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Academic year 2010-2011
An Analysis of Consumption Demand Elasticity and
Supply Response of Major Foodgrains in
Bangladesh
ALAM, Md. Akhtarul
Promoter: Prof. Dr. Dr. h.c. Harald Von Witzke
Co-promoter: PD Dr. Christian Franke
Thesis submitted in partial fulfilment of the requirements
for the joint academic degree of International Master of Science in Rural Development from Ghent University
(Belgium), Agrocampus Ouest (France), Humboldt University of Berlin (Germany), Slovak University of
Agriculture in Nitra (Slovakia) and University of Pisa (Italy) in collaboration with Wageningen University (The
Netherlands),
This thesis was elaborated and defended at Humboldt University of Berlin within the framework of the
European Erasmus Mundus Programme ―Erasmus Mundus International Master of Science in Rural
Development " (Course N° 2004-0018/001- FRAME MUNB123
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Certification
This is an unpublished M.Sc. thesis and is not prepared for further distribution. The author
and promoter give the permission to use this thesis for consultation and to copy parts of it for
personal use. Every other use is subject to the copyright laws; more specifically the source
must be extensively specified when using results from this thesis.
The promoter(s) The author
Prof. Dr. Dr. h.c. Harald Von Witzke Md. Akhtarul Alam
Thesis online access release
I hereby authorize the IMRD secretariat to make this thesis available on line on the
IMRD website.
The Author
Md. Ahtarul Alam
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ACKNOWLEDGEMENT
First I would like express my praise to almighty Allah, who is merciful and kind enough; give soul,
physical ability and knowledge to conduct this study. I would like to express my deepest and sincere
gratitude, profound regards and indebtedness to my thesis promoter Dr.Dr. h.c. Harald Von Witzke,
Professor of International Agricultural Trade and Development, Department of Agricultural
Economics, Faculty of Agriculture and Horticulture, Humboldt University, Berlin for his excellent
supervision, constructive criticism, scholastic guidance and valuable suggestions to complete the
research work.
I would like to express sincere appreciation and gratefulness to my reverend teacher and co-promoter
PD Dr. Christian Franke, International Agricultural Trade and Development, Humboldt University,
Berlin for cordial co-operation for conceptualizing econometric model and analysis the data. His
supportive suggestions and constructive criticism helped me to carrying out the study.
Sincere appreciations are due to my respected teacher Dr. Mohammad Jahangir Alam and Md. Fakir
Azmal Huda, Faculty of Agricultural Economics and Rural Sociology, Bangladesh Agricultural
University for their time to time supportive perception and encouragement to complete the study.
I would like to acknowledge for the financial and logistic support by the European Union through
Erasmus Mundus, especially to the Professor Guide Van Huylenbroeck, for whose the Master’s
program was made possible. Thanks are also extended to Mrs Rentate Judis and all the staffs of
IMRD secretariat for their assistance during the study time and also thanks to my IMRD friends
namely, Bhavya, Nevena, Kanchan, Xiaoxi, LuYu ,Elizabethi, Jan and all of those whose name could
not be mention but whose company makes my stay in Europe much more happy and comfortable.
Extended thanks to Ripon Kumar Mondal, Lecture, Shre-bangla Agricultural University, Bangladesh,
who helped for getting necessary data from different government official required for the study.
Lastly, I would like to express my deepest, boundless gratitude and indebtedness to beloved parents,
brother and sisters, whose affections, inspiration and encouragement always inspire me and paved
the way to higher education and brought me to this position.
Md. Akhtarul Alam
Berlin, August 2011
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Abstract
Foodgrains are the main staple food in Bangladesh. Among all grains rice and wheat
comprises above 90 percent of total food consumption. After green revolution in Asia and
trade liberalization in 1990s Bangladesh has achieved impressive growth in foodgrain
production, especially rice production. The study estimates the consumption demand
elasticity and supply response of rice and wheat in Bangladesh. The study is mainly
comprises in two section, first section one is to discusses food consumption pattern and food
grain demand estimation by using LA/AIDS model for the period 1980 to 2006. Second
section is discusses the growth rate of area, production and yield of rice and wheat, and the
supply response of rice and wheat were estimated using co integration approach incorporate
with Nerlovian partial adjustment model for the period 1980 to 2009. The study based on
secondary data from BBS and FAOSTAT online database, from different published and
unpublished sources. Before estimates the foodgrain demand different statistical tests were
conducted to test the restriction of demand theory. Since the study used yearly time series
data, thus the unit root test has been done by ADF test for concluding about the stationary of
data and the order of integration. Structural stability of data, adding-up, homogeneity and
symmetry restrictions of demand theory were tested. The result of ADF test indicates that all
the series are stationary after first order difference. The system Wald test of linear
homogeneity and symmetry showed that the estimated parameters of the model satisfied the
null hypothesis of valid linear homogeneity and symmetry restriction of demand theory.
Finally the LA/AIDS were estimated imposing homogeneity and symmetry restriction by
means of SUR method. The coefficient of real expenditure for rice was negative, which
indicates rice is a necessity good in Bangladesh. The expenditure elasticity for rice was 0.91,
while for wheat was 1.48. All the Marshallian own price elasticities were negative sign,
which satisfied the law of demand. The own price elasticity for rice was -0.81 and for wheat
was -0.48. The sign of Hicksian own-price elasticities were also negative. Hicksian
compensated cross price elasticity for rice with wheat price was 0.03 and for wheat with the
changes of rice price was 0.20. For the supply response analysis, the ADF test results showed
that all the variables of supply response function are stationary after first order difference.
Then, the Engle and Granger con-integration test were conducted to test the existence of
long-run equilibrium among the variables of the rice output response function. The results
showed that there are no unique long-run equilibrium relationships. Thus the study used first
order difference form of the variables to estimate supply response with respect to price and
non-price factors. The coefficients of real price and irrigated area in rice output response
model were positive and statistically significant, which indicates the positive influence of
these variables to increase rice production. For wheat area response model the coefficient of
relative price was negative, which indicates the inverse relation with area, while the
coefficient of yield was 0.18 and statistically significant, which indicating the supply of area
increases with the increase of yield. Thus, for rice effective price and irrigation water policy
may increase the output supply. Finally, some recommendation and further research
indications are made based on the findings of the study.
Key words: ADF, LA/AIDS, SUR, Demand elasticity and Supply response
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TABLE OF CONTENTS
Title Page
No
Acknowledgement…………………………………………………………. ii
Abstract…………………………………………………………………….. iii
Table of contents…………………………………………………………… iv
List of tables………………………………………………………………… vi
List of appendix tables……………………………………………………… vii
List of figures………………………………………………………………. viii
List of abbreviations……………………………………………………….. ix
1 Introduction……………………………………………………………….. 1
1.1 Back ground of the study………………………………………………. 1
1.2 Statement of the problem………………………………………………. 2
1.3 Research question………………………………………………………. 4
1.4 Objectives of the study…………………………………………………. 5
1.5 Outline/ framework of the thesis……………………………………….. 5
2 Foodgrains in the economy of Bangladesh ……………………………… 6
2.1 Agriculture sector in the economy of Bangladesh……………………. 6
2.2 Importance of foodgrain ……………………………………………… 9
2.2.1 Domestic foodgrain production…………………………………. 11
2.2.2 Import of foodgrain…………………………………………….. 11
2.2.3 Foodgrain consumption…………………………………………. 12
2.2.4 Food gap…………………………………………………………. 12
2.3 Food policy……………………………………………………………... 13
3 Theoretical concepts and empirical review……………………………… 15
3.1 Demand analysis………………………………………………………... 15
3.1.1. Almost Ideal Demand System…………………………………… 17
3.1.2 Studies on demand system……………………………………….. 19
3.2 Supply response analysis……………………………………………….. 25
3.2.1 Empirical studies on supply analysis…………………………….. 28
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4 Methodology……………………………………………………………….. 32
4.1 Data source…………………………………………………………….. 32
4.2 Empirical model for consumption demand……………………………. 32
4.2.1 Variables to be included in the model…………………………… 33
4.2.2 Relevant statistical tests of the model…………………………… 33
4.2.2.1 Test for Unit roots………………………………………... 33
4.2.2.2. Test for Homogeneity and Symmetry…………………… 34
4.3 Analytical technique for supply response analysis……………………... 34
4.3.1. Growth rate analysis……………………………………………. 34
4.3.2 Supply response analysis………………………………………… 35
4.3.2.1 Description of the variables to be used in the model…….. 36
5 Results and discussion……………………………………………………. 37
5.1 Food consumption pattern and food grain demand elasticity…………... 37
5.1.1 Food consumption pattern……………………………………….. 37
5.1.2 Changes in food consumption……………………………………. 38
5.1.3 Almost Ideal Demand System for foodgrain in Bangladesh…….. 39
5.1.3.1 Univariate properties of data……………………………... 40
5.1.3.2 Structural stability of data……………………………….. 41
5.1.3.3 Homogeneity and Symmetry test………………………… 43
5.1.3.4 Estimated elasticities……………………………………... 45
5.2 Supply response analysis of foodgrain production in Bangladesh…….. 46
5.2.1 Growth rate analysis……………………………………………... 47
5.2.2 Supply response analysis………………………………………… 48
5.2.2.1 Unit root tests…………………………………………….. 49
5.2.2.2 Empirical results of the rice supply response model……... 50
5.2.2.3 Empirical results of the wheat area response model……… 52
6 Summary, Conclusion and policy implication…………………………... 55
6.1 Summary of the study……………………………………………… 55
6.2 Conclusion and policy implication………………………………… 61
6.3 Limitations and possibility for further research……………………. 62
References…………………………………………………………………. 63
Appendices………………………………………………………………… 77
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List of tables
Table
Number
Title of the table Page
No.
Table 2.1 Agricultural sub-sectoral share of GDP (%) at constant price (base
year 1995-96)………………………………………………………
7
Table 2.2 Agricultural sub-sectoral growth rate of GDP at constant price
(base year 1995-1996)……………………………………………...
8
Table 2.3 Area, production and yield of rice and wheat in Bangladesh …….. 10
Table 2.4 Import of food grain (rice and wheat) for the period 1971/72-
2008/09……………………………………………………………
12
Table 3.1 Selected examples of AIDS model for demand analysis in
different countries…………………………………………………
23
Table 3.2 Summary of estimates elasticities in previous studies for different
time period…………………………………………………………
29
Table 5.1 ADF test results for the budget share, consumer price and total
expenditure…………………………………………………………
40
Table 5.2 Systems Wald test for Homogeneity and Symmetry……………… 43
Table 5.3 Parameter estimates of an LA/AIDS for food grain demand in
Bangladesh ………………………………………………………...
44
Table 5.4 Marshallian price and expenditure elasticities…………………….. 45
Table 5.5 Hicksian compensated price elasticities…………………………… 46
Table 5.6 Annual growth rate of area, production and yield of rice and wheat
in Bangladesh………………………………………………………
47
Table 5.7 ADF test results for the variables of supply response analysis……. 49
Table 5.8 Estimates of rice output response in Bangladesh …………………. 51
Table 5.9 Diagnostic tests for rice output response function………………… 52
Table 5.10 Estimates of area response of wheat in Bangladesh……………….. 53
Table 5.11 Diagnostic tests of estimated wheat response function …………… 54
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List of appendix tables
Table
Number
Title of the table Page
No.
Table A5.1 Changes in average per capita per day quantity of food (gram)
intake by food items…………………………………………………
77
Table A5.2 Changes in per capita consumption of rice and wheat in rural and
urban area…………………………………………………………….
77
Table A5.3 Per capita consumption of rice and wheat by different income
groups in rural and urban area………………………………………..
77
Table A5.4 Changes in average per capita per day protein (gram) intake by
different food items…………………………………………………..
78
Table A5.5 Co-integration test for consumer demand series…………………….. 78
Table A5.6 Population growth rate over the period……………………………… 79
Table A5.7 Engle-Granger test for long-run equilibrium co integration of rice
output response model………………………………………………..
79
Table A5.8 Engle-Granger test for long-run equilibrium co integration of wheat
area response model………………………………………………….
80
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List of figures
Figure
Number
Title of the figure Page
No.
Figure 2.1 Food grain balance, net production, import and gap over the period
2005-2010……………………………………………………………..
