿1𝑍1 + 𝛿2𝑍2 + 𝛿3𝑍3

Where,

Ui = Technical Inefficiency

Z1 = Sex of respondents (Dummy, Female = 2, Male = 1)

Z2 = Age of respondents (years)

Z3 = Highest level of education

δ0-δ3 are the parameters to be estimated.

The inefficiency model and production function were analysed at P < 0.05

56

3.7.2 Hypothesis II

Analysis of Variance (ANOVA) at α0.05 was used to determine the level of significant differences

in the mean monthly revenue, gross margin, marketing margin and marketing efficiency at each of

the marketing nodes and Duncan Multiple Range Test was used for the Post-Hoc test analysis.

3.7.3 Hypothesis III

The equality and inequality in the share of income among actors in the fish markets were measured

using Gini coefficient.

3.7.4 Hypothesis IV

Analysis of Variance (ANOVA) at α0.05 was used to determine the level of significant differences

in the mean monthly revenue, gross margin, marketing margin and marketing efficiency of the

various marketing actors in the different forms of fish markets. Where there was statistical

difference Duncan Multiple Range Test was used for the Post-Hoc analysis.

57

CHAPTER FOUR

4.0 RESULTS

4.1 Socio-economic characteristics of respondents in the marketing nodes

The socio-economic characteristics of respondents in the marketing nodes for fish trade were

analysed in terms of their main occupation- producer, processor and marketer. The results of these

analyses are presented in table 4.1. The percentage of female processors and marketers was more

than the male. Among the processors, women constituted 55.00% and men were 45.00%. In the

category of marketers, women constituted 56.00% and men were 44.00%. However, the

percentage of producers that are male (93.33%) were more than female (6.67%).

The percentage of producers, processors and marketers that fall within the age bracket of 41 and

50 years were 34.33%, 34.00% and 39.67% respectively. A significant proportion of the

respondents were within the age group of 31 and 40 years, 25% of the producers, 25% of the

processors and 32.33% of the marketers. The mean age of the respondents was 43.31±10.19 years

and the modal age bracket is 41-50 years.

The highest percentage of the fish producers (87.67%), fish processors (88.33%) and fish

marketers (85.33%) were married. The percentage of singles among the producers, processors and

marketers were 11.33%, 3.67% and 6.33% respectively. There were no divorced respondents

among producers, however, the percentage of processors and marketers that were divorced are

1.33% and 2.67% respectively.

The distribution of the respondents in terms of religion reveals that majority of them are Christians.

The percentage of Christians among the processors (68.67%) is more across the main occupation

of the respondents. Christianity was a common religion largely practiced among the producers

(61.67%), processors (68.67%) and marketers (63.33%). This category was followed by the

Muslims, reaching a percentage of 38.00% among the producers, 31.33% among the processors

and 36.67% among the marketers. Only one traditionalist was found among the producers.

The position of the actors in their respective households reveals that majority of the producers

(77.33%) and processors (51.67%) are household heads. However, majority of the marketers

(52.33%) are not the heads of their households.

58

Table 4.1: Socio-economic characteristics of respondents in the marketing nodes

Variables Groups Main occupation

Producer Processor Marketer

Freq Percentage (%) Freq Percentage (%) Freq Percentage (%)

Respondent sex Male 280 93.33 135 45.00 132 44.00

Female 20 6.67 165 55.00 168 56.00

Age of respondent ≤ 20years 2 0.67 1 0.33 2 0.67

21-30years 45 15.00 35 11.67 33 11.00

31-40years 75 25.00 75 25.00 97 32.33

41-50years 103 34.33 102 34.00 119 39.67

>50years 75 25.00 87 29.00 49 16.33

Marital Status Single 34 11.33 11 3.67 19 6.33

Married 263 87.67 265 88.33 256 85.33

Divorced 0 0.00 4 1.33 8 2.67

Widowed 3 1.00 20 6.67 17 5.67

Religion Christianity 185 61.67 206 68.67 190 63.33

Muslim 114 38.00 94 31.33 110 36.67

Traditionalist 1 0.33 0 0.00 0 0.00

Others 0 0.00 0 0.00 0 0.00

Household Head No 68 22.67 145 48.33 157 52.33

Yes 232 77.33 155 51.67 143 47.67

Household size ≤ 3 persons 68 22.67 53 17.67 53 17.67

4 - 7 persons 137 45.67 156 52.00 140 46.67

8 - 11 persons 69 23.00 65 21.67 84 28.00

≥12 persons 26 8.67 26 8.67 23 7.67

Level of Education Primary 63 21.00 91 30.33 92 30.67

Secondary 95 31.67 122 40.67 131 43.67

Tertiary 79 26.33 25 8.33 29 9.67

Qu'ranic 57 19.00 51 17.00 39 13.00

Informal 6 2.00 11 3.67 9 3.00

Years of Selling ˂1 year 4 1.33 2 0.67 2 0.67

1-5 years 65 21.67 31 10.33 45 15.00

6-10 years 77 25.67 88 29.33 98 32.67

11-15 years 65 21.67 98 32.67 69 23.00

˃15 years 89 29.67 81 27.00 86 28.67

Membership of

Association

No 146 48.67 103 34.33 97 32.33

Yes 154 51.33 197 65.67 203 67.67

59

The distribution of the household sizes reveals that majority of the producers (45.67%), processors

(52.00%) and marketers (46.67) have a household size of 4-7 persons. This was followed by

respondents having the household size of 8-11 persons, having a percentage of 23.00% among the

producers, 21.67% among the processors and 28.00% among the marketers. Very few of the fish

producers (8.67%), processors (8.67%) and marketers (7.67%) have household sizes of 12 persons

or more than.

The highest level of education of respondents across the marketing nodes is Secondary school

education with a percentage of 31.67% among fish producers, 40.67% among fish processors and

43.67% among fish marketers. The number of respondents with Tertiary education was high

among the producers (26.33%) compared to the other marketing nodes. Very few respondents had

informal education, 2.00% at the production node, 3.67% at the processing node and 3.00% at the

marketing node. This result implies that approximately 79.00%, 79.33% and 84.01% of the fish

producers, processors and marketers had formal education.

There were variations observed in the level of experience of the actors in terms of selling fish. The

percentage of respondents having less than a year of experience in fish marketing among the

producers (1.33%), processors (0.67%) and marketers (0.67%) was very low. Equal percentage

(21.67%) of respondents among the producers had between 1-5 years and 11-15 years of

experience. However, the largest number of respondents having more than 15 years of experience

were the fish producers with a percentage of 29.67%. Among the producers, processors and

marketers, 77.01%, 89.00% and 84.34% of them respectively had more than 5 years of experience

in fish marketing.

The percentage of respondents that belonged to a marketers’ association was highest across the

nodes, 51.33% among the producers, 65.67% among the processors and 67.67% among the

marketers.

Figure 4.1 below shows that personal savings was the major primary source of funds for all the

value chain actors. Across the nodes, producers (92.33%) had the highest percentage of

respondents that used their personal savings as their primary source of fund. Among the

processors, the percentage of respondents that obtained funds from inheritance (8.67%) is the

second highest category followed by cooperatives (4.33%). However, among the marketers, the

60

percentage of respondents that primarily obtained their funds from cooperatives (4.00%) is higher

than those that get funds from inheritance (3.67%).

The pie chart in figure 4.2 below revealed that the primary source of fund for the highest percentage

of fish producers is attributed to personal savings (93.90%) followed by cooperatives (3.73%).

Producers that had primary sources of funds from government, loans from commercial banks,

inheritance, gifts, and money lender made up an insignificant percentage of 2.38%. Moreover, it

can also be observed from the pie chart that none of the fish producers derived loans from

microfinance banks and community banks.

The primary source of fund for the highest percentage of fish processors is attributed to personal

savings (82.37%) followed by inheritance (9.36%) as observed in figure 4.3. Those that obtained

fund primarily from cooperatives had a percentage of 4.67%. None of the actors in the fish

processing node derived fund from the government, neither obtained loan from commercial banks.

Those that got loans from microfinance banks, community banks and funds from inheritance, gifts

from family and friends, and money lenders have a very low percentage of 3.60%.

Among the marketers in the fisheries value chain, the major primary source of fund is personal

savings with a percentage of 89.04% marketers as observed in figure 4.4 below. Cooperatives and

inheritance were the important sources of primary fund for the marketers with percentages of

4.11% and 3.77% respectively. The remaining percentage of marketers (3.09%) obtained funds

from government, microfinance banks, community banks, inheritance and gifts. The commercial

banks and money lenders were not accessed for loans and funds in this node.

Figure 4.5 is a bar chart presentation of the secondary sources of fund for the respondents. Funds

from cooperatives was the major secondary source of funds for all the marketing chain actors with

a percentage of 35.41%, 23.77% and 40.39% of the producers, processors and marketers

respectively. Across the nodes, the marketers have the highest percentage of respondents that get

their secondary source of fund from cooperatives, followed by producers and processors. The

percentage of processors (22.12%) that still used their personal savings as their secondary source

of fund is high when compared to the other marketing actors.

61

Figure 4.1: Chart showing the primary sources of fund for the respondents

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

80.00

90.00

100.00


Pe

rce

nta

ge (

%)

Value-Addition Actors

Primary Source of Fund

Personal Savings

Cooperatives "Osusu"

Government

Loans from Commercial Banks

Loans from Microfinance Banks

Loans from Community Banks

Inheritance

Gifts

Money Lender

62

Figure 4.2: Chart showing percentages of Producers and their primary sources of fund

93.90%

3.73%

0.34% 0.34%0.00%

0.00%

0.68%0.34%

0.68%

Producer

Personal Savings


Government




Inheritance

Gifts

Money Lender

63

Figure 4.3: Chart showing percentages of Processors and their primary sources of fund

82.37%

4.67%

0.00%

0.00%

0.72%

1.80%

9.36%

0.36%

0.72%

Processor

Personal Savings


Government




Inheritance

Gifts

Money Lender

64

Figure 4.4: Chart showing percentages of Marketers and their primary sources of fund

89.04%

4.11%

0.34%

0.00% 0.69%1.03%

3.77%

1.03%0.00%

Marketer

Personal Savings


Government




Inheritance

Gifts

Money Lender

65

Figure 4.5: Bar Chart showing the secondary sources of fund for the respondents

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00


Pe

rce

nta

ge (

%)

Value-Addition Actors

Secondary Source of Fund

Personal Savings


Government




Inheritance

Gifts

Money Lender

None

66

As revealed in figure 4.6, a great percentage of the fish producers, processors and marketers were

engaged in other forms of income earning activities such as agriculture, menial business and

trading. A good number of producers were also civil servants in the government ministry. Few

respondents were engaged in fish production, menial businesses and civil service, with producers

having the greater percentage of respondents in this category. The pensioners were very few among

the respondents.

4.2 Socio-economic characteristics of respondents across the geopolitical zones

The result of the socio-economic characteristics of the respondents across the three geopolitical

zones sampled- South-South, North-Central and North-East are presented in table 4.2. The sex of

the respondents revealed that women made up 56.33% of all the respondents in the South-South,

while men were 43.67%. However, it was observed in North-Central and North-East, that the

number of men greatly exceeded the number of women. Women comprised 48.00% of the

respondents in North-Central while men were 52.00%. And in North-East, women were 24.89%

while men were 75.11% of the respondents.

Across the three geopolitical zones, the highest percentage of respondents was within the age

bracket of 41 and 50 years. Very few respondents were aged 20 years and below, the highest

percentage being in North-East (0.89%). The highest percentage of respondents within the age

bracket of 21-30 years was observed in North-East reaching 18.00%. The highest percentage of

respondents within the age bracket of 31-40 years was also observed in North-East reaching

28.89%. Furthermore, the highest percentage of respondents in the modal age group of 41-50 years

was observed in South-South reaching 46.33%.

In addition, the highest percentage of respondents aged over 50 years was found in South-South

reaching 26.33%. The mean ages of the respondents were 45.59, 42.42 and 42.08 in South-South,

North-Central and North-East respectively.

The marital status of the respondents across the geopolitical zone revealed that majority of them

were married; 92.00% of the respondents in South-South, 91.33% of the respondents in North-

Central and 82.44% of the respondents in North-East.

67

Figure 4.6: Chart showing respondents other sources of income

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

45.00

50.00

Pe

rce

nta

ges

(%)

Other sources of income1

Main occupation

Producer

Processor

Marketer

Other sources of income2

68

Table 4.2: Socio-economic characteristics of the respondents across the Geopolitical Zones

Variables Groups Geopolitical Zone South-South North-Central North-East

Freq Percentage (%) Freq Percentage (%) Freq Percentage (%)

Respondent sex Male 131 43.67 78 52.00 338 75.11 Female 169 56.33 72 48.00 112 24.89

Age of respondent ≤20 years 0 0.00 1 0.67 4 0.89 21-30 years 6 2.00 26 17.33 81 18.00 31-40 years 76 25.33 41 27.33 130 28.89 41-50 years 139 46.33 52 34.67 133 29.56 >50 years 79 26.33 30 20.00 102 22.67

Mean±Standard Deviation 45.59±7.60 42.42±10.62 42.08±11.25

Marital Status Single 6 2.00 6 4.00 52 11.56 Married 276 92.00 137 91.33 371 82.44 Divorced 5 1.67 0 0.00 7 1.56 Widowed 13 4.33 7 4.67 20 4.44

Religion Christianity 300 100.00 121 80.67 160 35.56 Muslim 0 0.00 28 18.67 290 64.44 Traditionalist 0 0.00 1 0.67 0 0.00 Others 0 0.00 0 0.00 0 0.00

Household Head No 173 57.67 65 43.33 132 29.33 Yes 127 42.33 85 56.67 318 70.67

Household size ≤3 persons 28 9.33 20 13.33 126 28.00 4-7 persons 182 60.67 78 52.00 173 38.44 8-11 persons 86 28.67 40 26.67 92 20.44 ≥12 persons 4 1.33 12 8.00 59 13.11

Mean±Standard Deviation 6.00±2.00 7.00±3.00 7.00±4.00

Highest Education Primary 93 31.00 65 43.33 88 19.56 Secondary 150 50.00 50 33.33 148 32.89 Tertiary 53 17.67 18 12.00 62 13.78 Qu'ranic 0 0.00 9 6.00 138 30.67 Informal 4 1.33 8 5.33 14 3.11

Years of selling ˂1 year 3 1.00 0 0.00 5 1.11

1-5 years 58 19.33 7 4.67 76 16.89

6-10 years 94 31.33 34 22.67 135 30.00

11-15 years 85 28.33 27 18.00 120 26.67

˃15 years 60 20.00 82 54.67 114 25.33

Membership of

Association

No 156 52.00 28 18.67 162 36.00

Yes 144 48.00 122 81.33 288 64.00

69

The highest percentage of single respondents was observed in North-East (11.56%); the highest

percentage of married and divorced respondents was observed in South-South (92.00% and 1.67%

respectively) and the highest percentage of widowed respondents was observed in North-Central

(4.67%).

All the respondents in South-South and majority of those in North-Central (80.67%) were

Christians. However, the Muslim respondents in North-East were more, reaching 64.44%.

The respondents in North-Central and North-East had more household heads with a percentage of

56.67% and 70.67% respectively. However, in South-South, those that were not household heads

were more reaching 57.67%.

Majority of the respondents had a household size of 4-7 persons, 60.67% in South-South, 52.00%

in North-Central and 38.44% in North-East as shown in table 4.2 below. 9.33% of the respondents

in South-South, 13.33% in North-Central and 28.00% in North-East had a household size 3 persons

and less. In the household size of 8-11 person’s category, respondents in North-East had the highest

count of 92 respondents (20.44%) followed closely by South-South with a count of 86 respondents

(28.67%) and in North-Central, 40 respondents (26.67%). Very few of the respondents had a

household size of 12 persons and more, 1.33% in South-South, 8.00% in North-Central and

13.11% in North-East. The mean household size in South-South, North-Central and North-East

was 6.23, 6.81 and 6.56, respectively.

The educational status of the respondents showed that majority of them in South-South (50.00%)

and North-East (32.89%) were Secondary school leavers. Respondents who attended only Primary

school was highest in North-Central reaching 43.33%. Respondents that had Qu’ranic and

Informal education were high in North-East reaching 30.67% and 3.11%, respectively.

Percentage of respondents with marketing experiences of 6-10 years was highest in South-South

and North-East reaching 31.33% and 30.00%, respectively. The highest percentage of respondents

in North-Central (54.67%) had more than 15 years of experience in fish marketing. The

respondents with less than a year marketing experience had the least percentages across the

geopolitical zones; 1.00% and 1.11% in South-South and North-East respectively.

70

Respondents that were members of marketers’ association were higher in North-Central and

North-East reaching 81.33% and 64.00% respectively. However, in South-South the respondents

that were not members of marketers’ association were higher reaching 52.00%.

4.3 Socio-economic characteristics of respondents in each of the sampled State

The socio-economic characteristics of the fish marketing actors in each of the State along Nigeria-

Cameroon-Chad border are presented in tables 4.3a and 4.3b. The sex distribution of the

respondents indicates the dominance of males in the production node and dominance of females

in the processing and marketing nodes, except in Taraba and Borno States. In Taraba State, men

dominated the processing (58.00%) and marketing (76.00%) nodes. Similarly, in Borno State, a

higher percentage of men was observed in the processing (86.00%) and marketing (92.00%) nodes.

There was only one female producer in Benue State (2.00%) and none was recorded in Borno

State. Furthermore, it was observed that the percentage of female processors and marketers were

highest in Cross River State, reaching 90.00% in each of the marketing node. The pooled sex

distribution of the respondents in the six States sampled is illustrated in figure 4.7. The chart

reveals that the percentage of male was higher than females in the study area, except in Cross River

State. The number of females in Borno State was very low compared to the other States that were

sampled for this study.

The actors in the marketing nodes for fish trade across the six States along Nigeria-Cameroon-

Chad border, showed that majority of the respondents were within the age group of 41-50 years.

The marketers in Taraba and Benue States (40.00% and 34.00% respectively) and producers and

marketers in Borno State (40.00% and 36.00% respectively) had a higher percentage of

respondents within the age group of 31 and 40 years. Furthermore, producers and processors in

Adamawa State (42.00% and 40.00% respectively) and processors in Borno State (36.00%) had a

higher percentage of respondents reaching over 50 years of age.

In addition, very few respondents were aged 20 years and below and they were observed among

the marketers in Benue State (2.00%), processors and marketers in Adamawa State (2.00% each)

and producers in Borno State (4.00%). The age distribution of the respondents in each of the

sampled states is presented in figure 4.8.

71

Table 4.3a: Socio-economics characteristics of the respondents in the States along Nigeria-Cameroon-Chad border

Variables Groups Akwa Ibom

Cross River

Benue

Producer Processor Marketer Producer Processor Marketer Producer Processor Marketer

Freq % Freq % Freq % Freq % Freq % Freq % Freq % Freq % Freq %

Respondent sex Male 46 92.00 18 36.00 12 24.00 45 90.00 5 10.00 5 10.00 49 98.00 16 32.00 13 26.00

Female 4 8.00 32 64.00 38 76.00 5 10.00 45 90.00 45 90.00 1 2.00 34 68.00 37 74.00

Age of respondent ≤20 years 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 1 2.00

21-30 years 0 0.00 3 6.00 1 2.00 1 2.00 0 0.00 1 2.00 12 24.00 8 16.00 6 12.00

31-40 years 9 18.00 17 34.00 19 38.00 14 28.00 8 16.00 9 18.00 12 24.00 12 24.00 17 34.00

41-50 years 28 56.00 22 44.00 26 52.00 18 36.00 22 44.00 23 46.00 18 36.00 18 36.00 16 32.00

>50 years 13 26.00 8 16.00 4 8.00 17 34.00 20 40.00 17 34.00 8 16.00 12 24.00 10 20.00

Marital Status Single 0 0.00 2 4.00 1 2.00 3 6.00 0 0.00 0 0.00 4 8.00 0 0.00 2 4.00

Married 49 98.00 46 92.00 39 78.00 45 90.00 50 100.00 47 94.00 46 92.00 47 94.00 44 88.00

Divorced 0 0.00 0 0.00 4 8.00 0 0.00 0 0.00 1 2.00 0 0.00 0 0.00 0 0.00

Widowed 1 2.00 2 4.00 6 12.00 2 4.00 0 0.00 2 4.00 0 0.00 3 6.00 4 8.00

Religion Christianity 50 100.00 50 100.00 50 100.00 50 100.00 50 100.00 50 100.00 35 70.00 43 86.00 43 86.00

Muslim 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 14 28.00 7 14.00 7 14.00

Traditionalist 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 1 2.00 0 0.00 0 0.00

Household Head No 13 26.00 23 46.00 28 56.00 23 46.00 44 88.00 42 84.00 2 4.00 30 60.00 33 66.00

Yes 37 74.00 27 54.00 22 44.00 27 54.00 6 12.00 8 16.00 48 96.00 20 40.00 17 34.00

Household size ≤3 persons 4 8.00 3 6.00 2 4.00 10 20.00 5 10.00 4 8.00 8 16.00 6 12.00 6 12.00

4-7 persons 26 52.00 33 66.00 24 48.00 34 68.00 35 70.00 30 60.00 23 46.00 28 56.00 27 54.00

8-11 persons 18 36.00 14 28.00 23 46.00 6 12.00 10 20.00 15 30.00 11 22.00 14 28.00 15 30.00

≥12 persons 2 4.00 0 0.00 1 2.00 0 0.00 0 0.00 1 2.00 8 16.00 2 4.00 2 4.00

Highest Education Primary 15 30.00 20 40.00 17 34.00 10 20.00 11 22.00 20 40.00 20 40.00 23 46.00 22 44.00

Secondary 23 46.00 24 48.00 19 38.00 20 40.00 37 74.00 27 54.00 16 32.00 16 32.00 18 36.00

Tertiary 12 24.00 6 12.00 10 20.00 20 40.00 2 4.00 3 6.00 10 20.00 3 6.00 5 10.00

Qu'ranic 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 2 4.00 4 8.00 3 6.00

Informal 0 0.00 0 0.00 4 8.00 0 0.00 0 0.00 0 0.00 2 4.00 0 0.00 2 4.00

72

Table 4.3b: Socio-economics characteristics of the respondents across the sampled States (continued)

Variables Groups Taraba

Adamawa

Borno

Producer Processor Marketer Producer Processor Marketer Producer Processor Marketer

Freq % Freq % Freq % Freq % Freq % Freq % Freq % Freq % Freq %

Respondent sex Male 47 94.00 29 58.00 38 76.00 43 86.00 24 48.00 18 36.00 50 100.00 43 86.00 46 92.00

Female 3 6.00 21 42.00 12 24.00 7 14.00 26 52.00 32 64.00 0 0.00 7 14.00 4 8.00

Age of respondent ≤20 years 0 0.00 0 0.00 0 0.00 0 0.00 1 2.00 1 2.00 2 4.00 0 0.00 0 0.00

21-30 years 9 18.00 12 24.00 7 14.00 10 20.00 7 14.00 3 6.00 13 26.00 5 10.00 15 30.00

31-40 years 14 28.00 14 28.00 20 40.00 6 12.00 10 20.00 14 28.00 20 40.00 14 28.00 18 36.00

41-50 years 15 30.00 15 30.00 15 30.00 13 26.00 12 24.00 24 48.00 11 22.00 13 26.00 15 30.00

>50 years 12 24.00 9 18.00 8 16.00 21 42.00 20 40.00 8 16.00 4 8.00 18 36.00 2 4.00

Marital Status Single 10 20.00 2 4.00 7 14.00 10 20.00 2 4.00 3 6.00 7 14.00 5 10.00 6 12.00

Married 40 80.00 42 84.00 40 80.00 40 80.00 40 80.00 43 86.00 43 86.00 40 80.00 43 86.00

Divorced 0 0.00 1 2.00 1 2.00 0 0.00 2 4.00 1 2.00 0 0.00 1 2.00 1 2.00

Widowed 0 0.00 5 10.00 2 4.00 0 0.00 6 12.00 3 6.00 0 0.00 4 8.00 0 0.00

Religion Christianity 22 44.00 23 46.00 14 28.00 23 46.00 27 54.00 27 54.00 5 10.00 13 26.00 6 12.00

Muslim 28 56.00 27 54.00 36 72.00 27 54.00 23 46.00 23 46.00 45 90.00 37 74.00 44 88.00

Traditionalist 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00 0 0.00

Household Head No 11 22.00 16 32.00 16 32.00 15 30.00 23 46.00 27 54.00 4 8.00 9 18.00 11 22.00

Yes 39 78.00 34 68.00 34 68.00 35 70.00 27 54.00 23 46.00 46 92.00 41 82.00 39 78.00

Household size ≤3 persons 16 32.00 15 30.00 21 42.00 11 22.00 13 26.00 8 16.00 19 38.00 11 22.00 12 24.00

4-7 persons 18 36.00 24 48.00 14 28.00 15 30.00 20 40.00 27 54.00 21 42.00 16 32.00 18 36.00

8-11 persons 12 24.00 8 16.00 13 26.00 14 28.00 7 14.00 8 16.00 8 16.00 12 24.00 10 20.00

≥12 persons 4 8.00 3 6.00 2 4.00 10 20.00 10 20.00 7 14.00 2 4.00 11 22.00 10 20.00

Highest Education Primary 6 12.00 15 30.00 6 12.00 8 16.00 10 20.00 20 40.00 4 8.00 12 24.00 7 14.00

Secondary 17 34.00 18 36.00 34 68.00 17 34.00 14 28.00 20 40.00 2 4.00 13 26.00 13 26.00

Tertiary 15 30.00 7 14.00 5 10.00 12 24.00 5 10.00 3 6.00 10 20.00 2 4.00 3 6.00

Qu'ranic 9 18.00 9 18.00 4 8.00 12 24.00 15 30.00 6 12.00 34 68.00 23 46.00 26 52.00

Informal 3 6.00 1 2.00 1 2.00 1 2.00 6 12.00 1 2.00 0 0.00 0 0.00 1 2.00

73

Figure 4.7: Sex distribution of respondents in the sampled States

0.00

20.00

40.00

60.00

80.00

100.00

Akwa Ibom Cross River Benue Taraba Adamawa Borno

Pe

rce

nta

ge (

%)

Sampled States

Sex of Respondents

Male

Female

74

Figure 4.8: Bar chart showing the age distribution of respondents

0.00

10.00

20.00

30.00

40.00

50.00

60.00


Pe

rce

nta

ge (

%)

Sampled States

Categorized Age of Respondent

<20years

21-30years

31-40years

41-50years

>50years

75

The category of respondents of age 20 years and below had the lowest percentage across the six

States. In Akwa Ibom, Cross River and Benue States, the highest percentage of respondents fall

within the category of 41 and 50 years, followed by respondents aged 31-40 years only in Akwa

Ibom and Benue States. In Cross River State, the second highest category of respondents are those

over 50 years of age. In Adamawa State, the highest number of respondents are within the age

groups of 41-50 years and above 50 years, with a percentage of 32.67%. Furthermore, in Taraba

and Borno States, the highest percentage of respondents fall within the category of 31-40 years,

followed by respondents aged between 41 and 50 years.

Majority of the respondents in each of the marketing nodes across the States were married, the

highest being in Cross River State among the processors reaching hundred percent married

respondents. There were very few divorced and widowed persons among the respondents in all the

States. The highest percentage of divorced respondents was among the marketers in Akwa Ibom

State (8.00%). The highest percentage of widowed respondents was among the marketers in Akwa

Ibom State (12.00%) and processors in Adamawa State (12.00%). In addition, the highest

percentage of single respondents was among the producers in Taraba State (20.00%). Figure 4.9

is a bar chart illustrating the marital status of the respondents. It reveals that the percentage of

married respondents was highest across the six states in Nigeria-Cameroon-Chad border region.

This was closely followed by the percentage of respondents that are single in Taraba, Adamawa

and Borno states.

Christianity was largely practiced among the respondents in each of the marketing nodes across

Akwa Ibom, Cross River and Benue States and among the processors (54.00%) and marketers

(54.00%) in Adamawa State. It was observed in Akwa Ibom and Cross River States that all of the

respondents were Christians. However, across the marketing nodes in Taraba and Borno States

including the producers in Adamawa State, majority of the respondents were Muslims. There was

only one traditionalist among the producers (2.00%) in Benue State.

The religion of the respondents in each of the states is shown in figure 4.10. Christianity was high

in Akwa Ibom, Cross River and Benue states than in Taraba, Adamawa and Borno states. In

Adamawa state, the percentage of Christian respondents is slightly higher than Muslim

respondents. The percentage of the other forms of religion and traditional religion is negligible

across the sampled states.

76

Figure 4.9: Bar chart illustrating the marital status of respondents

0.00

20.00

40.00

60.00

80.00

100.00

AkwaIbom

CrossRiver

Benue Taraba Adamawa Borno

Pe

rce

nta

ge (

%)

Sampled States

Marital Status

Single

Married

Divorced

Widowed

77

Figure 4.10: Bar chart showing the religion distribution of respondents

0.00

20.00

40.00

60.00

80.00

100.00

AkwaIbom

CrossRiver

Benue Taraba Adamawa Borno

Pe

rce

nta

ge (

%)

Sampled States

Religion

Christianity

Muslim

Traditionalist

Others

78

Majority of the producers were household heads in Akwa Ibom State (74.00%), Cross River State

(54.00%), Benue State (96.00%), Taraba State (78.00%), Adamawa State (70.00%) and Borno

State (92.00%). Processors that were household heads were more than those that were not

household heads in Akwa Ibom State (54.00%), Taraba State (68.00%), Adamawa State (54.00%)

and Borno State (82.00%). And higher percentage of marketers that were household heads was

found in Taraba State (68.00%) and Borno State (78.00%).

The category of household size of 4-7 persons had the highest percentage of respondents across

the marketing nodes in the six States, except among the marketers in Taraba State. In Taraba State,

the highest percentage of respondents among the marketers (42.00%) have a household size of

three persons and less. The highest percentage of respondents with a household size of 3 persons

and less was found among the producers (38.00%) in Borno State. The highest percentage of

respondents with a household size of 4-7 persons was observed among the processors (70.00%) in

Cross River State. The highest percentage of respondents with a household size of 8-11 persons

was observed among the marketers (46.00%) in Akwa Ibom State. The highest percentage of

respondents with a household size of 12 persons and more was found among the processors

(22.00%) in Borno State. Figure 4.11 below shows the distribution of the household sizes of the

respondents in the six States in the study area. Respondents with household sizes of 4-7 persons

had the highest percentage across the six States sampled. This category is closely followed by

respondents with household sizes of 8-11 persons in Akwa Ibom, Cross River and Benue States.

While in Taraba, Adamawa and Borno States, respondents with household sizes of 3 persons or

less than is the second highest category. Furthermore, the category of respondents having

household sizes of 12 persons and over has the lowest percentage across all the states.

The educational qualification of the respondents as presented in tables 4.3a and 4.3b revealed that

the highest percentage of respondents with Primary school certificate was among the processors

(46.00%) in Benue State. The highest percentage of respondents with Secondary school leaving

certificate was observed among the processors (74.00%) in Cross River State. Furthermore, the

highest percentage of respondents that attended Tertiary institutions was found among the

producers (40.00%) in Cross River State. In addition, respondents that had qu’ranic education was

highest among the producers (68.00%) in Borno State.

79

Figure 4.11: Bar chart showing the household sizes of respondents

0.00

20.00

40.00

60.00

80.00

100.00

AkwaIbom

Cross River Benue Taraba Adamawa Borno

Pe

rce

nta

ge (

%)

Sampled States

Household size

<3 persons

4 - 7 persons

8 - 11 persons

>12 persons

80

However, the percentage of respondents that had informal education was low across the six States,

the highest percentage being among the processors (12.00%) in Adamawa State. The educational

status of the respondents in each of the sampled State is revealed in figure 4.12. It indicates that

Secondary school education was the highest educational level attained by majority of the

respondents in Akwa Ibom, Cross River, Taraba and Adamawa States. In Benue State, the highest

percentage of respondents are primary school leavers. While, majority of the respondents in Borno

State went to Qu’ranic schools.

The marketing experiences of the respondents across the six states as presented in figure 4.13,

shows that majority of the respondents in Akwa Ibom, Cross River and Adamawa States had 6-10

years of marketing experiences. Very few of the respondents had a short marketing experience of

less than a year across all the States, except in Cross River, Benue and Borno States where there

was no respondent in that category. Benue State had a large number of respondents with more than

15 years of marketing experience.

4.4 Marketing Nodes

The research identified participants in the fish marketing system in Nigeria-Cameroon-Chad

border region and categorized them based on the major roles and functions they performed. These

participants include artisanal fishermen who are the capture producers of fish; fish farmers who

are the culture producers of fish; the processors who undertake preservation and/ or value addition

to the product; and the marketers or traders. Hence, three major marketing nodes for fresh and

processed fish were identified in the study area. These are Production, Processing and Marketing

nodes. Figure 4.14 illustrates the marketing chain for fish trade in the study area.

4.5 Profile of fish species produced and traded

Table 4.14 presents a profile of some of the fish species produced and traded in the study area. The

table shows that family Bagridae has the highest count (3) of species. Family Clariidae,

Mormyridae, Osteoglossidae, Characidae and Clupeidae have two (2) species each. The remaining

twenty-six (26) families were represented by one species each. This made up a total of 32 fish

species from 25 families presented in the table. These fish species are sourced from fresh water,

brackish and marine water bodies found in the study area.