13
Figure 5.1 Monthly food expenditure share in Bangladesh in 2005……………. 37
Figure 5.2 Per capita per day calorie (gram) intake by food items……………… 38
Figure 5.3 Annual per capita consumption of rice and wheat for the period 1980-
2006……………………………………………………………………
39
Figure 5.4 Residual plot of rice share equation in two standard error bands……. 42
Figure 5.5 Residual plot of wheat share equation in two standard error bands….. 42
Figure 5.6 Total food grain growth rate and population growth rate over the
period 1971/72-2008/09……………………………………………….
48
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List of abbreviations
ADF Augmented Dickey-Fuller
AIDS Almost Ideal Demand System
BBS Bangladesh Bureau of Statistics
BER Bangladesh Economic Review
DW Durbin-Watson
ECM Error correction model
FAO Food and Agriculture Organization
FAOSTAT Food and Agriculture Organization Statistics
FPMU Food policy monitoring unit
GDP Gross Domestic Product
HIES Household Income and Expenditure Survey
HYV High yielding varieties
IMF International Monetary Fund
LA/ADIS Linear approximate Almost Ideal Demand System
LES Linear Expenditure System
LM Lagrange multiplier
LR Likelihood ratio
MOA Ministry of Agriculture
OLS Ordinary Least Square
PIGLOG Price Independent Log
PP Philips-Perron
QUADIS Quadratic Almost Ideal Demand System
SUR Seemingly Unrelated Regression
UR Uruguay Round
WTO World Trade Organization
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CHAPTER I
INTRODUCTION
1.1 Background of the study
The economy of Bangladesh is mainly dominated by the agriculture sector since the
independence in 1971. It is the largest and most significant source for providing food, income
generation and employment opportunities for the rural people in Bangladesh. It is also one of
the important sources for economic development of the country. Thus, the productivity,
growth and efficiency of this sector are the central phenomenon to any economic
development planning of the country. This sector is dominated by food grains production.
Although the agriculture sector of Bangladesh has experienced a great deal of disorder due to
natural calamities (e.g. Flood, drought, Cyclone, Sidar etc.) and acute governance problems
but the growth in food grain production in Bangladesh, specially rice has outpaced
population growth largely, because of the spread of green revolution technology in Asia
through input market liberalization (Islam, 2010). After trade liberalization at ends of the
1990s, first time the food grain production exceeded the target requirement in Bangladesh.
But due to rapid growth of population food grain mainly wheat is necessary to import to meet
the chronic shortage of food deficit. Agriculture has also the major sources of raw material
for the domestic industry while at the same time it makes substantial contribution to the
country‘s trade of balance. The food security situation of Bangladesh depends on the
development of agricultural sector which provides 96 percent of yearly requirement and such
as its improvement would contributes towards the economic growth of the nation‘s (Hossain,
2007). Thus, any policy changes or shocks in this sector will largely affected the wellbeing of
the majority people, consumer, producer and the rural poor people who are directly or
indirectly involved in this sector (Baffes and Gautam, 2001, Chowdhury. et.al, 2006, Ahmed
et.al. 2000 and Kamruzzaman. et. al, 2006; Awal et al, 2007 and also quoted by Islam,2010 ).
Domestic food production plays an important role to quest the food security in Bangladesh.
From national point of view, food security means the availability of sufficient stock of food
to meet the domestic consumption demand in the country. Among all the agricultural
commodities, food grain specially rice and wheat are at the forefront of food security in
Bangladesh, since it are the main staple food. In the context of Bangladesh, food security is
closely linked to the production, import and the price stability of food grain. Consumer
demand for food is an important component of the structure within which the agriculture
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sector must operate (Huq et al, 2010). The consumption of rice in Bangladesh has increased
over a period of decade, particularly after 1996 and the price of food grain in the world
market have been steadily rising for years (Economic outlook, 2008)1. The government of
Bangladesh has pursued different policy for achieving self-sufficiency in food grain
production in different times, like input subsidy and price support to the producers, and
making low and stable price for consumer. After trade liberalization the production of food
grain in Bangladesh has increased. Thus, the study is an attempt to estimate the demand
elasticity of foodgrains by implication of price change and the supply response with relation
to changing policy, which is important for achieving food security, economic development
programme and the policy makers.
1.2 Statement of the problem
Ensuring a balance between the consumer demand and supply of food is one of the important
issues in economic development programme in a developing country. Generally demand for
food is inelastic and production or supply somewhat variable, thus actual estimates of
demand parameters are important for development of national price, stabilization, trade,
storage, production and other policies (Hassan and Johnson, 1976). Markets in the developing
countries are highly imperfect, as supply does not co-relate with the actual demand. This
situation has led to serious bottlenecks in the processes of marketing (Huq et. al., 2004).
Agriculture sector plays a vital role in the economy of Bangladesh: so called backbone of the
economy although the share of agriculture to the country‘s GDP is decreasing. Nevertheless,
more than 60 percent labour forces are employed in agriculture sector on part time or full
time basis. About 88 percent people live in the rural areas of Bangladesh and agriculture is
their main occupation (BBS, 2007). Moreover, agriculture production provides linkage for
the development of the rest of the economy; its performance has an important bearing on
employment generation, food security, sustainable livelihood and poverty alleviation. For
these reasons, still agricultural growth remains a development priority in Bangladesh.
Agricultural scenario of Bangladesh is largely dominated by the cereals production,
especially rice and wheat in respect of both cropped area and production. About 74.42
percent of the total cropped area is used for rice cultivation and wheat is cultivated in about
3.00 percent of the gross cropped area (BBS 2007). Rice and wheat production are the major
1 For details please see Bangladesh Economic Outlook, March 2008
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sources of livelihood in terms of providing food, income and employment generation.
Historically, Bangladesh is net importer of rice and wheat, although in some years only
minimal quantities were imported. Given the predominance in the country‘s agricultural
sector, the impact of trade policy on overall agriculture in Bangladesh is largely determined
by the price and trade policy of food grain (Ahmed et al., 2007 and Hossain et.al, 2003). So,
any shift or change in agricultural policy particularly price policy in food grain sector
respecting to agricultural trade liberalization have a larger impact on producer, consumer,
government revenue earnings, the balance of trade, employment opportunities and sustainable
rural livelihood in Bangladesh.
Food availability situation in a country depends on the estimation of domestic production and
food consumption pattern. In Bangladesh, rice and wheat are the major food grain. The
requirement of food grain depends on the consumption pattern. Although the share of food
grain in the daily diet has decreased in terms of weight and calorie intake over the years, but
it is still the main source of food calorie and protein supply in Bangladesh
(www.wfp.org/wfp078255.pdf). In Bangladesh, the food calorie and protein intake from food
grain was 78 and 58.5 percent respectively in 1995-1996 (HIES, 2000).
Thus determining the food consumption behavior in rice and wheat will determine the
government policy and producer position in Bangladesh. Estimation of food demand
elasticities in a particular country is of interest of policy makers for designing effective price
and income support policies as well as for other policy intervention (Nzuma et. al, 2010).
These estimates are also essentials for planned investments and future prosperity of business
venture in a country (Sadoulet and de Janvry, 1995). Despite significant progress in economic
theory and estimation methods, the analysis of food consumption demand, especially food
grain in Bangladesh has received very limited attention. So, it is important to determine the
consumer demand elasticity of rice and wheat to know the consumption pattern of food
grains. From the last two decades consumption analysis moved to a system wide approach
and single equation system do not adhere to all implied restrictions of macroeconomic
demand theory. Thus the study will use AIDS complete demand system to estimate
consumption demand elasticity.
The government of Bangladesh pursued different policy mix in different times such as
providing subsidies in food to the selected groups of consumers, price support, import tariff,
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quantitative restrictions, quotas and input subsidies to the producers with regards to the
reform of world trade policy. These policy mixes continued up to 1980s. However, due to
severe budget constraint and continued objection of donor organization (IMF and World
Bank) and with the re-emergence of the neo-classical orthodoxy as the ‗new‘ development
paradigm, Bangladesh started to implement donor induced structural adjustment policy
reforms (Rahman, 1994). Bangladesh launched a deep and wide- ranging trade liberalization
reforms strategy in 1990s. Although recently trade liberalization has been the subject to a lot
of controversies among the researcher, policy makers and society think tank particularly in
the developing countries (Islam, 2010). Also, as a founder member of the WTO, Bangladesh
is committed to follow the rules and regulations of Uruguay round (UR) and applied to
agriculture.
Liberalization of agricultural input markets in Bangladesh helped to increase domestic cereal
production and reduced variability of supply. In the late 1990s trade liberalization and
privatization of input markets coincided with a large expansion of irrigation in winter season
rice cultivation (Ahmed et. al. 2000). Import of rice and wheat in private sector were also
liberalized in the early 1990s. After trade liberalization in 1990s, Bangladesh has successfully
used private sector trade to stabilize rice and wheat price following major production
shortfalls, reducing need for large government stock (Dorosh, 2001). Rice and wheat are
typically procured at fixed prices through direct purchase from farmers or traders. Until the
early 1990s, subsidies sale of food grains through ration programme were major distribution
channels to fulfil the requirement of the poor household. As part of trade liberalization
reforms undertaken in 1990s, however, major ration programme were shutdown and most of
the public sector distribution was targeted to poor household through direct distribution
channels such as food for work and food for education etc. So, it is important to determine
the responses of farmers and determinants of supply response of major food grains in
Bangladesh with the face in the increasing competition of the globalized economy.
1.3 Research questions
The present study will use quantitative analysis to considering following research questions;
i) What is the dynamics of demand elasticity of foodgrains?
ii) What is the response of foodgrain production with price and non-price factors?
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1.4 Objectives
The overall objective of the study is to estimate consumption demand and the impact of price
and non-price factors on the supply responses of major foodgrains in Bangladesh.
The specific objectives are:
i) To study the consumption pattern and estimate the demand elasticities for rice and
wheat.
ii) To analyze the growth of rice and wheat over the years and the supply responses to
changes in price and non-price factors.
1.5 Outline/ framework of the dissertation
The study aims to investigate the consumption pattern and supply response of food grains in
Bangladesh. Thus the study estimates the consumption demand elasticity and supply
responses of food grains production with regards to change in price. To fulfill the objectives
the thesis is breakdown in to five main chapters which are further divided in to sub sections.
The first chapter starts with giving brief introduction of background of the study, the
statement of the research problem which included objectives and framework of the study to
give an overview of the thesis. In the second chapter, brief discussion is about the
importance of agriculture in the economy of Bangladesh and food grains production,
consumption and trade (import and export). Furthermore, it explains the policy scenario of
food sector. The chapter three mainly focused on theoretical concepts which deal with the
demand systems and supply responses. Moreover, reviews of the relevant literature about the
demand systems and supply response mentioning the scope of the present study are includes
in this chapter as well. The methodology of the study is presented in chapter four. The main
aim of this chapter to present the empirical model, estimation technique and discussed the
data sources. Chapter five deals with the findings of the demand elasticity and production
response of major food grains (rice and wheat). Sixth chapter summaries the whole research
work carried out to draw a general conclusion and briefly discuss the policy implication of
the study, scope of further research and ends with limitation of the present study
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CHAPTER II
FOODGRAINS IN THE ECONOMY OF BANGLADESH
It‘s already mentioned that agriculture is the backbone of the economy of Bangladesh and
food grain, especially rice plays an important role within agriculture sector. This chapter is
about the discussion of the contribution of agriculture sector in the economy of Bangladesh
followed by an overview of food grains situation, domestic production, import, consumption
and the importance of food grains sectors. Finally, the food policies are taken by the
Government of Bangladesh to attain self-sufficiency in food grains sector are discussed.
2.1 Agriculture sector in the economy of Bangladesh2
Bangladesh is one of the world‘s highest densely populated countries with about 160 million
people in an area of 147,570 sq km. The population density is around 1000 people per sq km
with annual growth of rate 1.40 (BBS, 2009). As an agro-based economy, agriculture is the
driving force of the economy of Bangladesh. It is the dominant economic activity of the vast
majority of people and produce multiplier effects on the other sector of the economy.
Agriculture is the main source of livelihood in terms of providing food, income and
employment generation activities. About 80 percent people live in the rural area of
Bangladesh and are directly or indirectly engaged in a wide range of agricultural activities
(BBS, 2009). Agriculture sector employing about 48.1 percent of the country‘s total labour
supply (BBS, labour force survey 2005-06 and BER 2009). It also the major source of raw
material of the country‘s agro-based industries. Agriculture sector is the single largest sector
as a contributor to food and nutritional security, income and employment generation as well
as reducing poverty. Its play a vital role in socio-economic progress and sustainable
development through up-liftment of rural economy, ensuring food security by attaining
autarky in food grain production, poverty alleviation, achieving self-sufficiency in food
production and so on (Islam,2010). Agriculture accelerates economic growth and reduces
poverty, because agricultural growth increase the rural wages of the poor households whose
major share of income comes from agriculture and non-agricultural activities, and increase
the related non-farm activities (MOA, 2006; Kafiluddin and Islam,2008; Mustafi and
Islam,2008).