81

Figure 4.12: Bar Chart showing the respondents’ highest level of Education

0.00

10.00

20.00

30.00

40.00

50.00

60.00


Pe

rce

nta

ges

Sampled States

Educational Status

Primary

Secondary

Tertiary

Qu'ranic

Informal

82

Figure 4.13: Distribution of respondents’ marketing experiences in years

0.00

10.00

20.00

30.00

40.00

50.00

60.00


Per

cen

tage

s(%

)

Sampled States

Categories

less than 1 year

1-5 years

6-10 years

11-15 years

more than 15 years

83

Figure 4.14: Schematic view of fish marketing chain along Nigeria-Cameroon-Chad border

84

Table 4.4: Profile of fish species produced and traded in the study area

Family Name Scientific Name Common Name Local Name

Clariidae Clarias spp Catfish Tarwada

Heterobranchus spp catfish Ramboshi, Mari

Cichlidae Oreochromis niloticus Tilapia Karfasa

Mormyridae Mormyrus rume Trunk fish

Gnathonemus senegalensis Kuma

Bagridae Auchenoglanis occidentalis Buro

Chrysichthys nigrodigitatus Silver catfish Dunu

Bagrus bayad macropterus Silver catfish Ragon ruwa

Mochokidae Synodontis spp catfish Kurungu

Protopteridae Protopterus annectens African lungfish Bodami, Mai mama

Osteoglossidae Heterotis niloticus African bony tongue Berigi

Clupisidus niloticus Berigi

Gymnarchidae Gymnarchus niloticus Trunk fish Yauni

Characidae Hydrocynus spp Tiger fish Tsege

Alestes leucisus Silversides Kawara

Ariidae Arius gigas Marine catfish

Centropomidae Lates niloticus Nile perch Giwa ruwa

Sciaenidae Pseudotholitus spp Croaker

Lutjanidae Lutjanus agennes Red Snapper

Sphyraenidae Sphyraena spp Barracuda

Polynemidae Polydactylus spp Shiny nose

Pomadasyidae Pomadasys jubelini Grunter

Serranidae Epinephelus spp Grouper

Penaenidae Penaeus notialis Crayfish

Channidae Parachanna obscura Snake head Tufi

85

Table 4.4 cont’d: Profile of fish species produced and traded in the study area

Family Name Scientific Name Common Name Local Name

Clupeidae Ethmalosa fimbriata Bonga

Sardinella spp Sardine Ekpai

Citharinidae Citharinus spp Moon fish

Schibeidae Schilbe spp

Cynoglossidae Cynoglossus senegalensis

Cyprinidae Labeo spp African carp Burdo

Anabantidae Ctenopoma spp Climbing gouramies Takasa

Note: This list is not exhaustive of the fish species produced and traded along Nigeria-Cameroon-

Chad border.

86

4.6 Analysis of fish market structure

This section assessed the nature of fish marketing for the different forms of fish products and at

the level of operation in each marketing node in the study area by analyzing the variability in fish

distribution amongst all the categories of market participants (producers, processors, wholesalers

and retailers), pricing system, nature of competition and the barriers to/ ease of entry into the fish

markets.

4.6.1 Forms of fish sold

Fish in its different forms were sold in Nigeria-Cameroon-Chad border region as fresh/live, frozen,

smoked and dried as revealed in figure 4.15. The highest form of fish sold is fresh/live fish

(46.33%) and frozen fish (0.67%) was reported as the least form of fish sold. The other forms of

fish marketed in the study area were smoked (45.40%) and dried fish (7.67%). The results of forms

of fish marketed in each State presented in Figure 4.16 indicates that fresh, smoked dried and

frozen fish were marketed majorly in Cross River (20.62%), Borno and Akwa Ibom (21.81%

each), Benue (31.88%), and Cross River and Adamawa (33.33% each) States, respectively along

Nigeria-Cameroon-Chad border.

Plate 4.1 is a picture showing a display of fresh fish for sale in Wadata fish market in Benue State,

Nigeria. This market lies on longitude 7044’42.1’’N and latitude 8031’09.7’’E. It is located on

Bank Road, Makurdi, very close to one of the landing sites for River Benue. The different fish

species were displayed for the buyers to select their choices. Plate 4.2 shows female retailers

selling processed smoked fish in Mayogwoi market, Taraba State, Nigeria. Mayogwoi market lies

on longitude 8052’52.6’’N and latitude 11022’20.9’’E in Jalingo, the capital city of Taraba State.

Fresh and processed fish were sold in this market by both male and female marketers.

4.6.2 Pricing Mechanism

The pricing mechanism for fish sale adopted in the study area were negotiation between buyer and

seller, fixed or controlled price by value chain actors. Figure 4.17 reveals that majority of the

respondents in the production node (84.33%), processing node (94.00%) and marketing node

(91.67%) employed negotiation or bargaining method to place prices on their fish products.

87

Figure 4.15: Percentage of forms of fish marketed in Nigeria-Cameroon-Chad border

region

46.33%

45.33%

7.67%

0.67%

Marketed forms of fish

Fresh Smoked Dried Frozen

88

Figure 4.16: Percentage of forms of fish marketed in States along Nigeria-Cameroon-Chad

border

0% 20% 40% 60% 80% 100%

Akwa Ibom

Cross River

Benue

Taraba

Adamawa

BornoSt

ate

s A

lon

g N

ige

ria

-Cam

ero

on

-Ch

ad

Bo

rde

r

Fresh

Smoked

Dried

Frozen

89

Plate 4.1: Sales of fresh fish in Wadata fish market, Benue State, Nigeria

90

Plate 4.2: Processed fish retailers in Mayogwoi fish market, Taraba State, Nigeria

91

Figure 4.17: Fish pricing mechanism in the study area

0

10

20

30

40

50

60

70

80

90

100


Pe

rce

nta

ge (

%)

Value Chain Actors

Fish PricingFixed

Negotiated

Contolled by value chainactors

92

4.6.3 REVENUE DISTRIBUTION AND GINI COEFFICIENT

The Gini coefficient (GI) was used to measure the level of equality or inequality in revenue

distribution of the respondents marketing different fish products in the study area.

4.6.3.1 Fresh Fish Production Node

The computation of Gini coefficient presented in table 4.5 indicates that 28.70% of the culture

producers of fresh fish along Nigeria-Cameroon-Chad border region had monthly sales between

N250000.01 – N500000.00 representing 20.58% of the total volume of monthly sales. However,

the highest percentage of culture producers (37.70%) with average monthly sales of N 250000.00

and less than accounted for just 12.30% of total monthly sale. The mean value of monthly sales

was N495005.93±415129.58. The empirical results indicate that the fish culture producers were

concentrated with Gini coefficient of 0.63.

Analysis of Gini coefficient in table 4.6 reveals that 61.20% of the capture producers (fishermen)

of fresh fish had monthly revenue of N 250000.00 and less than, representing 32.84% of the total

monthly sales. This was the highest, followed by capture producers (23.00%) with total monthly

revenue range of N 250000.01 – N 500000.00 handling 26.70% of the total monthly sales. The

mean monthly revenue was N 296777.62±242844.22. The computations revealed that the market

was non-competitive with Gini coefficient of 0.53.

4.6.3.2 Fresh Fish Marketing Node

Table 4.7 presents the analysis of Gini coefficient and indicates that 41.90% percent of the

wholesalers of fresh fish had monthly revenue range of N 1000000.01 – N 1250000.00,

representing 37.16% of the total monthly sales. The least percentage of wholesalers (6.50%) of

fresh fish made had total sales ranging from N 1500000 – N 1750000, making 8.67% of the total

monthly sales. The mean monthly sale was N 1228039.90±293507.44. The computed Gini

coefficient was 0.43.

The computation of Gini coefficient as presented in table 4.8 indicates that 34.90% of the retailers

of fresh fish had monthly sales of N 250000.01 – N 500000.00 representing 47.99% percent of the

total volume of monthly sales.

93

Table 4.5: Distribution of total monthly revenue of fresh fish Producers (Culture) in Nigeria-Cameroon-Chad border region

Total Revenue (₦) Frequency % of Culture

Producers

(X)

Cumulative

Percent

Total Value of

Monthly Sales

(₦)

% of Total

Sales

Cumulative

Percent (Y)

XY

≤ 250000.00 46 37.70 37.70 7427856.96 12.30 12.30 0.04637

250000.01 - 500000.00 35 28.70 66.40 12430368.90 20.58 32.88 0.09437

500000.01 - 750000.00 13 10.70 77.00 8290502.86 13.73 46.61 0.04987

750000.01 - 1000000.00 11 9.00 86.10 10035994.55 16.62 63.23 0.05691

1000000.01 - 1250000.00 9 7.40 93.40 9903000.00 16.40 79.63 0.05893

1250000.01 - 1500000.00 5 4.10 97.50 6953000.00 11.51 91.14 0.03737

1500000.01 - 1750000.00 2 1.60 99.20 3350000.00 5.55 96.69 0.01547

1750000.01 - 2000000.00 1 0.80 100.00 2000000.00 3.31 100.00 0.00800

Total 122 100.00

∑xy 0.36728

GI = 0.63

94

Table 4.6: Distribution of total monthly revenue of fresh fish Producers (Capture) in Nigeria-Cameroon-Chad border region

Total Revenue (₦) Frequency % of Capture

Producers

(X)

Cumulative

Percent

Total Value of

Monthly Sales

(₦)

% of Total

Sales

Cumulative

Percent (Y)

XY

≤ 250000.00 109 61.20 61.20 17346933.86 32.84 32.84 0.20098

250000.01 - 500000.00 41 23.00 84.30 14102165.88 26.70 59.54 0.13694

500000.01 - 750000.00 17 9.60 93.80 10199114.8 19.31 78.85 0.07570

750000.01 - 1000000.00 6 3.40 97.20 5018302.21 9.50 88.35 0.03004

1000000.01 - 1250000.00 2 1.10 98.30 2199900 4.15 92.50 0.01018

1250000.01 - 1500000.00 3 1.70 100.00 3960000 7.50 100.00 0.01700

Total 178 100.00

∑xy 0.47083

GI = 0.53

95

Table 4.7: Distribution of total monthly revenue of fresh fish Wholesalers in Nigeria-Cameroon-Chad border region

Total Revenue (₦) Frequency % of

Marketers

(X)

Cumulative

Percent

Total Value of

Monthly Sales

(₦)

% of Total

Sales

Cumulative

Percent (Y)

XY

750000.01 - 1000000.00 6 19.40 19.40 5439000 14.29 14.29 0.02772

1000000.01 - 1250000.00 13 41.90 61.30 14150032.94 37.16 51.45 0.21558

1250000.01 - 1500000.00 7 22.60 83.90 9707503.88 25.5 76.95 0.17391

1500000.01 - 1750000.00 2 6.50 90.30 3299800 8.67 85.62 0.05565

1750000.01 - 2000000.00 3 9.70 100.00 5472900 14.38 100.00 0.09700

Total 31 100.00

∑xy 0.56986

GI = 0.43

96

Table 4.8: Distribution of total monthly revenue of fresh fish Retailers in Nigeria-Cameroon-Chad border region

Total Revenue (₦) Frequency % of Marketers

(X)

Cumulative

Percent

Total Value of

Monthly Sales (₦)

% of Total

Sales

Cumulative

Percent (Y)

XY

≤ 250000.00 50 58.10 58.10 8019000.98 36.24 36.24 0.21

250000.01 - 500000.00 30 34.90 93.00 10619328.69 47.99 84.23 0.29

500000.01 - 750000.00 6 7.00 100.00 3487900.00 15.77 100.00 0.07

Total 86 100

∑xy 0.57

GI = 0.43

97

However, the highest percentage of fresh fish retailers (58.10%) with average monthly sales of N

250000.00 and less than accounted for just 36.24% percent of the total monthly sales. The mean

value of monthly sales was N 257281.74±138440.97. The empirical results revealed Gini

coefficient of 0.43.

4.6.3.3 Smoked fish Processing Node

Analysis of Gini coefficient in table 4.9 reveals that the highest percentage of smoked fish

processors (32.20%) had monthly revenue of N 250000.01 – N 500000.00, representing 16.89%

of the total monthly sales. The least percentage of processors (1.60%) handled the least percentage

of total monthly sales (5.29%). Processors of smoked fish realized a mean monthly revenue of

693986.88±687491.96. The computed Gini coefficient for processors of smoked fish in the States

along Nigeria-Cameroon-Chad border was 0.68.

4.6.3.4 Smoked fish Marketing Node

Table 4.10 reveals that 34.70% of the wholesalers of smoked fish had monthly revenue of N

2500000.01 and more than, representing 45.00% of the total monthly sales. The lowest percentage

of these wholesalers (1.30%) with total monthly revenue range of N 1000000.01 – N 1250000.00

realized 0.74% of the total monthly revenue. The mean monthly revenue made by wholesalers of

smoked fish was N 2251098.73±685618.74. The empirical findings revealed a Gini coefficient of

0.46 for wholesalers in smoked fish markets in Nigeria-Cameroon-Chad border region.

Table 4.11 indicates that 61.50% of the retailers of smoked fish in Nigeria-Cameroon-Chad border

region represented 59.02% of the total monthly sales had monthly revenue of N 250000.01 – N

500000.00. The lowest percentage of these retailers (3.80%) with total monthly revenue range of

N 750000.01 – N 1000000.00 realized 8.21% of the total monthly revenue. The mean monthly

revenue made by retailers of smoked fish was N 369509.11±162581.13. The computed value of

Gini coefficient for smoked fish retailers was 0.39.

98

Table 4.9: Distribution of total monthly revenue of smoked fish Processors in Nigeria-Cameroon-Chad border region


Processors

(X)

Cumulative

Percent

Total Value

of Monthly

Sales (₦)

% of Total

Sales

Cumulative

Percent (Y)

XY

≤ 250000.00 67 26.30 26.30 12086966.26 6.83 6.83 0.02

250000.01 - 500000.00 82 32.20 58.40 29886830.96 16.89 23.72 0.08

500000.01 - 750000.00 31 12.20 70.60 19045534.07 10.76 34.48 0.04

750000.01 - 1000000.00 19 7.50 78.00 16365132.93 9.25 43.73 0.03

1000000.01 - 1250000.00 16 6.30 84.30 18270495.74 10.32 54.05 0.03

1250000.01 - 1500000.00 10 3.90 88.20 13469913.50 7.61 61.66 0.02

1500000.01 - 1750000.00 7 2.70 91.00 11308218.42 6.39 68.05 0.02

1750000.01 - 2000000.00 5 2.00 92.90 9599392.68 5.42 73.47 0.01

2000000.01 - 2250000.00 6 2.40 95.30 12621432.65 7.13 80.60 0.02

2250000.01 - 2500000.00 4 1.60 96.90 9365423.08 5.29 85.89 0.01

≥2500000.01 8 3.10 100.00 24947314.53 14.11 100.00 0.03

Total 255 100.00

∑xy 0.32

GI = 0.68

99

Table 4.10: Distribution of total monthly revenue of smoked fish Wholesalers in Nigeria-Cameroon-Chad border region


Marketers

(X)

Cumulative

Percent

Total Value

of Monthly

Sales (₦)

% of Total

Sales

Cumulative

Percent (Y)

XY

250000.01 - 500000.00 3 4.00 4.00 997672.27 0.59 0.59 0.00

1000000.01 - 1250000.00 1 1.30 5.30 1245500 0.74 1.33 0.00

1250000.01 - 1500000.00 5 6.70 12.00 6555972.73 3.88 5.21 0.00

1500000.01 - 1750000.00 2 2.70 14.70 3353422.76 1.99 7.20 0.00

1750000.01 - 2000000.00 14 18.70 33.30 26228127.24 15.53 22.73 0.04

2000000.01 - 2250000.00 13 17.30 50.70 28137017.88 16.67 39.40 0.07

2250000.01 - 2500000.00 11 14.70 65.30 26337839.62 15.60 55.00 0.08

≥2500000.01 26 34.70 100.00 75976852.27 45.00 100.00 0.35

Total 75 100

∑xy 0.54

GI = 0.46

100

Table 4.11: Distribution of total monthly revenue of smoked fish Retailers in Nigeria-Cameroon-Chad border region


Marketers

(X)

Cumulative

Percent

Total Value

of Monthly

Sales (₦)

% of Total

Sales

Cumulative

Percent (Y)

XY

≤ 250000.00 18 23.10 23.10 3599383.14 12.49 12.49 0.03

250000.01 - 500000.00 48 61.50 84.60 17010795.99 59.02 71.51 0.44

500000.01 - 750000.00 9 11.50 96.20 5846098.02 20.28 91.79 0.11

750000.01 - 1000000.00 3 3.80 100.00 2365433.45 8.21 100.00 0.04

Total 78 100.00

∑xy 0.61

GI = 0.39

101

4.6.3.5 Dried fish Processing Node

Analysis of Gini coefficient in table 4.12 reveals that the highest percentage of dried fish

processors (24.40%) had monthly revenue of N 250000.00 and less than, made up 4.07% of the

total revenue in a month. However, the processors (6.70%) of dried fish handling the highest share

of total revenue (27.25%) had total monthly revenue of N 2500000.01 and more. The empirical

results revealed a computed Gini coefficient of 0.69 for processors of dried fish in the States along

Nigeria-Cameroon-Chad border.

4.6.3.6 Dried fish Marketing Node

Analysis of Gini coefficient in table 4.13 reveals that the highest percentage of dried fish

wholesalers (37.50%) had monthly revenue of N 2500000.01 and more, handled the highest share

(58.68%) of the total monthly sales. The wholesalers of dried fish realized a mean total monthly

revenue of N1748846.85±1350367.72. The Gini coefficient computed was 0.51 for dried fish

wholesale markets in Nigeria-Cameroon-Chad border region.

Table 4.15 reveals that 62.50% of the retailers of dried fish handled 44.97% of the total monthly

sales and realized a monthly revenue of N 250000.00 and less. The other category handled 55.03%

of the total monthly revenue and constituting 37.50% of retailers of dried fish realized a total

monthly revenue range of N 250000.01 – N 500000.00. The estimated value of Gini coefficient

determined was 0.34 for the retailers of dried fish in fish markets in Nigeria-Cameroon-Chad

border region.

4.6.3.7 Frozen fish Marketing Node

Analysis of Gini coefficient in table 4.16 reveals that 66.7% of the wholesalers of frozen fish

handled 46.66% of the total monthly revenue and realized a monthly revenue range of N

750000.01– N 1000000.00. The other category handled 53.34% of the total monthly revenue and

constituting 33.30% of wholesalers of frozen fish realized a total monthly revenue range of N

1750000.01 – N 2000000.00. The mean monthly revenue made was N 1174718.32±611143.64.

The computed Gini coefficient was 0.36 for the wholesalers of frozen fish in fish markets in the

States along Nigeria-Cameroon-Chad border.

102

Table 4.12: Distribution of total monthly revenue of dried fish Processors in Nigeria-Cameroon-Chad border region


Processors

(X)

Cumulative

Percent

Total Value of

Monthly Sales

(₦)

% of Total

Sales

Cumulative

Percent (Y)

XY

≤ 250000.00 11 24.40 24.40 1718600.17 4.07 4.07 0.0099

250000.01 - 500000.00 8 17.80 42.20 2749571.43 6.51 10.58 0.0188

500000.01 - 750000.00 2 4.40 46.70 1274742.86 3.02 13.60 0.0060

750000.01 - 1000000.00 8 17.80 64.40 6748954.03 15.98 29.58 0.0527

1000000.01 - 1250000.00 5 11.10 75.60 5635612.50 13.34 42.92 0.0476

1250000.01 - 1500000.00 5 11.10 86.70 6893053.51 16.32 59.24 0.0658

1500000.01 - 1750000.00 2 4.40 91.10 3423763.78 8.11 67.35 0.0296

2250000.01 - 2500000.00 1 2.20 93.30 2280000.00 5.40 72.75 0.0160

≥2500000.01 3 6.70 100.00 11506970.47 27.25 100.00 0.0670

Total 45 100.00

∑xy 0.3134

GI = 0.69

103

Table 4.13: Distribution of total monthly revenue of dried fish Wholesalers in Nigeria-Cameroon-Chad border region


Marketers

(X)

Cumulative

Percent

Total Value

of Monthly

Sales (₦)

% of

Total

Sales

Cumulative

Percent (Y)

XY

≤ 250000.00 1 12.50 12.50 216857.14 1.27 1.27 0.0016

250000.01 - 500000.00 0 00.00 00.00 0.00 0.00 1.27 0.0000

500000.01 - 750000.00 0 0.00 0.00 0.00 0.00 1.27 0.0000

750000.01 - 1000000.00 0 0.00 0.00 0.00 0.00 1.27 0.0000

1000000.01 - 1250000.00 1 12.50 25.00 1108727.08 6.51 7.78 0.0097

1250000.01 - 1500000.00 1 12.50 37.50 1264369.23 7.42 15.20 0.0190

1500000.01 - 1750000.00 0 0.00 0.00 0.00 0.00 15.20 0.0000

1750000.01 - 2000000.00 1 12.50 50.00 1957444.44 11.49 26.69 0.0334

2000000.01 - 2250000.00 0 0.00 0.00 0.00 0.00 26.29 0.0000

2250000.01 - 2500000.00 1 12.50 62.50 2492470.59 14.63 41.32 0.0517

≥2500000.01 3 37.50 100.00 9996600.00 58.68 100.00 0.3750

Total 8 100.00

∑xy 0.4903

GI = 0.51

104

Table 4.14: Distribution of total monthly revenue of dried fish Retailers in Nigeria-Cameroon-Chad border region


Marketers

(X)

Cumulative

Percent

Total Value of

Monthly Sales (₦)

% of Total

Sales

Cumulative

Percent (Y)

XY

≤ 250000.00 10 62.50 62.50 1690615.55 44.97 44.97 0.281

250000.01 - 500000.00 6 37.50 100.00 2069184.80 55.03 100.00 0.375

Total 16 100.00

∑xy 0.656

GI = 0.34

105

Table 4.15: Distribution of total monthly revenue of frozen fish Wholesalers in Nigeria-Cameroon-Chad border region


Marketers

(X)

Cumulative

Percent

Total Value of

Monthly Sales

(₦)

% of Total

Sales

Cumulative

Percent (Y)

XY

750000.01 - 1000000.00 2 66.70 66.70 1644210.53 46.66 46.66 0.31

1750000.01 - 2000000.00 1 33.30 100.00 1879944.44 53.34 100.00 0.33

Total 3 100.00

∑xy 0.64

GI = 0.36

106

Table 4.16 reveals that the highest percentage of retailers (66.70%) of frozen fish handled 62.78%

of the total monthly sales. The mean monthly revenue made was N165523.81±16881.95. The Gini

coefficient computed for retailers of frozen fish in fish markets in Nigeria-Cameroon-Chad border

region was 0.25.

4.6.3.8 Fresh Fish Markets

Table 4.17 shows the computation of Gini coefficient of fresh fish markets in along Nigeria-

Cameroon-Chad border. The highest percentage of fresh fish marketing actors (49.16%) realized

a monthly revenue of N 250000.00 and less and handled 18.91% of the total sales. The category

of fresh fish marketers that handled the largest percentage of the total sales (21.42%) realized a

monthly revenue of N 2500000.01 – N 500000.00 and constituted 25.42% of the fresh fish

marketing actors. The empirical results revealed a computed Gini coefficient of 0.65. The Lorenz

curve for fresh fish markets in Nigeria-Cameroon-Chad border region in figure 4.18 shows the

departure of the curve from the 45-degree line.

4.6.3.9 Smoked Fish Markets

The computation for Gini coefficient in table 4.18 reveals that the highest percentage of smoked

marketing actors (32.60%) in Nigeria-Cameroon-Chad border region realized a monthly revenue

range of N 250000.01 – N 500000.00 and handled 12.79% of the total sales in smoked fish markets.

The marketing actors (8.33%) of smoked fish that had the largest percentage of total sales (26.94%)

in smoked fish markets made a monthly sale of N 2500000.01 and more. The computations

revealed that smoked fish market had Gini coefficient value of 0.70. Figure 4.19 represents the

Lorenz curve for smoked fish markets in Nigeria-Cameroon-Chad border region.

4.6.3.10 Dried Fish Markets

The analysis for Gini coefficient in table 4.19 indicates that the highest percentage of actors

(31.9%) in dried fish markets realized a monthly revenue range of N 250000.00 and less, and

handled 5.75% of the total revenue in dried fish markets. The dried marketing participants (8.7%)

that had the largest percentage of total revenue (34.12%) made a monthly revenue of N 2500000.01

and more.

107

Table 4.16: Distribution of total monthly revenue of frozen fish Retailers in Nigeria-Cameroon-Chad border region


Marketers

(X)

Cumulative

Percent

Total Value of

Monthly Sales

(₦)

% of Total

Sales

Cumulative

Percent (Y)

XY

≤ 160000.00 2 66.70 66.70 311771.43 62.78 62.78 0.42

160000.01 - 172500.00 0 0.00 0.00 0.00 0.00 0.00 0.00

≥172500.01 1 33.30 100.00 184800.00 37.22 100.00 0.33

Total 3 100.00

∑xy 0.75

GI = 0.25

108

Table 4.17: Computation of Gini-coefficient of fresh fish markets in Nigeria-Cameroon-Chad border region

Total Revenue (₦) Frequency % of Actors

(X)

Cumulative

Percent

Total Value of

Monthly Sales

(₦)

% of Total

Sales

Cumulative

Percent (Y)

XY

≤ 250000.00 205 49.16 49.16 32793791.80 18.91 18.91 0.0930

250000.01 - 500000.00 106 25.42 74.58 37151862.48 21.42 40.33 0.1025

500000.01 - 750000.00 36 8.63 83.21 21977517.66 12.67 53.01 0.0458

750000.01 - 1000000.00 23 5.52 88.73 20493296.76 11.82 64.83 0.0358

1000000.01 - 1250000.00 24 5.76 94.48 26252932.94 15.14 79.97 0.0460

1250000.01 - 1500000.00 15 3.60 98.08 20620503.88 11.89 91.86 0.0330

1500000.01 - 1750000.00 4 0.96 99.04 6649800.00 3.83 95.69 0.0092

1750000.01 - 2000000.00 4 0.96 100.00 7472900.00 4.31 100.00 0.0096

Total 417 100.00

∑xy 0.3749

GI= 0.63

109

Figure 4.18: Lorenz curve for fresh fish markets in Nigeria-Cameroon-Chad border region

0.00

20.00

40.00

60.00

80.00

100.00

120.00

0.00 20.00 40.00 60.00 80.00 100.00 120.00

Cu

mu

lati

ve

% o

f M

on

thly

Rev

enu

e

Cumulative % of Fresh fish marketing actors

110

Table 4.18: Computation of Gini-coefficient of smoked fish markets in Nigeria-Cameroon-Chad border region

Total Monthly Revenue Frequency % of Actors

(X)

Cumulative

Percent

Total Value of Monthly

Sales (₦)

% of Total

Sales

Cumulative

Percent (Y)

XY

≤ 250000.00 85 20.83 20.83 15686349.39 4.19 4.19 0.0087

250000.01 - 500000.00 133 32.60 53.43 47895299.22 12.79 16.97 0.0553

500000.01 - 750000.00 40 9.80 63.24 24891632.09 6.64 23.62 0.0232

750000.01 - 1000000.00 22 5.39 68.63 18730566.38 5.00 28.62 0.0154

1000000.01 - 1250000.00 17 4.17 72.79 19515995.74 5.21 33.83 0.0141

1250000.01 - 1500000.00 15 3.68 76.47 20025886.23 5.35 39.17 0.0144

1500000.01 - 1750000.00 9 2.21 78.68 14661641.18 3.91 43.09 0.0095

1750000.01 - 2000000.00 19 4.66 83.33 35827519.91 9.56 52.65 0.0245

2000000.01 - 2250000.00 19 4.66 87.99 40758450.53 10.88 63.53 0.0296

2250000.01 - 2500000.00 15 3.68 91.67 35703262.69 9.53 73.06 0.0269

≥ 2500000.01 34 8.33 100.00 100924166.80 26.94 100.00 0.0833

Total 408 100.00

0.3049

GI= 0.70

111

Figure 4.19: Lorenz curve for smoked fish markets along Nigeria-Cameroon-Chad border

0.00

20.00

40.00

60.00

80.00

100.00

120.00

0.00 20.00 40.00 60.00 80.00 100.00 120.00

Cu

mu

lati

ve

% o

f M

on

thly

Rev

enu

e

Cumulative % of Smoked fish marketing actors

112

Table 4.19: Computation of Gini-coefficient of dried fish markets in Nigeria-Cameroon-Chad border region


(X)

Cumulative

Percent

Total Value of

Monthly Sales (₦)

% of Total

Sales

Cumulative

Percent (Y)

XY

≤ 250000.00 22 31.9 31.9 3626072.86 5.75 5.75 0.0183

250000.01 - 500000.00 14 20.3 52.2 4818756.23 7.65 13.40 0.0272

500000.01 - 750000.00 2 2.9 55.1 1274742.86 2.02 15.42 0.0045

750000.01 - 1000000.00 8 11.6 66.7 6748954.03 10.71 26.13 0.0303

1000000.01 - 1250000.00 6 8.7 75.4 6744339.58 10.70 36.83 0.0320

1250000.01 - 1500000.00 6 8.7 84.1 8157422.74 12.94 49.77 0.0432

1500000.01 - 1750000.00 2 2.9 87.0 3423763.78 5.43 55.20 0.0160

1750000.01 - 2000000.00 1 1.4 88.4 1957444.44 3.11 58.31 0.0085

2250000.01 - 2500000.00 2 2.9 91.3 4772470.59 7.57 65.88 0.0191

≥ 2500000.01 6 8.7 100.0 21503570.47 34.12 100.00 0.0870

Total 69 100.0

0.2861

GI = 0.71

113

The Gini coefficient value estimated for marketers of dried fish in the States along Nigeria-

Cameroon-Chad border was 0.71. Figure 4.20 shows the Lorenz curve for dried fish marketers and

the extent of departure of the curve from the 45-degree line.

4.6.4.11 Frozen Fish Markets

Table 4.20 shows the computation of Gini coefficient of market participants in the frozen fish

markets in Nigeria-Cameroon-Chad border region. The highest percentage of frozen fish marketers

(50.00%) realized a monthly revenue of N 250000.00 and less and handled 12.35% of the total

revenue. The category of frozen fish marketers that handled the largest percentage of the total sales

(46.76%) realized a monthly revenue of N 1750000.01 – N 2000000.00 and constituted 16.70%

of the frozen fish marketers. The empirical results revealed that the marketers of frozen fish were

concentrated with Gini coefficient of 0.59, indicating the possibility of existence of non-

competitive behaviour with monopolistic nature in the imperfect structure of frozen fish markets

and inequality in market share among frozen fish marketers in Nigeria-Cameroon-Chad border

region. The Lorenz curve for frozen fish marketers in Nigeria-Cameroon-Chad border region is

illustrated in figure 4.21.

4.6.4 HERFINDAHL INDEX


The analysis for Herfindahl index for fresh fish markets comprising of producers, wholesalers and

retailers is presented in table 4.21. The value of Herfindahl index estimated was 0.32.


The analysis for Herfindahl index for smoked fish markets comprising of processors, wholesalers

and retailers is presented in table 4.22. The Herfindahl index estimated was 0.46 for smoked fish

markets.

114

Figure 4.20: Lorenz curve for dried fish markets in Nigeria-Cameroon-Chad border region

0.00

20.00

40.00

60.00

80.00

100.00

120.00

0.0 20.0 40.0 60.0 80.0 100.0 120.0

Cu

mu

lati

ve

% o

f M

on

thly

Rev

enu

e

Cumulative % of Dried fish marketing actors

115

Table 4.20: Computation of Gini-coefficient of frozen fish markets in Nigeria-Cameroon-Chad border region


(X)

Cumulative

Percent

Total Value of

Monthly Sales (₦)

% of Total

Sales

Cumulative

Percent (Y)

XY

≤ 250000.00 3 50.0 50.0 496571.43 12.35 12.35 0.0618

750000.01 - 1000000.00 2 33.3 83.3 1644210.53 40.89 53.24 0.1775

1750000.01 - 2000000.00 1 16.7 100.0 1879944.44 46.76 100.00 0.1667

Total 6 100.0

0.4059

GI = 0.59

116

Figure 4.21: Lorenz curve of frozen fish markets along Nigeria-Cameroon-Chad border

0.00

20.00

40.00

60.00

80.00

100.00

120.00

0.0 20.0 40.0 60.0 80.0 100.0 120.0

Cu

mu

lati

ve

% o

f M

on

thly

Rev

enu

e

Cumulative % of Frozen fish marketing actors

117

Table 4.21: Computations of Herfindahl index for fresh fish markets in Nigeria-Cameroon-

Chad border region

Marketing Participants Total Quantity Sold (Kg) Market Share (Si) Si2

Producer (Culture) 110272.47 43.81 0.1919

Producer (Capture) 77365.40 30.74 0.9446

Wholesaler 43932.65 17.45 0.0305

Retailer 20132.10 8.00 0.0064

Total 251702.62 100.00 0.3233

Herfindahl Index = 0.32

118

Table 4.22: Computations of Herfindahl index for smoked fish markets in Nigeria-

Cameroon-Chad border region


Processor 121827.71 56.06 0.3142

Wholesaler 81838.77 37.66 0.1418

Retailer 13656.47 6.28 0.0039

Total 217322.94 100.00 0.4600


119


Table 4.23 presents the computations for Herfindahl index for dried fish markets comprising of

processors, wholesalers and retailers. The Herfindahl index estimated was 0.55 for dried fish

markets which signifies high degree of concentration and low competition among marketers in

dried fish markets in Nigeria-Cameroon-Chad border region.


The determination of Herfindahl index for frozen fish markets comprising of wholesalers and

retailers is presented in table 4.24. The Herfindahl index estimated was 0.72 for frozen fish markets

which signifies high degree of concentration and low competition among frozen fish marketers in

fish markets in Nigeria-Cameroon-Chad border region. This suggests that wholesalers had the

highest market power as a result of their huge market share in the frozen fish markets in the study

area.

4.6.4.5 Herfindahl index of Fish Markets in each sampled State

Table 4.25 reveals the herfindahl index of the forms of fish products identified across the six States

along Nigeria-Cameroon-Chad border. In Akwa Ibom State, the Herfindahl indices for fresh,

smoked, dried and frozen fish were estimated at 0.48, 0.54, 0.61 and 1.00, respectively. In Cross

River State, the Herfindahl indices computed were 0.36, 0.80, 0.40 and 1.0 for fresh, smoked, dried

and frozen fish markets, respectively.

The fish market in Benue State had Herfindahl indices of 0.31, 0.48 and 0.45 for fresh, smoked

and frozen fish markets. In Taraba State, the Herfindahl index for fresh fish was 0.32, Herfindahl

index for smoked fish was 0.73 and Herfindahl index for dried fish was 0.68. Fresh, smoked, dried

and frozen fish markets in Adamawa State had Herfindahl indices of 0.28, 0.48, 0.99 and 0.71,

respectively. The Herfindahl indices estimated for fish markets in Borno State were 0.71, 0.48,

0.70 and 1.00 for fresh, smoked, dried and frozen fish markets, respectively.

120

Table 4.23: Computations of Herfindahl index for dried fish markets in Nigeria-Cameroon-

Chad border region



Processor 29053.82 69.74 0.4864

Wholesaler 10403.47 24.97 0.0624

Retailer 2199.93 5.28 0.0028

Total 41657.22 100.00 0.5515

121

Table 4.24: Computations of Herfindahl index for frozen fish markets in Nigeria-

Cameroon-Chad border region

Marketing Participants Total Quantity Sold (Kg) Market Share (Si) Si2 HI

Wholesaler 2675.76 83.11 0.6907 0.7192

Retailer 543.71 16.89 0.0285

Total 3219.47 100.00 0.7192

Herfindahl Index (HI) = 0.72

122

Table 4.25: Herfindahl index of the forms of fish marketed in the States along Nigeria-

Cameroon-Chad border

Fish Products Akwa Ibom Cross Rivers Benue Taraba Adamawa Borno

Fresh 0.4854 0.3575 0.3106 0.3150 0.2780 0.7146

Smoked 0.5449 0.8045 0.4755 0.7298 0.4785 0.4796

Dried 0.6106 0.3954 0.4548 0.6846 0.9857 0.6963

Frozen 1.0000 1.0000 - - 0.7145 1.0000

123

4.6.5 ECONOMIES OF SCALE

Linear regression was used to assess the barriers to entry for the marketing participants into fish

markets based on the coefficient of quantities of fish sold by the marketing actors.