2 This section is update from the Ministry of Agriculture (MOA,2006)
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Bangladesh has about 13.7 million hectares of arable land of which net cultivated land is
around 8.2 million hectares with on an average 176 percent cropping intensity (BBS, 2006).
Agriculture sector is divided into different sub sectors, such as crop (including non-crop),
livestock, fishery and forestry. The main agricultural products are rice, wheat, maize, jute,
sugarcane, winter and summer vegetables, oil seeds, pulses, tuber crop, tobacco and tea etc.
(BER,2009; Kafiluddin and Islam,2008; Mustafi and Islam,2008).
Agriculture sector contributed 20.30 percent to the Gross Domestic Product in Bangladesh in
the year 2009-2010, which down from about one-half in early 1970s. Although the
contribution of agriculture sector has decreased slightly, however considering the related
activities the share of agriculture sector in total GDP is still high. Within the agriculture, the
share of crop sub-sector is 56.25 percent in 2009-2010 (table 2.1) which is mainly dominated
by food grain production. In spite of decreasing trend of agricultural contribution to the GDP,
still 98 percent of food comes from agriculture (BER, 2009; MOA, 206).
Table 2.1 Agricultural sub-secctoral share of GDP (%) at constant price (base year 1995-96)
Ag. Sub-sector 2003-
04
2004-
05
2005-
06
2006-
07
2007-
08
2008-
09
2009-
10
i) Agriculture
&forestry
a) Crop &vegetables
b)Livestock
c) Forestry
17.97
13.23
2.91
1.83
17.27
12.51
2.95
1.82
16.98
12.28
2.92
1.79
16.64
12.00
2.88
1.76
16.18
11.64
2.79
1.75
15.91
11.43
2.73
1.75
15.81
11.42
2.65
1.73
ii) Fisheries 5.11 5.00 4.86 4.73 4.65 4.58 4.49
Total agricultural
sector
23.08 22.27 21.84 21.37 20.83 20.49 20.30
Source: BER, 2011
The annual economic growth rate was 6.0 percent in the financial year 2009-2010, within
agriculture sector, the growth rate of agriculture & forestry and fisheries sub-sector were 4.36
and 4.50 percent respectively. Although the relative share of agriculture is declining but the
growth of agricultural production is growing at a faster rate than the country‘s population
growth rate (Islam, 2010). In Bangladesh, agriculture sector has achieved significant
structural changes over the past three and half decades. Even there exit many problems and
constraints, a quiet agricultural revolution has taken place which is still evolving in response
to natural calamities, socio-political changes, population growth, urbanization, new
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agricultural technology and new opportunities in rural non-farm activities, commercialization
and change in macro policy and sector policy reforms including market and trade
liberalization and substantial reduction in public sector intervention in agriculture. Nowadays,
agriculture is more of a commercial entrepreneurial activity than ever before from the peasant
based subsistence activity. Today the agriculture is more diversified within the sector because
of unstable growth in crop sector than the growth of other sub-sectors. Sub-sector growth
performance indicates the diversification in favour of fisheries sector (table 2.2) (BER, 2010;
MOA, 2006).
Agricultural productivity as measured by value added per worker increased by 24 percent
between 1990-1991 and 1999-2000 as compared with 104 percent for industry, while the
productivity in service sector was stagnant (Mujeri, 2002 cited in MOA, 2006).
Table 2.2 Agricultural sub-sectoral growth rate of GDP at constant price (base year 1995-96)
(In percentage)
Ag. Sub-sector 2003-
04
2004-
05
2005-
06
2006-
07
2007-
08
2008-
09
2009-
2010
i) Agriculture and
forestry
a) Crop &vegetables
b)Livestock
c) Forestry
4.38
4.27
4.98
4.18
1.80
0.15
7.23
5.09
5.23
5.03
6.15
5.18
4.69
4.43
5.49
5.24
2.93
2.67
2.44
5.47
4.10
4.02
3.48
5.69
4.36
4.22
3.98
5.89
ii) Fisheries 3.09 3.65 3.91 4.07 4.18 4.16 4.50
Economic growth rate
(%)
6.26 5.96 6.63 6.43 6.19 5.74 6.0
Source: BER, 2010
The export earnings from agricultural product were at US$ 870.11 million in the financial
year 2008-09, which is 5.59 percent of total export earnings. The main agricultural export
commodities are raw jute, jute goods, tea and frozen foods. Besides these export
commodities, the government of Bangladesh has taken initiative to increasing export of non-
traditional agricultural commodities. In terms of value addition, the contribution of
agriculture to the national economy is immense (BER, 2009 cited in Islam,
2010).Technological change with market forces has greatly influenced the agriculture sector
in Bangladesh in mid-sixties and seventies. Agriculture emerged as a dynamic sector during
the green revolution in Asia compare to pre-green revolution period. There was a significant
growth in institutional structures as well as a shift towards trade liberalization from
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government control. Agricultural mechanization including power tiller for cultivation,
shallow tube well for irrigation, and threshers and rice mills for converting paddy in to rice
increased. Due to liberalization of agricultural input markets use of power tiller as well as
irrigated area increases day by day in Bangladesh (MOA, 2006).
However, the growth of agricultural sector is threatened due to declining trend of cultivable
land by 1 percent by increasing population in every year and the quality of land is
deteriorating by degradation of soil fertility due to overuse of chemical fertilizer, soil erosion
and soil salinity. In addition, due to uplifting a huge amount of ground water for irrigation
and use for increasing population, water resources are also shrinking. So, in order to produce
more food for the growing population, it is essential to increase agricultural growth through
higher productivity, including yield, agricultural intensification, crop diversification and
value addition (MOA, 2006; Mustafi and Islam, 2008 cited in Islam, 2010). Thus for policy
indication it is necessary to know the consumption pattern and production response of major
cereals in Bangladesh.
2.2 Importance of foodgrains
Food grains are the major source of food in Bangladesh. In Bangladesh rice and wheat are the
major food grains which constitute 90 percent of the total food grain production and
consumption, while there are some minor cereals such as maize, millet and barley are
produced in a very small quantity. Bangladesh has made significant progress in rice and
wheat production likely to the world production trend3. During the last three decades the food
grain4 (rice and wheat) production has increased considerably from 10 million metric ton in
the early 1970s to 25 million metric tons in the late 1990s. The overall growth of food grains
was 3.4 percent during 1990s, which exceed the population growth rate 1.8 percent (Planning
commission, 2002). Like other Asian countries rice and wheat are the main staple food of 150
million Bangladeshi peoples and major livelihood of the farm household. And also the main
sources of calories (HIES, 2005; BER, 2009 and Ahmed et al, 2007). In Bangladesh, food
security situation is based on the availability of foodgrain (rice and wheat). Availability of
foodgrain mainly depends on domestic production and import.
3For world rice, production, consumption, trade and price over time, please see, patil 2009
4 For details please see, analysis of food grain sector in Bangladesh, Ahmed, Haggblade and Chowdhury (2000)
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Table 2.3 Area, production and yield of rice and wheat in Bangladesh
Year Total Area*
Total Production**
Yield***
Rice Wheat Rice Wheat Rice Wheat
1972-73 9646.40 120.2 9901 90 1.03 0.75
1973-74 10049.30 123.4 11720 109 1.15 0.88
1974-75 9790.20 125.8 11109 115 1.13 0.91
1975-76 10327.70 150.1 12560 215 1.22 1.43
1976-77 9877.70 159.8 11569 255 1.17 1.6
1977-78 10026.60 189 12764 343 1.27 1.81
1978-79 10111.50 264.6 12645 486 1.25 1.84
1979-80 10157.40 433 12539 827 1.23 1.91
1980-81 10307.00 591.2 13883 1092 1.35 1.85
1981-82 10457.60 533.7 13631 966 1.3 1.81
1982-83 10583.90 519.1 14129 1098 1.33 2.12
1983-84 10546.60 526 14415 1229 1.37 2.34
1984-85 10222.20 676.1 14622 1483 1.43 2.19
1985-86 10397.00 540.2 15041 1060 1.45 1.36
1986-87 10607.70 584.7 15407 1092 1.45 1.87
1987-88 10321.30 597.2 15414 1048 1.49 1.75
1988-89 10222.56 560 15544 1022 1.52 1.83
1989-90 10411.10 592 17710 890 1.7 1.5
1990-91 10430.50 598.9 17785 1004 1.71 1.68
1991-92 10243.10 574.6 18255 1065 1.78 1.85
1992-93 10177.70 636.9 18341 1176 1.8 1.85
1993-94 10073.50 615.1 18041.60 1131 1.82 1.84
1994-95 9921.46 639.4 16833.40 1245 1.7 1.5
1995-96 9941.82 700.9 17686.60 1369 1.78 1.95
1996-97 10177.37 707.8 18881 1454 1.86 2.05
1997-98 10262.89 804.57 18861.71 1802.8 1.84 2.24
1998-99 10116.43 882.44 19904.58 1908.4 1.97 2.16
1999-00 10708.08 832.8 23067 1840 2.15 2.21
2000-01 10797.03 772.87 25085.50 1673 2.32 2.16
2001-02 10660.74 741.8 24300 1606 2.28 2.17
2002-03 10770.67 706.48 25191.32 1506.7 2.34 2.13
2003-04 10823.69 641.87 26189.43 1253.3 2.42 1.95
2004-05 10368.39 558.00 25156.05 976.00 2.45 1.75
2005-06 10529.09 479 26530.30 735 2.52 1.53
2006-07 10583.80 400.00 27318 725 2.57 1.84 2007-08 10578.54 387.85 28931 844 2.73 2.18 2008-09 11283.80 394.78 31317 844 2.77 2.15
Source: various issues of BBS and BER
NB: *(Figures in thousand hectares), **( Figures in thousand metric tons)
***(Figures in metric ton per hectare)
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2.2.1 Domestic food grain production
In Bangladesh, most of the required food grain around 90 percent is supplied from the
domestic production. Cropping intensity is very high, which is dominated by cereals
production, especially rice. Generally, rice is grown in three seasons namely Aus (mid March
to mid August), Aman (mid June to November) and Boro (mid December to mid June) in
Bangladesh (BBS, 2005). In Boro season HYV varieties cover 60 percent of the total
production. Seventy and eighty percent value added from crop production in 1973 and 1999
respectively comes from rice sector alone and contributes 40 percent of total national
employment (48 percent in rural employment) (Islam, 2010). There is an increasing trend of
production of rice. In the financial year 2008/09 total rice production was 31317 thousand
metric ton which is higher than the previous years (see table 2.3). The production is increased
due to adoption of HYV varieties and development of irrigation system and input market
liberalization. And the area under rice production also increased.
Wheat is the second most important staple food grain after rice in Bangladesh. After
independence in 1971 the production of wheat increased gradually up to 1999/2000, then
decreases. Although in 2006/07 it was lowest in quantity but now it increasing (table 2.3).
The overall growth rate of food grain production is higher than the population growth rate.
But only in 1980s the growth rate of food grain production was less than the population
growth rate, because of huge damaged of food grain due to flood and natural calamities in the
country of that time. In the period 1971/72 to 1979/80 the country achieved an impressive
growth in wheat production. Bangladesh achieved an impressive growth in rice production in
the period 2000/01 to 2008/09 due to adoption of HYV varieties, investment in irrigation
infrastructure and increased used of fertilizer.
2.2.2. Import of food grain
Although food grain production increased over the years but it is not sufficient to meet the
requirement the country‘s growing population. Bangladesh imported on an average 10
percent of domestic food grain requirement in every year. Wheat is constituted major percent
of imports. After independence in 1971, imports of food grain was mainly dominated by
public sector up to 1999/2000 (see table 2.4). Bangladesh government liberalized markets in
1992 with relation to world trade liberalization, and allows the private sector to imports food
grain. Consequently, large number of importers have involved in this sector. That‘s why, last
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two decades the import in private sector has increased dramatically and the amount of import
in private sector is higher than public sector (see table 2.4).