4.6.5.1 Fresh Fish Market

The linear regression model Y = 1103.826 + 84.154X obtained from the regression curve presented

in figure 4.22 connotes the positive relationship between total marketing cost and total monthly

quantity of fresh fish sold in Nigeria-Cameroon-Chad border region. The coefficient of

determination (R2) was 0.470 and significant (P ≤ 0.05). This indicated that at 5% significant level

only 47.0% of the total quantity of fish sold by the fresh fish marketers was predicted by the total

marketing cost they incurred. The coefficient of the explanatory variable was 84.154.

4.6.5.2 Smoked Fish Market

The regression curve for smoked fish marketers is presented in figure 4.23. The linear regression

model Y = 8171.989 + 10.288X reveals the positive relationship between total marketing cost and

total monthly quantity of smoked fish sold in Nigeria-Cameroon-Chad border region. The

coefficient of determination (R2) was 0.318 and significant (P ≤ 0.05). Therefore, at 5% significant

level only 31.8% of the total quantity of fish sold by the smoked fish marketers was explained by

the total marketing cost they incurred. The coefficient of the total quantity of smoked fish sold in

a month was positive (10.288).

4.6.5.3 Dried Fish Market

The linear regression model Y = 7367.471 + 31.439X obtained from the regression curve shown

in figure 4.24, connotes the positive relationship between total marketing cost and total monthly

quantity of dried fish sold in the States along Nigeria-Cameroon-Chad border is presented in figure

4.24. The coefficient of determination (R2) was 0.301 and significant (P ≤ 0.05). The coefficient

of the total quantity of dried fish sold in a month was 31.439.

124

Figure 4.22: Relationship between total marketing cost and total monthly quantity of fresh

fish sold

Y = 1103.826 + 84.154X

R2 = 0.470; Sig = 0.00

b = + (Barrier to Marketing Area: Increase in

quantity sold, increase in marketing cost)

125

Figure 4.23: Relationship between total marketing cost and total monthly quantity of

smoked fish sold

Y = 8171.989 + 10.288X

R2 = 0.318; Sig = 0.00


quantity sold, increase in marketing cost)

126

Figure 4.24: Relationship between total marketing cost and total monthly quantity of dried

fish sold

Y = 7367.471 + 31.439X

R2 = 0.301; Sig = 0.00


quantity sold increase in marketing cost)

127

Therefore, at 5% significant level only 30.1% of the total quantity of fish sold by the dried fish

marketers was predicted by the total marketing cost incurred by dried fish marketers.

4.6.5.4 Frozen Fish Market

Figure 4.25 presents the regression curve for frozen fish marketers having a linear regression

model Y = 11332.924 + 10.313X which connotes the positive relationship between total marketing

cost and total monthly quantity of fresh fish sold in Nigeria-Cameroon-Chad border region. The

coefficient of determination (R2) was 0.404 and significant (P ≤ 0.05). This indicated that at 5%

significant level only 40.4% of the total quantity of fish sold by the frozen fish marketers was

accounted for by the total marketing cost they incurred. The coefficient of the explanatory variable

was 10.313.

4.6.5.5 Linear regression estimates for fish markets in Akwa Ibom State

Table 4.26 shows the linear regression estimates for fresh, smoked and dried fish products sold in

Akwa Ibom State. It reveals that the coefficient of determination (R2) is significant at 5% for all

the forms of fish. The coefficient of determination (R2) for fresh, smoked and dried fish were

0.611, 0.616 and 0.999, respectively. This indicated that at 5% significance, 61.1%, 61.6% and

99.9% of the total quantities of fresh, smoked and dried fish, respectively marketed in Akwa Ibom

State can be explained by the total marketing cost incurred by the fish marketers. The coefficient

of explanatory variable for fresh, smoked and dried fish sold were 149.874, 14.842 and 21.302,

respectively.

4.6.5.6 Linear regression estimates for fish markets in Cross River State

Table 4.27 presents the linear regression estimates for the forms of fish sold in Cross River State.

It reveals that the coefficient of determination (R2) is significant at 5% for fresh and smoked fish.

The coefficient of determination (R2) for fresh, smoked and dried fish were 0.583, 0.682 and 0.067,

respectively.

128

Figure 4.25: Relationship between total marketing cost and total monthly quantity of

frozen fish sold

Y = 11332.924 + 10.313X

R2 = 0.404; Sig = 0.00


quantity sold increase in marketing cost)

129

Table 4.26: Linear regression estimates showing the relationship between total quantities sold (kg) and total marketing cost (₦)

of major forms of fish marketed in Akwa Ibom State

Fish Products Unstandardized Coefficients Standardized

Coefficients

t-value Sig. R2 Sig.

B Std. Error Beta

Fresh Total Quantity Sold (Kg) 149.874 16.128 0.782 9.293 0.000* 0.611 0.000*

(Constant) -19598.579 22324.808

-0.878 0.384

Smoked Total Quantity Sold (Kg) 14.842 1.256 0.785 11.816 0.000* 0.616 0.000*

(Constant) 9495.658 732.622

12.961 0.000*

Dried Total Quantity Sold (Kg) 21.302 0.522 1.000 40.775 0.016* 0.999 0.016*

(Constant) 6350.507 316.336

20.075 0.032*

The dependent variable is Total Marketing Cost (₦); *Significant at P < 0.05

130

Table 4.27: Linear regression estimates showing the relationship between total quantities sold (kg) and total marketing cost (₦)

of the forms of fish marketed in Cross River State


Coefficients


B Std. Error Beta


(Constant) 16417.465 2129.767

7.709 0.000*


(Constant) 1021.678 1195.248

0.855 0.397

Dried Total Quantity Sold (Kg) 32.066 34.654 0.258 0.925 0.373 0.067 0.313*

(Constant) 12474.044 5730.716

2.177 0.050*

Frozen Total Quantity Sold (Kg) -254.545 0.000 -1.00 - - - -

(Constant) 59800.000 0.000


131

This indicated that at 5% significance, 58.3% and 68.2% of the total quantities of fresh and smoked

fish respectively marketed in Cross River State can be accounted for by the total marketing cost

incurred by these fish marketers. The coefficient of total quantities of fresh, smoked, dried and

frozen fish sold were 30.794, 61.624, 32.066 and -254.545, respectively.

4.6.5.7 Linear regression estimates for fish markets in Benue State

The linear regression estimates for fresh, smoked and dried fish products sold in Benue State are

shown in table 4.28. It reveals that the coefficient of determination (R2), significant at 5% for all

the forms of fish were 0.383, 0.267 and 0.666, respectively. This indicated that at 5% significance,

38.3%, 26.7% and 66.6% of the total volume of fresh, smoked and dried fish, respectively can be

explained by the total marketing cost incurred by the fish marketers in Benue State. The coefficient

of explanatory variable for fresh, smoked and dried fish sold were 20.088, 8.989 and 77.065,

respectively.

4.6.5.8 Linear regression estimates for fish markets in Taraba State

The coefficient of determination (R2) for fresh, smoked and dried fish were 0.603, 0.132 and 0.404,

respectively as obtained in table 4.29 on the linear regression estimates for fish products sold in

Taraba State. At 5% significant level, 60.3% and 13.2% of the total marketed quantities of fresh

and smoked, respectively can be predicted by the total marketing cost incurred by these fish

marketers in Taraba State. The coefficient of the total quantities of fresh, smoked and dried fish

sold were 58.295, 5.102 and -14.366, respectively.

4.6.5.9 Linear regression estimates for fish markets in Adamawa State

In Adamawa State, the coefficient of determination (R2) for fresh, smoked and dried fish

significant at 5% were 0.582, 0.077 and 0.565, respectively as obtained from the linear regression

estimates for fish products sold in the State as shown in table 4.30. This indicated that at 5%

significance, 58.2%, 0.7% and 56.5% of the total marketed quantity of fresh, smoked and dried

fish, respectively can be explained by the total marketing cost incurred by the fish marketers in

Benue State.

132

Table 4.28: Linear regression estimates showing the relationship between total quantities sold (kg) and total marketing cost

(₦) of the forms of fish marketed in Benue State

Fish

Products

Unstandardized Coefficients Standardized

Coefficients


B Std. Error Beta


(Constant) 17522.273 2603.165

6.731 0.000*


(Constant) 7553.119 1190.178

6.346 0.000*


(Constant) -18700.227 11692.284

-1.599 0.125


133


(₦) of the forms of fish marketed in Taraba State

Fish

Products


Coefficients


B Std. Error Beta


(Constant) 6517.118 3686.209

1.768 0.082


(Constant) 5139.534 873.123

5.886 0.000*

Dried Total Quantity Sold (Kg) -14.366 8.726 -0.636 -1.646 0.175 0.404 0.175

(Constant) 16760.353 3034.512

5.523 0.005*


134


(₦) of the forms of fish marketed in Adamawa State


Coefficients


B Std. Error Beta


(Constant) 8593.280 3360.670

2.557 0.013*


(Constant) 11267.499 1956.411

5.759 0.000*


(Constant) 10641.345 2427.384

4.384 0.000*

Frozen Total Quantity Sold (Kg) -4.490 0.000 -1.000

(Constant) 15790.170 0.000


135

The coefficient of explanatory variable was positive for fresh, smoked and dried fish sold (45.710,

5.666 and 10.137, respectively) while frozen fish had a negative coefficient of explanatory variable

(-4.490).

4.6.5.10 Linear regression estimates for fish markets in Borno State

Table 4.31 presents the linear regression estimates for fresh, smoked and dried fish marketed in

Borno State. The coefficient of determination (R2) is significant for these forms of fish at 5% level.

The values of R2 were 0.688, 0.328 and 0.980 for fresh, smoked and dried fish, respectively. This

revealed that at 5% significance, 68.8%, 32.8% and 98.0% of the total marketed quantity of fresh,

smoked and dried fish, respectively can be predicted by the total marketing cost incurred by these

fish marketers in Borno State. The coefficient of explanatory variable was positive for fresh,

smoked and dried fish sold (58.344, 10.754 and 0.929, respectively).

4.7 QUANTITIES, COSTS, PROFITABILITY INDICES AND MARKETING

EFFICIENCY OF FISH PRODUCTS

4.7.1 Average Monthly Quantities, Costs, Profitability and Marketing Efficiency Indices of

Fish Products Marketed

Average monthly quantities, prices, costs, profitability indices and marketing efficiency of

different forms of fish marketed in Nigeria-Cameroon-Chad border region is presented in Table

4.32. The results of this study revealed that fresh fish had the highest average monthly quantity of

603.60±582.11kg while smoked fish had the least average quantity of 532.65±477.29kg as there

was no significant difference (P>0.05) in the average monthly quantities of fish products marketed

along Nigeria-Cameroon-Chad border region. There was significant variation (P<0.05) in the

average buying and selling prices of fish products marketed in the study area. Smoked fish had

the highest buying and selling prices of ₦1,004.94±499.51 per kg and ₦1715.34±505.91 per kg

respectively while fresh fish had the least buying and selling prices of ₦323.39±337.03 per kg and

₦765.37±322.04 per kg. Fresh fish had the highest average marketing cost of

₦49,691.63±31,426.81 while smoked fish had the least average marketing cost of

₦13,651.84±8,710.74.

136


(₦) of the major forms of fish marketed in Borno State

Fish

Products


Coefficients


B Std. Error Beta


(Constant) 9714.355 3109.601

3.124 0.003*


(Constant) 8487.076 1815.236

4.675 0.000*

Dried Total Quantity Sold (Kg) 0.929 34.728 0.013 0.027 0.980 0.980 0.000*

(Constant) 34847.165 35809.153

0.973 0.386


137

Table 4.32: Average monthly quantities, profitability and marketing efficiency indices of the forms of fish marketed in

Nigeria-Cameroon-Chad border region

Variables Fresh

Smoked

Dried

Frozen

Mean SD Mean SD Mean SD Mean SD

Total Quantity Sold (Kg) 603.60a 582.11 532.65 a 477.29 603.73 a 567.73 536.58 a 392.95

Buying Price (₦ Per Kg) 323.39c 337.03 1004.94a 499.51 783.12ab 327.57 696.67b 193.05

Selling Price (₦ Per Kg) 765.37d 322.04 1715.34a 505.91 1429.46b 416.42 1100.00c 401.25

Total Purchase Cost (₦) 162042.06b 148950.35 544344.91a 602017.62 433149.98ab 424308.14 403951.94ab 361861.12

Total Marketing Cost (₦) 49691.63a 31426.81 13651.84b 8710.74 26347.83ab 24815.80 16866.67b 6377.04

Other operational costs (₦) 27451.37a 20855.62 12860.29b 12299.38 8757.97b 7928.83 5050.00b 3689.85

Total Variable Cost (₦) 170016.03b 118951.04 570857.04a 603184.50 468255.78a 423284.36 425868.61ab 368329.91

Fixed Cost (Depreciated) (₦) 1557.96a 1057.02 446.82b 337.93 361.03b 227.10 481.65b 319.11

Total Production Cost (₦) 171570.25b 118712.20 571303.87a 603208.98 468616.81a 423274.33 426350.26ab 368594.95

Total Monthly Revenue (₦) 415857.57b 384194.19 918188.16a 895554.23 913442.57a 858396.88 670121.07ab 654577.42

Gross Margin (₦) 245841.54a 159031.67 347331.12a 393850.24 445186.80a 387369.96 244252.46a 219549.57

Gross Margin/kg (₦) 434.51bc 257.86 622.93a 310.00 555.93ab 391.28 342.78c 267.63

Net Return (₦) 244287.31a 158706.18 346884.30a 393754.59 444825.77a 387344.86 243770.81a 219325.62

Net Return/kg 430.37bc 257.53 621.43a 309.97 554.70ab 391.54 341.78c 267.79

Marketing Margin (₦) 322984.54a 309126.24 373843.26a 402853.05 480292.59a 704419.24 266169.12a 226991.32

Marketing Margin/kg 580.02ab 263.51 710.40a 313.93 646.34a 369.57 403.33b 250.73

Marketing Efficiency 16.49b 21.87 83.28a 82.52 44.35b 42.93 35.64b 27.68

Mean values with the same alphabet superscripts on the same row are not significantly different (P>0.05)

138

The average total production cost of fresh fish (₦171,570.25±118,712.20) was significantly

(P<0.05) lower than that of smoked fish which had the highest average production cost of

₦571,303.87±603,208.98. There were also significant differences (P<0.05) in the average

purchase, other operational, variable and fixed costs of fish products marketed along Nigeria-

Cameroon-Chad border. The profitability indices results (Table 4.32) revealed that there was

significant difference (P<0.05) in the average monthly revenue realized from the fish products

marketed along Nigeria-Cameroon-Chad border region. The highest average monthly revenue of

₦918,188.16±895,554.23 was realized from smoked fish while fresh fish had the least revenue of

₦415,857.57±384,194.19. The highest average gross margin, net return per kg and marketing

margin of ₦445,186.80±387,369.96, ₦621.43±309.97 and ₦480,292.59±704,419.24 respectively

were recorded in dried, smoked and dried fish products marketed in the region. There also existed

a significant difference (P<0.05) in the marketing efficiency of the fish products. Smoked fish had

the highest average marketing efficiency of 83.28±82.52 while fresh fish had the least marketing

efficiency of 16.49±21.87.

4.7.2 Average monthly quantities of fish products marketed across the States along Nigeria-


The results presented in Tables 4.33 and figure 4.22 indicated that the highest average monthly

quantity of fresh fish and frozen fish of 1,175.37±737.72kg and 989.44±0.00kg respectively were

marketed in Akwa Ibom State while Borno State had the highest average monthly quantity of

smoked and dried fish of 967.15±529.57kg and 881.81±585.46kg respectively in the study region.

Cross Rivers State had the least average quantities of fresh (481.46±489.36kg), smoked

(171.30±89.22kg) and dried fish (154.73±60.55kg) while no information was supplied on frozen

fish marketed in Benue and Taraba States. There was significant difference (P<0.05) in the average

total quantities of fish products marketed in the study area. These forms of fish were sold in

different selling modules. These modules are- baskets, cartons, basins, bags, counting and scales

(kilogram). Fish either in its fresh or processed form under goes some level of sorting at different

level of the marketing system. The sorting is basically dependent on the species and size of the

fish. The different fish species had different values to the consumers and as such attracted different

prices in the markets.

139

Table 4.33: Average monthly quantities of fish products in fish markets in the States along Nigeria-Cameroon-Chad border

States

Fresh

Smoked

Dried

Frozen

Mean SD % Mean SD % Mean SD % Mean SD %

Akwa Ibom 1175.37a 737.72 26.62 417.28b 409.87 17.09 460.82ab 451.09 3.32 989.44a 0.00 30.73

Cross River 481.46b 489.36 16.45 171.30c 89.22 3.78 154.73b 60.55 5.20 183.86d 11.11 11.42

Benue 593.17b 610.24 16.73 442.01b 397.40 11.59 776.27ab 576.22 41.00 NS 0.00 0.00

Taraba 499.08 b 407.50 13.88 454.16b 341.00 15.46 305.83ab 181.37 4.40 NS 0.00 0.00

Adamawa 542.04 b 538.56 17.01 531.04b 455.40 12.46 772.48ab 763.57 33.38 510.11c 472.50 31.69

Borno 433.89 b 374.64 9.31 967.15a 529.57 39.61 881.81a 585.46 12.70 842.11b 0.00 26.16

Total 603.60 582.11 100.00 532.65 477.29 100.00 603.73 607.73 100.00 536.58 392.95 100.00

Mean values with the same alphabet superscripts on the same column are not significantly different (P>0.05);

NS-No Information Supplied

140

Figure 4.26: Average monthly quantities of forms of fish sold in fish markets in the States

along Nigeria-Cameroon-Chad border

Note: Forms of fish with the same alphabet on error bar are not significantly different (P<0.05)

a

b

b

bb

bb

c

b b

b

a

ab

b

ab

ab

ab

a

a

d

c

b

0.00

200.00

400.00

600.00

800.00

1000.00

1200.00

1400.00


Av

era

ge

Mo

nth

ly Q

ua

nti

ty o

f F

ish

Pro

du

cts

in F

ish

Ma

rket

s (K

g)

States along Nigeria-Cameroon-Chad Border Region

Fresh

Smoked

Dried

Frozen

141

4.7.3 Average Monthly Prices, Costs, Profitability Indices and Marketing Efficiency of

Fresh Fish Marketed in the States along Nigeria-Cameroon-Chad border

The results presented in Table 4.34 indicated that the highest average monthly buying and selling

prices of N383.16±350.16 per kg quantities and N 835.00±359.38 per kg respectively were

recorded in Cross Rivers State as there was no significant difference (P>0.05) in the buying price

while the selling price of fresh fish differs significantly (P<0.05) according to States. Revealed in

this study was the variation (P<0.05) that existed in the all average monthly costs except fixed cost

associated with fresh fish products according to States in the study area. The average monthly cost

of marketing incurred on fresh fish was highest (N35610.71±30594.49) in Taraba State while

Akwa Ibom had the least average marketing cost of N156558.77±131456.81.

Akwa Ibom State had the highest average revenue of ₦696,064.96±403,589.26 while Borno State

had the least average revenue of ₦336,034.23±285,999.42 recorded from marketed fresh fish in

the study area. Statistically, there was no significant difference (P<0.05) in the average monthly

revenue realized from marketed fresh fish in the region. The average marketing margin per kg of

₦762.13±273.93 recorded in Borno State was significantly (P<0.05) higher than that recorded for

other States in the study area. Meanwhile, Adamawa had the highest marketing efficiency of

21.83±21.16 as Akwa Ibom had the least efficiency of 9.36±8.02.


Smoked Fish Marketed in the States along Nigeria-Cameroon-Chad border

The results presented in Table 4.35 indicated that the highest average monthly buying and selling

prices of N1140.00±675.55 per kg quantities and N1908.51±564.48 per kg respectively were

recorded in Adamawa State while Cross Rivers had the least buying price of ₦777.92±322.33 and

Taraba State had the least selling price of ₦1,488.46±436.49. There was significant difference

(P<0.05) in the buying and selling prices of marketed smoked fish according to States in the study

area. The highest average total marketing and variable costs of N18887.64±9936.18 and

₦967167.27±606938.09 respectively incurred on smoked fish were recorded in Borno State while

Taraba State had the least average total marketing and variable costs of N7456.76±4786.60 and

₦361,573.84±236,572.84 respectively.

142

Table 4.34: Average monthly quantities, profitability indices and marketing efficiency of fresh fish marketed in the States

along Nigeria-Cameroon-Chad border

Variables Akwa Ibom Cross River Benue

Mean SD Mean SD Mean SD

Total Quantity Sold (Kg) 1175.37a 737.72 481.46b 489.36 593.17 b 580.24

Buying Price (₦ Per Kg) 136.53b 124.32 383.16 a 350.99 377.29 b 318.88

Selling Price (₦ Per Kg) 619.12c 205.39 835.00a 359.38 788.59ab 253.49

Total Purchase Cost (₦) 119317.69ab 108645.61 129530.19ab 112094.18 218638.31a 339701.80

Total Marketing Cost (₦) 156558.77a 131456.31 31243.60b 20538.82 29438.03 b 19810.37

Other operational costs (₦) 63737.72a 57786.24 25817.44b 27475.17 20887.32 b 15298.27

Total Variable Cost (₦) 287281.86a 176807.60 148937.11 b 144257.52 158104.80b 256620.33

Fixed Cost (Depreciated) (₦) 1837.07a 1725.24 1350.09 a 2108.13 1657.69 a 1434.39

Total Production Cost (₦) 289086.70 a 176750.05 150287.20b 144056.93 159762.49b 256453.80

Total Revenue (₦) 696064.96a 403589.26 359198.08b 349097.97 422257.30b 426659.02

Gross Margin (₦) 408783.10a 322271.19 210260.97bc 265381.67 264152.49b 282619.96

Gross Margin/kg 339.37cd 251.69 420.29bc 241.34 480.97b 229.28

Net Return (₦) 406978.26a 322053.08 208910.88bc 264847.30 262494.80b 282179.28

Net Return/kg 337.11cd 251.59 416.84bc 241.11 476.29b 227.19

Marketing Margin (₦) 629079.59a 393194.00 267322.01b 168222.09 314477.85b 307957.93

Marketing Margin/kg 542.47b 210.93 563.22b 250.03 602.61b 261.57

Marketing Efficiency 9.36b 8.02 13.50bc 10.78 18.23ab 18.17

Mean values with the same alphabet superscripts on the same column are not significantly different (P>0.05)

143

Table 4.34 cont’d: Average monthly quantities, profitability indices and marketing efficiency of fresh fish marketed in the

States along Nigeria-Cameroon-Chad border

Variables Taraba

Adamawa

Borno


Total Quantity Sold (Kg) 499.08 b 407.50 542.04 b 538.56 433.89a 374.64

Buying Price (₦ Per Kg) 317.67 b 308.01 338.22 b 304.36 315.33b 457.87

Selling Price (₦ Per Kg) 816.54a 459.74 683.21bc 235.44 832.21ab 266.55

Total Purchase Cost (₦) 191897.80a 278424.37 187659.27a 292367.25 48933.55b 76769.56

Total Marketing Cost (₦) 35610.71 b 30594.49 33369.62 b 32260.92 35028.89 b 26348.77

Other operational costs 18530.00 b 12157.51 19741.39 b 15867.53 23225.93 b 13107.32

Total Variable Cost (₦) 177503.59b 255915.50 181384.44b 272470.33 69128.94c 45142.03

Fixed Cost (Depreciated) 1613.15 a 1616.93 1430.10 a 1257.81 1583.98 a 1624.45

Total Production Cost (₦) 179116.73b 255483.96 182814.54b 272037.96 70712.92c 44870.45

Total Revenue (₦) 385512.61b 358607.09 351061.64b 366507.16 336034.23b 285999.42

Gross Margin (₦) 208009.02bc 168777.80 169677.20c 184226.29 266905.30b 263419.59

Gross Margin/kg 467.67b 338.50 331.32d 119.09 604.48a 249.75

Net Return (₦) 206395.88bc 168453.47 168247.10c 184028.78 265321.32b 263416.27

Net Return/kg 462.50b 340.06 327.06d 118.32 599.44a 249.48

Marketing Margin (₦) 262149.74b 182310.80 222788.21b 209049.87 325160.11b 292352.67

Marketing Margin/kg 612.32b 325.97 452.02c 146.95 762.13a 273.93

Marketing Efficiency 20.61ab 18.20 21.83a 21.16 13.38bc 12.45


144

Table 4.35: Average monthly quantities, profitability indices and marketing efficiency of smoked fish products marketed in

the States along Nigeria-Cameroon-Chad border

Akwa Ibom Cross River Benue

Variables Mean SD Mean SD Mean SD

Total Quantity Sold (Kg) 417.28b 409.87 171.30a 89.22 442.01b 397.40

Buying Price (₦ Per Kg) 1091.91a 482.33 777.92c 322.33 1003.16ab 389.83

Selling Price (₦ Per Kg) 1784.98ab 496.18 1545.00cd 288.59 1688.95bc 371.96

Total Purchase Cost (₦) 571116.86b 707786.93 127805.79d 72771.59 477440.50bc 393648.68

Total Marketing Cost (₦) 15688.76b 7749.93 11578.13b 6656.88 11526.32b 6918.16

Other operational costs (₦) 12341.57b 9571.45 16400.00a 8646.80 11907.02b 8356.67

Total Variable Cost (₦) 599147.20b 708582.14 155783.91d 78910.94 500873.84bc 493623.02

Fixed Cost (Depreciated) (₦) 404.01b 357.19 294.24c 127.18 423.56b 256.14

Total Production Cost (₦) 599551.21b 708562.86 156078.16d 78903.36 501297.39bc 493598.64

Total Monthly Revenue (₦) 803930.01bc 872984.67 256764.36d 116975.19 770886.20bc 720974.75

Gross Margin (₦) 204782.81cd 208422.26 100980.45d 62950.44 270012.37bc 256033.50

Gross Margin/kg 560.51c 337.80 594.51bc 280.07 603.39bc 201.47

Net Return (₦) 204378.80cd 208428.55 100686.20d 62943.91 269588.81bc 256016.74

Net Return/kg 558.53c 337.52 592.41bc 280.09 601.79bc 201.46

Marketing Margin (₦) 232813.15cd 210095.26 128958.57d 71633.33 293445.70bc 260327.55

Marketing Margin/kg 693.07ab 333.57 767.08a 294.02 685.79ab 218.60

Marketing Efficiency 46.95c 34.65 32.43c 31.92 76.10b 67.83


145

Table 4.35 cont’d: Average monthly quantities, profitability indices and marketing efficiency of smoked fish products

marketed in the States along Nigeria-Cameroon-Chad border

Taraba

Adamawa

Borno


Total Quantity Sold (Kg) 454.16b 341.00 531.04b 455.40 967.15a 529.57

Buying Price (₦ Per Kg) 886.35bc 302.56 1140.00a 678.55 1062.75ab 608.32

Selling Price (₦ Per Kg) 1488.46d 436.49 1908.51a 564.48 1832.40ab 604.97

Total Purchase Cost (₦) 349871.13c 234588.54 576905.56b 559048.27 928111.09a 613262.06

Total Marketing Cost (₦) 7456.76d 4786.60 14276.51bc 9316.69 18887.64a 9936.18

Other operational costs (₦) 4245.95c 3463.63 11245.10b 9982.83 20168.54b 18206.06

Total Variable Cost (₦) 361573.84c 236572.84 602427.17b 555380.17 967167.27a 606938.09

Fixed Cost (Depreciated) (₦) 267.46a 171.91 454.73b 264.14 731.44a 402.61

Total Production Cost (₦) 361841.30c 236619.88 602881.89b 555328.79 967898.71a 606808.17

Total Monthly Revenue (₦) 628562.75c 492618.51 981485.74b 913165.48 1688049.22a 947495.53

Gross Margin (₦) 266988.92bc 208491.67 379058.57b 283965.26 720881.95a 512614.29

Gross Margin/kg 567.04c 353.48 689.60bc 301.36 721.46a 296.21

Net Return (₦) 266721.46bc 208456.12 378603.85c 283929.42 720150.51a 512598.54

Net Return/kg 566.21c 353.42 687.96ab 301.22 720.36a 296.33

Marketing Margin (₦) 278691.62c 208961.00 404580.18b 390291.64 759938.13a 528123.59

Marketing Margin/kg 602.10b 349.69 768.51a 316.09 769.65a 303.20

Marketing Efficiency 111.65a 90.34 95.66ab 87.33 120.93a 87.81


146

Significant difference (P<0.05) was observed in the cost variables associated with smoked fish

products marketed in the study area according to the sampled States in the study area. The results

of the profitability analysis in Table 4.35 indicated that the average monthly revenue of

₦1688049.22±947495.53 recorded in Borno State was significantly (P<0.05) higher than the least

average monthly revenue of ₦628562.75±492618.51 reported in Taraba State. Borno State also

recorded the highest gross margin, marketing margin per kg and marketing efficiency of

₦720881.95±512614.29 ₦769.65±303.20 and 120.93±87.81 respectively while Cross River State

had the least marketing efficiency of smoked fish of 32.43±31.92. There was significant difference

(P<0.05) in the profitability indices recorded in this study.


Dried Fish Marketed in the States along Nigeria-Cameroon-Chad border

Table 4.36 presents the average monthly prices, quantities, profitability indices and marketing

efficiency of dried fish marketed in the States along Nigeria-Cameroon-Chad border. The mean

buying price of dried fish ranged from N589.17±189.85 per kg in Adamawa State to

N1383.33±464.58 per kg in Akwa Ibom State while the average selling price ranged from

N1132.50±416.42 per kg in Cross River State to ₦1850.30±710.92 per kg in Akwa Ibom State.

There was significant difference (P<0.05) in the buying and selling prices of dried fish products

marketed among the study States.

The average monthly total cost of marketing dried fish was highest in Benue State

(N41122.73±34398.42) while Taraba State had the least marketing cost of N12366.67±4099.59

that was not significantly different (P>0.05) from that of Benue State. Similarly, the highest and

the least average purchase cost of ₦675497.35±529063.65 and ₦228,083.33±77,805.63 were

recorded in Benue and Taraba States respectively. In Borno State the highest average monthly

revenue, marketing margin and efficiency of ₦1422830.25±1142132.10, N907254.84±885027.93

and 61.47±61.36 respectively while Cross Rivers State had the least average monthly revenue,

marketing margin and efficiency of ₦163488.76±55674.91, ₦45486.30±37955.20 and

10.50±4.26. There was significant difference (P<0.05) in the profitability indices and marketing

efficiency of dried fish among States along Nigeria-Cameroon-Chad border.

147

Table 4.36: Average monthly quantities, profitability indices and marketing efficiency of dried fish products marketed in the


Akwa Ibom Cross River Benue


Total Quantity Sold (Kg) 460.82ab 481.09 154.73ab 60.55 776.27ab 576.22

Buying Price (₦ Per Kg) 1383.33a 464.58 695.71bc 362.38 928.18b 248.01

Selling Price (₦ Per Kg) 1850.30a 710.92 1132.50b 416.42 1512.83ab 332.46

Total Purchase Cost (₦) 489327.73ab 324500.76 94995.32a 29755.27 675497.35a 529063.65

Total Marketing Cost (₦) 16166.67a 10251.02 17435.71a 7524.18 41122.73 a 34398.42

Other operational costs (₦) 2700.00c 3724.24 5571.43bc 3468.86 6100.00bc 5734.69

Total Variable Cost (₦) 508194.39ab 338475.58 118002.46b 30801.87 722720.08a 577662.10

Fixed Cost (Depreciated) (₦) 403.16ab 44.91 299.57ab 140.31 307.25ab 225.90

Total Production Cost (₦) 508597.55ab 338453.13 118302.03b 30830.29 723027.33a 577633.44

Total Monthly Revenue (₦) 641720.63ab 407431.03 163488.76b 55674.91 1214054.92ab 1055678.36

Gross Margin (₦) 133526.23ab 77219.83 45486.30b 37955.20 491334.84ab 427025.01

Gross Margin/kg 416.18ab 283.98 281.43b 195.30 515.09ab 333.75

Net Return (₦) 133123.07ab 77258.55 45186.72b 37903.27 491027.59ab 427035.12

Net Return/kg 414.54ab 283.44 279.35b 195.26 514.40ab 333.91

Marketing Margin (₦) 152392.90ab 89604.98 68493.44b 41773.94 538557.57ab 470363.77

Marketing Margin/kg 466.99a 294.49 436.79a 202.96 584.65a 323.84

Marketing Efficiency 39.69a 3.84 10.50a 4.26 42.37a 31.55


148

Table 4.36 cont’d: Average monthly quantities, profitability indices and marketing efficiency of dried fish products marketed

in the States along Nigeria-Cameroon-Chad border

Taraba

Adamawa

Borno


Total Quantity Sold (Kg) 305.83ab 181.37 772.48ab 793.57 881.81a 585.46

Buying Price (₦ Per Kg) 841.67bc 267.24 589.17c 189.85 678.33bc 310.51

Selling Price (₦ Per Kg) 1499.05ab 501.20 1437.22ab 366.94 1513.33ab 365.88

Total Purchase Cost (₦) 228083.33ab 77805.63 431474.27ab 419832.34 515575.41ab 317476.11

Total Marketing Cost (₦) 12366.67 a 4099.59 18472.22 a 10702.49 35666.67 a 40667.76

Other operational costs (₦) 6833.33bc 5776.39 15361.11a 10134.11 11083.33ab 6931.21

Total Variable Cost (₦) 247283.33ab 75842.97 465307.61ab 434631.71 562325.40ab 350084.35

Fixed Cost (Depreciated) (₦) 310.36ab 157.68 520.28a 260.12 253.47b 218.05

Total Production Cost (₦) 247593.69ab 75792.84 465827.89ab 434662.69 562578.88ab 349982.39

Total Monthly Revenue (₦) 467178.57ab 362367.09 1153570.67ab 1357892.21 1422830.25a 1142132.10

Gross Margin (₦) 219895.24ab 202759.19 688263.06ab 567280.48 860504.84a 792268.32

Gross Margin/kg 577.02ab 463.84 766.97a 385.04 761.78a 567.42

Net Return (₦) 219584.88ab 202779.31 687742.78ab 567228.16 860251.37a 792331.09

Net Return/kg 575.76ab 464.35 765.65a 385.26 761.09a 567.52

Marketing Margin (₦) 239095.24ab 196582.99 722096.39ab 579611.45 907254.84a 885027.93




149


Frozen Fish Marketed in the States along Nigeria-Cameroon-Chad border

Marketing of frozen fish in the States along Nigeria-Cameroon-Chad border was major in Akwa

Ibom, Cross Rivers, Borno and Adamawa States. Results presented in Table 4.37 are the average

monthly quantities, costs, profitability indices and marketing efficiency of marketing frozen fish

in the study States. The highest average buying and selling prices of frozen fish per kilogram of

₦1000.00±0.00 and N1900.00±0.00 respectively were recorded in Akwa Ibom State while the

least average buying and selling prices of frozen fish of N550.00±141.42 and N850.00±70.00 were

recorded in Cross Rivers State. There was significant difference (P<0.05) in the buying and selling

prices of frozen fish products marketed among the study States.

In Akwa Ibom State, the highest average monthly cost of marketing frozen fish of N28200.00±0.00

while in Cross Rivers State the least average cost of marketing of N13000.00±2828.43 were

incurred. The highest and least average fixed cost of ₦833.33±0.00 and ₦242.50±152.03 were

recorded in Borno and Cross Rivers States respectively. Significant difference (P<0.05) was

noticed in the cost variables associated with frozen fish marketed in the sampled States along

Nigeria-Cameroon-Chad border. The average monthly revenue made from frozen fish range from

N800000.00±0.00 in Borno State to N1879944.44±0.00 in Akwa Ibom State. Akwa Ibom State

had the highest average net return per kg and efficiency of ₦864.66±0.00 and 66.66±0.00

respectively which was significantly (P<0.05) higher than the least average net return per kg of

198.90±43.49 in Adamawa State and least marketing efficiency of 12.25±2.39 recorded in Cross

Rivers State.

4.7.7 Average monthly quantities, costs, profitability indices and marketing efficiency of

fish marketing nodes in Nigeria-Cameroon-Chad border region

Presented in Table 4.38 are the average monthly quantities, costs, profitability indices and

marketing efficiency of fish marketing node in Nigeria-Cameroon-Chad border region. It was

observed that there were significant differences (P<0.05) in the average monthly quantities, prices,

costs, profitability indices and marketing efficiency at the marketing nodes for fish trade along

Nigeria-Cameroon-Chad border region.

150

Table 4.37: Average monthly quantities, profitability indices and marketing efficiency of frozen fish products marketed in the


Akwa Ibom

Cross River Adamawa

Borno

Variables Mean SD Mean SD Mean SD Mean SD

Total Quantity Sold (Kg) 989.44a 0.00 183.86c 11.11 510.11b 472.50 842.11ab 0.00

Buying Price (₦ Per Kg) 1000.00a 0.00 550.00b 141.42 765.00ab 21.21 550.00b 0.00

Selling Price (₦ Per Kg) 1900.00a 0.00 850.00b 70.71 1025.00ab 35.36 950.00b 0.00

Total Purchase Cost (₦) 989444.44a 0.00 100335.71d 19889.90 385218.95c 350638.62 463157.89b 0.00

Total Marketing Cost (₦) 28200.00a 0.00 13000.00b 2828.43 13500.00b 2121.32 20000.00a 0.00

Other operational costs (₦) 6000.00b 0.00 2500.00d 707.11 3650.00c 1202.08 12000.00a 0.00

Total Variable Cost (₦) 1023644.44a 0.00 115835.72c 23425.44 402368.95b 349719.38 495157.89b 0.00

Fixed Cost (Depreciated) (₦) 768.00a 0.00 242.50c 152.03 401.79b 391.43 833.33a 0.00

Total Production Cost (₦) 1024412.44a 0.00 116078.22c 23577.46 402770.73b 350110.81 495991.22b 0.00

Total Monthly Revenue (₦) 1879944.44 0.00 155885.71d 3555.74 514505.26c 466273.65 800000.00b 0.00

Gross Margin (₦) 856300.00a 0.00 40050.00d 19869.70 112136.32c 116554.27 304842.11b 0.00

Gross Margin/kg 865.44a 0.00 214.96bc 95.08 199.66c 43.55 362.00b 0.00

Net Return (₦) 855532.00a 0.00 39807.50d 20021.73 111734.53c 116162.84 304008.78b 0.00

Net Return/kg 864.66a 0.00 213.61c 95.99 198.90c 43.49 361.01b 0.00

Marketing Margin (₦) 890500.00a 0.00 55550.00c 16334.17 129286.32b 115635.03 336842.11b 0.00

Marketing Margin/kg 900.00a 0.00 300.00b 70.71 260.00c 14.14 400.00b 0.00

Marketing Efficiency 66.66a 0.00 12.25c 2.39 41.34b 41.03 40.00b 0.00


151

Table 4.38: Economic characteristics, profitability indices and marketing efficiency at fish marketing node in the study area

Variables

Fish Marketing Nodes

Production Processing Marketing


Total Quantity Sold (Kg) 625.46a 586.79 504.71c 482.11 582.84ab 536.28

Buying Price (₦ Per Kg) 20.82c 4.50 688.70b 247.19 1122.84a 519.20

Selling Price (₦ Per Kg) 650.52c 238.21 1459.08b 377.24 1637.90a 641.31

Total Purchase Cost (₦) 109403.96c 17593.42 325265.66b 298942.29 643949.52a 639171.44

Total Marketing Cost (₦) 58529.57a 79408.30 16000.01b 8141.30 19500.73b 30244.40

Other operational costs (₦) 37139.33a 31423.32 17834.17b 11746.99 2789.23c 1907.51

Total Variable Cost (₦) 103564.74c 107960.88 359099.83b 306865.98 666239.48a 658917.63

Fixed Cost (Depreciated) (₦) 2007.22a 1739.66 506.54b 363.22 348.13b 291.40

Total Production Cost (₦) 105571.96c 108016.36 359606.37b 306939.13 666586.45a 658999.87

Total Monthly Revenue (₦) 377390.47c 337881.03 730659.75b 650706.41 942221.92a 851618.02

Gross Margin (₦) 273825.72b 265376.36 371559.91a 282965.56 275982.44b 232028.94

Gross Margin/kg 462.56b 253.77 653.95a 330.82 469.36b 295.28

Net Return (₦) 271818.51b 265182.01 371053.37a 282887.68 275635.47b 231936.75

Net Return/kg 457.18b 253.75 652.21a 330.94 468.37b 295.29

Marketing Margin (₦) 369499.52a 327198.53 405394.09a 392255.64 298272.41b 244721.17

Marketing Margin/kg 642.06b 242.02 770.38a 318.74 516.66c 288.61

Marketing Efficiency 8.26c 5.10 50.66b 45.56 88.17a 84.93


152

The highest average monthly quantity of fish sold of 625.46±586.79kg was recorded in production

node while processing node had the least average monthly quantity of 504.71±482.11kg. The

marketing node had the highest buying and selling prices of ₦1122.84±519.20 per kg and

₦1637.90±641.31 per kg while production node had the least buying and selling prices of

₦20.82±4.50 per kg and ₦650.52±238.21 per kg. The marketing node incurred the highest

marketing cost of ₦58529.57±79408.30 while processing node recorded the least marketing cost

of ₦16000.01±8141.30. With respect to profitability indices, marketing node recorded the highest

average monthly revenue of ₦942221.92±851618.02 while production node recorded the least

revenue of ₦377390.47±337881.03. Processing node had the most average gross margin

₦371559.91±282965.56, net return ₦371053.37±282887.68 and marketing margin

₦405394.09±392255.64 while production node had the least average gross margin

₦273825.72±265376.36 and net return ₦271818.51±265182.01 while the marketing node

recorded the highest average marketing efficiency of 88.17±84.93 compared to production node

with the least average efficiency of 8.26±5.10.

4.7.8 Economic characteristics, profitability indices and marketing efficiency of actors in

fresh fish marketing nodes in Nigeria-Cameroon-Chad border region

Table 4.39 indicates the economic characteristics and marketing efficiency of fresh fish marketing

actors in Nigeria-Cameroon-Chad border region. The mean quantity of fresh fish sold by culture

producers, capture producers, processors, wholesalers and retailers was 903.87±734.36kg,

434.63±350.63kg, 1417.18±382.59kg and 234.09±119.57kg, respectively. There were significant

differences (P<0.05) in average monthly quantities and selling price of fresh fish marketed by

actors in the marketing node of fresh fish in the study area. Wholesalers had the highest mean total

variable cost ₦812998.62±232003.60 and culture producers had the least ₦153544.53±144489.74.

The mean monthly fixed cost (depreciated) at each node was ₦2321.56±2182.27,

₦1791.76±1319.87, ₦895.55±447.57 and ₦213.96±101.50, respectively. The highest mean gross

margin was ₦415041.28±219709.11 for wholesalers and the least was ₦87231.70±77049.95 for

retailers. The mean marketing margin and efficiency of these marketing actors in marketing fresh

fish were ₦475601.97±398940.08 and 7.94±4.99, ₦296777.62±242844.22 and 8.49±5.18,

₦494004.83±213846.36 and 26.56±21.89, ₦99076.12±76900.03 and 41.58±34.15, respectively.

153

Table 4.39: Economic characteristics, profitability indices and marketing efficiency of actors in fresh fish marketing nodes

Variables Production Node Marketing Node

Producer (Culture) Producer (Capture) Wholesaler Retailer


Total Quantity Sold (Kg) 903.87b 734.36 434.64c 350.63 1417.18a 382.59 234.09d 119.57

Buying Price (₦ Per Kg) 20.82c 4.50 0.00 0.00 519.35b 81.85 681.98a 200.40

Selling Price (₦ Per Kg) 549.91d 89.20 719.48c 280.46 888.71b 201.95 1121.55a 336.32

Total Purchase Cost (₦) 19403.96b 17593.42 0.00 0.00 734035.07a 216836.73 158205.62a 89210.07

Total Marketing Cost (₦) 90175.00a 11409.39 36848.26b 23528.57 74632.26a 43914.31 9854.30c 8520.89

Other operational costs (₦) 43965.57a 24424.60 32460.67b 34728.57 4331.29c 2986.96 1990.12c 930.17

Total Variable Cost (₦) 153544.53b 144489.74 69308.93c 50153.96 812998.62a 232003.60 170050.04b 90885.72

Fixed Cost (Depreciated) (₦) 2321.56a 2182.27 1791.76b 1319.87 895.55c 447.57 213.96d 101.50

Total Production Cost (₦) 155866.10b 144377.31 71100.70c 50211.98 813894.17a 231795.12 170261.50b 90881.30

Total Monthly Revenue (₦) 495005.93b 415129.58 296777.62c 242844.22 1228039.90a 293507.44 257281.74c 138440.97

Gross Margin (₦) 341461.40a 325598.64 227468.69b 224306.11 415041.28a 219709.11 87231.70c 77049.95

Gross Margin/kg 363.71b 130.15 530.31a 293.02 311.05a 193.07 381.17a 272.97

Net Return (₦) 339139.83a 325313.65 225676.93b 224295.72 414145.73a 219628.70 87020.24c 77053.69

Net Return/kg 359.20a 130.89 524.34b 293.10 310.37a 192.94 380.06a 273.11

Marketing Margin (₦) 475601.97a 398940.08 296777.62b 242844.22 494004.83a 213846.36 99076.12c 76900.03

Marketing Margin/kg 529.09b 89.42 719.48a 280.46 369.35c 191.22 439.57c 266.77

Marketing Efficiency 7.94c 4.99 8.49c 5.18 26.56b 21.89 41.58a 34.15


154


smoked fish marketing nodes in Nigeria-Cameroon-Chad border region

The economic characteristics and marketing efficiency of smoked fish marketing actors in Nigeria-

Cameroon-Chad border region is presented in table 4.40. Average quantity of smoked fish sold by

processors, wholesalers and retailers was 477.76±456.81kg, 1091.18±266.31kg and

175.08±65.27kg, respectively. The mean buying price of smoked fish per kg ranged from N

₦704.61±251.32 for processors to ₦1522.05±452.60 for retailers. The mean selling price of

smoked fish per kg ranged from ₦1,487.21±365.34 for processors to ₦2106.29±498.31 for

retailers. The highest average monthly revenue was realized by wholesalers

₦2251098.73±685,618.74, while retailers realized the least ₦369509.11±162581.13, respectively.

There was significant difference (P<0.05) in the average revenue of smoked fish marketing actors

in Nigeria-Cameroon-Chad border.

The average monthly total cost of marketing incurred in marketing of smoked fish by processors,

wholesalers and retailers were ₦15,599.22±7,979.66, ₦17,422.67±7,899.82, and

₦3,659.62±1,869.22, respectively. The mean gross margin and net returns of processors,

wholesalers and retailers in marketing smoked fish were ₦346,688.82±315,064.43 and

₦346,170.35±314,958.81, ₦612,603.13±346,835.96 and ₦612,173.92±346832.46,

₦94,361.68±51365.52 and ₦94,132.18±51,319.28, respectively. The mean marketing margin and

efficiency of these marketing actors in marketing smoked fish processors, wholesalers and retailers

were ₦381,130.20±325,675.68 and 49.80±46.20, ₦634,383.13±345735.93 and 159.72±99.33,

N99501.43±51835.05 and 119.20±73.36, respectively as shown in table 8. Significant difference

(P<0.05) was observed in the profitability indices and marketing efficiency of the actors in the

marketing node of smoked fish in the study area.


dried fish marketing nodes in Nigeria-Cameroon-Chad border region

Table 4.41 presents the economic characteristics and marketing efficiency of dried fish marketing

actors in Nigeria-Cameroon-Chad border region. Average quantity of dried fish sold by processors,

wholesalers and retailers was 657.46±588.91kg, 1233.96±659.85kg and 137.50±38.14kg,

respectively.

155

Table 4.40: Economic characteristics, profitability indices and marketing efficiency of actors in smoked fish marketing nodes

Variables Processing Node Marketing Node

Processor Wholesaler Retailer


Total Quantity Sold (Kg) 477.76b 456.81 1091.18a 266.31 175.08c 65.27

Buying Price (₦ Per Kg) 704.61b 251.32 1488.27a 336.00 1522.05a 452.60

Selling Price (₦ Per Kg) 1487.21b 365.34 2084.38a 461.22 2106.29a 498.31

Total Purchase Cost (₦) 312856.68b 291075.62 1616715.60a 503118.82 270007.68b 138263.55

Total Marketing Cost (₦) 15599.22a 7979.66 17422.67a 7899.82 3659.62b 1869.22

Other operational costs (₦) 18842.16a 12032.46 4357.33b 1159.82 1480.13c 776.41

Total Variable Cost (₦) 347298.06b 298936.03 1638495.60a 504819.11 275147.43a 138116.56

Fixed Cost (Depreciated) (₦) 518.48a 380.05 429.21b 220.05 229.51c 124.34

Total Production Cost (₦) 347816.53b 299024.54 1638924.81a 504797.87 275376.93b 138169.30

Total Monthly Revenue (₦) 693986.88b 687491.96 2251098.73a 685618.74 369509.11c 162581.13

Gross Margin (₦) 346688.82b 315064.43 612603.13a 346835.96 94361.68c 51365.52

Gross Margin/kg 659.31a 311.46 573.33b 320.75 551.67b 277.80

Net Return (₦) 346170.35b 314958.81 612173.92a 346832.46 94132.18c 51319.28

Net Return/kg 657.48a 311.57 572.88ab 320.70 550.26b 277.60

Marketing Margin (₦) 381130.20b 325675.68 634383.13a 345735.93 99501.43c 51835.05

Marketing Margin/kg 782.60a 299.69 596.11b 321.45 584.24b 281.50

Marketing Efficiency 49.80c 46.20 159.72a 99.33 119.20b 73.36


156

Table 4.41: Economic characteristics, profitability indices and marketing efficiency of actors in dried fish marketing nodes




Total Quantity Sold (Kg) 657.46b 588.91 1233.96a 659.85 137.50c 38.14

Buying Price (₦ Per Kg) 598.56c 202.06 975.00b 188.98 1206.25a 192.89


Total Purchase Cost (₦) 395583.22b 335025.64 1174086.90a 566500.49 168338.05b 65255.5

Total Marketing Cost (₦) 18271.11b 8753.48 97125.00a 69101.25 13675.00b 1804.25

Other operational costs (₦) 12122.22a 7917.30 3712.50b 1568.84 1818.75b 1038.73

Total Variable Cost (₦) 425976.55b 344467.13 1274924.40a 624700.13 183831.8b 64193.45


Total Production Cost (₦) 426415.47b 344482.33 1275150.25a 624638.82 184041.35b 64247.7

Total Monthly Revenue (₦) 938472.64b 824320.90 2129558.56a 1231284.37 234987.52c 106663.88

Gross Margin (₦) 512496.09ab 452770.03 854634.17a 668429.17 51155.72b 50665.98

Gross Margin/kg 623.57a 427.33 622.11a 280.20 332.57a 229.13

Net Return (₦) 512057.17ab 752751.43 854408.31a 668472.93 50946.17b 50647.47

Net Return/kg 622.35a 427.55 621.65a 280.39 330.94a 229.26

Marketing Margin (₦) 542889.42ab 460184.96 955471.66a 712788.38 66649.47b 50661.89


Marketing Efficiency 55.50a 52.11 34.57ab 30.04 17.89b 10.10


157

The mean buying price of dried fish per kg ranged from N598.56±202.06 for processors to

₦1,206.25±192.89 for retailers. The mean selling price of dried per kg ranged from

₦1299.68±407.39 for processors to ₦1,660.69±324.17 for retailers. The highest mean gross

margin ₦854634.17±668429.17 belonged to wholesalers and the least ₦51155.72±50665.98

belonged to retailers of dried fish. The mean marketing margin and efficiency of processors,

wholesalers and retailers in marketing dried fish were ₦542889.42±460184.96 and 55.50±52.11,

₦955471.66±712788.38 and 34.57±30.04, ₦66649.47±50661.89 and 17.89±10.10, respectively.

There were significant differences (P<0.05) in the profitability indices and marketing efficiency

of processors, wholesalers and retailers in the marketing node of dried fish in the study area.


frozen fish marketing nodes in Nigeria-Cameroon-Chad border region

Table 4.42 includes the average quantities of fish sold, prices, profitability and marketing

efficiency of frozen fish marketing actors in Nigeria-Cameroon-Chad border region. The average

quantity of frozen fish sold by wholesalers and retailers was 891.92±84.47kg and 181.24±9.07kg,

respectively. The mean buying and selling price of frozen fish per kg was 766.67±225.46 and

1283.33±534.63 respectively for wholesalers and ₦626.67±166.23 and ₦916.67±125.83

respectively for retailers. The mean total cost of marketing incurred and the monthly revenue made

from the sales of frozen fish by wholesalers and retailers was ₦20,066.67±8,100.21 and

₦1,174,718.32±611,143.64, ₦13,666.67±2,309.40 and ₦165,523.81±16,881.95, respectively.

The mean gross margin and net returns were ₦451,898.25±354,537.06 and

₦451,138.28±354,518.16, ₦36,606.67±15,263.42 and ₦36,403.33±15,336.23, respectively. The

mean marketing margin and efficiency of these marketing actors in marketing frozen fish were

₦479,464.91±361,480.47 and 59.01±16.56 respectively, ₦52873.33±12445.73 and 12.27±1.69,

respectively for wholesalers and retailers respectively. There were significant differences (P<0.05)

in the profitability indices (except gross margin) and marketing efficiency of processors,

wholesalers and retailers in the marketing node of frozen fish in the study area.

158

Table 4.42: Economic characteristics, profitability indices and marketing efficiency of

actors in frozen fish marketing node in Nigeria-Cameroon-Chad border region

Variables Marketing Node

Wholesaler Retailer

Mean SD Mean SD

Total Quantity Sold (Kg) 891.92a 84.47 181.24b 9.07

Buying Price (Per Kg) 766.67a 225.46 626.67a 166.23

Selling Price (Per Kg) 1283.33a 534.63 916.67a 125.83

Total Purchase Cost (₦) 695253.41a 268581.97 112650.48b 25549.25

Total Marketing Cost (₦) 20066.67a 8100.21 13666.67a 2309.40

Other operational costs (₦) 7500.00a 3968.63 2600.00a 529.15

Total Variable Cost (₦) 722820.07a 271733.39 128917.14b 28066.83

Fixed Cost (Depreciated) (₦) 759.97a 77.69 203.33b 127.12

Total Production Cost (₦) 723580.04a 271718.08 129120.48b 28075.79

Total Monthly Revenue (₦) 1174718.32a 611143.64 165523.81b 16881.95

Gross Margin (₦) 451898.25a 354537.06 36606.67b 15263.42

Gross Margin/kg 485.96a 335.15 199.59b 72.31

Net Return (₦) 451138.28a 354518.16 36403.33b 15336.23

Net Return/kg 485.11a 335.20 198.46b 72.77

Marketing Margin (₦) 479464.91a 361480.47 52873.33a 12445.73

Marketing Margin/kg 516.67a 340.34 290.00b 52.92

Marketing Efficiency 59.01a 16.56 12.27b 1.69

159

4.8 STOCHASTIC PRODUCTION FRONTIER MODEL AND TECHNICAL

INEFFICIENCY

The Maximum Likelihood estimate (MLE) of the parameters of the stochastic production frontier

model of the respondents is presented in table 4.43. This model was used to know the effects of

costs incurred by the respondents in fish production, processing and marketing operations. The

estimated sigma parameter (δ2) showed that about 57% of the variation in productivity (monthly

revenue) was attributed to differences in technical efficiencies of the fish marketing actors. There

was a positive relationship between the monthly revenue of the respondents and total purchase

cost, total marketing cost and depreciated fixed cost. The other operational costs had a negative

relationship with the monthly revenue of the respondents.

Tables 4.44 to 4.4.46 presents the estimates of inefficiency model which was used to analyse the

effect of the socio-economic characteristics of the fish trade actors on the technical efficiencies.

Table 4.44 presents the estimates of technical inefficiency of producers in fish markets along

Nigeria-Cameroon-Chad border. The coefficient of regression (R2) was 0.050 and significant (P<

0.05). Hence, only 5.0% of the producer’s technical efficiency was predicted by their socio-

economic factors, though none of these factors was significant.

Table 4.45 presents the estimates of technical inefficiency of processors in fish markets along

Nigeria-Cameroon-Chad border. The coefficient of regression (R2) was 0.054 and significant (P<

0.05). Hence, only 5.4% of the efficiency of the processors was predicted by their socioeconomic

characteristics. The highest education attained by the processors had a coefficient value of 0.032

at 5% significance.

The estimated technical inefficiency of marketers in fish markets in the study area is shown in

table 4.46. The coefficient of regression (R2) was 0.025 and not significant (P< 0.05), therefore,

the socio-economic characteristics of the marketers affected only 2.5% of their efficiency. This

model further revealed that only the sex of the marketers had a significant relationship with their

technical efficiency with a coefficient value of -0.097.

160

Table 4.43: Estimated maximum likelihood parameters of the Stochastic frontier

production function

Variables Parameters Coefficients Standard Error t-ratio

Constant β0 0.8021 0.4859 0.1651

Total purchase cost β1 0.1210 0.6134 0.1972

Total marketing cost β2 0.3539 0.3145 0.1125

Other operational cost β3 -0.5312 0.2842 -0.1870

Fixed cost (depreciated) β4 0.1257 0.3468 0.3625

Diagnostic Statistics

Gamma γ 0.5003 0.9707 0.5154

Sigma square δ2 0.5651 0.2608 0.2155

Log likelihood function L -0.1018

Likelihood ratio (LR) ʎ

161

Table 4.44: Estimates of efficiency model for producers

Socio-economic

parameters

Parameter Coefficients Standard

error

t-value Sig.

Constant δ0 -0.515 0.231 -2.227 0.027

Sex of respondents δ1 0.100 0.138 0.727 0.468

Age of respondents δ2 0.004 0.032 0.123 0.902

Highest education δ3 0.010 0.032 0.323 0.747

162

Table 4.45: Estimates of efficiency model for processors

Socio-economic

parameters


error

t-value Sig.

Constant δ0 0.141 0.112 1.264 0.207

Sex of respondents δ1 -0.044 0.037 -1.215 0.225

Age of respondents δ2 -0.031 0.018 -1.727 0.085


163

Table 4.46: Estimates of efficiency model for marketers

Socio-economic

parameters


error

t-value Sig.

Constant δ0 -0.007 0.148 -0.049 0.961

Sex of respondents δ1 -0.097 0.049 -1.975 0.049

Age of respondents δ2 0.029 0.027 1.090 0.276


164

4.9 TRADE FLOW OF FISH PRODUCTS

In this study, trade flow was reported accordingly as Intra-State trade (marketing of fish within the

studied States), Inter-State trade (marketing of fish to other States in the region) and Intra-regional

trade (marketing of fish products across the border in the States along Nigeria-Cameroon-Chad

border).

4.9.1 Average Monthly Quantities and Revenue of Trade Flow of Forms of Fish Entering

Fish Markets along Nigeria-Cameroon-Chad border

The Intra-State trade flow (inflow) of fish within each of the six States along Nigeria-Cameroon-

Chad border and with other States in Nigeria (inter-state) and cross border (intra-regional) fish

trade is presented in table 4.47. The volume of inflow of fresh, smoked, dried and frozen fish

traded intra-state in kilogram was estimated at 564.13±552.27kg, 523.89±474.19kg,

551.86±463.23kg and 536.58±392.95kg, respectively. The volume of fish traded (inflow) inter-

state was estimated at 1250.64±703.53kg, 494.88±408.10kg, 795.00±63.64kg for fresh, smoked

and dried fish, while frozen fish was not recorded in this category. The average quantity of fresh,

smoked and dried fish traded into Nigeria along the Nigeria-Cameroon-Chad border (intra-

regional) was estimated at 558.29±369.52kg, 1153.81±208.69kg, 2098.00±306.88kg,

respectively.

Table 4.48 shows the average monthly revenue obtained from these sales by the marketing actors.

The average monthly revenue of marketing actors involved in intra-state fresh, smoked, dried and

frozen fish trade (inflow) was N393703.93±367164.83, N893906.72±878026.54,

N822252.89±810582.18 and N 670121.07±674577.42, respectively. The marketing actors

involved in inter-state trade (inflow) made a monthly revenue of N788744.74±482023.46,

N824659.06±814547.02 and N1140750.00±455023.21 from fresh, smoked and dried fish trade,

respectively. Cross border trade (inflow) actors along Nigeria-Cameroon-Chad border made a

monthly revenue of N312733.33±170735.36, N2625833.98±424981.57 and

N3649800.00±240345.59 from the trade of fresh, smoked and dried fish, respectively.

165

Table 4.47: Average monthly quantities and percentage of forms of fish entering fish markets along Nigeria-Cameroon-Chad

border through inter-State, intra-State and intra-regional fish trade

Trade Flow (Inflow) Fresh

Smoked

Dried

Frozen


Intra-State Trade 564.13 552.27 87.41 523.89 474.19 95.22 551.86 463.23 86.11 536.58 392.95 100.00

Inter-State Trade 1250.64 703.53 11.92 494.88 408.10 1.59 795.00 63.64 3.82 NS NS 0.00

Intra-regional Trade 558.29 369.52 0.67 1153.81 208.69 3.19 2098.00 306.88 10.07 NS NS 0.00

Total 603.60 582.11 100.00 532.65 477.29 100.00 603.73 607.73 100.00 536.58 392.95 100.00

NS- No Information Supplied

166

Table 4.48: Average monthly revenue from sales of fish entering fish markets along Nigeria-Cameroon-Chad border through

inter-State, intra-State and intra-regional fish trade

Trade Flow (Inflow) Fresh

Smoked

Dried

Frozen


Intra-State Trade 393703.93 367164.83 893906.72 878026.54 822252.89 810582.18 670121.07 674577.42

Inter-State Trade 788744.74 482023.46 824659.06 814547.02 1140750.00 455023.21 NS NS

Intra-Regional Trade 312733.33 170735.36 2625833.98 424981.57 3649800.00 240345.59 NS NS


167

The inter-State trade flow (outflow) of fish between each of the six States studied and other States

in Nigeria and cross border (intra-regional) fish trade is presented in table 4.49. The quantity of

fish traded (outflow) inter-state was estimated at 1719.44±638.63kg, 907.21±500.94kg,

1049.82±524.51kg for fresh, smoked and dried fish, respectively. The average quantity of fresh,

smoked and dried fish traded out of Nigeria to other African countries, along the Nigeria-

Cameroon-Chad border (intra-regional) was estimated at 2175.00±275.38kg, 1624.62±512.74kg,

2205.11±987.43kg, respectively

Table 4.50 shows the average monthly revenue obtained from inter-State and cross-border trade

(outflow) by the marketing actors. The marketing actors involved in inter-State trade (outflow)

made a monthly revenue of N1149726.69±449406.14, N1617968.31±958389.84 and

N1649045.26±1034956.41 from fresh, smoked and dried fish trade, respectively. Cross border

trade (outflow) actors along Nigeria-Cameroon-Chad border made a monthly revenue of

N112500.00±125000.00, N2634357.45±813701.64 and N3317327.74±2302822.44 from the trade

of fresh, smoked and dried fish, respectively.

4.9.2 Trade flow of Fresh Fish along Nigeria-Cameroon-Chad border

Table 4.51 shows the profitability indices and marketing efficiency of the marketing nodes and

actors involved in intra-state marketing of fresh fish in fish markets in Nigeria-Cameroon-Chad

border region. The mean quantity of fresh fish sold by culture producers, capture producers,

wholesalers and retailers was 852.44±734.08kg, 422.89±339.33kg, 1332.22±266.55kg and

234.09±119.57kg, respectively. The mean total production cost in a month at each marketing node

was N152253.49±144973.29, N68964.44±44715.90, N765902.59±206094.73 and

N170261.50±90881.30, respectively. The mean total cost of marketing incurred by fresh fish

marketing node actors in a month was highest for culture producers (fish farmers) at

N88350.00±11448.32 and lowest for retailers at N9854.30±8520.89. Wholesalers had the highest

average monthly revenue of N1181499.49±269331.50 and retailers had the least

N257281.74±138440.97.

168

Table 4.49: Average monthly quantities and percentage of forms of fish sold from the fish markets along Nigeria-Cameroon-

Chad border through inter-State, intra-State and intra-regional fish trade

Trade Flow

(Outflow)

Fresh

Smoked

Dried

Frozen


Inter-State Trade 1719.44 638.63 11.61 907.21 500.94 32.14 1049.82 524.51 32.76 NS NS 0.00

Intra-Regional Trade 2175.00 275.38 3.46 1624.62 512.74 8.22 2205.11 987.43 15.88 NS NS 0.00


169

Table 4.50: Average monthly revenue from forms of fish sold from the fish markets along Nigeria-Cameroon-Chad border

through inter-State, intra-State and intra-regional fish trade

Trade Flow

(Outflow)

Fresh

Smoked

Dried

Frozen


Inter-State Trade 1149726.69 449409.14 1617968.31 958389.84 1649045.26 1034956.41 . .

Intra-Regional Trade 1112500 125000 2634357.45 813701.64 3317327.74 2302822.44 . .

170

Table 4.51: Profitability and efficiency of the marketing nodes and actors involved in intra-State trading of fresh fish in fish

markets in Nigeria-Cameroon-Chad border region


Producer (Culture) Producer (Capture) Wholesaler

Retailer


Total Quantity Sold (Kg) 852.44 734.08 422.89 339.33 1332.22 266.55 234.09 119.57

Buying Price (₦ Per Kg) 21.01 4.45 0.00 0.00 513.46 81.34 681.98 200.40

Selling Price (₦ Per Kg) 546.84 86.85 724.46 277.05 901.92 210.94 1121.55 336.32

Total Purchase Cost (₦) 18622.26 17882.54 0.00 0.00 684618.74 178153.97 158205.62 89210.07

Total Marketing Cost (₦) 88350.00 11448.32 36401.14 23641.49 76369.23 40592.82 9854.30 8520.89

Other operational costs (₦) 43026.13 24565.25 30769.46 28311.06 4010.38 2793.26 1990.12 930.17

Total Variable Cost (₦) 149998.39 145105.98 67170.60 44642.13 764998.35 206375.10 170050.04 90885.72

Fixed Cost (Depreciated) (₦) 2255.10 2204.39 1793.84 1335.89 904.24 452.96 213.96 101.50

Total Production Cost (₦) 152253.49 144973.29 68964.44 44715.90 765902.59 206094.73 170261.50 90881.30

Total Monthly Revenue (₦) 464475.03 416370.57 294266.99 245250.14 1181499.49 269331.50 257281.74 138440.97

Gross Margin (₦) 314476.64 312355.02 227096.39 225551.05 416501.14 232757.96 87231.70 77049.95

Gross Margin/kg 356.37 124.01 535.65 290.24 328.52 205.03 381.17 272.97

Net Return (₦) 312221.55 312107.87 225302.55 223555.87 415596.91 232674.33 87020.24 77053.69

Net Return/kg 351.65 124.76 529.60 290.41 327.80 204.90 380.06 273.11

Marketing Margin (₦) 445852.77 399620.72 294266.99 245250.14 496880.76 227021.44 99076.12 76900.03

Marketing Margin/kg 525.83 86.67 724.46 277.05 388.46 201.01 439.57 266.77

Marketing Efficiency 7.51 4.68 8.55 5.30 22.02 14.50 41.58 34.15

171

The mean gross margin and net returns of these marketing actors involved in intra-state fresh fish

marketing were N314476.64±312355.02 and N312221.55±312107.87, N227096.39±225551.05

and N225302.55±223555.87, N416501.14±232757.96 and N415596.91±232674.33,

N87231.70±77049.95 and N87020.24±77053.69, respectively. The mean marketing margin and

efficiency of these fresh fish marketing actors were N445852.77±399620.72 and 7.51±4.68,

N294266.992±245250.14 and 8.55±5.30, N496880.76±227021.44 and 22.02±14.50,

N99076.12±76900.03 and 41.58±34.15, respectively.