Table 2.4 Import of food grain (rice and wheat) for the period 1971/72 to 2008/09
Period Public import (‗000 M.
ton)
% of total
import of food
grain
Private import (‗000 M.
ton)
% of total
import of food
grain
Rice Wheat Total
food
grain
Rice Wheat Rice Wheat Total
food
grain
Rice Wheat
1971/72-
1979/80
508.0 1181.2 1689.2 30.1 69.9 - - - - -
1980/81-
1989/90
266.5 1571.5 1838.0 14.5 85.5 - - - - -
1990/91-
1999/00
131.1 1085.6 1216.7 10.8 89.2 677.3 401.6 1078.9 62.8 37.2
2000/01-
2008/09
81.6 1530.1 1611.7 5.1 94.9 718.4 667.0 1385.4 51.9 48.1
Source: Adopted from (Begum and Haese, 2010) using data from FAOSTAT (2010)
2.2.3 Foodgrain consumption
According to FPMU (2003), the minimum requirement of foodgrain consumption is 454
gms/capita/day. The availability of per capita foodgrain consumption for the first time has
exceeded the requirement level in 2000/01. That‘s for the bumper foodgrain production due
to adoption of HYV and infrastructure development. According to Household expenditure
survey 2010 the per capita consumption of foodgrain at the national level is 442.10
gms/capita/ day, which is declined compare to the year 2005 (HIES, 2010).
2.2.4 Food gap
The government of Bangladesh has still continuously imported food grain in every year to
tackling unavoidable circumstance (e.g. flood, cyclone and other natural calamities) although
after 2000 in some year net production exceeds the requirement due to bumper production of
rice. Food gap is the short fall of food grain requirements that are not met from domestic
production. Figure2.1 illustrates the average food grain balance considering net production,
import and gap over the period 2005-2010. Where the net domestic production was 64
percent of the total demand, import was 25 percent and 11 percent gap was exit considering
domestic production (Huda, 2010). In Bangladesh, the food gap in 2005 was 1.31 million
tones, which was close to attained level in 2008 (Huda, 2010). In the year 2009-2010 the net
production of food grains exceeds the requirement. Despite the significant increase of food
grains production some people don‘t have access to food because of abnormal increase of
price.
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Figure 2.1 Food grain balance, net production, and import and food gap over the period 2005-
2010
Source: Huda, 2010
2.3 Food policy
The main objective of Bangladesh food policy is to ensuring availability and access to food to
the household level. The strategies of the government to obtain policy object is sustainable
increase in food production especially food grain, intervention in food grain markets to price
stabilization, target group food distribution to the income vulnerable households and food
relief at the time of natural hazards, disaster. For obtaining self-sufficiency in food grain
production, the government policy is to providing subsidy and procuring the food grains
mainly rice and wheat in harvesting season for ensuring fair price for the producers.
The strategies, instruments and actions of national food policy for obtaining the objectives are
discussed below:
Efficient and sustainable increase in food production: Efficient and sustainable domestic
food production is the key aspect for long term food security. For achieving sustainable
domestic food production the agricultural diversification through developed modern
agricultural systems, extension services for the best and most efficient use of available land
and inputs are given to door steps of the farmer. Agricultural inputs like fertilizer, fuel and
electricity for irrigation water are subsidized for efficient use of available resources, and
ensure availability and fair price in the production season. In addition to this emphasis was
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given to non-cereals crops vegetables, pluses and non-crop agriculture like poultry, livestock
and fisheries that improved nutritional status and balance in food production. The instruments
of the policy goal were ensuring access to agricultural credit to all agricultural farmers.
Non-distortionary food grain market intervention for price stabilization: For the
developing country like Bangladesh, food grain price stabilization is a major goal of food
policy. Because, in Bangladesh the food grain price is an important determinant of both
producer‘s and consumer‘s welfare and standard of living. Instability of price due to
increasing trend of production cost increased uncertainty for the farmers and discourages
private investment in essential agricultural inputs and production sector. From consumer
point of view, the real income of poor household decreased with sharp increase in food grain
price because poor households are spend large portion of their income for food grain.
Considering the interest of the farmers and the consumers, government intervention in the
food market by maintaining food grain stock try to make balance, so that the overall
agricultural growth and food security doesn‘t affected.
The aim of the strategy of non-distortionary food grain market intervention is market price
stability without discouraging private sector trade. For intervention three major instruments
are widely used in Bangladesh namely, price incentives for domestic production, public food
grain stock and consumer‘s price support.
In Bangladesh, the challenges in agriculture are increasing day by day due to impact of
climate change and high population growth rate, while there have been impressive success.
Increasing trend of land fragmentation and farm size is decreasing due to population growth
which affects the yields. On the other hand, abnormal fluctuation of price hampers the
productivity. Major food grain, especially rice uses four or five times more water than the
other crops and availability of ground water for irrigation will be a major obstacle to future
agriculture productivity and negative impact on environment. Thus, in future planning for
agriculture development, especially food grain should give more consideration of these
issues.
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CHAPTER III
THEORITICAL CONCEPTS AND EMPIRICAL REVIEW
The purpose of this chapter is to develop the theoretical concepts of demand analysis and
supply response on the basis of the relevant theoretical and empirical literature. This chapter
is divided into two sub section; firstly, the chapter discusses the concepts and theoretical
model of demand analysis followed by review of empirical works from different relevant
studies carried out in different countries. Secondly, it discusses the concepts and theoretical
ideas of supply response in the similar way followed by the review of previous studies.
Finally, ends with conclusion.
3.1 Demand Analysis
In general, demand is the willingness and ability of consumers to buy a certain amount of a
commodity at a certain price during a given period of time. The demand for a commodity is
that an individual is willing to buy over a certain time period is a function of or depends on
the price of that commodity, the prices of the other commodities, income and individual
preference. There exist an inverse relationship between the price and the quantity demanded
of a commodity. That is, if the price of a commodity decreases, the quantity demanded of
that commodity will increases considering the other factors constant. Slope of the demand
curve measure the change of the price and quantity demand. However, this might cause
problems to measure the change because it depends on the unit in which the commodity is
measured. To overcome this problem the concepts of elasticity has been developed which
measured the percentage changes in demand with relation to percentage change in price. The
elasticities are used to measured how change the demand for a good with relation to the
change the price of the good itself, price of the related goods and to change in individual
income. There are different types of demand elasticities such as, own-price elasticity, income
elasticity, cross-price elasticity and elasticity of substitution to measure the change of
demand. The demand side in an equilibrium model is characterized by the consumer‘s utility
maximization, in which the utility derives from the consumptions of the goods that are
available in the economy within budget constrain (Ramskov and Munksgaard, 2001).
The application of the theory requires specific model. In general, the parameters of demand
equations are estimate by both single equation approach and systems of demand equations
(Chern et al., 2002). Although single equation model is convenient for policy analysis, but
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leads to problems that the prediction or quantity projection obtained do not satisfy the
restriction of the demand theory, particularly the budget constraint, such predictions are
inadequate for use in complete models (Mullah, 2005). In order overcome this problem,
complete systems of demand equations used, which are to take into account consistently the
mutual interdependence of large number of commodities preferred by consumers, required to
specified and estimated. Also the choice of functional form and restriction of demand theory
implied (Chang and Bettington, 2001).
There are various complete systems of demand equations have been proposed for
econometric use, all pay strong allegiance to classical demand theory, introduce restrictions
in order to simplify the model and reduce the number of parameters (Parks, 1969). Linear
expenditure system, Rotterdam model, Translog model and Almost Ideal Demand Systems
(AIDS) are widely used in the area of demand systems.
In the area of systems demand equations, Richard Stone (1954) first estimated a system of
demand equations, in which he specified a particular form of the utility function and then
used this to directly derive the demand equations of his linear expenditure system (LES). This
method derives explicitly from the consumer theory (see Deaton and Muellbauer, 1980) and
implied all restrictions. However, the model negated the opportunity to test whether the data
satisfied these restrictions, and suffers from the fact that the utility function is in additive and
not general. In order to test the restrictions, Thei (1965) and Barten (1969) developed the
Rotterdam model. This model abandoned the notion of specifying an explicit utility function,
opting to rather formulate a collection of demand equations which are capable to satisfying
the theoretical restrictions, using this specification the validity of the restrictions could then
be explored. However, it is still unanswered, what are the true functional forms of the
demand equations (Thomas, 1987 cited in Mullah, 2005).
The estimation of a demand system using the concept of duality was first used in
Houthakker‘s (1960) Indirect Addilog model. Although this specification highlighted the
opportunities of employing duality theory but it failed to significantly address the
aforementioned disadvantages of the LES and Rotterdam model (Thomas, 1987 cited in
Mullah, 2005). To overcome these disadvantages, there developed specifications that
approximate indirect utility and cost functions with flexible functional forms (Cooper and
McLaren, 1992). Christensen et al (1975) developed the Translog model using a flexible
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functional form to approximate an indirect utility function. Though the model comes a long
way in improved generality and ability to produce meaningful parameter estimates but they
possess limited regularity (i.e. can still violate the restrictions of consumer theory) (Cooper
and Mclaren, 1992) and are restricted to the consideration of convex consumer preference
orderings (Thomas, 1987 cited in Mullah, 2005).
The alternative to using flexible functional forms for describing indirect utility functions,
Deaton and Muellbauer (1980) developed a demand system called the Almost Ideal Demand
System (AIDS), which based on the duality of consumer decision making and gives an
arbitrary approximation to any demand system without violating any of the axioms of rational
consumer choice. Unlike other models, the demand equations of the AIDS model generates
nonlinear Engel curves and allows for exact aggregation across consumers (Moschini, 1998).
Moreover, the properties of homogeneity and symmetry of the AIDS model can be explored
with simple parametric restrictions (Nzuma and Sarker, 2010). In addition, the described
functional forms of AIDS model; lend themselves to being estimated using household budget
data. The AIDS model provides yields of price and income elasticities that are consistent with
consumer theory and are more flexible than those obtained from other commonly used
demand systems (Nzuma and Sarker, 2010). Due to these properties, the AIDS model has
been widely used in applied demand systems analysis.
3.1.1 The Almost Ideal Demand System (AIDS)
The AIDS model by Deaton and Muellauer (1980) is derived from a utility function specified
as a second-order approximation of any utility function. Deaton and Muellauer (1980)
specified an expenditure function, which belongs to the preference price independent
logarithmic (PIGLOG) class and defines the minimum expenditure to attain a specific utility
level at given prices, and satisfies the necessary conditions for consistent aggregation across
over consumers (theorem of Muellauer, 1975, 1976). These conditions ensure that the
functional forms of the market demand equations are consistent with the behavior of a
rational representative consumer (Deaton and Muellauer, 1980 cited in Nzuma and Sarker,
2010).
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The AIDS5 model in budget share for food grain can be written as:
Where is the ith budget share estimated as /M, are normalized nominal retail
price while are the price coefficients, and M is the total expenditure on
all goods, ‘s are random disturbances assumed with zero mean and constant variance. is
an aggregate price index defined as
And the parameters ‗s defined under the symmetry conditions as
(3)
The adding up restrictions and homogeneity hold if, , , and
While adding up is automatically imposed since the budget shares must sum up to unity,
homogeneity and symmetry are parametrically imposed.
The use of price index P* in equation (2) makes the system non-linear, which raises some
empirical difficulties in estimation, particularly when aggregate annual time series data are
used. To overcome this problem of non-linearity, Deaton and Muellauer (1980) suggest to
using Stone Geometric Price Index instead of , which can be written as follows:
The linear approximate AIDS model (LA-AIDS) with Stone price index has been
extensively used in applied demand system analysis (Greene and Alston, 1990). However,
Moschini (1995) mentioned that the Stone price index fails to satisfy the commensurability
property, in the sense that it is not invariant to the units of measurement of prices. In order get
out this problem, he proposes three alternative indices. Among them, the first one is the
Tornqvist index , which is a discrete approximation of the Divisia index.
5 For detail please see the article of Nzuma and Sarker (2010)
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Where and
denote the budget shares and prices in the base period. The second
alternative is the log-linear analogue to the Paasche index ( ), which is called ‗corrected‘
Stone price index (see Moschini, 1995).