Table 4.52 shows the average monthly quantities of fish sold, costs, returns and marketing

efficiency of the marketing nodes and actors involved in inter-state trade of fresh fish supplied

(inflow) into fish markets in Nigeria-Cameroon-Chad border region. The mean quantity of fresh

fish sold by culture producers, capture producers and wholesalers was 1422.89±521.70kg,

633.58±532.94kg and 1859.00±602.33kg, respectively. The mean total production cost in a month

at each marketing node was N192320.60±139376.05, N113680.53±118236.49 and

N1063450.38±211375.81, respectively. The highest mean total cost of marketing

N108590.91±113765.73 was incurred by culture producers and the least N44000.00±24108.39was

incurred by capture producers. The mean gross margin and net returns of these marketing actors

involved in marketing inter-state supplied (inflow) fresh fish were N613762.07±292016.56 and

N610769.81±291881.85, N231453.64±194892.73 and N229523.11±194393.01,

N407450.00±152817.32 and N406599.62±152749.71, respectively. The mean marketing margin

and efficiency of these fresh fish marketing actors were N775798.43±245227.05 and 12.20±6.24,

N343203.64±231889.78 and 7.58±3.33, N479050.00±143271.01 and 50.18±38.08, respectively.

The average monthly quantities of fish sold, profitability and marketing efficiency of the marketing

node and actors (capture producers) involved in intra-regional trade of fresh fish supplied (inflow)

into fish markets along Nigeria-Cameroon-Chad border is presented in table 4.53. The mean

quantity of fresh fish sold by this category of capture producers was 558.29±369.52kg. Total

variable cost and fixed cost spent on this fishing enterprise on a monthly basis was estimated at

N75166.67±23991.32 and N1306.18±255.49, respectively. The mean total production and

marketing costs incurred in a month was estimated at N76472.84±23757.49 and

N42666.67±17214.34, respectively.

172

Table 4.52: Profitability and efficiency of the marketing nodes and actors involved in inter-State trading of supplied (inflow)

fresh fish into fish markets in Nigeria-Cameroon-Chad border region




Total Quantity Sold (Kg) 1422.89 521.70 633.58 532.94 1859.00 602.33

Buying Price (₦ Per Kg) 18.91 4.76 0.00 0.00 550.00 86.60

Selling Price (₦ Per Kg) 580.93 110.15 666.67 392.29 820.00 144.05

Total Purchase Cost (₦) 27291.98 12346.35 0.00 0.00 991000.00 236340.86

Total Marketing Cost (₦) 108590.91 113765.73 44000.00 24108.39 65600.00 63586.95

Other operational costs (₦) 53445.45 21720.24 67750.00 99912.40 6000.00 3741.66

Total Variable Cost (₦) 189328.35 139477.03 111750.00 118307.66 1062600.00 211302.04

Fixed Cost (Depreciated) (₦) 2992.25 1904.63 1930.53 1259.75 850.38 465.84

Total Production Cost (₦) 192320.60 139376.05 113680.53 118236.49 1063450.38 211375.81

Total Monthly Revenue (₦) 803090.41 251914.21 343203.64 231889.78 1470050.00 324711.98

Gross Margin (₦) 613762.07 292016.56 231453.64 194892.73 407450.00 152817.32

Gross Margin/kg 437.72 170.75 457.46 400.42 220.19 67.44

Net Return (₦) 610769.81 291881.85 229523.11 194393.01 406599.62 152749.71

Net Return/kg 435.42 170.44 452.24 399.57 219.74 67.50

Marketing Margin (₦) 775798.43 245227.05 343203.64 231889.78 479050.00 143271.01

Marketing Margin/kg 562.02 113.17 666.67 392.29 270.00 83.67

Marketing Efficiency 12.20 6.24 7.58 3.33 50.18 38.08

173

Table 4.53: Profitability and efficiency of the marketing node and actors involved in intra-

regional trading of supplied (inflow) fresh fish along Nigeria-Cameroon-Chad border

Variables Production Node

Producers (Capture)

Mean SD

Total Quantity Sold (Kg) 558.29 369.52

Buying Price (₦ Per Kg) 0.00 0.00

Selling Price (₦ Per Kg) 583.33 104.08

Total Purchase Cost (₦) 0.00 0.00

Total Marketing Cost (₦) 42666.67 17214.34

Other operational costs (₦) 32500.00 7262.92

Total Variable Cost (₦) 75166.67 23991.32

Fixed Cost (Depreciated) (₦) 1306.18 255.49

Total Production Cost (₦) 76472.84 23757.49

Total Monthly Revenue (₦) 312733.33 170735.36

Gross Margin (₦) 237566.67 147833.74

Gross Margin/kg 427.13 76.29

Net Return (₦) 236260.49 148088.27

Net Return/kg 423.80 77.08

Marketing Margin (₦) 312733.33 170735.36

Marketing Margin/kg 583.33 104.08

Marketing Efficiency 7.10 1.52

174

The average monthly revenue, gross margin and net returns made from these sales was computed

as N312733.33±170735.36, N237566.67±147833.74 and N236260.49±148088.27, respectively.

The capture producers had a mean marketing margin and efficiency N312733.33±170735.36 and

7.10±1.52, respectively from the supply (inflow) of intra-regional fresh fish trade.

Table 4.54 presents the average monthly quantities of fish sold, profitability and marketing

efficiency of the marketing nodes and actors involved in inter-state trade (outflow) of fresh fish

from the six States studied along Nigeria-Cameroon-Chad border. The mean quantity of fresh fish

sold by culture producers, capture producers and wholesalers was 1997.24±735.66kg,

1597.63±512.41kg and 1436.77±459.75kg, respectively. Culture producers had the highest mean

marketing cost of N237125.00±147470.52 and capture producers had the least mean marketing

cost of N55250.00±7424.62 in a month. The mean gross margin and net returns of these marketing

actors involved in inter-state marketing (outflow) of fresh fish were N856125.60±479796.11 and

N854204±478922.53, N428644.61±256171.34 and N428182.11±256189,


and efficiency of these fresh fish marketing actors were N1159813.10±478540.78 and 8.03±7.40,


Table 4.55 shows the average monthly quantities of fish sold, profitability and marketing

efficiency of the marketing actors (culture producers) involved in intra-regional trade (outflow) of

fresh fish along Nigeria-Cameroon-Chad border. The mean quantity of fresh fish sold by this

category of culture producers was 2175.00±275.38kg. Total variable cost and fixed cost spent on

this fishing enterprise on a monthly basis was estimated at N188175.00±53786.76 and

N2532.79±586.87, respectively. The mean total production and marketing costs incurred in a

month was estimated at N190707.79±53976.42 and N62500.00±9574.45, respectively. The

average monthly revenue and gross margin made from these sales was computed as

N1112500.00±125000.00 and N924325.00±103284.82, respectively. These culture producers had

a mean marketing margin and efficiency N1063300.00±121036.06 and 17.93±1.59, respectively

from intra-regional fresh fish trade (outflow).

175

Table 4.54: Profitability and efficiency of the marketing nodes involved in inter-State trading (outflow) of fresh fish from fish















Gross Margin (₦) 856125.60 479796.11 428644.61 256171.34 457856.86 225986.71

Gross Margin/kg 418.67 192.55 255.74 78.32 351.42 218.08

Net Return (₦) 854204.29 478922.53 428182.11 256189.02 456985.90 225666.44

Net Return/kg 417.55 192.50 255.43 78.43 350.73 217.71




176

Table 4.55: Profitability and efficiency of the marketing actors involved in intra-regional

trading (outflow) of fresh fish along Nigeria-Cameroon-Chad border

Variables Producer (Culture)

Mean SD











Gross Margin (₦) 924325.00 103185.19


Net Return (₦) 921792.21 103284.82





177

4.9.3 Smoked Fish Intra-State, Inter-State and Intra-Regional Trade flow along Nigeria-



nodes and actors involved in intra-state trade of smoked fish in the six States studied along Nigeria-

Cameroon-Chad border is shown in Table 4.56. The mean quantity of smoked fish sold by


175.08±65.27kg, respectively. The mean marketing cost incurred and total revenue realized in a

month was estimated at N15391.21±7605.15 and N687432.74±683137.87, N18225.37±7841.58

and N2274824.75±623246.06, N3659.62±1869.22and N369509.11±162581.13, respectively. The

highest mean gross margin was made by wholesalers at N625621.68±333999.14 and the least by

retailers at N94361.68±51365.52. The mean marketing margin of these smoked fish marketing

(intra-state) actors was estimated at N375885.92±321872.50, N648239.59±332197.42 and

N99501.43±51835.05, respectively.

Table 4.57 shows the economic characteristics and marketing efficiency of the marketing nodes

and actors involved in inter-state trade of supplied (inflow) smoked fish into the six States studied

along Nigeria-Cameroon-Chad border. The mean quantity of smoked fish sold by processors and

wholesalers was 634.84±549.14kg and 145.00±7.07kg, respectively. The mean marketing cost

incurred and total revenue realized in a month was estimated at N26000.00±17464.25 and

N1021694.12±908504, N6000.00±0.00and N332071.43±101.02, respectively. Processors had the

highest mean gross margin computed as N590284.37±555800.53. The mean marketing margin of

these smoked fish marketing (inter-state) actors was estimated at N643344.37±582658.19 and

N119571.43±102429.47, respectively.

Table 4.58 shows the economic characteristics of wholesalers involved in intra-regional trade

(inflow) of smoked fish along Nigeria-Cameroon-Chad border. The mean quantity of smoked fish

sold by this category of wholesalers was 1153.81±208.698kg. The mean marketing costs incurred

in a month was estimated at N12266.67±4384.82. The gross margin and marketing margin made

from intra-regional smoked fish trade (inflow) were computed as N635239.95±448590.65 and

N651256.62±448754.23, respectively. These wholesalers had a marketing efficiency of

N230.42±72.57.

178

Table 4.56: Profitability and efficiency of the marketing nodes and actors involved in intra-State trading of smoked fish in fish















Gross Margin (₦) 341816.91 311776.68 625621.68 333999.14 94361.68 51365.52

Gross Margin/kg 654.78 312.47 568.15 305.37 551.67 277.80

Net Return (₦) 341303.48 311674.15 625177.24 334003.65 94132.18 51319.28

Net Return/kg 652.94 312.56 567.72 305.35 550.26 277.60




179

Table 4.57: Profitability and efficiency of the marketing nodes and actors involved in inter-State trading of supplied (inflow)

smoked fish into fish markets in Nigeria-Cameroon-Chad border region


Processor Wholesaler

Mean SD Mean SD

Total Quantity Sold (Kg) 634.84 549.14 145.00 7.07

Buying Price (₦ Per Kg) 598.00 79.50 1450.00 636.40

Selling Price (₦ Per Kg) 1588.00 87.86 2292.86 111.12

Total Purchase Cost (₦) 378349.74 327639.65 212500.00 102530.48

Total Marketing Cost (₦) 26000.00 17464.25 6000.00 0.00

Other operational costs (₦) 27060.00 9847.23 5000.00 0.00

Total Variable Cost (₦) 431409.74 354285.06 223500.00 102530.48

Fixed Cost (Depreciated) (₦) 770.75 253.72 197.92 73.66

Total Production Cost (₦) 432180.49 354444.08 223697.92 102456.82

Total Monthly Revenue (₦) 1021694.12 908504.52 332071.43 101.02

Gross Margin (₦) 590284.37 555800.53 108571.43 102429.47

Gross Margin/kg 886.13 129.05 766.90 743.81

Net Return (₦) 589513.63 555661.41 108373.51 102355.81

Net Return/kg 884.39 129.98 765.53 743.23

Marketing Margin (₦) 643344.37 582658.19 119571.43 102429.47

Marketing Margin/kg 990.00 122.88 842.86 747.51

180


trading of supplied (inflow) smoked fish into fish markets along Nigeria-Cameroon-Chad

border

Variables Wholesaler

Mean SD











Gross Margin (₦) 635239.95 448590.65


Net Return (₦) 634903.68 448613.92





181


efficiency of the marketing nodes and actors involved in inter-state trade (outflow) of smoked fish

from the six States studied along Nigeria-Cameroon-Chad border region. The mean quantity of

smoked fish sold (inter-state) by processors, wholesalers and retailers was 779.75±586.28kg,

1121.77±219.88kg and 215.00±77.78kg, respectively. Processors had the highest mean marketing

cost of N22702.33±9678.87 and retailers had the least N3350.00±212.13. Wholesalers made the

highest mean gross margin of N683064.67±324812.39 and retailers made the least

N96750.00±9263.10. The mean marketing margin was estimated at N676245.89±522524.93,

N705400.60±323632.47, N102000.00±8485.28, respectively. Retailers had the highest efficiency

of 175.62±73.81.


nodes and actors involved in intra-regional trade (outflow) of smoked fish along Nigeria-

Cameroon-Chad border are presented in table 4.60. The mean quantity of smoked fish sold by

processors and wholesalers in this category was 1754.60±603.87kg and 1397.16±196.49kg,

respectively. The mean total marketing costs incurred in a month was estimated at

N34000.00±4873.40 and N17400.00±14093.97, respectively. The mean gross margin computed

was N1636648.31±513513.95 and N702983.22±381585.45, respectively. Wholesalers had the

highest efficiency of 193.23±140.30.

4.9.4 Dried Fish Intra-State, Inter-State and Intra-Regional Trade flow along Nigeria-



nodes and actors involved in intra-state trade dried fish in the six States studied along Nigeria-

Cameroon-Chad border region is shown in table 4.61. The mean quantity of dried fish sold by


137.50±38.14kg, respectively. Wholesalers sold dried fish at the highest selling price per kg of

fish valued at N1679.32±373.99 while processors sold at the least price valued at

N1292.10±401.53. The mean gross margin computed was N504019.16±466078.39,

N559120.55±448851.55, N51155.72±50665.98, respectively.

182

Table 4.59: Profitability and efficiency of the marketing nodes and actors involved in inter-State trading (outflow) of smoked

fish from fish markets in Nigeria-Cameroon-Chad border region














Gross Margin (₦) 623652.86 506925.90 683064.67 324812.39 96750.00 9263.10

Gross Margin/kg 769.45 271.53 615.70 295.02 473.17 128.10

Net Return (₦) 622843.53 506867.28 682567.59 324839.48 96268.71 9263.10

Net Return/kg 767.58 272.05 615.24 295.02 470.78 127.23




183

Table 4.60: Profitability and efficiency of the marketing nodes and actors involved in intra-

regional trading (outflow) of smoked fish from fish markets along Nigeria-Cameroon-Chad

border



Mean SD Mean SD


Buying Price (₦ Per Kg) 622.86 136.35 1155 330.81

Selling Price (₦ Per Kg) 1625.51 293.84 1680 516.66


Total Marketing Cost (₦) 34000 4873.4 17400 14093.97

Other operational costs (₦) 50714.29 7867.96 4500 1000





Gross Margin (₦) 1636648.31 513513.95 702983.22 381585.45

Gross Margin/kg 951.26 169.95 508.81 292.19

Net Return (₦) 1635763.38 513323.34 702332.7 381864.7

Net Return/kg 950.75 170 508.3 292.37


Marketing Margin/kg 1002.65 176.76 525 301.28

Marketing Efficiency 80.84 15.85 193.23 140.3

184

Table 4.61: Profitability and efficiency of the marketing nodes and actors involved in intra-State trading of dried fish in fish















Gross Margin (₦) 504019.16 466078.39 559120.55 448851.55 51155.72 50665.98

Gross Margin/kg 610.71 421.04 548.02 275.19 332.57 229.13

Net Return (₦) 503574.84 466059.43 558883.25 448912.35 50946.17 50647.47

Net Return/kg 609.45 421.25 547.43 275.30 330.94 229.26




185

The mean marketing margin and efficiency of these dried fish marketing (intra-state) actors were

estimated at N534442.42±473763.81 and 55.11±52.79, N636120.55±469309.52 and 38.34±36.50,


Table 4.62 shows the average monthly quantities of fish sold, profitability and marketing

efficiency of the marketing node actors involved in inter-state trade of supplied (inflow) dried fish

into fish markets in Nigeria-Cameroon-Chad border region. The mean quantity of dried fish sold

by processors was 795.00±63.64kg. The average selling price of these smoked fish per kg sold

(Inter-State) at the processing node was valued at N1462.50±689.43. The mean total cost of

production and marketing incurred in a month were estimated at N446322.76±8377.02 and

N21000.00±8485.28, respectively. The average monthly revenue made from these sales was

N1140750.00±455023.21. The mean gross margin and net returns were computed as


and efficiency of processors marketing (inter-state) dried fish were estimated at


The average monthly quantities of dried fish sold, costs and returns and marketing efficiency of

wholesalers involved in intra-regional trade (inflow) of dried fish along Nigeria-Cameroon-Chad

border is presented in table 4.63. The mean quantity of dried fish sold by this category of

wholesalers was 2098.00±306.88kg at a selling price of N1750.00±141.42 per kilogram (kg). The

mean marketing costs incurred in a month was estimated at N169000.00±69296.46. The average

gross margin and marketing margin realized from the intra-regional trade (inflow) of dried fish

were computed as N1741175.00±156093.82 and N1913525.00±87009.49 respectively.


efficiency of the marketing nodes and actors involved in inter-state trade (outflow) of dried fish

from the six States studied along Nigeria-Cameroon-Chad border region. The mean quantity of

dried fish sold (inter-state) by processors and wholesalers was 915.81±382.03kg,

1786.91±746.83kg, respectively. Dried fish selling price per kg was valued at N1424.94±340.80

and N1815.00±233.35, respectively

186

Table 4.62: Profitability and efficiency of the marketing actors involved in inter-State

trading of supplied (inflow) dried fish into fish markets in Nigeria-Cameroon-Chad border

region

Variables Processors

Mean SD











Gross Margin (₦) 694750.00 463508.50


Net Return (₦) 694427.24 463400.24





187


trading of supplied (inflow) dried fish into fish markets along Nigeria-Cameroon-Chad

border

Variables Wholesalers

Mean SD











Gross Margin (₦) 1741175.00 156093.82


Net Return (₦) 1740983.50 156011.09





188

Table 4.64: Profitability and efficiency of the marketing nodes and actors involved in inter-State trading (outflow) of dried fish

from fish markets in Nigeria-Cameroon-Chad border region



Mean SD Mean SD











Gross Margin (₦) 771537.60 741719.41 1242341.17 549363.74

Gross Margin/kg 723.45 468.71 691.38 18.48

Net Return (₦) 771172.90 741771.07 1242161.34 549429.97

Net Return/kg 722.89 468.86 691.26 18.56


Marketing Margin/kg 765.84 452.67 790.00 14.14


189

The mean total cost of marketing incurred by dried fish inter-state marketing (outflow) node actors

in a month was estimated at N17000.00±5366.56 and N171500.00±65760.93 for processors and

wholesalers, respectively. The mean marketing margin and marketing efficiency was estimated at

N803219.41±740821.23 and 86.69±52.57, N1416941.18±615266.09 and 18.73±1.71,

respectively.

The average monthly quantities of fish sold, profitability and marketing efficiency of the

processors involved in intra-regional trade (outflow) of dried fish along Nigeria-Cameroon-Chad

border is shown in table 4.65. The mean quantity of dried fish sold was 2205.11±987.43kg. The

mean total production and marketing costs incurred in a month was estimated at

N1268642.63±409296.40 and N38333.33±12583.06, respectively. The average gross margin and

marketing margin made was N2049354.76±1902399.39 and N2121021.42±1912202.52,

respectively. The processors involved in this intra-regional trade had an efficiency of 84.41±38.57.

4.9.5 Frozen Fish Intra-State marketing in Nigeria-Cameroon-Chad border region

Table 4.66 shows the average monthly quantity, profitability and marketing efficiency of fish

marketing actors involved in intra-State trade of frozen fish in Nigeria-Cameroon-Chad border

region. Average quantity of frozen fish sold by wholesalers and retailers was 891.92±84.47kg and

181.24±9.07kg, respectively. The mean buying and selling price of frozen fish per kg was

N766.67±225.46 and N1283.33±534.63 for wholesalers and N626.67±166.23 and

N916.67±125.83 for retailers. The mean total cost of marketing incurred from the sales of frozen

fish by wholesalers and retailers was N20066.67±8100.21 and N13666.67±2309.40, respectively.

Wholesalers and retailers realized an average mean gross margin of N451898.25±354537.06 and

N36606.67±15263.42, respectively. The mean marketing margin and efficiency of these marketing

actors in marketing frozen fish were N479464.91±361480.47 and 59.01±16.56,


190

Table 4.65: Profitability and efficiency of actors involved in intra-regional trading (outflow)

of dried fish from fish markets along Nigeria-Cameroon-Chad border

Variables Processors

Mean SD











Gross Margin (₦) 2049354.76 1902399.39


Net Return (₦) 2048685.11 1902473.89





191

Table 4.66: Profitability and efficiency of the marketing node involved in intra-State trading

of frozen fish in fish markets in Nigeria-Cameroon-Chad border region

Variables Marketing Node

Wholesaler Retailer

Mean SD Mean SD






Other operational costs (₦) 7500 3968.63 2600 529.15





Gross Margin (₦) 451898.25 354537.06 36606.67 15263.42

Gross Margin/kg 485.96 335.15 199.59 72.31

Net Return (₦) 451138.28 354518.16 36403.33 15336.23

Net Return/kg 485.11 335.2 198.46 72.77


Marketing Margin/kg 516.67 340.34 290 52.92


192

4.10 TRADE FLOW (INFLOW) OF FISH PRODUCTS ACCORDING TO STATES

ALONG NIGERIA-CAMEROON-CHAD BORDER

4.10.1 AKWA IBOM STATE

Intra-State inflow of forms of fish traded in Akwa Ibom State

The results presented in Table 4.67 shows the average monthly quantities of fish sold, prices,

profitability and marketing efficiency of the marketers involved in intra-State trade of the forms

of fish traded in Akwa Ibom State. The mean quantity of fresh, smoked, dried and frozen fish sold

in the State was 1167.04±753.20kg, 417.28±409.87kg, 460.82±451.09kg and 989.44±0.00kg,

respectively. The average monthly revenue realized from these sales was N696924.13±413171.92,

N803930.01±772984.67, N641720.63±407431.03 and N1879944.44±0.00, respectively. The

mean gross margin and net returns of the marketing actors involved in marketing (intra-state) fresh,

smoked, dried and frozen fish in Akwa Ibom State were N418330.31±326526.23 and

N416565.84±326299.30, N204782.81±108422.26 and N204378.80±108428.55,

N133526.23±77219.83 and N133123.07±77258.55, N856300.00±0.00 and N855532.00±0.00,

respectively. The mean marketing margin and efficiency of these fish marketing actors were

N627559.94±402674.35 and 9.67±8.24, N232813.15±210095.26 and 46.95±34.65,


Inter-State inflow of fresh fish traded in Akwa Ibom State

The average monthly quantities of fish sold, profitability and marketing efficiency of the marketers

involved in inter-State trade (inflow) of fresh fish into Akwa Ibom State is presented in table 4.68.

The mean quantity of fresh fish sold was 1325.33±411.25kg. The selling prices was estimated at

N516.67±28.87. The mean total production and marketing costs incurred in a month was estimated

at N446198.29±40545.08 and N252500.00±145911.79, respectively. The average monthly

revenue, gross margin and net returns realized from inter-State trade of fresh fish in Akwa Ibom

State were computed as N680600.00±191151.98, N236933.33±189396.58 and

N234401.71±188323.46, respectively. The traders had a mean marketing margin and efficiency of

N656433.33±175419.96 and 3.78±2.83, respectively from fresh fish inter-State trade.

193

Table 4.67: Average monthly quantities, prices, profitability and marketing efficiency of the forms of fish in Intra-State trade

(inflow) in Akwa Ibom State

Variables Fresh

Smoked

Dried

Frozen












Gross Margin (₦) 418330.31 326526.23 204782.81 108422.26 133526.23 77219.83 856300.00 0.00

Gross Margin/kg (₦) 349.09 254.54 560.51 337.80 416.18 283.98 865.44 0.00

Net Return (₦) 416565.84 326299.30 204378.80 108428.55 133123.07 77258.55 855532.00 0.00

Net Return/kg (₦) 346.81 254.46 558.53 337.52 414.54 283.44 864.66 0.00


Marketing Margin/kg (₦) 544.83 216.41 693.07 333.57 466.99 294.49 900.00 0.00



194

Table 4.68: Average monthly quantities, prices, profitability and marketing efficiency of

fresh fish in Inter-State trade (inflow) in Akwa Ibom State

Variables Fresh

Mean SD











Gross Margin (₦) 236933.33 189396.58

Gross Margin/kg (₦) 164.31 90.98

Net Return (₦) 234401.71 188323.46

Net Return/kg (₦) 162.46 90.84


Marketing Margin/kg (₦) 500.00 43.30


195

4.10.2 CROSS RIVER STATE

Intra-State inflow of forms of fish traded in Cross River State

The mean quantity of fresh, smoked, dried and frozen fish traded (intra-State) in Cross River State

was 475.40±396.56kg, 171.30±89.22kg, 154.73±60.55kg and 183.86±11.11kg, respectively as

presented in Table 4.69. The average buying and selling price for these forms of fish in Cross River

State were valued at N389.33±350.60 and N849.88±364.40, N777.92±322.33 and

N1545.00±288.59, N695.71±362.38 and N1132.50±416.42, N550.00±141.42 and

N850.00±70.71, respectively. The mean total production cost in a month for each form of fish

traded (intra-State) in Cross River State was N153853.20±147468.40, N156078.16±78903.36,

N118302.03±30830.29 and N116078.22±23577.46, respectively. The mean total cost of marketing

incurred for marketing fresh, smoked, dried and frozen fish in Cross River State was

N30295.68±20119.51, N11578.13±6656.88, N17435.71±7524.18 and N13000.00±2828.43,

respectively. The average monthly revenue realized from these sales was N359521.42±255363.01,


mean gross margin and net returns of the marketing actors involved in marketing (intra-state) fresh,

smoked, dried and frozen fish in Cross River State were N206984.48±168894.62 and

N205668.21±168347.40, N100980.45±62950.44 and N100686.20±62943.91,

N45486.30±37955.20 and N45186.72±37903.27, N40050.00±19869.70 and

N39807.50±20021.73, respectively. The mean marketing margin and efficiency of the actors

marketing these forms of fish were N262134.48±201565.95 and 13.90±10.97,

N128958.57±71633.33 and 32.43±31.92, N68493.44±41773.94 and 10.50±4.26,

N55550.00±16334.17 and 12.25±2.39, respectively in Cross River State.

Inter-State inflow of fresh fish traded in Cross River State


involved in inter-State trade (inflow) of fresh fish into Cross River State is presented in Table 4.70.

The mean quantity of fresh fish sold was 611.60±549.28kg. The selling price was estimated at

N610.00±155.56. The mean total production and marketing costs incurred in a month was

estimated at N116585.72±58509.71 and N52500.00±38890.87, respectively.

196

Table 4.69: Average monthly quantities, prices, profitability and marketing efficiency of the forms of fish traded (Intra-State

Trade) in Cross River State

Variables Fresh

Smoked

Dried

Frozen


Total Quantity Sold (Kg) 475.40a 396.56 171.30a 89.22 154.73a 60.55 183.86a 11.11

Buying Price (₦ Per Kg) 389.33a 350.60 777.92a 322.33 695.71a 362.38 550.00a 141.42

Selling Price (₦ Per Kg) 849.88b 364.40 1545.00a 288.59 1132.50b 416.42 850.00b 70.71

Total Purchase Cost (₦) 131472.36a 112744.77 127805.79a 72771.59 94995.32a 29755.27 100335.71a 19889.90

Total Marketing Cost (₦) 30295.68a 20119.51 11578.13b 6656.88 17435.71ab 7524.18 13000.00ab 2828.43

Other operational costs (₦) 24854.32a 17853.85 16400.00a 8646.80 5571.43a 3468.86 2500.00a 707.11

Total Variable Cost (₦) 152536.93a 147668.49 155783.91a 78910.94 118002.46a 30801.87 115835.72a 23425.44

Fixed Cost (Depreciated) (₦) 1316.27a 1160.28 294.24a 127.18 299.57a 140.31 242.50a 152.03

Total Production Cost (₦) 153853.20a 147468.40 156078.16a 78903.36 118302.03a 30830.29 116078.22a 23577.46

Total Monthly Revenue (₦) 359521.42a 255363.01 256764.36a 116975.19 163488.76a 55674.91 155885.72a 3555.74

Gross Margin (₦) 206984.48a 168894.62 100980.45a 62950.44 45486.30a 37955.20 40050.00a 19869.70

Gross Margin/kg (₦) 421.28ab 246.42 594.51a 280.07 281.43b 195.30 214.96b 95.08

Net Return (₦) 205668.21a 168347.40 100686.20a 62943.91 45186.72a 37903.27 39807.50a 20021.73

Net Return/kg (₦) 417.92ab 246.07 592.41a 280.09 279.35b 195.26 213.61b 95.99

Marketing Margin (₦) 262134.48a 201565.95 128958.57a 71633.33 68493.44a 41773.94 55550.00a 16334.17

Marketing Margin/kg (₦) 561.48ab 256.56 767.08a 294.02 436.79b 202.96 300.00b 70.71

Marketing Efficiency 13.90a 10.97 32.43a 31.92 10.50a 4.26 12.25a 2.39


197


fresh fish traded (Inter-State Trade) in Cross River State

Variables Fresh

Mean SD











Gross Margin (₦) 302000.00 271938.17

Gross Margin/kg (₦) 369.87 275.96

Net Return (₦) 299214.29 271694.05

Net Return/kg (₦) 362.53 282.15




198

The average monthly revenue, gross margin and net returns realized from inter-State trade of fresh

fish supplied to Cross River State were computed as N415800.00±330203.77,

N302000.00±271938.17 and N299214.29±271694.05, respectively. The traders had a mean

marketing margin and efficiency of N409300.00±321011.38 and 6.73±3.21, respectively from

fresh fish inter-State trade (inflow).

Intra-Regional Trade of fresh fish in Cross River State


involved in intra-regional trade (inflow) of fresh fish into Cross River State is presented in Table

4.71. The mean quantity of fresh fish sold was 558.29±369.52kg. The selling price was estimated

at N583.33±104.08. The mean total production and marketing costs incurred in a month was

estimated at N76472.84±23757.49 and N42666.67±17214.34, respectively. The average monthly

revenue, gross margin and net returns realized from intra-regional trade of fresh fish in Cross River

State were computed as N312733.33±170735.36, N237566.67±147833.74 and


N312733.33±170735.36 and 7.10±1.52, respectively from fresh fish intra-regional trade (inflow).

4.10.3 BENUE STATE

Intra-State inflow of the forms of fish traded in Benue State

Table 4.72 shows the average monthly quantities of fish sold, prices, profitability and marketing

efficiency of the marketers involved in intra-State trade of the forms of fish traded in Benue State.

The mean quantity of fresh, smoked and dried fish sold in the State was 480.95±474.01kg,

416.75±373.08kg and 627.33±418.72kg, respectively. The average buying and selling price for

these forms of fish in Benue State were valued at N389.17±329.33 and N801.90±259.47,

N1004.04±379.86 and N1678.27±376.79, N984.44±228.27 and N1492.07±316.27, respectively.

The mean total production cost in a month for each form of fish traded (intra-State) was


mean total cost of marketing incurred for marketing fresh, smoked and dried fish in Benue State

was N27890.48±18497.87, N11096.15±7071.79 and N29150.00±35291.80, respectively. The

average monthly revenue realized from these sales was N350992.35±348876.14,

N709038.97±744994.59 and N951561.57±767811.08, respectively.

199

Table 4.71: Average monthly quantities, prices, profitability and marketing efficiency of the

forms of fish traded (Intra-Regional Trade) in Cross River State

Variables Fresh Mean SD











Gross Margin (₦) 237566.67 147833.74


Net Return (₦) 236260.49 148088.27

Net Return/kg (₦) 423.80 77.08




200


Trade) in Benue State

Variables Fresh

Smoked

Dried


Total Quantity Sold (Kg) 480.95a 474.01 416.75a 373.08 627.33a 418.72


Selling Price (₦ Per Kg) 801.90c 259.47 1678.27a 376.79 1492.07b 316.27

Total Purchase Cost (₦) 146003.37b 215060.27 432320.13a 523893.87 586438.43a 436779.80

Total Marketing Cost (₦) 27890.48a 18497.87 11096.15b 7071.79 29150.00a 35291.80


Total Variable Cost (₦) 117527.00b 163114.88 455189.36a 524501.73 621699.54a 466573.59

Fixed Cost (Depreciated)(₦) 1627.76a 1473.25 416.71b 251.82 318.39b 245.38

Total Production Cost (₦) 119154.76b 162974.74 455606.07a 424502.23 622017.93a 466572.26

Total Monthly Revenue (₦) 350992.35b 348876.14 709038.97a 744994.59 951561.57a 767811.08

Gross Margin (₦) 233465.35a 168948.79 253849.61a 250316.56 329862.03a 235837.71

Gross Margin/kg (₦) 489.79ab 227.61 591.72a 200.68 435.72b 270.52

Net Return (₦) 231837.59a 168448.41 253432.90a 250280.16 329543.64a 235813.12

Net Return/kg (₦) 484.88ab 225.62 590.12a 200.71 434.94b 270.62

Marketing Margin (₦) 281466.94a 192335.63 276718.84a 255368.83 365123.14a 261409.76

Marketing Margin/kg (₦) 616.59ab 256.99 674.23a 215.30 507.62b 260.75



201

The mean gross margin and net returns of the marketing actors involved in marketing (intra-state)

fresh, smoked and dried fish in Benue State were N233465.35±168948.79 and

N231837.59±168448.41, N253849.61±250316.56 and N253432.90±250280.16,


and efficiency of the actors marketing these forms of fish were N281466.94±192335.63 and

16.03±14.48, N276718.84±255368.83 and 75.33±69.51, N365123.14±261409.76 and

42.10±31.55, respectively.

Inter-State inflow of forms of fish Traded in Benue State

Table 4.73 presents the average monthly quantities of fish sold, prices, profitability and marketing

efficiency of the marketers involved in inter-State trade of the forms of fish traded into Benue

State. The mean quantity of fresh, smoked and dried fish sold in the State was 1476.88±853.23kg,

281.23±28.62kg and 795.00±63.64kg, respectively. The mean total cost of marketing incurred for

supplying (inter-State) fresh, smoked and dried fish into Benue State was N41625.00±26505.73,

N15000.00±0.00 and N21000.00±8485.28, respectively. The average monthly revenue realized

from these sales was N983468.75±580237.34, N439495.80±38281.44 and

N1140750.00±455023.21, respectively. The mean gross margin and net returns of the marketing

actors involved in marketing (inter-state) fresh, smoked and dried fish into Benue State were

N505813.75±287844.33 and N503920.33±287912.86, N232008.40±23103.02 and


mean marketing margin and efficiency of these fish marketing actors were

N574438.75±323120.65 and 35.53±35.23, N267008.40±23103.02 and 29.30±2.55,


Intra-Regional inflow of the forms of fish traded in Benue State

The mean quantity of smoked and dried fish traded intra-regionally into Benue State was

1340.00±141.42kg and 2098.00±306.88kg, respectively as revealed in Table 4.74. The mean total

cost of marketing incurred for intra-regional trade (inflow) of smoked and dried fish into Benue

State was N17500.00±3535.53 and N169000.00±69296.46, respectively.