The Stone‘s price index is equal to the Paasche index if prices are normalized to one before
computed the index. And the third alternative proposed by Moschini (1995) is the log-linear
version of the Laspeyres index ( ) which can be written as
In the demand system parameters are usually difficult to directly interpret like other
regression function because of the complexity of empirically adequate specifications (Lewbel
1997, cited in Kulinskuon, 2001). It is therefore, useful to interpret the price and income
elasticity derived from the demand system. When all prices are normalized to unity, the
elasticities derived from the LAIDS and AIDS are identical at the point of normalization
(Asche and Wessells, 1997 cited in Nzuma and Sarker, 2010). Then, at the point of
normalization the Marshallian price and expenditure elasticities for the LAIDS are obtained
by the following Chalfant‘s (1987) formula as
and
where is the Kronecker delta ( ). The Hicksian
elasticities for good with respect to j can be derived from the Marshallian price elasticities
using the Slutsky equation as:
or
3.1.2 Empirical studies on demand analysis
Review of related literature in any research work is necessary because it provides
opportunities to reviewing the previous knowledge and information related to the proposed
research, which give a guideline in designing the research work and validating the research
findings. The aim of this section is to reviewing the existing studies concerned to the demand
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analysis and supply response. With this end in view, the following section presents the most
common and relevant recent studies of demand analysis and supply response on both
theoretical and empirical perspectives.
In Bangladesh, food demand system analysis is continuously refinement in estimation
methods since 1970s although there is a constrained use of more sophisticated methods due to
data limitations. In the earlier studies, the food demand system was focused on only food
grains, especially rice and wheat (Alamgir and Berlage, 1973a, 1973b; Mahmud, 1979) and
then latter a broader aspect that is a basket of food commodities were incorporated in demand
system analyses (Chowdhury, 1982; Ahmed, 1981; Pitt, 1983; Deb, 1986; Rahman and
Hossain, 1988; Bouis, 1989; Goletti and Boroumand, 1992; Ahmed and Shams, 1994;
Shahabuddin and Zohir, 1995). While most of the studies did not consider the theoretical
restrictions imposed on the estimation methods used.
Mullah (2005) studied consumer demand behavior in Bangladesh by using Engel and AIDS
model for the HIES-2000 data. He estimated the expenditure elasticity using AIDS model for
different food and non-food items. For doing this study he reviewed some past studies in
home and abroad as well. In abroad, Murty (1980) analyzed consumer demand behavior
using time series data, Ray (1982) household AIDS on time series and pooled cross section
data and test the restriction of homogeneity and symmetry, Blanciforti, Green and King
(1986) estimated AIDS for four food groups and compared with LES using time series data
were reviewed. Chowdhury (1982), complete consumer model, Ahmed and Shams (1994)
complete demand system for rural Bangladesh, Ferdous (1997) for consumer demand
behavior and Khanam and Ferdous (2000) food preference and consumer demand behaviour
in Bangladesh he also reviewed. Most of the study he reviewed used AIDS model to estimate
expenditure (income) and price elasticity. He found the expenditure elasticity for rice and
wheat was 0.31 and 0.84 respectively.
In the area of meat demand analysis in Bangladesh, Wadud (2006) estimates Marshallian and
Hicksian price and expenditure elasticities for the period 1980 to 2000 and found that
different types of meat have inelastic demand. Murshid et al., (2008) studied the food
availability, consumption pattern and nutritional standard in Bangladesh. They estimated the
income (expenditure) elasticity, own price elasticity of major food items by using the Linear
Approximation of the Almost Ideal Demand System (LA/AIDS) and compared with previous
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studies (e.g. see Ahmed and Shams, 1993; Shahabuddin and Zohir, 1995). They found that
the income elasticity of wheat (flour) was higher than those in found in previous studies, and
consumption of wheat (flour) was found to be highly income elastic in the urban areas.
Huq and Arshad (2010) estimated demand elasticities for different food items in the context
of Bangladesh by using AIDS model with corrected Stone Price Index from HIES data in
2000. They were found that the uncompensated own price elasticity for all food items except
edible oil and spices were price inelastic. They also reviewed some past studies (Sabur, 1983;
Talukder, 1990a; Islam 2002; Ali, 2002; Huq et at., 2004) that provided information on price
and income (expenditure) elasticity for food and non-food items.
Likewise, some of the recent studies about AIDS model carried out in different countries are
reviewed. Wu (1995) studied consumption patterns of urban households in China using
aggregated household consumption data and estimated the demand system of different
commodities (rice, pork, vegetable, fish, egg and fruits). Lind and Frandsen (2000) studied
food demand behaviour in India using annual time series data for the period 1967-1997. They
used AIDS model and vector error correction approach for estimation of a dynamic consumer
food demand system. The estimated econometric result showed that the system fulfilled the
theoretical properties of a demand system.
Chern et al., (2002) studied food consumption behaviour of Japanese households. They
analyzed the food consumption patterns applying Linear Almost Ideal Demand System
(LA/AIDS) and non linear Almost Ideal Demand System (AIDS). They found that the
expenditure elasticity of rice was positive and close to one, this proves that rice consumed in
Japan is normal goods, and also Marshallian uncompensated and Hicksian compensated own-
price elasticities for rice is highly elastic.
Quang Le (2008) studied food demand in Vietnam by using a linear approximation of Almost
Ideal Demand System (AIDS) and extended AIDS model. He estimated income and price
elasticities for three different components of food categories and found that rice food and
meat/fish food were normal goods while non-rice food was luxury. Sheng et al., (2008)
estimated a complete demand system of food in Malaysia by using Linear Approximate
Almost Ideal Demand System (LA/AIDS) with incorporation of Stone price index and
Laspeyres price index. The result showed that the application of Laspeyres price index
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produced more plausible estimate of expenditure and own-price elasticity in Malaysia and
consumers are seeking high protein value food, as well functionally healthy foods.
Most recently, Nzuma and Sarker (2010) estimated error corrected almost ideal demand
system for major cereals in Kenya. They used annual time series data for the period 1963 to
2005 and AIDS model with corrected Stone price index for its well theoretical and empirical
grounds. They found all own-price elasticities were negative and significant while
expenditure elasticities of all cereals (rice, wheat, maize and sorghum) were positive and
inelastic in both short-run and long-run. Another study by Zheng and Henneberry (2010)
analyzed the food grain consumption in urban Jiangsu province of China by using both the
QUAIDS and AIDS model. They found that the demands for wheat flour and coarse grains
are price elastic and the demands for rice and food grain products are price inelastic and
certain demographic variable indicated the impact of food grain demand and change the
consumption of rice.
Other than these some of the recent studies about demand system using AIDS model were
reviewed which are shown in the table 3.1.
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Table 3.1 Selected examples of AIDS model for demand analysis in different countries
Author
Title
Country/
year
Objective/
Objectives of the study
Data/
Methodology
Results/Remarks
Karagiannis et al.,:
An error correction
almost ideal
demand system for
meat in Greece
Greece
2000
-explore the methodology of
error correction form of
demand system.
-estimate short-run and long-
run elasticity for meat demand
Annual time series data
for the period 1958-
1993.
ECM-AIDS model.
The proposed formulation of
methodology performs well and all the
properties were supported by the data.
All meat items were found to
substitutes each other except chicken
and mutton-lamb, and pork and
chicken.
Zahedi: Estimating
an ECM-AIDS
model for urban-
area‘s household
expenditure: The
case of Iran
Iran
2006
-estimate the short-run and
long-run elasticity for
household expenditure demand
Annual time series data
over the period 1984-
2004.
ECM-AIDS model
The proposed formulation of dynamic
specification performs well on both
theoretical and statistical grounds as
the theoretical restriction of
homogeneity and symmetry
Zhuang and Abbott
: Price elasticities of
key agricultural
commodities in
China
China
2007
-study the relevant domestic
and trade elasticities for the
Chinese market and test the
hypothesis that China has
market power in agricultural
trade.
Annual time series for
the period 1978-2001.
LA/AIDS model
China has market power in the trade
for wheat, rice, corn, pork, and poultry
meat. The estimated own-price
elasticities for all commodities were
relevant with previous studies and the
estimation approach was appropriate
for agricultural policy analysis.
Pomboza and
Mbaga : The
estimation of food
demand elasticities
in Canada
Canada
2007
- estimate food demand
elasticity of major food groups
- identify factors that influence
the change in food expenditure
pattern
Food expenditure
survey-2001.
Modified AIDS model
suggested by Huang
and Lin (2000)
The results of the estimation were
consistent with economic theory. Own
price elasticities were negative, while
expenditure elasticities were positive
and less one.
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24
Armagan and
Akbay : An
econometric
analysis of urban
households animal
product
consumption in
Turkey
Turkey
2008
-household animal products
demand and consumption
patterns.
-estimate demand parameters
and elasticities.
Household consumer
survey in Aydin
province
LA/AIDS model for
expenditure, own-price
and cross-price
elasticity
Own-price elasticities were negative
and significant. Expenditure elasticity
was significant only meat and fish.
Price elasticity was higher than one
only for meat.
Hannan et al.,:
Household demand
for dairy products
in Bangladesh
Bangladesh
2010
-estimate different elasticities
and identify the factors
affecting the household
demand for dairy products.
Household expenditure
survey data 2000.
AIDS model
The empirical results showed that the
AIDS model was a useful instrument
for this analysis. Budget shares were
more responsive to per capita total
expenditure than price.
Islam and Jabber :
Consumer
preference and
demand for
livestock products
in urban
Bangladesh
Bangladesh
2010
-nature of preference for
different livestock products and
demand for different livestock
products within households
budget
Household survey data
LA-AIDS model for
analysis of demand
quality and safety
livestock products
The demand for quality and safety food
has been increasing with the increasing
demand for livestock products.
Estimated Household expenditure
showed that the demand for food was
unitary elastic in the major urban areas
in Bangladesh. High own-price
elasticities for fish, cereals and
vegetables.
Ulubasoglu et al.,:
Food demand
elasticities in
Australia
Australia
2010
- Consumer behaviour of food
demand.
- estimate own-price, cross-
price and expenditure
elasticities
Household expenditure
survey-1998/99 and
2003/2004
LA/AIDS model
All possible items of different food
categories were analyzed. Some
elasticities were differs from the
estimates found in previous studies.
Source: Mentioned in the first column of the table
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25
3.2 Supply response analysis
In agricultural development economics supply response is an important issue since the
responsiveness of farmers to economic incentives largely determines the contribution of
agriculture to the economy. Agricultural pricing policy plays a major role in increasing both
the farm production and incomes and fundamental to an understanding of this price
mechanism in supply response (Nerlove and Bachman, 1960 cited in Mushtaq and Dawson,
2003). The responses of elasticities are also important for decision making about policy
regarding to agricultural growth and development. Supply response is a dynamic concept and
different from supply function; it indicates the change in output with the changes in prices as
well as supply shifter and, therefore, approximates to the long-run, dynamic concept of
supply theory (Tripathi, 2008). The observed output prices in agriculture are known after the
production has occurred, while cultivation decision based on the expected price on prevail
later at the harvesting period. Thus, producer price expectation is important because of this
time lag. In agriculture there are three alternative producer price expectation hypothesis
commonly found in different literature namely naïve expectation, adaptive expectation and
rational expectation (Tripathi, 2008). Farmer‘s in the developing countries are mainly rely on
the adaptive expectation that is the expectations about what will happened in future based on
what was happened in the past, because they are mostly low literate and it is difficult for them
to obtain all relevant information which need to rational expectation behaviour. There are
two7 approaches to estimate agricultural supply response. These are;
Indirect structural form approach: This approach involves derivation of input demand
function, supply function, production function and the individual behaviours from the
available information. It is more theoretically precise but fails to take into account partial
adjustment in production and forming expectations. Moreover, for this approach requires
detail information on all inputs prices but in developing countries it is difficult to get
information on price at which inputs are supplies to farmers, because of agricultural inputs
market are functioning properly. Considering these aspect most of the previous studies have
chosen direct form reduced approach.
Direct reduced form approach: In direct reduced form, the supply response is estimated
directly by including partial adjustment and restricted adaptive expectations (see Nerlove,
7 Please see Tripathi, A. (2008) for details
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26
1958). This approach is also known as Nerlovian model. Most of the existing studies on the
supply response in Bangladesh and abroad have applied this method.
Nerlovian‘s model describes the dynamic of supply by incorporating price expectations and
partial area adjustment. According to Nerlove‘s price expectation model, desired output is a
function of price expectation. So, the form of the supply function can be written as:
Where is the desired output of the period t,
is the expected price, Zt is the set of
exogenous shifters (e.g. weather, irrigation, non-price factors) and is the unobserved
random effects affecting the output from cultivation and has expected value zero and variance
constant; ‘s are parameters with is the long –run elasticity coefficient of output with
respect to price.
Response of output by farmers may be constrained by different risk factors, credit constraint,
lack of availability of inputs etc. For this, in the Nerlovian tradition it is assumed that the
actual output may differ from the desired ones because of the adjustment lags of variable
factors. Since the full adjustment to the desired level of output is only possible in the long-
run, therefore, it is assumed that the actual output would only be a fraction δ of the desired
output.