202

Table 4.73: Average monthly quantities, prices, profitability and marketing efficiency of the forms of fish traded (Inter-State

Trade) in Benue State

Variables Fresh

Smoked

Dried



Buying Price (₦ Per Kg) 306.00a 265.65 606.67a 110.15 525.00a 35.36


Total Purchase Cost (₦) 654448.00a 607105.13 172487.39a 48434.15 416250.00a 5303.30

Total Marketing Cost (₦) 41625.00a 26505.73 15000.00a 0.00 21000.00a 8485.28

Other operational costs (₦) 27000.00a 17703.91 20000.00a 0.00 8750.00a 5303.30

Total Variable Cost (₦) 477655.00a 539781.32 207487.39a 48434.15 446000.00a 8485.28

Fixed Cost (Depreciated) (₦) 1893.43a 1130.93 673.47a 293.80 322.76a 108.25

Total Production Cost (₦) 479548.43a 539184.64 208160.86a 48649.86 446322.76a 8377.02

Total Monthly Revenue (₦) 983468.75a 580237.34 439495.80a 38281.44 1140750.00a 455023.21

Gross Margin (₦) 505813.75a 287844.33 232008.40a 23103.02 694750.00a 463508.50

Gross Margin/kg (₦) 411.46a 246.20 834.73a 152.28 900.12a 655.08

Net Return (₦) 503920.33a 287912.86 231334.93a 23394.04 694427.24a 463400.24

Net Return/kg (₦) 408.59a 243.64 832.38a 153.07 899.71a 654.91


Marketing Margin/kg (₦) 492.50a 289.16 960.00a 163.71 937.50a 654.07



203


the forms of fish traded (Intra-Regional Trade) in Benue State

Variables Smoked

Dried

Mean SD Mean SD











Gross Margin (₦) 747250.00 30052.04 1741175.00 156093.82

Gross Margin/kg (₦) 559.58 36.63 844.40 197.92

Net Return (₦) 747023.33 30052.04 1740983.50 156011.09

Net Return/kg (₦) 559.41 36.61 844.30 197.86


Marketing Margin/kg (₦) 575.00 35.36 925.00 176.78


204

4.10.4 TARABA STATE

Intra-State inflow of forms of fish traded in Taraba State


efficiency of the marketers involved in intra-State trade of fresh, smoked and dried fish in Taraba

State. The mean quantity of fresh, smoked and dried fish sold in Taraba State was

465.93±371.79kg, 462.75±341.74kg and 305.83±181.37kg, respectively. The average buying and

selling price for these forms of fish in Taraba State were valued at N317.41±273.37 and

N811.84±469.53, N870.69±281.46 and N1466.11±420.70, N841.67±267.24 and

N1499.05±501.20, respectively. The mean total production cost in a month for each form of fish

traded (intra-State) was N160205.04±120487.05, N365678.61±238465.45 and

N247593.69±75792.84, respectively. The mean total cost of marketing incurred for intra-State

marketing of fresh, smoked and dried fish in Taraba State was N32722.66±26413.53,

N7497.22±4847.21 and N12366.67±4099.59, respectively. The mean gross margin and net returns

of the marketing actors involved in marketing (intra-state) fresh, smoked and dried fish in Taraba

State were N194459.12±154148.50 and N192875.64±154056.46, N271389.40±211405.74 and


mean marketing margin and efficiency for intra-State trade of these forms of fish were

N245661.47±166102.94 and 21.49±14.20, N283111.62±211873.41 and 113.21±91.10,


Inter-State inflow of forms of fish traded in Taraba State


involved in inter-State trade (inflow) of fresh and smoked fish into Taraba State is presented in

table 4.76. The mean quantity of fresh and smoked fish sold was 852.65±621.14kg and

145.00±7.07kg. The buying and selling prices were valued at N320.25±257.18 and

N866.70±368.31, N1450.00±636.40 and N2292.86±111.12. The average gross margin and net

returns realized from inter-State trade of fresh and smoked fish into Taraba State were computed

as N352541.29±257469.05 and N350611.75±255456.95, N108571.43±102429.47 and


N438024.62±265403.79 and 11.28±5.51, N119571.43±102429.47 and 55.35±0.02 respectively

from the inflow of fresh and smoked fish inter-State trade.

205


Trade) in Taraba State

Variables Fresh

Smoked

Dried





Total Purchase Cost (₦) 167678.77b 244716.76 353687.00a 236405.53 228083.33ab 77805.63

Total Marketing Cost (₦) 32722.66a 26413.53 7497.22b 4847.21 12366.67b 4099.59


Total Variable Cost (₦) 158621.55b 220867.74 365409.22a 238418.18 247283.33ab 75842.97


Total Production Cost (₦) 160205.04b 220487.05 365678.61a 238465.45 247593.69ab 75792.84

Total Monthly Revenue (₦) 353080.68a 318261.61 636798.62a 496954.54 467178.57a 362367.09

Gross Margin (₦) 194459.12a 154148.50 271389.40a 211405.74 219895.24a 202759.19

Gross Margin/kg (₦) 463.20a 335.12 561.49a 345.72 577.02a 463.84

Net Return (₦) 192875.64a 154056.46 271120.01a 211370.89 219584.88a 202779.31

Net Return/kg (₦) 457.83a 336.92 560.67a 345.68 575.76a 464.35


Marketing Margin/kg (₦) 608.49a 318.38 595.42a 340.85 657.38a 434.85

Marketing Efficiency 21.49b 14.20 113.21a 91.10 58.33b 46.71


206

Table 4.76: Average monthly quantities, prices, profitability and marketing efficiency of the forms

of fish traded (Inter-State Trade) in Taraba State

Variables Fresh Smoked

Mean SD Mean SD

Total Quantity Sold (Kg) 852.65a 621.14 145.00b 7.07

Buying Price (₦ Per Kg) 320.25b 357.18 1450.00a 636.40

Selling Price (₦ Per Kg) 866.70b 368.31 2292.86a 111.12

Total Purchase Cost (₦) 440142.95a 498291.22 212500.00b 102530.48

Total Marketing Cost (₦) 66416.67a 53673.47 6000.00b 0.00

Other operational costs (₦) 19066.67a 13765.42 5000.00b 0.00

Total Variable Cost (₦) 378911.97a 485692.89 223500.00b 102530.48

Fixed Cost (Depreciated) (₦) 1929.54a 2909.24 197.92b 73.66

Total Production Cost (₦) 380841.51a 484563.41 223697.92b 102456.82

Total Monthly Revenue (₦) 731453.26a 584237.75 332071.43b 101.02

Gross Margin (₦) 352541.29a 257469.05 108571.43b 102429.47

Gross Margin/kg (₦) 515.29b 403.99 766.90a 743.81

Net Return (₦) 350611.75a 255456.95 108373.51b 102355.81

Net Return/kg (₦) 512.40b 402.83 765.53a 743.23

Marketing Margin (₦) 438024.62a 265403.79 119571.43b 102429.47

Marketing Margin/kg (₦) 653.20b 432.30 842.86a 747.51

Marketing Efficiency 11.28b 5.51 55.35b 0.02

Mean values with the same alphabet superscripts on the same column are not significantly different

(P>0.05)

207

4.10.5 ADAMAWA STATE

Intra-State inflow of forms of fish traded in Adamawa State

The mean quantity of fresh, smoked, dried and frozen fish traded (intra-State) in Adamawa State

was 472.10±466.88kg, 476.87±425.90kg, 772.48±793.57kg and 510.11±472.50kg, respectively as

presented in Table 4.77. The average buying and selling prices for these forms of fish in Adamawa

State ranged from N363.60±302.20 and N697.16±235.31 to N1133.40±676.86 and

N1897.75±573.47, respectively. The mean total cost of marketing incurred for intra-State

marketing in Adamawa State ranged from N13287.28±7129.09 for smoked fish to

N31833.78±32750.14 for fresh fish. The mean marketing margin for the actors involved in intra-

State marketing of these forms of fish in Adamawa State ranged from N129286.32±115635.03 for

frozen fish to N722096.39±979611.45 for dried fish. The marketing efficiency of the actors selling

(intra-State) fresh, smoked, dried and frozen fish was 22.37±17.95, 88.69±79.69, 63.52±52.27 and

41.34±41.03, respectively.

Inter-State inflow of forms of fish traded in Adamawa State

The mean quantity of fresh and smoked fish traded (inter-State) into Adamawa State was

1577.06±498.21kg, and 1165.24±516.53kg, respectively as presented in Table 4.78. The mean

total cost of marketing incurred for inter-State marketing into Adamawa State was

N56100.00±5572.25 for fresh fish and N42500.00±17677.67 for smoked fish. The mean

marketing margin for the actors involved in inter-State marketing of these forms of fish into

Adamawa State was N732620.82±294033.92 and N1207848.33±542843.51, respectively. The

marketing efficiency of the actors was 13.79±5.83 and 44.15±2.10, respectively.

Intra-Regional inflow of smoked fish traded in Adamawa State


involved in intra-regional trade (inflow) of smoked fish into Adamawa State is presented in table

4.79. The mean quantity of fresh fish sold was 1169.86±12.46kg. The selling price was estimated

at N2450.00±212.13. The gross margin and net returns realized from intra-regional trade of

smoked fish in Adamawa State were computed as N684171.93±603595.63 and

N683905.43±603572.29, respectively.

208


Trade) in Adamawa State

Variables Fresh

Smoked

Dried

Frozen


Total Quantity Sold (Kg) 472.10a 466.88 476.87a 425.90 772.48a 793.57 510.11a 472.50

Buying Price (₦ Per Kg) 363.60b 302.20 1133.40a 676.86 589.17ab 189.85 765.00ab 21.21

Selling Price (₦ Per Kg) 697.16c 235.31 1897.75a 573.47 1437.22b 366.94 1025.00bc 35.36

Total Purchase Cost (₦) 199934.01a 300623.59 504518.52a 586240.25 431474.27a 419832.34 385218.95a 350638.62

Total Marketing Cost (₦) 31833.78a 32750.14 13287.28a 7129.09 18472.22a 10702.49 13500.00a 2121.32

Other operational costs (₦) 18117.16a 15050.10 10446.81a 8631.96 15361.11a 10134.11 3650.00a 1202.08

Total Variable Cost (₦) 185041.50a 281237.58 528252.61a 582156.95 465307.61a 434631.71 402368.95a 349719.38

Fixed Cost (Depreciated) (₦) 1354.83a 1221.39 443.08a 254.10 520.28a 260.12 401.79a 391.43

Total Production Cost (₦) 186396.33a 280803.47 528695.69a 582108.12 465827.89a 434662.69 402770.73a 350110.81

Total Monthly Revenue (₦) 323430.61a 355059.23 862470.62a 827003.86 1153570.67a 1357892.21 514505.26a 466273.65

Gross Margin (₦) 138389.11b 125779.64 334218.01ab 325759.68 688263.06a 667280.48 112136.32b 116554.27

Gross Margin/kg (₦) 327.22b 118.98 682.24a 285.96 766.97a 385.04 199.66b 43.55

Net Return (₦) 137034.28b 125814.37 333774.94ab 325759.39 687742.78a 667228.16 111734.53b 116162.84

Net Return/kg (₦) 322.80b 118.11 680.50a 285.79 765.65a 385.26 198.90b 43.49

Marketing Margin (₦) 188340.06b 151497.55 357952.10ab 327821.82 722096.39a 679611.45 129286.32b 115635.03

Marketing Margin/kg (₦) 451.49b 149.76 764.35a 301.84 848.06a 366.32 260.00b 14.14

Marketing Efficiency 22.37a 27.95 88.69a 79.69 63.52a 52.27 41.34a 41.03


209


forms of fish traded (Inter-State Trade) in Adamawa State

Variables Fresh

Smoked

Mean SD Mean SD











Gross Margin (₦) 632740.82 294867.86 1127698.33 521418.17

Gross Margin/kg (₦) 391.88 115.30 963.24 20.49

Net Return (₦) 630196.82 294523.77 1126781.66 521300.32

Net Return/kg (₦) 390.11 114.52 962.39 20.77




Mean values with the same alphabet superscripts on the same column are not significantly different

(P>0.05)

210


smoked fish traded (Intra-Regional Trade) in Adamawa State

Variables Smoked

Mean SD











Gross Margin (₦) 684171.93 603595.63

Gross Margin/kg (₦) 588.98 778.67

Net Return (₦) 683905.43 603572.29

Net Return/kg (₦) 588.75 778.64




211

The traders had a mean marketing margin and efficiency of N697071.93±602464.26 and

311.05±56.51, respectively from smoked fish intra-regional trade (inflow).

4.10.6 BORNO STATE

Intra-State inflow of forms of fish traded in Borno State

The mean quantity of fresh, smoked, dried and frozen fish traded (intra-State) in Borno State was

433.89±374.64kg, 967.51±535.19kg, 881.81±585.46kg and 842.11±0.000kg, respectively as

presented in Table 4.80. The average selling prices for these forms of fish in Borno State ranged

from N832.21±266.55 for fresh fish to N1,822.42±607.95 for smoked fish. The mean total cost of

marketing incurred for intra-State marketing in Borno State ranged from N19,091.95±9,957.13 for

smoked fish to N35,666.67±40,667.76 for dried fish. The mean marketing margin for the actors

involved in intra-State marketing of these forms of fish in Borno State ranged from

N325,160.11±29,2352.67 for fresh fish to N907,254.84±885,027.93 for dried fish.

Intra-Regional inflow of smoked fish traded in Borno State

The mean quantity of smoked fish traded (intra-regional) into Borno State was 951.56±214.34kg

as presented in Table 4.81. The mean total cost of marketing incurred for intra-regional trading of

smoked fish into Borno State was N10,000.00±0.00. The mean marketing margin and efficiency

for the actors involved in intra-regional trade of smoked fish into Borno State was

N488,697.94±327,110.52 and 213.67±30.64, respectively.

4.11 TRADE FLOW (OUTFLOW) OF FISH PRODUCTS ACCORDING TO STATES

ALONG NIGERIA-CAMEROON-CHAD BORDER

4.11.1 AKWA IBOM STATE

Inter-State outflow of forms of fish traded in Akwa Ibom State


efficiency of the marketers involved in inter-State trade (outflow) of fresh and smoked fish from

Akwa Ibom State. The mean quantity of fresh and smoked fish traded (inter-State) from Akwa

Ibom State was 1888.88±643.14kg, and 560.42±459.94kg, respectively.

212


Trade) in Borno State

Variables Fresh

Smoked

Dried

Frozen












Gross Margin (₦) 266905.30 263419.59 726550.54 515938.56 860504.84 792268.32 304842.11 0.00

Gross Margin/kg (₦) 604.48 249.75 725.37 294.18 761.78 567.42 362.00 0.00

Net Return (₦) 265321.32 263416.27 725814.14 515925.35 860251.37 792331.09 304008.78 0.00

Net Return/kg (₦) 599.44 249.48 724.26 294.32 761.09 567.52 361.01 0.00


Marketing Margin/kg (₦) 762.13 273.93 774.31 300.84 835.00 530.65 400.00 0.00



213


smoked fish traded (Intra-Regional Trade) in Borno State

Variables Smoked

Mean SD











Gross Margin (₦) 474297.93 327251.94

Gross Margin/kg (₦) 551.16 468.06

Net Return (₦) 473782.29 327203.36

Net Return/kg (₦) 550.60 467.88




214


forms of fish traded (Inter-State Outflow Trade) in Akwa Ibom State

Variables Fresh

Smoked

Mean SD Mean SD











Gross Margin (₦) 739862.58 168262.20 260833.87 238917.68

Gross Margin/kg (₦) 421.43 138.18 491.38 139.75

Net Return (₦) 738298.65 168002.17 260292.80 239006.01

Net Return/kg (₦) 420.54 138.01 489.10 139.80




215

The mean total cost of marketing incurred for inter-State marketing was N219125.00±170517.23

for fresh fish and N20282.14±7191.52 for smoked fish. The mean marketing margin for the actors

involved in inter-State marketing of these forms of fish from Akwa Ibom State was

N1002362.58±322378.19 and N295308.87±237299.08, respectively. The marketing efficiency of

the actors was 19.24±11.43 and 46.15±33.80, respectively.

4.11.2 CROSS RIVER STATE

Inter-State outflow of smoked fish traded in Cross River State

The mean quantity of smoked fish inter-State trade (outflow) from Cross River State was

311.74±14.83kg as presented in table 4.83. The mean total cost of marketing incurred for inter-

State trading of smoked fish from Cross River State was N22000.00±0.00. The mean marketing

margin and efficiency for the actors involved in inter-State trade (outflow) of smoked fish from

Cross River State was N575.00±247.49 and 21.57±0.47, respectively.

Cross-border outflow of fresh fish traded in Cross River State

The average quantity of fresh fish traded (outflow) from Cross River State was 2250.00±353.55kg

as presented in Table 4.84. The mean total cost of marketing incurred from this trade (cross-border)

of fresh fish from Cross River State was N70000.00±0.00. The mean monthly revenue from this

sale was N1175000.00±106066.02. The mean gross margin and net returns for the actors was


and efficiency for the actors involved in this trade (outflow) of fresh fish from Cross River State

was N1118750.00±97227.18 and 16.79±1.52, respectively.

4.11.3 BENUE STATE

Inter-State outflow of forms of fish traded in Benue State


efficiency of the marketers involved in inter-State trade (outflow) of fresh, smoked and dried fish

from Benue State. The mean quantity of fresh, smoked and dried fish sold was 1906.25±839.69kg,

530.60±380.48kg and 1368.46±659.08kg, respectively.

216


the forms of fish traded (Inter-State Outflow Trade) in Cross River State

Variables Smoked

Mean SD











Gross Margin (₦) 131583.33 82142.23

Gross Margin/kg (₦) 416.30 243.70

Net Return (₦) 131152.25 82298.63

Net Return/kg (₦) 414.91 244.26




217


fresh fish traded (Cross-border Outflow Trade) in Cross River State

Variables Fresh

Mean SD











Gross Margin (₦) 940250.00 106419.57


Net Return (₦) 937548.61 105820.50

Net Return/kg (₦) 418.16 18.68

Marketing Margin (₦) 1118750 97227.18



218


Outflow Trade) in Benue State

Variables Fresh

Smoked

Dried












Gross Margin (₦) 1379531.25 633523.48 341711.87 252744.37 771170.59 635034.75

Gross Margin/kg (₦) 720.38 15.02 696.48 213.30 499.10 227.07

Net Return (₦) 1376696.18 631713.98 341066.73 252821.33 770903.59 635151.02

Net Return/kg (₦) 718.97 14.69 694.55 213.18 498.84 227.26


Marketing Margin/kg (₦) 795.00 14.14 772.00 248.44 570.00 257.42


219

The average selling price for these forms of fish in Benue State was valued at N810.00±14.14,

N1620.00±327.11 and N1582.50±324.38, respectively. The mean total cost of marketing incurred

for inter-State marketing (outflow) of fish from Benue State ranged from N10800.00±3834.06 for

smoked fish to N95750.00±95353.29 for dried fish. The mean marketing margin and efficiency

for inter-State trade (outflow) of fresh, smoked and dried fish were N1509531.25±640594.55 and

20.51±8.71, N366511.87±249240.90 and 98.62±90.10, N878470.59±720729.87 and 40.87±25.69,

respectively.

Intra-Regional outflow of smoked fish traded in Benue State

The average quantity of smoked fish intra-regional trade (outflow) from Benue State was

1278.06±0.00kg as presented in Table 4.86. The mean total cost of marketing incurred for intra-

regional trading (outflow) of smoked fish from Benue State was N38000.00±0.00. The mean gross

margin and net returns for the actors was N1132811.11±0.00 and N1132351.73±0.00, respectively.

The mean marketing margin and efficiency for the actors involved in intra-regional trade (outflow)

of smoked fish from Benue State was N1175811.11±0.00 and 67.94±0.00, respectively.

4.11.4 TARABA STATE

Inter-State outflow of forms of fish traded in Taraba State



from Taraba State. The mean quantity of fresh, smoked and dried fish sold was 1350.00±0.00kg,

338.20±0.00kg and 342.50±81.32kg, respectively. The average selling price for these forms of fish

in Taraba State ranged from N800.00±0.00 for fresh fish to N2000.00±0.00 for smoked fish. The

mean total cost of marketing incurred for inter-State marketing (outflow) of fish from Taraba State

ranged from N15000.00±0.00 for smoked and dried fish to N115000.00±0.00 for fresh fish. The

mean marketing margin and efficiency for inter-State trade (outflow) of fresh, smoked and dried

fish were N337500.00±0.00 and 9.39±0.00, N439660.00±0.00 and 45.09±0.00,


220


the forms of fish traded (Intra-Regional Outflow Trade) in Benue State

Variables Smoked

Mean SD











Gross Margin (₦) 1132811.11 0.00


Net Return (₦) 1132351.73 0.00

Net Return/kg (₦) 886.00 0.00




221


Outflow Trade) in Taraba State

Variables Fresh

Smoked

Dried












Gross Margin (₦) 219500.00 0.00 412660.00 0.00 104785.71 20910.16

Gross Margin/kg (₦) 162.59 0.00 1220.17 0.00 322.27 137.57

Net Return (₦) 219121.52 0.00 412410.00 0.00 104379.05 20660.32

Net Return/kg (₦) 162.31 0.00 1219.43 0.00 320.96 136.53




222

4.11.5 ADAMAWA STATE

Inter-State outflow of forms of fish traded in Adamawa State



from Adamawa State. The mean quantity of fresh, smoked and dried fish sold was

1691.40±499.53kg, 830.08±500.03kg and 847.06±131.88kg, respectively. The mean marketing

margin and efficiency for inter-State trade (outflow) of fresh, smoked and dried fish were

N509345.79±179642.17 and 10.62±4.07, N760006.02±568969.08 and 53.43±45.63,

N756351.34±350423.60 and 114.62±51.52 respectively.

Intra-Regional outflow of forms of fish traded in Adamawa State

The average monthly quantities of fish sold, prices, profitability and marketing efficiency of the

marketers involved in intra-regional trade (outflow) of fresh, smoked and dried fish from

Adamawa State is presented in Table 4.89. The mean quantity of fresh, smoked and dried fish sold

was 2100.00±282.84kg, 1563.29±31.71kg and 2205.11±987.43kg, respectively. The mean

marketing margin and efficiency for intra-regional trade (outflow) of fresh, smoked and dried fish

were N1007850.00±148987.40 and 19.08±0.12, N684260.87±339780.18 and 271.09±174.07,

N2121021.42±1912202.52 and 84.41±38.57 respectively.

4.11.6 BORNO STATE

Inter-State outflow of forms of fish traded in Borno State


efficiency of the marketers involved in inter-State trade (outflow) of smoked and dried fish from

Borno State. The mean quantity of smoked and dried fish traded (inter-State) from Borno State

was 1084.89±445.10kg and 1366.87±182.57kg, respectively. The mean total cost of marketing

incurred for inter-State marketing was N20304.00±8805.29 for smoked fish and

N22666.67±4618.80 for dried fish. The mean marketing margin for the actors involved in inter-

State marketing of these forms of fish from Borno State was N825733.04±426381.34 and

N1621145.58±937244.60, respectively. The marketing efficiency of the actors was 119.01±77.95

and 106.44±57.43 respectively.

223


Outflow Trade) in Adamawa State

Variables Fresh

Smoked

Dried












Gross Margin (₦) 381665.79 165383.93 708946.02 553131.31 732976.35 359225.72

Gross Margin/kg (₦) 226.99 82.71 834.70 257.69 844.67 328.69

Net Return (₦) 381154.92 165403.59 708186.30 553130.03 732499.69 359041.28

Net Return/kg (₦) 226.68 82.76 833.13 257.59 844.09 328.52




224

Table 4.89: Average monthly quantities, prices, profitability and marketing efficiency of the forms of fish traded (Intra-

Regional Outflow Trade) in Adamawa State

Variables Fresh

Smoked

Dried












Gross Margin (₦) 908400.00 140007.14 668460.87 345719.88 2049354.76 1902399.39

Gross Margin/kg (₦) 432.00 8.49 429.93 229.87 804.01 419.92

Net Return (₦) 906035.82 140755.92 668139.54 345585.05 2048685.11 1902473.89

Net Return/kg (₦) 430.84 9.00 429.72 229.78 803.67 420.05




225


forms of fish traded (Inter-State Outflow Trade) in Borno State

Variables Smoked

Dried

Mean SD Mean SD











Gross Margin (₦) 785757.04 413650.22 1581812.24 944594.03

Gross Margin/kg (₦) 742.95 298.44 1107.04 582.32

Net Return (₦) 785037.87 413662.24 1581617.80 944641.14

Net Return/kg (₦) 742.00 298.34 1106.89 582.38




226

Intra-Regional Trade

The average quantity of smoked fish intra-regional trade (outflow) from Borno State was

1683.27±594.36kg as presented in Table 4.91. The mean total cost of marketing incurred for intra-

regional trading (outflow) of smoked fish from Borno State was N30750.00±10239.98. The mean

gross margin and net returns for the actors was N1474842.27±659905.44 and

N1473880.46±659929.18, respectively. The mean marketing margin and efficiency for the actors

involved in intra-regional trade (outflow) of smoked fish from Borno State was


227


forms of fish traded (Intra-Regional Outflow Trade) in Borno State

Variables Smoked

Mean SD











Gross Margin (₦) 1474842.27 659905.44

Gross Margin/kg (₦) 868.48 282.10

Net Return (₦) 1473880.46 659929.18

Net Return/kg (₦) 867.87 282.34




228

CHAPTER FIVE

5.0 DISCUSSIONS

5.1 Socio-economic characteristics of respondents across the marketing nodes

The socio-economic characteristics of the respondents across the three major marketing nodes

(production, processing and marketing) presented in table 4.1 are discussed as follows. Sex is an

important social factor in the society that influences responsibility as observed in the sex

distribution of the respondents across the fish marketing nodes. Both male and female were

involved in fish trade along Nigeria-Cameroon-Chad border. This is similar to the findings of

Dambatta et al. (2016) who revealed that both male and female were involved in all the activities

of fishing such as fishing, processing, marketing and consumption. However, the results in this

study showed the dominance of men in the production node. This could be because fish production

is a tedious business for women. Similarly, Udoh and Nyienakuma (2008) reported that most of

the respondents who engage in fishing activities in the sea were males. Generally, men are more

involved in the production (upstream) activities and invest in fishing vessels, nets, other fishing

gear and pond construction (Lem et al., 2014). Furthermore, it was observed from the results that

the percentage of women was more in the processing and marketing nodes. This could be because

of the persuasive nature of women in promoting fish sales. The finding of this research is in line

with Esiobu et al., (2014a) who asserted that females constitute a greater proportion of those

involved in agribusiness activities.

Age of the respondents gives an indication of their fishing experience and productivity. As

observed from table 4.1, majority of the marketing actors were within the age brackets of 41 and

50 years. It can be deduced that more of middle aged men and women, who are still very productive

are involved in fishing, processing and marketing activities in the study area. The implication of

this result is that majority of the respondents are experienced adults within the productive and

economic active age, and could still improve the livelihood of their families. This supports the

assertion by Ahmed et al. (2015) that majority of the respondents from their study that are in their

economic active years were able to support the rigors of food production and general livelihood

sustenance. Similarly, Omitoyin and Okeowo (2015) reported majority of catfish producers,

229

processors and marketers in Lagos State to be between 41 and 50 years of age. The mean age of

the respondents is 43 years. Esiobu et al., (2014b) reported that this age group constitutes the major

productive workforce and that young individuals have more potential to withstand stress, strain,

risk and have more strength to face tedious task associated with fish marketing than the too young

or too old individual.

The marital status of the actors in the marketing nodes showed that the percentage of married

respondent was highest across the three nodes. This could be because of the opportunity of getting

cheap family labour to use in fish production, processing and marketing by married persons. The

involvement of married people in fish marketing could mean that the trade is remunerative to cater

for family responsibilities as opined by Kwaghe et al. (2008). This result is consistent with the

findings of Shetimma et al. (2014), who reported that majority of the fishermen in Lake Jere,

Borno State, Nigeria were married. The percentage of divorced respondents was lowest across the

marketing nodes, with no divorced respondent among the producers. The low percentage of single

and divorced value chain actors could be attributed to the value given to marriage institution in the

study area.

The position of the actors in their respective households revealed that majority of the producers

and processors were household heads. The percentage of household heads among the respondents

implies that some of the female respondents among the processors were household heads. This

could be as a result of the high expectation of responsibility and generation of income from the

respondents. However, majority and yet not all the male respondents among the producers were

heads of their households. Similarly, in the study by Ahmed et al. (2015), household heads in the

study area were mostly males. They further asserted that it was in consonance with the religious

inclinations of the respondents. Majority of the marketers were not heads of their households.

Religion affects the way of life of people. The distribution of the respondents according to their

main occupation, reveals that majority of them are Christians across the fish marketing nodes. This

category was followed by Muslim respondents and only one traditionalist was recorded in the

production sector. Similarly, Odebiyi et al. (2013) found the majority of fish processors in their

research to be Christians.

Household size is referred to in this study as the number of persons living under the care of the

respondent at the time of the field survey. The largest proportion of the marketing participants

230

have a household size of 4-7 persons, followed by households with 8-11 persons as observed in

table 4.1 represented on the socio-economic characteristics of the respondents according to their

main occupation. It is obvious that there is high dependency ratio in the households of the

respondents. The mean household size is 6 persons. Ahmed et al. (2015) reported a moderate

household size with an average of 7 persons per household. Fisher folks prefer to have a moderate

to large household size because of the cheap and free labour obtainable from the household

members. This therefore explains why the use of hired labour in small-scale agribusiness enterprise

is very low (Esiobu and Onugbuogu, 2014).

Education plays an important role in technology adoption and personal advancement. The highest

level of education of the respondents across the marketing nodes was Secondary school education.

It can be inferred that the actors in the fish marketing nodes have the ability to read and write and

make decisions that will expand their businesses and improve their livelihoods. The number of

respondents with tertiary education was high among the producers compared to the other

marketing nodes. This high level of education will enable fish producers to make use of

innovations and new techniques of fish management, as well as comprehend policy measures put

in place to ensure socio-economic and environmental sustainability of fish production. Similarly,

Oluwemimo and Damilola (2013) and Olaoye et al. (2013) observed that majority of the fish

farmers in Osun and Oyo States respectively had Tertiary education. This finding supports the

assertion that it is expected that the higher level of education will contribute significantly to

decision making of marketers and that exposure to high level of education is an added advantage

in terms of achieving huge income, efficient marketing and sustainable agribusiness all year round

(Esiobu and Onubuogu, 2014).

Variations were observed in the level of experience of the actors in terms of marketing fish. Very

few of them had less than a year experience in fish marketing. Majority of the producers,

processors and marketers had more than 15 years of marketing experience, 11-15 years of

marketing experience and 6-10 years of marketing experience respectively. This implies that the

actors have substantial number of years of experience in marketing and possess good skills and

ability to make wise decisions that will enhance their business performance. This is similar to the

findings of Udoh and Nyienakuma (2008), they reported 15 or more years of fishing experience

for majority of artisanal fishers in Akwa Ibom State. Similarly, Odebiyi et al. (2013), reported 11-

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20 years of experience for majority of fish processors in their study in Ogun State. In addition,

Babalola et al. (2015) observed that majority of fish marketers in their study had 6-10 years of fish

marketing experience.

The percentage of marketing actors that belonged to a marketers’ association was more than those

who did not belong to any. This is similar to the finding of Umoinyang (2014). This rate of

membership could be because it afforded the respondents access to credits and vital information

that will necessitate the expansion of their businesses. According to Coaster and Otufale (2010),

membership of cooperative society affords farmers the opportunity of sharing information on

modern production techniques, purchasing inputs in bulk as well as exchanging labour.

Based on the findings from the field survey, it was discovered that some of the respondents

engaged in other income-earning occupations apart from fish farming, processing and marketing

as seen in figure 4.6. Occupation remains valid in our society as people have one or two things

they engaged in which gives them sense of satisfaction and belonging in the society (Olaoye et al.,

2013). Assessing the occupational status of the respondents, they engaged in other income earning

activities such as trading, menial businesses, farming and some of them were pensioners. Some of

the processors were also fishers and some of the fish farmers were civil servants. Similarly, Ahmed

et al. (2015) reported both on-farm and off-farm activities such as crop production, civil service

employment, petty trading, livestock, poultry and tailoring as the commonest income generating

activities among in the households of respondents in their study. While this will enable farmers to

earn incomes from other sources which they could invest in the enterprise, it has the disadvantage

of keeping fish farming at small scale (Oluwemimo and Damilola, 2013). However, according to

Ahmed et al. (2015) households’ income generating activities are also forms of income

diversification activities that are key factors to household food security and they provide for

immediate needs of the households and also serve as buffers during lean periods.

Many of the respondents depend on personal savings and social funding- cooperatives and

inheritance for their operations as seen in figure 4.1 to figure 4.4. Personal savings was the highest

primary source of funds for all the marketing actors in fish trade. This is consistent with the

findings of Osarenren and Ojor (2014) and Nwabunike (2015), where majority of fish marketers

finance their businesses through personal savings. Contrarily, Udoh and Nyienakuma (2008)

reported that majority of artisanal fisherfolks in Akwa Ibom obtained their inputs through

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inheritance from their parents. The percentage of those that had access to institutional funding

from the government and banks was very insignificant. This could be due to the ignorance of the

fishers on how to tender their problems appropriately to the right quarters in the government or the

belief that both the government and banks are inaccessible sources to obtain funds and input

facilities. This factor is one of the major constraints faced by fisheries value chain actors. Majority

of those interviewed on the field complained of access to credits and lack of funds. The sales

proceeds are often reinvested to keep the business operations going. As seen in figure 4.5, another

common practice among the respondents in their associations or cooperatives is the contributions

they make, also called “esusu”, which is used to support their operations.

5.2 Socio-economic characteristics of respondents across the geopolitical zones

The socio-economic characteristics of the respondents across the three geopolitical zones

presented in table 4.2 are discussed as follows. Majority of the respondents in South-South were

female, while majority of the respondents in North-Central and North-Eat were male. The

dominance of men in North-Central and North-East may be due to religious factors like purdah.