Rearranging:
Where, is the actual output in period t, is the actual output in period t-1, is the
desired output of the period t and is the partial adjustment coefficient and its value lies
between 0 and 1. The adjustment coefficient , must lie between 0 and 2 for the adjustment to
converge over time, but >1 implies persistent over adjustment, and does not appear
plausible in subsistence peasant agriculture. So, the limit of coefficient lies between 0 and
1(Molua, 2010).
Similarly, assumed the price expectations are adaptive and based on the actual and expected
price.
According to Sadoulet and de Janvry (1995)
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27
Where, Pt is the current price and is the expected price.
Rearranging the equation:
Where is the price that prevails when the decision making for cultivation occurs in
period t and γ is the adaptive expectation coefficient. Since and
are not observable, so
we can eliminate them, and after rearranged the reduced form equation is:
Where;
, is the short –run elasticity coefficient of supply response,
and long-run elasticity coefficient
Although, most of the previous studies are used Nerlove‘s (1958) restrictive adaptive
expectations and partial adjustment model, however, most economic time series are trended
over time and the regressions between trended series may produce significant results with
high R2
value that may be spurious (Granger and Newbold, 1974). To overcome this
problem Engle-Granger co-integration with error correction approach are widely used. Co-
integration analysis with time series non-stationary data can avoid the spurious regressions
(Banerjee et al., 1993). Hallam and Zanouli (1993), Townsend and Thirtle (1994), Abdulai
and Rieder(1995), and Townsend (1996) have used co integration and ECM to estimate
supply response function at a commodity level on the basis of traditional partial adjustment
model ( quoted in McKay et al.,1997). The ECM allows testing the existing short-run and
long-run behavior among variables. Co-integration approach is better than the Nerlovian
methodology for describing the dynamics of supply, indeed, the dynamics of supply is
directly observed with co-integration, whereas in the Nerlovian model it can only be asserted
by resources to theoretical assumptions which are not explicitly tested (McKay et al., 1997).
The advantage of using ECMs is that it‘s overcome the problems of spurious regression by
passed as; differentiate and residuals are all co integrated I (0), and ECMs also convey
information for both short-run and long-run dynamics. In recent years, this technique is being
widely adopted by different economists (Ocran and Biekpe, 2008; Brescia and Lema, 2007;
Elbeydi et al., 2007; Thiele, 2003 and Muchapondwa, 2008) to estimate supply response
function (cited in Huq and Arshad, 2010).
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28
3.2.1. Empirical studies on supply response
Since the mid -1970s Bangladesh has made a substantial progress in food grain production,
especially in rice production. Numerous previous studies have estimated food grain supply,
area and price response elasticities in Bangladesh using different methodology. Of the recent
studies, Rahman and Yunus (1993) studied price responsiveness of supply of major crops
(rice, wheat, maize, barley, pulses and oil seeds etc) in Bangladesh. They used adaptive
expectations of Nerlovian framework and non-food agricultural output price index as deflate
the price of food grain for estimation of food grain supply response function. They found the
short-run and long-run elasticities were as follows:
Commodities Model Price elasticity
(short-run)
Price elasticity
(long-run)
Rice
Aus
Aman
Boro
Acreage
0.02
0.36
0.50
0.14
0.55
2.86
Rice Acreage
Output
0.06
0.24
0.06
0.24
Wheat Acreage 0.61 5.24
Foodgrain Acreage
Output
0.05
0.10
0.14
6.40
Dorosh et al., (2001) studied price responsiveness of food grain supply using traditional
Nerlovian adjustment model. They estimated short-run and long-run supply elasticities, price
and area responsiveness of rice (Aus, Aman and Boro season) and wheat, and found that
short –run supply elasticity of rice in Aus season was low while the long-run elasticity in
quite high, in Boro season both long-run and short-run elasticity was high while in Aman
season both was low. For wheat, the supply elasticity in short-run was low while in long –run
very high. They also found significant price responsiveness for all food grains. For doing this
study they reviewed some earlier studies, such as Rahman (1986) Nerlovian framework in the
analysis of supply responsiveness of rice and wheat, Alam (1992) improved methodology
(instrumental variable, non-linear least square and maximum likelihood estimate) in
estimating acreage response of rice, wheat and jute, and Shahabuddin and Zohir (1995)
dynamic production system model of Macguirk and Mundlak (1991) to estimate the supply
elasticities of rice and wheat in Bangladesh. The estimated elasticities are in the table 3.2.
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29
Table 3.2 Summary of estimates elasticities in previous studies for different time period
Source Period coverage Dependent
variable
Short-run
elasticity
Long-run
elasticity
Alam (1992) 1971-87 Aus Area
Aman Area
Boro Area
Wheat Area
0.32
0.32
0.22
1.28
Yunus (1993) 1973-89 Food grain Area
Rice Area
Aus Area
Aman Area
Boro Area
Wheat Area
0.05
0.06
0.02
0.36
0.50
0.36
0.14
0.06
0.14
0.55
2.86
5.24
Shahabuddin
and Zohir
(1995)
1984-91 Rice Area
Wheat Area
0.062
0.147
Dorosh et. al.
(2001)
1973-2000
1979-2000
1973-2000
1979-2000
Aus Area
Aman Area
Boro Area
Wheat Area
0.10
0.16
0.05
0.12
0.44
0.32
0.06
0.56
Source mentioned in the first column of the table
Begum et al., (2002) studied supply response of wheat in Bangladesh by using partial
adjustment model. They estimated the wheat response to selected factor and the short-run and
long-run supply elasticities for the period 1972-73 to 1998-99 in Bangladesh. They found the
significant price responses of wheat supply in short-run and long-run as well, and the
response of supply to the factor lagged irrigation was relatively high. The price response of
wheat supply in the short-run and long-run were 0.67 and 1.06 respectively. They suggested
that farm price support and price stabilization policy of government could increase the wheat
supply in Bangladesh. Different studies were conducted to analyze the demand and supply
situations for major crops and food items in Bangladesh. The overall growth rate of food
grain for the period 1972-2009 was higher than the population growth rate (Begum and
Haese, 2010).
Most of the previous studies related to supply response in Bangladesh used the Nerlovian
partial adjustment model. In the recent years, co-integration approach is widely adopted by
the economist to estimate supply response for advantage to overcome spurious regressions for
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30
the time series data. But in Bangladesh, co-integration approach is rarely used to estimate
supply response, especially in food grain sector. Huq and Arshad (2010) used vector error-
correction approach to estimate supply response of potato production in Bangladesh. They
estimated the short-run and long-run elasticities and found that the supply elasticities of
potato area in respect to price are positively significant for Bangladesh. They suggested that
effective price policy is essential to obtain desired level of potato production.
Likewise, some of the recent studies about supply response carried out in different countries
are reviewed. Hallam and Zanoli (1993) studied the relevance of error correction
specification to agricultural supply response and concluded that error correction model
provides a superior alternative to the partial adjustment model on both theoretical and
empirical basis. McKay et al., (1999) used error correction and co-integration approach to
estimated aggregate supply for food crop in Tanzania, because of advantage of error
correction model in time series data and for information on both short-run and long-run
dynamics.
Non-price factors such as technology, irrigation water and rainfall has significant influence
on supply response. Mushtaq and Dawson (2002) found irrigated area was an important
determinant of acreage response of wheat, rice, cotton and sugarcane in Pakistan by using co-
integration technique and impulse response analysis. Another study by Mushtaq and Dawson
(2003) evaluated the yield response of wheat and cotton in Pakistan using co-integration
approach for the period 1960-96. They found that wheat supply was significantly influenced
by the prices of wheat, cotton and fertilizer, the percentage of area under high yielding wheat
varieties and inelastic in both short-run and long-run situation. Bhatti (2011) also studied the
supply response of wheat growers in Pakistan.
Tripathi (2008) studied agricultural supply response in India. He reexamined agricultural
supply response for Indian agriculture and found that supply response is inelastic and non-
price factors (technology, irrigation and annual rainfall) have impact on agricultural output
supply. He also reviewed Mythili (2008) acreage and yield response of major crops in pre and
post-reform periods in India. Most of the studies, he reviewed have followed Nerlovian
approach with some modification and reported low supply response, and non-price factors are
relatively more important than price factors and complementary. Gurikar (2007) analyzed
growth rate and supply response of onion with price and non-price factors in India.
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31
Ogazi (2009) used error correction version of autoregressive distributed lagged model for
estimating rice output supply response to the changes in real prices in Nigeria for the period
1974 to 1996. He found inelastic price elasticity in long-run that indicated the structural
constraints facing by the farmers, price policy in the form of incentive is not a sufficient
instrument for effecting domestic rice farmers‘ response in Nigeria.
Most recently, Molua (2010) used co-integration and error correction model to measure the
response of rice yield in Cameroon. She evaluate the effect of producer price in relation to
world market price for both local rice and maize as competing crop, to determine their effect
on production, and found that rice yield responds to increasing prices to some degree with
the complementarily of better weather and irrigation. She suggested that producer supply
response could be enhanced by effective policy related to irrigation technology, development
of market infrastructure and input incentive package. She also studied rice production
response to trade liberalization in Cameroon and concluded that world market price for rice
has complementary direct relationship with local rice production in Cameroon.
In conclusion, for Bangladesh, appropriate food grain production and marketing policy is
essential for attaining self sufficiency and overcome the uncircumstance shocks due to natural
calamities. From the above discussion it is concluded that the analysis of consumption pattern
and demand for food grain over the period could be helpful for policy formulation. Supply
mainly depends on domestic production which depends on price factors and non-price factors
such irrigation infrastructure and incentives. Thus the study is an attempt to analyze
consumption demand and supply response of food grains (rice and wheat) and policy
recommendation for attaining self –sufficiency in food grain production.
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CHAPTER IV
METHODOLOGY
Chapter three reviewed past studies on consumption demand and supply response of food
grain in different countries and in Bangladesh. This chapter is about the discussion of the
sources of data and the empirical framework for this research. Firstly, the empirical
framework for the consumer demand is the Almost Ideal Demand System which was
developed by Deaton and Muellauer (1980), and secondly the empirical models for supply
response analysis with associated variables are discussed.
4.1 Data source
For this study, the annual time series data for the period 1979-80 to 2008/09 were used.
Because the availability of annual price data and before 1980‘s the agriculture sector in
Bangladesh were highly subsidized by the government. From eighties, the government was
started privatization by handing over the fertilizer distribution, irrigation equipment to private
sector and withdrawal subsidies from agriculture after trade liberalization. Moreover, the
open market economy and privatization policy also started from the same period. The
wholesale harvest price and retail price and weather (annual rainfall) were collected from
various issues of Bangladesh Bureau of Statistics. Data on area of planted, production,
productivity (yield/hectare), irrigated area of rice and wheat were collected from The
Yearbook of Agricultural Statistics published by the Bangladesh Bureau of Statistics,
Ministry of planning and the Government of the People‘s Republic of Bangladesh. Data on
consumption were collected from Household Expenditure Survey and Bangladesh Bureau of
Statistics and complied with the consumption statistics of FAOSTAT food balance sheet
online database.
4.2 Empirical model for consumption demand
This study will use AIDS model to estimate a system demand equations of food grain for the
popularity, flexibility in estimation and the consistency with demand theory. The additional
advantage of AIDS model is that it aggregates exactly over consumers (Ward, 2000b). The
specific LA/AIDS model for estimation as follows:
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33
Where is the ith budget share of food grains, are normalized nominal retail price of
food grains while are the price coefficients, and M is the total
expenditure on food grains, is approximated corrected stone price index and ‘s random
disturbances assumed with zero mean and constant variance. The details about the model has
discussed in chapter III.
4.2.1 Variables to be included in the model
The dependent variable is the expenditure share of each grain for each equation and the
independent variables are the relative consumer price for each type of food grain and the real
total expenditure on food grains.
The expenditure share of each type of grain ( ) is expressed as the proportion of the
consumer expenditure for each type of food grain divided by the total expenditure for food
grains in the system ( .
The real total expenditure
is the ratio of total expenditure on food grains and the
approximated corrected stone price index. Total expenditure for food grains is the sum of
consumer expenditure on each type of grain ( ).