Yet it can be deduced from the results of this study that fishing is not exclusively the right of men

in the study areas, because the contribution of the women folk cannot be undermined. According

to Lem et al. (2014), women who are more highly educated or have better access to resources can

be involved in the higher levels of the fishery value chains, meaning that they can manage and

operate fishing enterprises.

The age distribution of the respondents showed that majority of them from the three geopolitical

zones are within the age bracket of 41-50 years. This shows that more of the men and women who

were still very productive and matured to support the rigors of food production were involved in

fish trade in the study area. There is high expectation for responsibility from this age group, hence

their expected high output. This confirms the assertion by Udoh and Nyienakuma (2008) that

matured respondents in their study put in more time and other resources in the business, thereby

resulting in increased output of fish.

The marital status of the respondents showed that the percentage of married respondents was

highest across the geopolitical zones. This afforded the respondents the opportunity of getting free

and cheap family labour to engage in fish production, processing and marketing activities.

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Moreover, the percentage of married respondents in North-East was more compared to the other

geopolitical zones. This could be a result of the prevalence of early marriage in the North. Median

age at marriage is lowest among girls in North-East region (Erulkar and Bello, 2007) and the

median age at first marriage among Nigerian men and women is 27.2 years and 18.1 years,

respectively (NPC and ICF International, 2014). This result is consistent with the findings of

Shetimma et al. (2014), who reported that majority of the fishermen in Lake Jere, Borno State,

Nigeria were married.

In South-South, all the respondents were Christian. Majority of the respondents in North-Central

were Christians with only one traditionalist in that geopolitical zone. Majority of the respondents

in North-East were Muslims. This could be as a result of tribal distribution in Nigeria and the

particular religion peculiar to the different tribes.

Majority of the respondents in North-Central and North-East were household heads. This could be

as a result of the dominance of male respondents in these two geopolitical zones. This implies that

responsibility was required from the male respondents as household heads to provide for their

family the basic necessities of life. Ahmed et al. (2015) reported that household heads in their

study area were mostly males and this is in consonance with the religious inclinations of the

respondents. However, in South-South, majority of the respondents were not household heads,

probably because majority of the respondents from this zone were females.

From the household size distribution as seen in table 4.2, majority of the respondents had a

household size of 4-7 persons. Across the three geopolitical zones assessed, North-East had the

highest number of respondents with household sizes of more than 7 persons. This implies that the

prevalence of polygamy amongst Muslims which forms the highest percentage of respondents

from North-East would encourage large household sizes. Therefore, it can be deduced that majority

of the respondents in the geopolitical zones have moderate to large household sizes that gives them

the privilege of engaging their household members in their businesses for free labour. This agrees

with the findings of Okeowo et al. (2015), that fishing households tend to have more children and

by extension larger families so they can contribute positively to their livelihood.

Education is very important in every aspect of life and plays an important role in receptiveness to

innovation. Majority of the respondents in South-South and North-East were Secondary school

leavers. Similarly, the highest percentage of fish marketers in Nasarrawa State (Abah et al., 2013)

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and Imo State (Esiobu and Onugbuogu, 2014) had secondary school education. Respondents who

attended only Primary school was highest in North-Central. And the respondents with tertiary

education was highest in North-East compared to the other geopolitical zones. Hence, majority of

the respondents in the three geopolitical zones had formal education. It can be inferred from this

study that these respondents have the ability to get new and valuable information from research

and adopt innovations. This finding is in line with that of Mele (2007), following his study of

economic analysis of fresh fish marketing in Dadin kowa, Gombe, State where he found that

majority of the respondents had formal education. However, in North-East, the higher percentage

of respondents that had Qu’ranic compared to the other geopolitical zones could be because of

Islamic religion largely practiced in this zone. Few respondents had informal education since the

assertion by Osarenren and Ojor (2014) states that they might not be able to process marketing

information that would enable them to improve their sales.

The years of marketing experience of the respondents showed that majority of respondents in

North-Central had the highest level of marketing experience of more than 15 years. Similarly,

Udoh and Nyienakuma (2008) reported 15 or more years of fishing experience for majority of the

respondents in their study. Very few respondents had less than a year marketing experience.

Majority of the respondents in South-South and North-East had marketing experiences of 6-10

years. Similarly, Madugu and Edward (2011) observed that majority of the marketers in their

studies in Adamawa State had less than and equal to 10 years of marketing experience. The longer

the experience in the fisheries business, the better the performances of the value chain actors. Ali

et al. (2008) stated that marketing experience is important in determining the profit levels of

marketers, the more the experience, the more the marketers understand the marketing system,

condition, and price trends etc.

Respondents that were members of marketers’ association were higher in North-Central and

North-East. However, in South-South, it was observed that the percentage of respondents that did

not belong to marketers’ association was higher. This could mean that majority of marketing actors

in this zone prefer independence in the activities. Similarly, in the study carried out by Kainga and

Adeyemo (2012) in Bayelsa State, majority of the respondents did not belong to any fish marketing

association because of leadership problem and level of education.

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5.3 Socio-economic characteristics of fish marketing actors in each of the sampled State

The socio-economic characteristics of the fish marketing actors in each of the marketing nodes in

the six sampled States are discussed as follows. The sex distribution of the respondents indicates

the dominance of males in the production node and dominance of females in the processing and

marketing nodes, except in Taraba and Borno States. This is supported by the results of the

investigations made by Umoinyang (2014) that revealed 100% male fish producers in Akwa Ibom

State. Similarly, Ayotunde and Oniah (2012) reported a higher percentage of male fishers in Cross

River State. This study confirms the assertion by Lem et al. (2014), who stated that women

generally invest more in processing equipment and are responsible for fish purchasing, processing

and retailing. In Taraba and Borno States, men dominated the processing and marketing nodes.

This could be because of religious factors like purdah in the Northern States. Only one female

producer was recorded in Benue State. This result can be justified by the assertion of Brummett et

al., (2010) that fisheries activities are mostly dominated by men. The pooled sex distribution of

the respondents in the six States sampled as illustrated in figure 4.7 reveals that the percentage of

male was higher than females in the study area, except in Cross River State. This could be as a

result of the huge percentage of female processors and marketers in Cross River State. The number

of females in Borno State was very low compared to the other States that were sampled for this

study.

The results showed that majority of the respondents were within the age group of 41-50 years.

Similarly, Udoh and Nyienakuma (2008) and Asa and Obinaju (2014) reported that majority of

the fishers in Akwa Ibom were aged between 41 and 50 years in their respective studies.

Furthermore, Ibok et al. (2013) in their research in Calabar, Cross River State reported that

majority of farmers that are actively involved in fish farming falls within 41 and 50 years and this

means that the farmers still have the strength to run the business. However, majority of marketers

in Benue, Taraba and Borno States including producers in Borno State were within the age

category of 31-40 years. In addition, majority of producers in Adamawa State and processors in

Adamawa and Borno States fall within the age group of over 50 years. Similarly, Madugu and

Edward (2011) and Odebiyi et al. (2013) in their studies observed a majority of marketers within

the age group of 31 and 40 years. The age distribution of the respondents in each of the sampled

states as presented in figure 4.8 showed that the category of respondents aged 20 years and below

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had the lowest percentage across the six States. This means that younger persons cannot withstand

the rigours of fish production, marketing and processing. In Adamawa State, the highest number

of respondents are within the age groups of 41-50 years and above 50 years. This shows that adults

with wealth of experience are largely involved in fish production and marketing activities in these

States.

Majority of the respondents in each of the marketing nodes across the States were married, the

highest being in Cross River State among the processors reaching hundred percent married

respondents. Similarly, over eighty-five percent of the respondents in Akwa Ibom State were

married according to the findings of Asa and Obinaju (2014). There were very few divorced and

widowed persons among the respondents in all the States. This signifies the value of marriage in

these sampled States. Asa et al. (2012) noted that marriage is a highly cherished social value among

fish farmers in Akwa Ibom State and this finding corroborates that. The bar chart illustrating the

marital status of the respondents in figure 4.9 reveals that the percentage of married respondents

was highest across the six states in Nigeria-Cameroon-Chad border region. This is consistent with

the findings of Shetimma et al. (2014), who reported that majority (80.5%) of the fishermen in

Lake Jere, Borno State, Nigeria were married.

Christianity was largely practiced among the respondents in each of the marketing nodes across

Akwa Ibom, Cross River and Benue States and among the processors and marketers in Adamawa

State. It was observed in Akwa Ibom and Cross River States that all of the respondents were

Christians. However, across the marketing nodes in Taraba and Borno States including the

producers in Adamawa State, majority of the respondents were Muslims. This implies that Islamic

religion is largely practiced in the North-Eastern States. There was only one traditionalist recorded

among the producers in Benue State. This implies that traditional worshippers are not involved in

fish marketing activities. Figure 4.10 reiterates the prevalence of Christianity in Akwa Ibom, Cross

River, Benue and Adamawa States than in Taraba and Borno states. The predominance of

Christians against Muslims in Adamawa state is a result of the high percentage of Christian

respondents among the processors and marketers in Adamawa State.

Majority of the producers in the six sampled States were household heads. Processors that were

household heads were more than those that were not household heads in Akwa Ibom State, Taraba

State, Adamawa State and Borno State. And higher percentage of marketers that were household

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heads was found in Taraba and Borno States. This could be because majority of the marketers in

Taraba and Borno States were male and this agrees their religious inclinations. Similarly, Ahmed

et al. (2015) reported household heads were mostly males.

The category of household size of 4-7 persons had the highest percentage of respondents across

the marketing nodes in the six States, except among the marketers in Taraba State. In Taraba State,

the highest percentage of respondents among the marketers have a household size of three persons

and less. This could be because the modal age group for marketers in Taraba is 31-40 years,

therefore they can only support small household sizes. The highest percentage of respondents with

a household size of 4-7 persons was observed among the processors in Cross River State and

majority of them were within the age bracket of 41and 50 years. The highest percentage of

respondents with a household size of 12 persons and more was found among the processors in

Borno State. This large household size is a function of the prevalence of polygamy in the North.

Figure 4.11 showing the distribution of the household sizes of the respondents in the six States in

the study area revealed that respondents with household sizes of 8-11 persons in Akwa Ibom, Cross

River and Benue States form the second highest category of household sizes. This agrees with the

findings of Okeowo et al. (2015), that fishing households tend to have more children and by

extension larger families so they can contribute positively to their livelihood.

Education is the bedrock of development and the highest educational qualification of the

respondents as presented in tables 4.3a and 4.3b revealed that the highest percentage of

respondents with Primary school certificate was among the processors in Benue State. The highest

percentage of respondents with Secondary school leaving certificate was observed among the

processors in Cross River State. Similarly, the highest percentage of fish marketers in Nasarrawa

State (Abah et al., 2013) and Imo State (Esiobu and Onugbuogu, 2014) had secondary school

education. Furthermore, the highest percentage of respondents that attended Tertiary institutions

was found among the producers in Cross River State. This shows that Cross River State has a lot

of highly educated respondents probably as a result of the availability of infrastructural amenities

that supports schooling. Furthermore, figure 4.12 revealed that Secondary school education was

the highest educational level attained by majority of the respondents in Akwa Ibom, Cross River,

Taraba and Adamawa States. In Benue State, the highest percentage of respondents are primary

school leavers. While, majority of the respondents in Borno State, up in the North-East went to

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Qu’ranic schools. This could mean that less value is placed on basic education in Borno State and

they prefer Qu’ranic education because of their Islamic religion. However, the percentage of

respondents that had informal education was low across the six States. Osarenren and Ojor (2014)

posited that as a result of informal education, respondents might not able to process marketing

information that would enable them to improve their sales.

The marketing experiences of the respondents across the six states as presented in figure 4.13,

shows that majority of the respondents had substantial years of experience to improve their

marketing skills. In Akwa Ibom, Cross River and Adamawa States, majority of the respondents

had 6-10 years of marketing experiences. Similarly, Madugu and Edward (2011) and Abah et al.

(2013) observed that majority of the marketers in their studies in Adamawa and Nassarawa States

had less than and equal to 10 years and 5-9 years marketing experiences respectively. Udoh and

Nyienakuma (2008) posited that experience is the act of gaining knowledge through constant

practices of skill, which brings about specialization and that the sum of experience increases

output. Very few of the respondents had a short marketing experience of less than a year across all

the States, except in Cross River, Benue and Borno States where there was no respondent in that

category. Benue State had a large number of respondents with more than 15 years of marketing

experience. It can be inferred that majority of the respondents in Benue State were satisfied with

fisheries marketing activities being their source of income and Olaoye et al. (2013) opined that

fisheries related activities can give people a sense of belonging and satisfaction in the society and

should thus be encouraged. Udoh and Nyienakuma (2008) further stated that respondents with

longer years of experience have the ability to forecast market situation in which they can sell their

products at higher prices.

5.4 Marketing nodes

The market survey of this study revealed three major marketing nodes for the fresh and processed

fish in the study area. The nodes are Production, Processing and Marketing. These marketing nodes

are comprised of five stakeholders before fish reaches the consumers, namely: fish farmers and

fishermen (Producers); Fish Processor (Processors); wholesalers and retailers (Marketers).

Similarly, Odebiyi et al. (2013) identified three major marketing nodes including: fishermen, fish

processors and the fish marketers, along the coastal area of Ogun Waterside Local Government

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Area (LGA), Nigeria. The wholesalers actually occupy the suppliers/middlemen stage of

marketing, while the retailers formed the major marketers that sold fish directly to the consumers.

5.5 Profile of fish traded in the study area

A summary of some of the fish species produced and traded in the study area is presented in table

4.4. A total of 32 fish species from 25 families was found along Nigeria-Cameroon-Chad border.

These fish species were sourced from fresh water, brackish and marine water bodies. Ekundayo et

al. (2014) identified a total of fourteen (14) species of thirteen (13) families during the period of

their study on Lake Gerio in Adamawa State. Emmanuel (2010) identified forty (40) families of

fish species in their assessment of Lekki lagoon.

5.6 Fish market structure

5.6.1 Forms of fish sold in the study area

The highest form of fish sold is fresh fish and the least form of fish sold is frozen. Fresh fish was

also reported as the highest form of fish sold in a similar study by Nwabunike (2015). This may

be due to the considerable implication of costs incurred from processing. Contrarily, Babalola et

al. (2015), reported frozen fish as the majorly marketed fish form in Ogun State. Fish either in its

fresh or processed form under goes some level of sorting at different level of the marketing system.

The sorting is basically dependent on the species and size of the fish. Different species have

different values to the consumers and as such attract different prices in the markets.

5.6.2 Pricing

The pricing methods for fish in the study area revealed that majority of the respondents in the

marketing nodes employed negotiation with buyers or bargaining method to place prices on their

fish products. Similarly, the prices of catfish were determined through bargaining powers of the

parties involved (buyers and sellers) in the study carried out by Irhivben et al. (2015). Some of the

factors that influenced the prices of fish include: forces of demand and supply, cost of production,

cost of transportation, value addition, season, fish species, quantity, etc. Some of the producers

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fixed their fish prices. Very few respondents acknowledged that the prices of fish sold was

controlled by value chain actors. In addition, some of the producers fixed their fish prices, however

the processors could not do that. Contrarily, majority of fishers set their fish prices in the study

carried out by Chiwaula et al. (2012).

5.6.3 Revenue Distribution and Gini coefficient

5.6.3.1 Fresh Fish Production Node

The empirical results revealed that the fish culture producers were concentrated having a high Gini

coefficient value. This means that there was high inequality in the earnings of culture producers of

fresh fish, and the gap between those that are producing on a large scale and the small-scale

producers is wide. The result indicates the existence of an imperfect market structure and high

inefficiency among fish farmers in Nigeria-Cameroon-Chad border region. Phiri et al. (2013) also

reported a very high Gini coefficient index for fishers. The Gini coefficient of capture producers

indicated a partial inequality in revenue distribution. This could be as a result of the level of

mechanization of the actors. The revenue realized by artisanal fishermen using traditional fishing

gears will be lower than those using modern fishing gears. Furthermore, it revealed that the market

was concentrated and this means that fresh fish market for capture producers had monopolistic

nature. This empirical results corroborated the finding of Oparinde and Ojo (2014) who reported

a high Gini coefficient value and inequality in the income share of artisanal fish marketers in Ondo

State.

5.6.3.2 Fresh Fish Marketing Node

The findings revealed that there was partial equality in the share of monthly revenue among the

wholesalers and retailers of fresh fish in fish markets in Nigeria-Cameroon-Chad border region.

This implies that both wholesalers and retailers of fresh fish had similar revenue distribution. This

could be as a result of their access to buy directly from the production node. This contradicts the

findings of Adeleke and Afolabi (2012) who reported a high concentration of sellers in fresh fish

markets in Ondo State. This disparity could be as a result of difference in location and the direct

distribution channel from producers to consumers that largely exists in the study area.

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5.6.3.3 Smoked Fish Processing Node

The computed high Gini coefficient revealed the inequality in market share and possibility of

existence of non-competitive behaviour among the processors of smoked fish in the States along

Nigeria-Cameroon-Chad border. This implies that processors engaged in fish processing to

smoked fish are highly concentrated in the fish markets along Nigeria-Cameroon-Chad border.

Yet these processors were highly inefficient in their operations because a large proportion of them

fall within the margin of those making low monthly revenue and the processors making high

revenue in a month contributed a low percentage to the total monthly sales. Contrarily, Sakib et

al. (2016) reported a low Gini index for fish in their study.

5.6.3.4 Smoked Fish Marketing Node

The empirical findings revealed a lesser Gini coefficient for smoked fish retailers, hence their

lower concentration in smoked fish marketing node. The marketing actors both had a fair share of

equality in the distribution of their marketing income and this portrays a fair competition among

the markets of smoked fish along Nigeria-Cameroon-Chad border. The degree of equality is higher

at smoked fish retailing than wholesaling. This implies that the pricing system is more consistent

among the retailers in the marketing node. Similarly, Ayinde et al. (2012) reported that Gini

coefficient in rural areas regarding agriculture was 0.41in Nigeria. Contrarily, Phiri et al. (2013)

reported a concentrated fish market for wholesalers and retailers in their study in Malawi. This

difference in concentration could be as a result of differences in consumer’s preference for fish

products and the prices for processed fish in the two locations.

5.6.3.5 Dried Fish Processing Node

The results revealed a very high Gini coefficient that indicated inequality in marketing income and

possibility of existence of non-competitive behaviour with monopolistic nature among the

processors of dried fish in the States along Nigeria-Cameroon-Chad border. This means there was

a wide gap in the profitability status of the dried fish processors and shows their high level of

inefficiency. Oparinde and Ojo (2014) also reported a very high Gini coefficient index in their

study.

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5.6.3.6 Dried Fish Marketing Node

The Gini coefficient for wholesalers revealed their moderate concentration and the possibility of

existence of non-competitive behaviour with monopolistic nature in dried fish wholesale markets

in Nigeria-Cameroon-Chad border region. This is very similar to the result reported by Ismail et

al. (2014) for dried fish wholesalers in their research. However, the retailers had a low Gini

coefficient value that tended towards equality in the share of monthly revenue among the retailers

of dried fish in fish markets in Nigeria-Cameroon-Chad border region. This could be attributed to

the efficiency of retailers in their pricing system and in fish marketing. Though, this concentration

was not as low as what Garba et al. (2015) reported among retailers in Niger State.

5.6.3.7 Frozen Fish Marketing Node

The computed Gini coefficient indicated a partial equality in the share of monthly revenue among

the wholesalers of frozen fish in fish markets in the States along Nigeria-Cameroon-Chad border.

The concentration of these wholesalers could have been low because of the huge capital and

operating cost required for frozen fish wholesaling enterprise. Similarly, Agom et al. (2012)

examined wholesale frozen fish markets and reported a perfectly competitive market structure.

However, a much lower concentration of frozen fish retailers was observed from the low Gini

coefficient value. The distribution of monthly revenue of frozen fish retailers in fish markets in

Nigeria-Cameroon-Chad border region greatly tended towards equality. This means that the gap

in the revenue made by these retailers was very narrow. Garba et al. (2015) reported a much lower

concentration of retailers in Shea butter market having a greater degree of equality in market share.


The empirical findings revealed a computed high Gini coefficient for fresh fish markets in Nigeria-

Cameroon-Chad border region which signified inequality in market share and possibility of

existence of non-competitive behaviour among the market partcipants in the fresh fish markets.

This finding corroborates the result of Adeleke and Afolabi (2012) who reported high Gini

coefficient for fresh fish markets. Similarly, Irhivben et al. (2015) reported a high level of

inequality in the share of fresh catfish marketers in Oyo State, Nigeria. The departure of the Lorenz

curve from the 45-degree line measured the level of inequitable distribution of market share in

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terms of revenue among the marketing actors in fresh fish markets as shown in figure 4.18. This

supports the findings of Oparinde and Ojo (2014) who reported the presence of inequality in the

income share of artisanal fish marketers.


The computations revealed that smoked fish markets were highly concentrated with a high Gini

coefficient value. This indicated the imperfect low competition and high degree of inequality in

the distribution of market revenue among the marketing actors because of the imperfect market

structure at the concentrated smoked fish markets in the States along Nigeria-Cameroon-Chad

border. This is confirmed from the Lorenz curve for smoked fish markets in Nigeria-Cameroon-

Chad border region in figure 4.19.


The Gini coefficient value was very high for dried fish markets which indicated the non-

competitive imperfect market in the dried fish markets and implied the presence of high

concentration with monopolistic nature of sellers, hence high inequality in the distribution of

market revenue among the marketing actors in dried fish markets in the States along Nigeria-

Cameroon-Chad border. Figure 4.20 shows the greater departure of Lorenz curve from the 45-

degree line to buttress the great degree of inequality in the share of market revenue among the

actors in all the marketing nodes identified in dried fish markets. This is similar to the findings of

Ismail et al. (2014) on dried fish wholesaling and retailing (marketers).


The empirical results revealed the possibility of existence of monopolistic condition in the

imperfect structure of frozen fish markets and inequality in market share among the market

participants in frozen fish markets in Nigeria-Cameroon-Chad border region. Phiri et al. (2013)

reported the exact Gini coefficient value for retailers in their study. The Lorenz curve in figure

4.21 illustrates the level of inequality in market revenue.

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5.6.4 Interpretations of Herfindahl Index


The analysis for Herfindahl index for fresh fish markets comprising of producers, wholesalers and

retailers revealed some level of concentration of sellers and non-monopolistic nature of fresh fish

markets in Nigeria-Cameroon-Chad border region. This suggests that the actors in the fresh fish

marketing nodes jointly control the fresh fish market in keen competition. Similar findings by

Oparinde and Ojo (2014) reported a much lower index among artisanal fish marketers and some

degree of concentration in the market.


The analysis for Herfindahl index for smoked fish markets comprising of processors, wholesalers

and retailers is presented in table 48. The Herfindahl index estimated for smoked fish markets

signifies a greater degree of concentration and moderate competition of sellers in smoked fish

markets in Nigeria-Cameroon-Chad border region. Oluwadare et al. (2009) reported a much lower

index in their study.


Table 49 presents the computations for Herfindahl index for dried fish markets comprising of

processors, wholesalers and retailers. The Herfindahl index estimated for dried fish markets

signifies high degree of concentration and low competition among marketers in dried fish markets

in Nigeria-Cameroon-Chad border region. However, a much lower herfindahl index for marketers

was reported by Oluwadare et al. (2009).


The Herfindahl index estimated was high for frozen fish markets which signifies high degree of

concentration and low competition among frozen fish marketers in fish markets in Nigeria-

Cameroon-Chad border region. This suggests that wholesalers had the highest market power as a

result of their huge market share in the frozen fish markets in the study area. Contrarily, Agom et

245

al. (2012) reported a perfectly competitive frozen fish market with herfindahl index of 0.211 in

Cross River State. This could be because wholesalers had a huge market share in this study.

5.6.4.5 Herfindahl index of Fish Markets in each sampled State

Fresh fish market structure in Adamawa State was perfectly competitive and oligoponistic in

market structure having a low index value. Similarly, Oparinde and Ojo (2014) in their study in

Ondo State, estimated Herfindahl index of 0.05 which implied some degree of concentration.

Smoked fish market structure in Cross River State was monopolistic with high concentration of

sellers and low competition having the highest Herfindahl index across the sampled States. In

Adamawa State, dried fish marketers were highly concentrated in the fish markets and exhibited

low competition in the monopolistic dried fish market structure. Akwa Ibom, Cross River and

Borno States, where frozen fish markets were recorded, had total concentration of sellers

exhibiting complete monopoly as indicated by the estimated Herfindahl index. This contradicts the

finding of Agom et al. (2012) who reported a perfectly competitive market structure for wholesale

frozen fish.

5.6.5 Economies of scale

The results of the linear regression estimates and the relevance of the coefficients of quantities of

fish sold by the marketing participants in the marketing nodes to determining barrier to entry into

fish markets along Nigeria-Cameroon-Chad border are discussed below.

The regression curve for fresh fish marketers (figure 4.22) revealed that at 5% significant level,

47.0% of the total quantity of fish sold by the fresh fish marketers was predicted by the total

marketing cost they incurred. The coefficient of the explanatory variable was a positive value

which implies that there was no scale economy. Therefore, as the quantity of fish sold by the fresh

fish marketing actors increased, their marketing cost increased. Cost of storage and preservation,

extra cost of labour could have contributed to increasing marketing cost as the quantity sold by

fresh fish marketing actors increased. This was no barrier to entry because new entrants into the

fresh fish market could maximize profit at any level of production. Similarly, Suleiman (2007)

reported that there was no barrier to entry into fish markets existed in his study area.

246

Only 31.8% of the total quantity of fish sold by the smoked fish marketers was explained by the

total marketing cost they incurred at 5% significance. The coefficient of the total quantity of

smoked fish sold in a month was positive which revealed that as the quantity of fish sold by the

smoked fish marketing actors increased, their marketing cost increased, as shown in figure 4.23.

The factors that could have increased marketing cost as quantity produced increased could be cost

of transportation, extra cost of labour and processing, additional market space for storage.

However, new entrants are not discouraged from entering this market because they could produce

at their level of initial investment and yet maximize profits and compete with the larger firms in

smoked market. This indicated the absence of economies of scale and presence of ease of entry

into the smoked fish market for new entrants. However, Ismail et al. (2014) reported that there was

barrier to entry in the fish market they studied.

Figure 4.24 revealed that at 5% significance, 30.1% of the total quantity of fish sold by the dried

fish marketers was predicted by the total marketing cost incurred by dried fish marketers. The

positive value for coefficient of the total quantity of dried fish sold in a month indicated that as the

quantity of fish sold by the dried fish marketing actors increased, their marketing cost increased.

Some of the factors that could have contributed to increase in marketing cost as quantity produced

increased could be increased cost of transportation, cost of storage and preservation, additional

market space for storage, extra cost of labour and processing. Therefore, new entrants could

produce at any level feasible and yet maximize profits. This presented an ease of entry into the

dried fish markets along Nigeria-Cameroon-Chad border. This contradicts the findings of Ismail

et al. (2014), who reported a negative coefficient of the quantity of dried fish marketed by

wholesalers and retailers. This contradiction could be because processors, wholesalers and retailers

of dried fish were considered in this analysis and the coefficient of determination differs in these

two analyses.

Observed from the regression curve for frozen fish marketers in figure 4.25, at 5% significant

level, only 40.4% of the total quantity of fish sold by the frozen fish marketers was accounted for

by the total marketing cost they incurred. The coefficient of the explanatory variable was positive

which implies that there were no scale economies and as such no form of barrier to entry into the

frozen fish market. The frozen fish marketers did not have to increase the quantity of fish sold in

order to reduce the cost of marketing and maximize profits. Cost of refrigeration (preservation)

247

could increase as the quantity of frozen fish sold increases. Similarly, Suleiman (2007) reported

the absence of barrier to market entry in his study.

The linear regression estimates (table 4.26) for fresh, smoked and dried fish products sold in Akwa

Ibom State reveals at 5% significance, 61.1%, 61.6% and 99.9% of the total quantities of fresh,

smoked and dried fish, respectively marketed in Akwa Ibom State can be explained by the total

marketing cost incurred by the fish marketers. The positive coefficient of explanatory variable for

fresh, smoked and dried fish sold indicated an increase in the cost of marketing as the quantities

of these forms of fish sold increased. Hence, there was ease of entry to fish markets in Akwa Ibom

and no economies of scale. That is smaller firms could compete with

It can be deduced from table 4.27 that at 5% significance, 58.3% and 68.2% of the total quantities

of fresh and smoked fish respectively marketed in Cross River State can be accounted for by the

total marketing cost incurred by these fish marketers. The coefficient of total quantities of fresh,

smoked and dried fish sold had positive values which signified an increase in the cost of marketing

as the quantities of these forms of fish sold increased and ease of entry into these fish markets. The

negative coefficient of total quantities of frozen fish sold indicated the presence of economies of

scale. This means that as the quantity of frozen fish sold increased in fish markets in Cross River

State, the cost of marketing reduced. This gave preference to larger firms that produced in larger

quantities to maximize profit. This factor was a barrier to new marketing entrants who could not

compete with these larger firms in Cross River State frozen fish market. Similarly, Ismail et al.

(2014) reported the presence of scale economies in their study.

At 5% significance, 38.3%, 26.7% and 66.6% of the total volume of fresh, smoked and dried fish,

respectively can be explained by the total marketing cost incurred by the fish marketers in Benue

State as indicated in table 4.28. The coefficient of explanatory variable for fresh, smoked and dried

fish sold were positive. These positive values indicated the absence of economies of scale and the

ease of entry for new entrants in these fish markets in Benue State. This means there was increase

in the cost of marketing as the quantities of these forms of fish sold increased. This contradicts the

results reached by Ismail et al. (2014) who reported the presence of scale economy in fried fish

markets in Ondo State.

In table 4.29, the linear regression estimates for fish products sold in Taraba State indicated that at

5% significant level, 60.3% and 13.2% of the total marketed quantities of fresh and smoked,

248

respectively can be predicted by the total marketing cost incurred by these fish marketers in Taraba

State. The positive coefficients of explanatory variable for fresh and smoked fish indicated an

increase in the cost of marketing as the quantities of these forms of fish sold increased. Hence,

there was absence of economies of scale and no barrier to entry for new entrants in fresh and

smoked fish markets in Taraba. However, the coefficient of the quantity of dried fish sold was

negative which signified the presence of economies of scale. This corroborates the findings made

by Ismail et al. (2014) that scale economies existed in the wholesale and retail markets of dried

fish. This implies that the cost of marketing reduced as the quantity of dried fish sold increased

and profit was maximized. This could be a form of barrier to entry for new entrants because they

have to produce in large quantities in order to maximize profit and to efficiently compete in the

market.

In Adamawa State, the coefficient of determination (R2) indicated that at 5% significance, 58.2%,

0.7% and 56.5% of the total marketed quantity of fresh, smoked and dried fish, respectively can

be explained by the total marketing cost incurred by the fish marketers in Adamawa State. The

positive coefficient of explanatory variable for fresh, smoked and dried fish sold as observed in

table 4.30 indicated the absence of economies of scale and the presence of ease of entry in these

fish markets in Adamawa State. However, frozen fish had a negative coefficient of explanatory

variable which indicated a reduction in marketing cost as the quantity of frozen fish marketed

increased signifying a barrier to entry into frozen fish market by new entrants.

The linear regression estimates for fresh, smoked and dried fish marketed in Borno State from

table 4.31 reveals the significant (P < 0.05) coefficient of determination (R2) for these forms of

fish. This indicated that at 5% significance, 68.8%, 32.8% and 98.0% of the total marketed quantity

of fresh, smoked and dried fish, respectively can be predicted by the total marketing cost incurred

by these fish marketers in Borno State. The positive coefficient of explanatory variable for fresh,

smoked and dried fish sold indicated the absence of economies of scale and the presence of ease

of entry in these fish markets in Borno State. This was a contradiction to the conclusion reached

by Ismail et al. (2014). This contradiction could be as a result of the inclusion of the quantity of

dried fish sold by processors in Borno State to get the regression estimate for this analysis.

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5.7 Quantities, Costs, Profitability Indices and Marketing Efficiency of Fish Products

5.7.1 Average Monthly Quantities, Costs, Profitability and Marketing Efficiency Indices of

Fish Products Marketed

Fresh fish was the highest quantity of fish sold in a month by the marketing actors, though it had

no significant difference from the average quantity of the other forms of fish marketed in a month

in Nigeria-Cameroon-Chad border region as reported in table 4.32. The significant variation in the

prices of the forms of fish could be as a result of value addition in the marketing nodes. The high

marketing cost for fresh fish implies that the actors marketing fresh fish incurred a high cost for

marketing fresh fish which reduced its marketing efficiency. This is because the production node

for fish is labour intensive. The gross margin and marketing margin of dried fish was the highest

across the forms of fish sold, making it more profitable than the other forms of fish sold, followed

by smoked fish which had the statistically highest efficiency. Similarly, Adebo and Toluwase

(2014) found smoked catfish marketing to be more profitable than fresh catfish in their study.

5.7.2 Average monthly quantities of fish products marketed across the States along Nigeria-


Akwa Ibom had the highest average monthly quantity of fresh fish sold (table 4.33). This could be

as a result of the predominance of fishing activities in the State. Smoked and dried fish were sold

more in Borno State in terms of average quantities per month. This implies the presence of high

intensity of fish processing in that State. Frozen fish was marketed more in Akwa Ibom State. This

could be as a result of the capture fishing in Atlantic Ocean bounding the State. There was no

statistical difference in the buying price of fresh fish but Cross River State had a statistically

highest value for fresh fish selling price in Nigeria-Cameroon-Chad border region as observed in

table 4.34. This could be as a result of the high standard of living in this State. Akwa Ibom State

had the highest average marketing revenue because the quantity of fresh fish sold was highest in

this State. Hence, the marketing margin for fresh fish was highest in Akwa Ibom State. However,

Adamawa State was more efficient in fresh fish marketing because of the low marketing cost

incurred in the State for fresh fish marketing.

250

Adamawa State had the highest average monthly buying and selling price for smoked fish. Borno

State had more sales of smoked fish and the respondents in this State were highly efficient in the

marketing process. The marketing and gross margins for smoked fish was highest in Borno State

(table 4.35). This could mean that smoked fish is the most preferred form of fish in Borno State.

This indicates the profitability and efficiency.

Akwa Ibom State had the highest market value for dried fish per kg in a month. The high marketing

cost for this form of fish in Beune State could be attributed to high cost of transportation. The

profitability and efficiency of dried fish marketing was statistically highest in Borno State and least

in Cross River. Akwa Ibom, Cross River, Adamawa and Borno States are the States where frozen

fish was majorly marketed. The highest selling price of frozen fish was found in Akwa Ibom State

and the marketing in this State was more efficient. Agom et al. (2012) reported a lower marketing

margin for frozen fish in their Study in Cross River State.