4.2.2 Relevant statistical tests of the model
4.2.2.1 Test for Unit roots
Since the study used time series data, it is important to check the stationary for each series
before applying LA/AIDS model. For testing the stationary unit root test carried out, the
study used Augmented Dickey -Fuller (ADF) test to examine each of the variables for the
presence of a unit roots (indication of non-stationary), since it follows the first order auto-
regressive processes and include the first order difference in lags in the test such a way that
the error term is distributed as a white noise processes. The equation of ADF tests as follows:
Where, Y is the processes to be tested, b is the test coefficient and j is the lag length chosen
for the ADF such that ut is a white –noise- process. Here the significance of the b is tested
against the null hypothesis that the process is not weak stationary (non-stationary). Thus, if
the null hypothesis of not weak stationary cannot be rejected, the variables are differenced
until they become stationary (until the existence of unit root is rejected), before proceeding
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34
the co-integration test. Then the co-integration test will be carried out to examine the
existence of long-run dynamics of consumption demand.
4.2.2.2 Test for Homogeneity and Symmetry
There are different approaches like, the Likelihood ratio (LR) test, the Wald test and the
Lagrange multiplier (LM) test for testing the parameter restrictions implied by demand
theory. These approaches follow the Maximum likelihood method of estimation (Thomas,
1993) and the test statistics follow the chi-square distribution. The choice between the theses
test are mainly depends on the convenience of computation. For this study Wald test will be
carried out to test the parameter restrictions of the LA/AIDS model, under the null hypothesis
of valid homogeneity and symmetry.
For estimating this system equations the Seemingly Unrelated Regression are appropriate
estimation procedure (Pindyck and Rubinfield, 1998). This method has two distinguish
properties. It assumes that there are no endogenous regressors and the cross- equation terms
assumed to be contemporaneously correlated (Klinsukon, 2001). Thus, for this study the
LA/AIDS model was estimated by an iterative Seemingly Unrelated Regression method
using Microfit 4.0 program.
4.3 Analytical technique for supply response analysis
For fulfilling the second objective of this study, the following techniques will be used to
analysis the growth and supply response of foodgrains in Bangladesh.
4.3.1. Growth rate analysis
The growth rates in area, production and productivity/yield of foodgrains (rice and wheat) are
computed using by the following least squares method of fitting the semi-logarithmic
function:
(3)
Where, Y = dependent variable (area, production and yield)
a = intercept term,
b = (1+r) and r is the compound growth rate
t = time period (t = 1, 2, 3………….n)
et = error term
In the logarithmic form the function could be expressed as
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35
Where the coefficients are obtained using OLS procedure and the compound growth rate is
(Antilog of logb-1) *100, i.e. the percentage of growth rate.
4.3.2 Supply response analysis
This study will estimate area and yield/production response functions to provides an idea
about all those concerned with supply response of rice and wheat, if and to what extent, a
given price policy will be effective to determining the supply of foodgrains (rice and wheat)
in Bangladesh. Supply is the response of the total output to price and various non price
related explanatory variables. It is the planned output that the growers tended to plan certain
level of output to be produced in response to price and related explanatory variables. But the
time series data on planned output are not available, thus it is necessary to use some proxy
variable to estimate response. There is a little contradiction amongst the researchers about the
proxy variable. Some researchers claims that the actual planted area under crop production
could be better proxy variable. However, agricultural output differs considerably from
planned output because of environmental and climatic factors which are not under control of
farmer‘s. Agricultural outputs have led to approximate planned output by actual area
(Behrman, 1968). Nerlove (1958), Rahman and Yunus (1993), Dorosh et al., (2001),
Bhowmick and Ahamad (1993), Deshpande (1994) and Singh (1998) used actual area to
estimate supply response.
On the other hand, some researchers (Jha, 1970; Maji et al., 1971; Madhavan, 1972; Sawant,
1978; Mushtaq and Dawson, 2003; Gurikar, 2007; Ogazi, 2009; Molua, 2010) used yield/
production response rather than area response. Because of modern advance land saving
technology and land becomes a secondary factor in production.
Specification of empirical model:
The specific empirical parsimonious supply function for wheat area response (in the double
log form) as follows;
And the rice production/output response function as
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36
Where, is the actual planted crop area, is the production/output, Yt is the yield per
hectare, is the harvested price, is the irrigated area and i is the number of lag. The full
derivation of these equations has explained before (in chapter III). Since the study employs
time series data, the unit roots test for testing the stationary properties of data and the Engle-
Granger co-integration approach will carried out to test the existence of long-run equilibrium
and the ECM for short-term and long-term dynamics of supply function.
4.3.2.1 Description of variables to be used in the model
Competing Crops
In Bangladesh rice is normally produced in the whole (Aus, Aman and Boro seasons) year.
Thus it is difficult to find one competing crop. Rice in Aus season competes with Jute and
Boro rice competes with wheat production. For wheat production, Boro rice price, Mustard
price and Lentils price are postulated to be proxy for the best alternative use of land.
Price Variables and Deflator
Price is an important variable in production decision making processes. The question is what
price variable should be used in the model would effectively enter the resources allocation in
the decision making processes of the farmer‘s. It was observed from different studies that
usually farmers in the developing countries sell their product just after harvesting, because of
financial crisis. After development of Nerlovian model it is assumed that the price of the crop
received by the farmers is the harvest price of the respective crop. Therefore, the study was
proposed to use the harvest price of the crops and competing crop as a price variable. But the
price deflator is a serious problem in these types of model. It was observed some previous
studies (Rahman and Yunus, 1993; Dorosh et al., 2001) used Non-food consumer Price Index
to deflate the price of rice in estimating supply response function. Thus, the study used Non-
food consumer Price Index to deflate the price of rice for estimation of the supply response
function. For wheat, the weighted average price of Boro rice price, mustard price and lentils
price are used as competing crop price to avoid the risk of multicolinearity in the separate
specifications of all competing crop price in a single equation.
Irrigation
Irrigation is an important factor for production processes. It was expected that with the
increase of irrigation level the area under cultivation and yield as well as production would be
increased. Therefore, the present study will be used total irrigated area under each crop
production as an explanatory variable to assess the impact of irrigation on the area and yield.
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CHAPTER V
RESULTS AND DISCUSSION
This chapter is about the discussion of the empirical findings of the research. First sections of
this chapter are the food consumption pattern, their changes and elasticity of food grains in
Bangladesh. Growth rate of area, production and productivity of rice and wheat and their
supply responses with price and non-price factors are discussed in second section
5.1 Food consumption pattern and foodgrain demand elasticity
5.1.1 Food consumption pattern
The demand for food grains has several components; including consumption requirement and
demand for procurement. Rice and wheat are the main staple food in Bangladesh, which are
comprises around 90 percent of total food grain production and consumption. Average per
capita per day food intake for different food items shows that food grains are comprises about
50 percent of total food intake (Appendix A5.1). Percentage share of expenditure for different
food items (presented in figure 5.1) shows around 40 percent monthly food expenditure per
household for food grains. According to HIES 2005 average per capita consumption of rice
and wheat are 13.2 and 0.4 kg per month respectively, which is declined compare to the data
of HIES 2000( Appendix A5.2).
Figure5.1: Monthly food expenditure share in Bangladesh in 2005
Source: Own estimation using HIES 2005, BBS
Per capita consumption levels are different between the income groups and also in the rural
and urban area (see Appendix A5.3). In rural area per capita consumption of rice is higher in
39
2.6512.24
8.51
8.38
3.74
4.25
7.52
3.23
1.560.68
8.25Food grains
Pulses
Fish
Meat & eggs
Vegetables
Milk/milk products
Edible oil
Condim/spices
Fruits
Sugar/gur
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38
high income groups8 than the other groups while in urban area the middle income groups
consume more rice than others. For wheat the per capita consumption in urban area is higher
than rural area as well as the high income groups than others. Because of changed of food
habit of the urban inhabitants and high income.
5.1.2 Changes in food consumption
Food consumption pattern will be changed when the per capita income is higher than earlier.
Increasing per capita income also led to diversification of food items. Diversification of food
items will improve the nutritional status and well-being of human life. Monthly per capita
income in Bangladesh has increased by 31.65 percent over the year 2000 and increased by
137.6 percent over the year 1991-92 (HIES, 2005). Figure 5.2 shows that the per capita per
day calorie intake from food grain has decreased in 2005 compare to 2000 while from other
food items has increased. Average per capita per day food intake also has changed over the
year 2000 in Bangladesh (see Appendix A5.1).
Figure5.2: Per capita per day calorie intake (in gram) by food items.
Source: Own estimation using HIES 2005, BBS
However, if we look the annual per capita consumption level of rice and wheat over the
period 1980- 2006. It is observed that per capita consumption of rice and wheat started to
decline in 2003 (figure 5.3). But the domestic food grain production has increased, especially
rice production. This may be reduced due to changes in consumption habit and preference for
8 Income group are classified into three groups; poor, middle and high, for details please see appendix A5.3
0
200
400
600
800
1000
1200
1400
1600
1800
2005 2000
gram
/day
Year
Food grains
Potato
Vegetables
Pulses
Milk/milk product
Edible oils
Meat, poultry,Egg
Fish
Condim&Spices
Fruits
Sugar/Gur
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39
high protein value food. According to HIES 2005, the per day per capita protein intake from
different food items has changed. Compare to the year 2000 the per capita protein intake from
cereals has decreased, while from other food items such as potato, vegetables, meat and fish
has increased (Appendix A5.4).
Figure5.3: Annual per capita consumption of rice and wheat for the period 1980-2006
Source: Own estimation using BBS and FAOSTAT database
5.1.3 Almost Ideal Demand System for food grain in Bangladesh
Annual time series of consumption and price data of food grains for the period 1980 to 2006
have been used to estimate the LA/AIDS because of availability of data. In Bangladesh, rice
and wheat is the major food grain, they are comprises more than 90 percent in consumption
demand, while the others minor cereals like maize and barley are consumed a very low
percentage. Since the LA/AIDS model requires complete demand system. Thus, the study
considered the minor cereals maize and barley as other grain and the price of this group is the
weighted average price. In some earlier studies (e.g., Nzuma and Sarker, 2010) on cereal
demand in Kenya, sorghum was included. But in Bangladesh the weather condition is not
suitable for sorghum and it is not included in food consumption pattern. Finally, all the prices
are normalized to one based on 1980.
The data set used in estimating the food grain demand was tested by several statistical tests
prior to estimate the LA/AIDS model.
0.00
20.00
40.00
60.00
80.00
100.00
120.00
140.00
160.00
180.00
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Kg/
year
Year
Rice
Wheat
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40
5.1.3.1 Univariate properties of the data
In modern econometric methodology, one of the important properties of time series data is
that should be stationary. Because the non-stationary variables in the model will be often
result in spurious regression. Thus, the study used formal unit root tests like ADF tests to
ascertain the presence of unit roots in all the data series. The ADF test is used to test the
hypothesis that all grain prices, budget shares and total expenditure contain a unit root cannot
be rejected at the 5 % level of significance for both models with and without deterministic
trend. The results of the ADF tests with and without deterministic trend are presented in table
5.1. The results showed that all the prices, shares and total expenditure are appeared to be
non-stationary in the level series. As a result, this study proceeded to first order differentiated
of each series and the result indicates that the ADF test rejects the null hypothesis of non-
stationary in all cases. Therefore, the degree of integration is 0, that is Δyt ~ I (0). In other
words, they are integrated at order 1 (i. e. yt ~ I (1)). That is stationary in the first differenced
form.
Table 5.1 ADF test results for the budget share, consumer price and total expenditure
Series Level series First differences
No trend Trend No trend Trend
Budget share of rice -2.229 -2.234 -4.715 -4.721
Budget share of wheat -2.491 -2.483 -4.622 -4.537
Budget share of other grain 2.185 0.207 -3.069 -4.321
Log of rice price -2.457 -2.557 -4.415 -5.646
Log of wheat price -1.524 -2.563 -4.540 -4.724
Log of other grain price -1.787 -1.520 -4.742 -5.895
Real total expenditure on
food grain
-2.558 -2.624 -4.248 -5.154
5 % level critical values -3.00 -3.600 -3.00 -3.600
The econometric package STATA 11 was used and the critical values are the Mackinon
approximate value for rejection of the null hypothesis of a unit root
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41
Then the study was carried out ADF tests and PP tests for co-integration test to examine the
long-run equilibrium relationship between the budget shares and the corresponding
explanatory variables. The tests result did not find any unique long-run relationship
(Appendix A5.5).