5.7.3 Average monthly quantities, costs, profitability indices and marketing efficiency of

fish marketing nodes in Nigeria-Cameroon-Chad border region

As observed in table 4.38, there were significant differences (P<0.05) in the average monthly

quantities, prices, costs, profitability indices and marketing efficiency of fish marketing nodes in

fish markets along Nigeria-Cameroon-Chad border region. Marketers in the marketing node had

the highest buying and selling prices of fish because majority of them employ negotiation to fix

their fish prices. This supports the assertion by Chiwaula et al. (2012) who opined that when buyers

bid for fish, it would result in a more rewarding pricing mechanism for fishers. The high ratio of

variable costs to fixed costs suggests that fish marketing participants in the marketing nodes for

fish trade could easily adjust to market conditions since expenditures on variable inputs constitute

a very high proportion of total cost of production. However, it also implies that changes in the

market price of variable inputs could highly impact the gross margins obtained.

Marketing cost was highest at the production node because of the high cost of labour incurred by

culture producers (fish farmers) producing on a large scale. Marketing node had the higher

purchasing cost because all the quantity of fish they sell are bought from either production node

or processing node. However, as revealed from table 4.38, the marketing node was more efficient

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in fish marketing in Nigeria-Cameroon-Chad border region because the highest average monthly

revenue was realized in this node.

Production node had the lowest marketing margin and gross margin, therefore, the production node

had the least fish marketing profitability. Similarly, Osondu (2015) reported the least marketing

margin for fishermen (production node) among the respondents in their study. Fish processing

node was more profitable because it had the highest mean gross margin, net returns and marketing

margin in a month than the other marketing nodes for fish trade in Nigeria-Cameroon-Chad border

region. Contrarily, in the study of profitability of fisheries enterprise by Dambatta et al. (2016),

capture producers in the production node were found to be profitable.


fresh fish marketing nodes in Nigeria-Cameroon-Chad border region

Culture producers (fishermen) sold the highest average quantity of fresh fish in a month before

they have the capacity to increase their farm production. Retailers sold fresh fish at the highest

selling price since they sell directly to the fish consumers. This is similar to the results of Osondu

(2015), who reported that retailers had the highest marketing price per kilogram of fish sold. The

total marketing cost for retailers was lowest because most retailers sell fish directly to consumers

and at smaller quantities, compared to the other marketing participants. The gross and marketing

margins of wholesalers was greater than the margin of retailers and fish producers. Osondu (2015)

also reported the marketing margin of wholesalers to be highest than the producer’s and retailer’s

marketing margins and the findings of this study corroborates this conclusion. Similarly, Bassey

et al. (2015) reported a higher marketing margin for wholesalers than retailers in their study.

However, as revealed in table 4.39, the efficiency of retailers was the highest for fresh fish

marketing across the marketing nodes indicating their efficient fish pricing system.


smoked fish marketing nodes in Nigeria-Cameroon-Chad border region

Table 4.40 reveals that wholesalers sold the highest average quantity of smoked fish in a month

which implies that they buy smoked fish from more than one processor. However, Madugu and

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Edward (2011) reported the highest quantity of processed fish to be sold by producers-processors

in their study in Adamawa State. Smoked fish processors had the least marketing efficiency in

smoked fish markets in Nigeria-Cameroon-Chad border region. Wholesalers of smoked fish had

the highest profitability and marketing efficiency as deduced from their high marketing

performance in terms of gross and marketing margins. This implies that smoked fish wholesaling

in the study area is very efficient and requires little cost of input and yet yields great output in

terms of revenue.


dried fish marketing nodes in Nigeria-Cameroon-Chad border region

Wholesalers sold the highest average quantity of dried fish in a month, similarly to the smoked

fish marketing system in Nigeria-Cameroon-Chad border as indicated in table 4.41. Wholesalers

had the highest selling price for dried fish, probably a result of purchasing dried fish from various

processors. The profitability indices revealed that dried fish wholesaling was more profitable in

Nigeria-Cameroon-Chad border region. There were significant differences (P<0.05) in the

profitability indices and marketing efficiency of processors, wholesalers and retailers in the

marketing node of dried fish in the study area. The average total monthly revenue of wholesalers

was more than retailers, hence, wholesalers had a higher marketing margin. However, processors

of dried fish were more efficient in dried fish marketing. This contradicts the findings of Bassey

et al. (2013b) who reported a higher marketing margin for retailers than wholesalers in Akwa

Ibom.


frozen fish marketing nodes in Nigeria-Cameroon-Chad border region

Marketing costs of wholesalers was more than the retailers of frozen fish in the study area (table

4.42). The gross margin of wholesalers was statistically higher than the retailers’ and the marketing

margin of wholesalers was higher than the retailers though there was no statistical difference.

Contrarily, Bassey et al. (2015) reported a higher gross margin for retailers than wholesalers in

Akwa Ibom State. In this study, wholesalers sold more than retailers, therefore they had a higher

monthly revenue and hence higher gross margin and marketing efficiency than retailers.

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5.8 Stochastic Production Frontier Model and Technical Inefficiency

The negative coefficient values of the other operational costs consisting of costs of fuel,

fingerlings, feed, drugs, firewood, etc showed that these costs had a negative relationship with the

monthly revenue of the respondents. This means that the monthly revenue of the respondents

increase and their other operational cost reduce. This is expected as the profits made from fish

marketing is largely dependents on these costs. However, increase in the total purchase cost,

marketing cost and depreciated fixed cost had a positive effect on the productivity of the

respondents by increasing their monthly revenue. This could be as a result of expansion in the

scale of operation of the respondents and increased quantity of fish sold, which would have

increased their monthly depreciated fixed cost, purchase cost and marketing cost and yet increased

their monthly revenue.

The signs of the estimated coefficients in the estimated technical inefficiency model for the

respondents have important implications on their technical efficiencies. From the results, the sex,

age and education of the producers did not have significant influence on their technical efficiency.

The positive coefficient of the highest level of educational status attained by fish processors

significantly reduced their efficiency. This is unexpected, as the educational qualification attained

is expected to improve the efficiency of the respondents as reported by Sakib et al., (2016) that

farmers’ product commercialization increased with increase in their level of education. However,

the level of low technology adopted by the fish processors may have resulted in their reduced

efficiency since, variations in technical efficiency may arise from the characteristics of fish farmers

(fish processors) and existing technology as postulated by Giroh et al. (2008). The negative

coefficient of sex implies that this variable enhances the technical efficiency of fish marketers

significantly in Nigeria-Cameroon-Chad border region.

5.9 Trade Flow of Fish Products

This study revealed that trade flow of fish in its different forms (fresh, smoked, dried and frozen)

existed and was carried out within the sampled States (Intra-State) and to other States in the region

(Inter-State) and cross-border trades across the borders in the States along Nigeria-Cameroon-

Chad border. Fresh fish was the highest volume of fish sold in intra-State marketing in terms of

average quantity of fresh fish marketed within the sampled States in a month. Smoked fish

254

marketers realized the highest average monthly revenue made by the fish marketing actors

involved in intra-State trade.

The inter-State trade flow was both inflow from other States in Nigeria into the studied States and

outflow from the studied States to other States in Nigeria. Fresh, smoked and dried fish were traded

in inter-State inflow and fresh fish constituted the largest proportion of this trade. The inter-State

outflow trade had fresh, smoked, dried and frozen fish as the forms of fish sold. However, the bulk

of this trade came from the quantity of smoked fish traded from the sampled States to other

Nigerian States. The highest average monthly revenue made by the marketing actors involved in

inter-State inflow and outflow trades was realized by the dried fish traders.

The intra-regional fish trade was both inflow trade from other neighbouring African Countries

across the Nigeria-Cameroon-Chad border into the studied States and outflow trade from these

sampled States across the Nigeria-Cameroon-Chad border to neighbouring African countries.

Fresh, smoked and dried fish were the forms of fish traded intra-regionally (inflow) into Nigeria

across the Nigeria-Cameroon-Chad border and dried fish constituted the bulk of this trade. Fresh,

smoked and dried fish constituted the intra-regional outflow trade from Nigeria across the

Nigerian-Cameroon-Chad border to neighbouring African Countries. Dried fish had the highest

percentage of average quantity traded in month in the intra-regional outflow trade. The average

monthly revenue made from this trade by dried fish traders constituted the highest percentage

average revenue from inflow and outflow cross border trade made by intra-regional traders in a

month.

5.10 Pattern of fish trade

The pattern of fish trade in the study area was trade within the country and cross border trade to

neighbouring African countries. The business processes operated by the actors in the value chain

include: farm gate sales by the fish farmers; sales at landing sites by the artisanal fishermen;

hawking, neighbourhood store and central market store by the fish processors and marketers. The

general marketing channel or flow for fresh fish was from the producers (both fishermen and fish

farmers) to wholesalers (and sometimes to retailers), then to retailers (and sometimes to

consumers) and then to the final buyers (consumers). The channel for marketing processed fish

255

was from the producers to processors, then to wholesalers and retailers and then to the consumers.

In some cases, the fishermen sold directly to the consumers.

In Ibeno fishing settlement, Akwa Ibom State, the fish caught by the fishermen were processed by

the women in this settlement and sold at their markets to buyers coming from places as far as Abia,

Abuja. Some processors came from Eket to buy fish from this landing site. Sometimes, the

marketers took the fish to Port Harcourt. Buyers came from as far as Abuja, Lagos, Port Harcourt,

Uyo, to Ikang market in Cross River State to purchase fish. Though this market is at the border,

the Cameroonians do not come here to buy fish (from the fishermen) because the water body at

Peninsula is enriched with fisheries resources. Hence, Nigerian fishermen go to Cameroon to fish

and bring the catch to sell in Nigeria. In Benue State, some fish processors and marketers travel to

Adamawa, Taraba, Jigawa, Borno and Kebbi States to buy fish and sell to retailers in the market.

Some dry fish marketers travel to Chad, Cameroon and Niger to buy fish during periods of low

catch in Benue. Fresh fish marketers from Benue State usually go to Taraba and Nasarrawa State

with engine boat to buy fish for distribution to retailers and processors. Some respondents

acknowledged that there was a group of fishermen in Cameroon that catch and sell fish to them,

which they bring to sell in Nigeria. Some processors in Taraba State, after smoking the fish take it

other States like Benue to sell. At Gurin market in Adamawa State close to Cameroon border,

majority of the smoked fish is from Cameroon. The Cameroonians process the fish in their country

and bring to Adamawa State in Nigeria to sell. Fish marketers in Borno State sell smoked fish in

other market locations in Delta (Asaba), Lagos, Enugu and Anambra States.

5.11 Test of Hypotheses

5.11.1 Hypothesis I

The null hypothesis (H0) states that the socio-economic characteristics of the marketing actors have

no effect on their technical efficiency (productivity). From the estimates of technical inefficiency

model, at 5% significance, highest education attained by the processors reduced their technical

efficiencies, whereas, the sex of fish marketers enhanced the efficiency of the fish marketers.

Therefore, the null hypothesis is rejected.

256

5.11.1 Hypothesis II

The null hypothesis (H0) states that there is no significant difference in the profitability and

marketing efficiency of fish marketing across the marketing nodes for fish trade along Nigeria-

Cameroon-Chad border. The marketing profitability and efficiency were measured from the mean

monthly revenue, gross margin, marketing margin and marketing efficiency. From the analysis of

variance results, it was observed that there were significant differences (P<0.05) in the mean

monthly revenue, gross margin, marketing margin and marketing efficiency at the fish marketing

nodes for fish trade along Nigeria-Cameroon-Chad border region. Therefore, this negates and

rejects the null hypothesis that states that there is no significant difference in the profitability and

efficiency of fish marketing across the marketing nodes for fish trade along Nigeria-Cameroon-

Chad border.

5.11.3 Hypothesis III

The null hypothesis states that there is inequality in the share of monthly income among the actors

in the various nodes for fish trade identified in the fish (fresh, smoked, dried and frozen) markets

in the study area. The measure of equality and inequality was analysed using Gini coefficient. The

results in fresh markets showed that there was inequality in the share of monthly revenue among

the culture and capture producers. Therefore, the null hypothesis is accepted and retained.

However, a degree of equality was observed in the share of income among the wholesalers and

retailers and the null hypothesis is rejected.

In smoked fish market, the range of monthly revenue among the processors showed that there was

inequality in the distribution of monthly income and the null hypothesis is accepted and retained.

However, the wholesalers and retailers had a fair share of equality in the distribution of their

monthly income and this negates the null hypothesis, hence H0 is rejected.

The processors in dried fish market had a high degree of inequality in the share of their monthly

income as observed in the computations for Gini coefficient. This supports the null hypothesis

which is retained. In addition, wholesalers of dried fish exhibited inequality in the share of their

monthly income and the null hypothesis is accepted and retained, however, the Gini coefficient

value for retailers revealed equality in the distribution of their monthly income and this negates

the null hypothesis, which is rejected.

257

Wholesalers and retailers in the frozen fish markets along Nigeria-Cameroon-Chad border had a

fair share of equality in the distribution of their monthly income. Therefore, the null hypothesis

for wholesalers and retailers of frozen fish is rejected.

5.11.4 Hypothesis IV

The null hypothesis (H0) states that there is no significant difference in the profitability and

marketing efficiency among the marketing actors in the forms of fish (fresh, smoked, dried and

frozen) markets in Nigeria-Cameroon-Chad border region. In fresh fish market, the analysis of

variance results revealed that there were significant differences (P<0.05) in the mean monthly

revenue, gross margin, marketing margin and marketing efficiency of culture and capture

producers, wholesalers and retailers trading in fresh fish markets in Nigeria-Cameroon-Chad

border region.

In smoked fish market, the analysis of variance results showed that there were significant

differences (P<0.05) in the mean monthly revenue, gross margin, marketing margin and marketing

efficiency of processors, wholesalers and retailers marketing smoked fish along Nigeria-

Cameroon-Chad border.

In dried fish market, it was observed from the analysis of variance results that there were

significant differences (P<0.05) in the mean monthly revenue, gross margin, marketing margin

and marketing efficiency of processors, wholesalers and retailers trading in dried fish markets in

Nigeria-Cameroon-Chad border region.

The analysis of variance results revealed that there were significant differences (P<0.05) in the

mean monthly revenue, gross margin, marketing margin and marketing efficiency of wholesalers

and retailers in frozen fish markets in Nigeria-Cameroon-Chad border region.

Therefore, this negates the null hypothesis that states that there is no significant difference in the

profitability and efficiency among the marketing actors in the forms of fish (fresh, smoked, dried

and frozen) markets in Nigeria-Cameroon-Chad border region.

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CHAPTER SIX

6.0 SUMMARY, CONCLUSION AND RECOMMENDATIONS

This empirical study examined the marketing nodes and structure for fish trade along Nigeria-

Cameroon-Chad border. Based on the result of this study, both fresh and processed fish pass

through various marketing nodes and participants from the point of production to final

consumption. These marketing participants are producers, processors and marketers (wholesalers

and retailers) in the major marketing nodes of production, processing and marketing. Female

respondents dominated the processing and marketing nodes and this is in line with the assertion

that fish purchasing, processing and retailing is the responsibility of females. Majority of the

sampled actors in the marketing nodes for fish trade along Nigeria-Cameroon-Chad border were

married Christians, men and women within the age group of 41 and 50 years, still very productive

in fishing and marketing activities in the study areas. Also, the results gotten from the study

revealed that majority of the respondents had just secondary school education which infers that the

actors in the fish marketing nodes have the ability to read and write and make decisions that will

expand their businesses and improve their livelihoods. However, the marketing actors may find it

difficult to expand their business since majority of them depended on personal savings and

cooperatives societies where small amount of capital could be raised.

The empirical findings from the herfindahl indices revealed that fresh fish market in Adamawa

State was perfectly competitive and exhibiting oligopony. Smoked fish market structure in Cross

River State was monopolistic having high sellers’ concentration. Low competition and monopoly

was observed in the dried fish market in Adamawa State. In addition, the frozen fish markets in

Akwa Ibom, Cross River and Borno States exhibited complete monopoly as indicated from the

herfindahl index of 1.00. Gini coefficient was estimated for actors in fresh fish production node

(0.63, 0.53) and marketing node (0.43, 0.43); smoked fish processing node (0.68) and marketing

node (0.46, 0.39); dried fish processing node (0.69) and marketing node (0.51, 0.34) and frozen

fish marketing node (0.36, 0.25). The linear regression coefficient was positive for fresh, smoked

and dried fish products marketed in the States along Nigeria-Cameroon-Chad border, except for

dried fish market in Taraba State and frozen fish markets in Cross River and Adamawa States.

259

The processing node had the highest gross margin (₦371559.91±282965.56) and marketing

margin (₦405394.09±392255.64), connoting high profitability in the fish processing node.

Whereas, the marketing node had the highest marketing efficiency of 87.69±84.86 signifying the

most efficient node for fish marketing in Nigeria-Cameroon-Chad border region. Wholesalers had

the highest gross and marketing margin for fresh (N415041.28±219709.11 and

N494004.83±213846.36), smoked (N612603.13±346832.46 and N634383.13±345735.93), dried

(N854634.17±668429.17 and N955471.66±712788.38) and frozen (N451898.25±354537.06 and

N479464.91±361480.47) fish sold. The wholesalers were most efficient with the highest

marketing efficiency of in smoked (159.72±99.33) and frozen (59.01±16.56) fish markets.

Retailers and processors were most efficient in fresh (26.56±21.89) and dried (55.50±52.11) fish

markets.

The pattern of fish trade in the study area is trade within the country and cross border trade to

neighbouring African countries. Fresh fish (564.13±552.27kg) was the highest volume of fish sold

in intra-State marketing whereas, smoked fish marketers (N893906.72±878026.54) realized the

highest average monthly revenue made by the fish marketing actors involved in intra-State trade.

The bulk of inter-State inflow and outflow trade came from the quantity of fresh

(1250.64±703.53kg and 1719.44±638.63kg, respectively) fish trade between the sampled States

and other Nigerian States. The highest average monthly revenue made by the marketing actors

involved in inter-State inflow and outflow trades was realized by the dried fish traders

(N1140750.00±455023.21 and N1649045.26±1034956.41, respectively). Dried fish

(2098.00±306.88kg and 2205.11±987.43kg) constituted the bulk of fish traded intra-regionally in

both inflow and outflow trade across the Nigerian-Cameroon-Chad border to neighbouring African

Countries. The average monthly revenue made from this trade by dried fish traders

(N3649800.00±240345.59 and N3317327.74±2302822.44) constituted the highest percentage

average revenue from inflow and outflow cross border trade made by intra-regional traders in a

month.

Therefore, it can be concluded that the respondents in this study were generally middle aged men

and women with moderate household sizes and had formal education that gave them the ability to

make wise decisions that will improve their livelihoods. The processing node is the most profitable

and the marketing node is the most efficient node of the fish marketing nodes identified in Nigeria-

260

Cameroon-Chad border region. Wholesalers had the highest profitability for all the forms of fish

sold were most efficient in smoked and frozen fish markets. Retailers and processors were most

efficient in fresh and dried fish markets. The measures of market concentration revealed an

imperfect market structure, high concentration and some degree of competition in the industry,

especially in fresh, smoked and dried fish markets. Partial inequality and fair equality was

observed in the share of the market revenue (income) among the marketing participants in each of

the various marketing nodes identified for fish trade in fresh, smoked, dried and frozen fish markets

along Nigeria-Cameroon-Chad border. There existed free market entry for new entrants to

effectively compete in the fish markets, except in dried fish market in Taraba State and frozen fish

markets in Cross River and Adamawa States because of the presence of economies of scale. Hence,

people are advised to go into fish marketing being a profitable enterprise in order to make a living.

The test of hypothesis revealed that there were significant differences (P<0.05) in the profitability

and marketing efficiency across the marketing nodes and among the marketing actors involved in

fish trade in Nigeria-Cameroon-Chad border region.

It is pertinent to recommend the following based on these findings:

Policies that will guarantee fish sale, price stability and improvement in infrastructural

facilities should be put in place. This will go a long way to further increase the economic

returns from fish marketing in the study area in particular and in the nation as a whole. This

will also make the enterprise attractive to potential fish producers, processors and

marketers and make the market perfectly competitive.

Fish marketing actors should be encouraged to participate in intra-regional fish trade

following the due process of registration and certification in order to increase foreign

exchange earnings.

Efforts should be made to train processors and marketers on efficient fish processing and

storage techniques to improve the quality of processed fish handled by fish marketers,

Attainment of such knowledge could help to reduce the level of losses and improve profit.

The fish producers, processors and marketers should be encouraged to join cooperatives.

This will create an avenue to help members collectively through assistance such as loans,

subsidized fishing inputs and other benefits from the cooperative society.

261

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FISH TRADE RESEARCH QUESTIONNAIRE

Ref no: ………//…………

Date of Interview: ………………………………………….………………………………..

Name of Enumerator: ………………………………………………………………..………

State: …………………………………………………………………………………………

Local Government Area (Residence): ………………………………………………............

Name of Community: ……………………………………………………………………….

Location of actor GPS: N0 ………….…….…. E0 …….……………..

Dear correspondent,

I am a postgraduate student of the University of Ibadan. This data I collect will be used for research

purposes; to address the problem of data gap in fish trade and help provide policymakers with

information on fish trade’s contribution to national development and come up with

recommendations to improve benefits from fish trade in the country, region, and Africa as a whole.

I hope that you will be free to provide me with accurate data and information.

Thank you for your kind cooperation.

Section A: Demographics and Socio-economic Characteristics

1. Age: ______________________ years

2. Sex: a) Male b) Female

3. Marital Status: a) Single b) Married c) Divorced d) Widowed

4. Religion: a) Christianity b) Muslim c) Traditionalist e) Others

5. Household head: a) Yes b) No

6. Household size: Male ____________ Female _____________

7. State of Origin: ____________________________________________

8. Highest Education: a) Primary b) Secondary c) Tertiary

d) Qu’ranic e) Specify others, _____________________

[Type here]

277

9. a. Which of the following is your occupation? a) Producer b) Processor

c) Marketer d) Consumer e) Input supplier

b. If a producer, which of these do you operate? a) Culture b) Capture

c) Both

c. What is percentage of activities in Culture ____________ and Capture _____________

10. Other source(s) of income:

a. _______________________________________

b. _______________________________________

c. _______________________________________

d. _______________________________________

e. _______________________________________

Section B: Location

11. Country: __________________________________________

12. Geopolitical zone: ___________________________________

13. ADP Zone (If applicable): __________________________________________________

14. Group head (if applicable) _________________________ Phone number: ____________

15. Village (if applicable) _____________________________________________________

Section C: Fishermen/ Fish farmer operation

16. Water body: a) Freshwater b) Brackish water c) Marine

17. Name of the water body you carry out your fishing activities: _______________________

18. Season/ Months of the year you fish: __________________________________________

19. Landing site: _____________________________________________________________

20. Type(s) of fishing gear and crafts/ production facilities (earthen pond, concrete tanks,

plastic tanks, troughs) used:

a. _______________________________________

b. _______________________________________

c. _______________________________________

d. _______________________________________

e. _______________________________________

f. _______________________________________

g. _______________________________________

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278

21. List all your source(s) of fund (could be government, loans from commercial banks,

microfinance banks, community banks, cooperatives, personal savings, inheritance, gifts,

money lender, etc). Rank in order of preference.

a. _______________________________________

b. _______________________________________

c. _______________________________________

d. _______________________________________

e. _______________________________________

f. _______________________________________

22. Species, quantity and seasonality of fish catch/ cultured fish;

S/N Scientific and local name of fish

species

Weight/Quantity Season of catch

Section D: Market structure

23. Market location: __________________________________________________________

24. Name of market: _________________________________________________________

25. What form (s) of fish do you sell? a) Fresh/Live b) Smoked c) Dried

d) Frozen e) Spiced f) Others (specify) ______________________

26. At what class of market do you operate? a) Producer b) Processor

c) Wholesaler d) Retailer e) Consumer

27. Which business process do you operate? a) Hawker b) Neighbourhood store

c) Central market store e) Cold room f) Others __________________

28. For how long have you been selling fish? a) Less than 1 year b) 1-5years

c) 6-10 years d)11-15 years e) More than 15 years

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279

29. How is fish price determined in this market? a) Fixed b) Negotiated

c) Controlled by some value chain actors d) Others, specify __________

30. What are the factors that determine fish price in this market? …………………………….

………………………………………………………………………………………………

31. Who are the actors in the value chain that influence the prices of fish/fish products?

………………………………………………………………………………………………

………………………………………………………………………………………………

32. How do they do this? ………………………………………………………………………

33. Is the price of your fish determined by a time of the year? a) Yes b) No

34. At which months of the year is the fish more expensive? ……………………………..…..

35. For how long have you been marketing fish in this market? …………………….

months/years

36. At which other market(s) do you sell your fish? ………………………………………….

37. At what time of the year do you sell more? …………………………………………….….

38. In which of the markets do you sell more and make gain? ……………………………..…

39. Give reasons to your response above …………………………….………………..…..….

……………………………………………………………………………………………...

40. Do you belong to any fish marketers’ association? a) Yes b) No

41. If yes, how many fish marketers’ association do you belong to? .........................................

42. For how many years have you been a member? ………………………………………….

43. What position(s) do you hold in the association? …………………..………..…………….

44. Are you a member of any other association? a) Yes b) No

Section E: Fish Marketing Nodes

45. Who do you usually buy your fish from (main suppliers)? a) Fish farmers

b) Fishermen c) Frozen fish distributor d) Fish processors

e) Other fish traders

46. Where do you usually buy your fish from? a) Fish farms b) Landing sites

c) Cold rooms d) Processing plant e) Other markets

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280

47. Who do you sell your fish to (main buyers)? a) Wholesalers b) Distributors

c) Retailers d) Processors e) Consumers

48. What do you use in transporting your fish to this market? a) Trekking

b) Animal c) Bicycle d) Motor cycle e) Pick-up van

f) Lorry g) Train h) Others, specify _______________________

49. Which of these modules do you use to sell your fish? a) Basket b) Bags

c) Carton d) Pieces e) Kilogram

f) Please specify others ______________________________________________

50. Location and quantity of fish bought at each marketing node; fill the table as appropriate

Marketing

nodes

Location Weight of fish purchased (by module used) Value of fish

purchased

(N)

States in

Nigeria

Outside

Nigeria

(Country)

Kg Carton Bag Basket Local

measure

Fish farmer

Fishermen

Fish

processors

Cold room/

freezers

distributors

Fish traders

Other

distributors

Section F: Distribution and marketing

51. Who are the buyers of your fish? a) Wholesalers b) Retailers

c) Processors d) Consumers

52. Do you have peak and low periods of sale? a) Yes b) No

53. a. Peak period: From ___________________ To ______________________

b. Low period: From ____________________ To ______________________

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281

54. Please fill in the species, quantity and costs of fish purchased (from the last purchase);

Fish species Weight (by module used) Price (N)


measure

55. What are the species, weight and price (N) of fish sold? (From the last sales)

Scientific and Local name of

Fish species

Weight (by module used) Price (N)


measure

56. What form of fish do your buyers purchase? Tick as appropriate

Buyers What do they purchase?

Fresh Dried Smoked Frozen Others

(Specify)

Wholesalers

Retailers

Processors

Consumers

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282

Instruction to interviewer: Please clearly define and explain the terms to the interviewee for which you are collecting data. That is;

‘Capital costs’, ‘operational costs’ and ‘revenue’ before undertaking the interview on each.

57. Capital costs1

Items* Year &

month of

purchase

Expected

lifespan

(years)

Cost (at time of purchase) Source of capital (Tick more than one option where applicable for each item)

Local

currency

US $

equivalent

Government Private sector

(E.g. bank)

Self (E.g. savings) Cooperatives Others** (pls

mention)

Total

1Capital costs are fixed, one-off expenses incurred to purchase equipment required to bring a project to commercially operational status.

*Items such as buildings, generators, smoking kiln, vehicles, refrigerators, canoe, outboard engines (include capacity and model), fishing gears and

crafts, earthen ponds, concrete tanks, plastic tanks, reservoirs, drag net, etc.

**Other sources such as gifts from family or friend, rented, inherited or money lender.

Banks could be community banks, microfinance banks, commercial banks, etc.

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283

58. Operational costs2

2Operational costs are the day-to-day expenses required to run a business

For Fish farmers, operational items could be fingerlings, juveniles, fish feed, drugs, etc.

For Fishermen, operation items could be fuel, cost of maintenance

Notes

For Fishers, table could be adapted to add a column on length of fishing time for current/last fishing trip/cycle

For Fish farmers, table could be adapted to add a column on length of time for current/last production cycle

For Traders/processors, table could be adapted to include length of time it took to gather enough fish to take to the market, length of time for

transportation of consignment, and length of time to sell consignment for current/last transaction/cycle.

For Retailers, table could be adapted to add a column record length of time it took to sell current/last consignment

Item Source Cost for current transaction

(business cycle)

Cost for last transaction

(business cycle)

Cost per month Length of time

Local

currency

US $ equivalent Local

currency

US $

equivalent

Local

currency

US $

equivalent

Total

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284

59. Revenue costs3

Revenue

(Fish type)

Source

Destination

of fish

(Buyer)

Price/kg Volume

(kg)

Revenue from current

transaction (business

cycle)

Revenue from last

transaction (business

cycle)

Total revenue

for month

3Revenue is the total amount of money a business receives from conducting business. Revenue is the ‘gross income’ from which costs

(operational and Capital equipment depreciation) are subtracted to determine net income (profit).

Fish types are the species and form of fish (dried, fresh, smoked, frozen, spiced, etc)

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285

60. From which of these private sectors do you obtain your loan? a) Family or friends

b) Money lender c) Community bank d) Microfinance bank

e) Commercial bank f) Cooperatives g) Others ______________

61. What are the criteria (collateral) for obtaining the loan and payment? Indicate the interest

rate (i.e. percentage) _______________________________________________________

________________________________________________________________________

62. Who determines the price of capital inputs? (E.g. fixed by government, free market, etc.)

________________________________________________________________________

________________________________________________________________________

63. What are the main problems you encounter around the issue of capital investment? List

them in the order of severity (E.g. lack of credit, cost of equipment, import duties,

availability of equipment, etc.)

a. _________________________________________________________

b. _________________________________________________________

c. _________________________________________________________

d. _________________________________________________________

e. _________________________________________________________

64. Who determines the price of operational inputs? (E.g. fixed by government, free market,

etc.)

_______________________________________________________________

_______________________________________________________________

65. What are the main problems you encounter around the issue of operational costs? List them

in the order of severity (e.g. for fishers it could be variability in fuel price, for traders it be

accommodation while waiting for fish, for retailers it could cost of storage, etc.)

a. _________________________________________________________

b. _________________________________________________________

c. _________________________________________________________

d. _________________________________________________________

e. _________________________________________________________

66. Are there any problems around the issue of revenue from your business that you encounter?

List them in the order of severity (E.g. lack of banks and thus dangers of being robbed,

variability in selling price, lack of savings culture, etc.)

a. _________________________________________________________

b. _________________________________________________________

c. _________________________________________________________

d. _________________________________________________________

e. _________________________________________________________

[Type here]

286

67. In which of these months are you in operation?

* To reperesent low operation

** To represent medium operation

*** To represent high operation

Please tick as appropriate. Note: 1-12 represents January to December

1 2 3 4 5 6 7 8 9 10 11 12

68. What are the challenges of fish business and the possible solutions?

Problems/issues Suggested possible solutions

Problems such as water availability, electricity supply, transportation/ road condition, corruption, storage,

land accessibility, purchase of fishing gears, credit accessibility, man power, others.

Section G: Informal Cross Border Trade (ICBT)

69. Do you send fish to your friends/relatives outside the country? a) Yes b) No

70. If yes, how do you do this? ________________________________________

_______________________________________________________________

71. Which of the country(s) abroad to you send fish to? _____________________

72. Is the sent fish for sale or consumption? ______________________________

73. How often do you send fish abroad to your friends and relatives? a) Daily

b) Weekly c) Bi-weekly d) Monthly e) Bi-monthly

e) Others, pls specify ____________________

74. Do you export fish out of the country for sale? a) Yes b) No

[Type here]

287

75. Do you pay any dues at the borders/airports? a) Yes b) No

76. If yes, how much do you pay per kilogram of fish transported? N____________________

77. What are the species of fish you export out of the country?

a. _________________________________________________________

b. _________________________________________________________

c. _________________________________________________________

d. _________________________________________________________

e. _________________________________________________________

78. Species, weight and price (N) of fish traded out of the country

S/N Scientific and local name of fish species Weight (kg) Price (N)

79. Species, volume and price of fish imported into the country

S/N Scientific and local name of fish species Weight (kg) Price (N)

[Type here]

288

SECTION H: Other Marketing Costs

80. Do you have your own means of transportation? a) Yes b) No

81. If yes, indicate the form and fill the table as appropriate;

Forms Number Year of

acquisition

Cost of

Acquisition

(N)

Expected

life span

(years)

Maintenance cost (N)

Repairs/

month

Fuelling/

week

Other

costs

Trekking

Animal

Bicycle

Motor bike

Pick-up van

Lorry

Bus

82. Indicate the source, distance travelled and running costs;

83. What are the materials you use to package your fish for sales? _______________________

________________________________________________________________________

84. What is the cost of packaging? N _____________________________________________

Sources Time

taken

(hours)

Distance

travelled

(km)

Form of transportation and operational cost (N)

By head

(trekking)

Animal Bicycle Motor

bike

Pick-up

van

Bus Lorry Train

From farm to market/ store

From landing site to

market/ store

From coldroom to market

From processor to store

[Type here]

289

85. What are the other marketing activities you carry out and the costs?

Marketing activity Costs (N)

………………………………….. …………………………………

………………………………….. …………………………………

………………………………….. …………………………………

………………………………….. …………………………………

………………………………….. …………………………………

………………………………….. ………………………………….

Enumerator’s Phone Number: ___________________________

Duration of answering the questionnaire: Time Started_______ Time Ended_______

________________________________ ___________________________________

SIGN DATE

This is the end of the questionnaire

Thank you for your time and wish you a very nice day.

THANK YOU FOR YOUR TIME

[Type here]

290

APPENDIX 2

Fishermen sorting their harvest of crayfish at Iwuo Okpom landing site in Ibeno fishing

settlement, Akwa Ibom State

[Type here]

291

APPENDIX 3

Group photograph with fishermen and members of the Artisan Fishermen Association of

Nigeria (ARFAN) in Akwa Ibom State

[Type here]

292

APPENDIX 4

Fish marketers in Gurin market, Adamawa State

[Type here]

293

APPENDIX 5

Fishermen and fish buyers in Bakassi, Cross River State

Date post:	26-Sep-2020
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