Therefore, the LA/ADIS was estimated in first differenced form by means of a restricted
seemingly unrelated regression method. Taljaard et al., (2004) meat demand in South Africa
and Klinsukon, (2001) used first differentiated form of the variables to estimate the LA/AIDS
model in meat demand in Newzealand. Thus, the LA/AIDS model was transformed into first
order differentiated form with all variables and then redefine as:
The theoretical properties of the demand theory of adding up, homogeneity, and symmetry in
this system imply, respectively, that is
Therefore, the equation (1) was estimated by the iterative seemingly unrelated regression
method using the econometric software Microfit 4.0. To avoid a singular residual variance/
co-variance matrix for adding up conditions, the other grain share equation whose budget
share is the lowest was dropped for estimation.
5.1.3.2 Structural stability of data
A systematic method was developed to identify and captures the effect of the structural break
by Newbold, Rayner and Kellard (2000). According to Alemu, Oosthuizen and Van
Schalkwyk (2003), this method helps to detect and evaluate exogenous variables, which and
among others, could results from transition to new policy regime. For determining the periods
in which the structural breaks occurs, the series of residuals from the fitted LA/AIDS share
equations were examined and the structural breaks are then where the absolute values of the
residuals exceeded two standard deviations. Therefore, when the residual exceeds the two
standard error band in a specific year, an intercept and dummy variable are introduced into
equation that specific year (Taljaard, 2003).
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42
Residuals
Figure 5.4: Residual plot of the rice share equation in two standard error bands
Figure 5.4 indicates that in the case of rice share equation, the residual for the year 1986
passed the positive 2 standard error. There is no clear cut explanation of the breaks in the
practical terms; a possible explanation can be the weather condition was favourable for rice
production. The actual data showed that the per capita consumption was sharply increased for
that year. The per capita consumption of foodgrain has exceeded the minimum requirement
level first time in 2001 in Bangladesh. Although still in every year Bangladesh has imported
rice to overcome the unfavorable circumstance during the natural calamities. Thus, the study
considers a dummy variable for that year.
Residuals
Figure 5.5: Residual plot of the wheat share equation in two standard error bands
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43
The residual plot for the wheat share equation is shown in figure 5.5. The residual passed the
negative 2 standard error band in the year 1986. A possible explanation can be wheat is used
as a substitute for rice in Bangladesh. When there is shortage in rice production and price is
high, then people are consumed wheat.
5.1.3.3 Homogeneity and Symmetry test
The important properties of a demand function, which can be used to restrict an empirical
demand function, are; adding up, homogenous of degree zero in prices coefficient and the
cross price derivatives are symmetry. The Wald test are used to test the hypothesis of linear
homogeneity, symmetry, and both linear homogeneity and symmetry. To implement these
tests, the LA/AIDS model was estimated without imposing homogeneity and symmetry and
the budget share of others grain excluded to satisfy the adding up property. The results of the
parametric restrictions of homogeneity, symmetry and joint homogeneity and symmetry are
presented in Table 5.2. The results indicated that the null hypothesis of the restrictions of
valid homogeneity and symmetry are accepted at the 5 % significance level. This indicates
that the used data are consistent with the consumer utility maximizing theory.
Table 5.2 Systems Wald tests for Homogeneity and Symmetry
Parameter restrictions Calculated
χ2
values
Critical value Degrees of
freedom 5% 1%
Homogeneity 1.956 5.99 9.21 2
Symmetry 0.405 3.84 6.63 1
Homogeneity and symmetry 3.351 7.81 11.34 3
Another important concern before the demand model estimation is whether the expenditure
variable in the model is exogenous. If the expenditure variable in the model is endogenous,
i.e. correlated with random error term, then the SUR estimators are no longer unbiased
(Edgerton, 1993). According to Attfield (1985), the acceptance of the homogeneity restriction
property can be interpreted as an acceptance of the exogeneity of expenditures. Nzuma and
Sarker (2010) also considered the changes in income as exogenous in the study of major
cereals demand in Kenya. Thus, the study considered the expenditure variable to be
exogenous and does not consider the consumption of other food products. For satisfying
monotonicity in prices, all budget shares should be strictly positive. Since all budget share in
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44
this study are positive, thus the estimated parameter satisfy monotonicity of the underlying
cost function. Furthermore, since all computed own-price Hicksian elasticities from the
estimated parameters of LA/AIDS model are negative, thus, the concavity of the cost
function at the sample mean is ensured. Since the estimated parameters of the model are
consistent with all the theoretical restrictions, therefore the estimated elasticities are
important implication for policy analysis.
Table 5.3 Parameter estimates of an LA/AIDS for food grain demand in Bangladesh
(homogeneity and symmetry imposed)
Parameter Estimated parameters with respect to
Rice Wheat Other grain
γi1 0.09668**
(0.04427)
-0.09677**
(0.04426)
0.000087
(0.00607)
γi2 -0.09677**
(0.04426)
0.09687**
(0.04494)
-0.00010
(0.00574)
γi3 0.000087
(0.00607)
-0.00010
(0.00574)
0.00001
i -0.07176*
(0.03942)
0.07288*
(0.03974)
0.0011
Dummy86 0.06914***
(0.01796)
-0.06807***
(0.01814)
System weighted R2 = 0.40
Figure in the parenthesis are standard error, where
* denotes significant at 10 % level
** denotes significant at 5% level
*** denotes significant at 1% level
The estimated parameters of the restricted LA/AIDS model are presented in table 5.3. The
system weighted R2
indicates that the independent variables included in the model explain 40
percent of the variation in the data. The R2
is low, may be additional data would improve it
but it is not available due to time limitation and other constraints. Although, always low value
of R2
does not necessarily indicates miss-specification of model (McGurik and Driscoll, 1995
cited in Klinsukon, 2001). Over half of the estimated coefficients are statistically significant
at least at the 10 percent level (table 5.3). The real expenditure variable was significant at 10
percent level for rice and wheat share equation. The expenditure coefficient measure the
changes in budget share and indicates the nature of commodities whether it necessary or
luxuries. The estimated expenditure coefficient for rice is negative and significant at 10
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45
percent level which indicates rice grain is necessity in Bangladesh. The coefficients of wheat
and other minor cereals are positive. The actual data also showed that the consumption of
wheat is decreasing and a certain level of income group consumed for their habit. Other
estimated parameters of the LA/AIDS model do not have straight forward economic
interpretation but used to calculate elasticities for policy formulation.
5.1.3.4 Estimated elasticities
All the elasticities are estimated to the point of normalization, i.e. to 1980 because the model
is normalized to unity at the base period (1980). At the point of normalization, the elasticities
calculation for the AIDS and Linearized AIDS are the same (Asche and Wessells, 1997).
Since the study used LA/AIDS model, thus all the elasticities are estimated in the point of
normalization using Chalfont‘s (1987) formula. The estimates of own price Marshallian and
expenditure elasticities are presented in table 5.4.
Table 5.4 Marshallian price and expenditure elasticities (homogeneity and symmetry
imposed)
Food grain Marshallian (uncompensated) Price Elasticities Expenditure
elasticity Rice Wheat Other grains
Rice -0.81 -0.10 0.0001 0.91
Wheat -1.05 -0.48 -1.00 1.48
Other grains -1.21 -0.37 -0.98 2.61
All the Marshallian own price elasticities are found to be negative as expected. The negative
own-price elasticity indicates that the demand curve of the corresponding commodity is
downward sloping, that satisfied the law of demand. The own price elasticities for rice and
wheat were -0.81 and -0.48 respectively, which are consistent with the study by Dorash and
Haggblade (1997) where for rice in urban poor was -0.89 and wheat in urban non poor was -
0.43. All expenditure elasticities are positive and for rice it is inelastic, that indicates rice is a
necessary good in Bangladesh. The expenditure elasticity for rice was 0.91, which is quite
high but it is consistent with Pitt (1983) in high income group 0.94. Although, all of the
previous studies on demand estimation were based on cross section data. The expenditure or
income elasticity of wheat is very high i.e. 1.48, which indicates wheat demand increase a lot
if incomes increase. This is quite ambiguous. But Musrhid et al., (2008) also found high
income elasticity for wheat and other cereals in Bangladesh. For wheat in rural area it was
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46
1.44 and in urban area was 1.58. Generally, Marshallian estimates provide better measure of
the responsiveness for any particular grain to changes in its own-price than to the changes in
the price of other grains.
Hicksian elasticities provide better estimates for substitution effects among goods than the
Marshallian elasticities because they only capture the substitution effect not income effect.
All the estimated own-price Hicksian elasticities of demand are negative but smaller than
their respective Marshallian elasticities and the corresponding Slutsky matrix is negative
semi-definite that showing the reliability of the model. The sings of the cross price elasticities
in Hicksian estimates were positive while in Marshallian estimates these were negative that
was more ambiguous. It‘s may be due to strong income effect. Since Hicksian cross price
elasticities are better for substitution effects, thus the compensated cross price elasticities are
appropriate when one wants information about substitution effect. So we can make inference
about them.
Table 5.5 Hicksian (compensated) price elasticities (homogeneity and symmetry imposed)
Food grain Hicksian (compensated) Price Elasticities
Rice Wheat Other grains
Rice -0.04 0.03 0.0007
Wheat 0.20 -0.25 0.00003
Other grains 0.97 0.006 -0.97
The positive sign of the cross price elasticity of rice and wheat indicates that rice and wheat
are substitute. The cross price elasticity of demand for rice with respect to wheat price is 0.03
and other minor grain is near to zero. That means the change of rice demand respond to wheat
price change is very low, which is more or less consistent with the study Goletti (1993). On
the other hand, the cross price elasticity of demand for wheat with respect to rice price is
0.20, which indicates the higher response of wheat demand with rice price change compare to
rice demand respond to wheat price.
5.2 Supply response of food grain production in Bangladesh
Rice and wheat are the major staple food items in quantity of total calorie and protein intake
in Bangladesh. Thus, food security situation is mainly depends on the availability of food
grain especially domestic production of rice and wheat. The productions of grains are
influenced by price and different non-price factors like; irrigation, weather condition etc. The
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Government of Bangladesh has pursued different policy for attaining self-sufficiency in food
grain production since 1970s. At the end of 1990s, the country has achieved a great milestone
to achieve food security in terms of food grain availability, since for the first time in its
history, food grain production exceeded the target requirement 454 gm/person/day (Hossain
et al., 2005). Thus, the study will provides an idea about overall growth and all concerned
with supply response of foodgrain, if, and to what extend a given price policy will be
effective for food grain supply in Bangladesh.
5.2.1 Growth rate analysis
The compound growth rate of area, production and yield of rice and wheat were estimated
using semi-logarithmic least square method. Table 5.6 indicates that the overall growth rate
of foodgrain production for the period 1971/72-2008/09 was 2.92, which was higher than the
population growth rate 2.50. But only in 1980s the growth rate of food grain production was
less than the population growth rate (figure 5.4),because of huge damaged of food grain due
to flood and natural calamities in the country of that time and the decline in the growth rate in
production can be attributed to a decline in the growth rate in area.
Table5.6 Annual growth rate of area, production and yield of rice and wheat in Bangladesh
Period Growth rate (%)
Area Production Yield Total food
grain
production Rice Wheat Rice Wheat Rice Wheat
1971/72-1979/80 0.8 14.9 3.3 30.8 2.4 13.8 3.83
1980/81-1989/90 - 0.1 0.7 2.3 -1.4 3.0 -2.3 2.10
1990/91-1999/00 0.4 4.7 2.0 7.8 1.6 3.1 2.39
2000/01-2008/09 0.1 -9.6 2.5 -10.4 2.5 -0.9 2.38
1971/72-2008/09 0.2 3.7 2.8 5.3 2.6 1.5 2.92
Source: Own estimation using the data from BBS
In the period 1971/72 to 1979/80 the country achieved an impressive growth in wheat
production, which was much higher than the overall growth rate of food grain production
(table 5.6). Bangladesh has achieved an impressive growth in rice production in last decades
due to adoption of HYV varieties, investment in irrigation infrastructure and increased used
of fertilizer, and the overall growth in food grain production is largely reflected by the growth
in rice production. The fluctuation of the growth rate of rice production is largely dominated
by the growth rate of yield (table 5.6). The overall growth rate in area under food grain
production was 0.3% over the period 1971/72 to 2008/09, while in yield was 2.2% (Begum
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and Haese, 2010). Thus, for the increase in the food grain production the government should
give more attention to the policy related to increase the yield.
Figure 5.6: Total foodgrain growth rate and population growth rate over the period
Source: Own estimation using the calculated population growth rate from (Begum and Haese,
2010).
5.2.2 Supply response analysis
The Nerlovian partial adjustment models are widely used to estimate the area and yield
responses of rice and wheat with single equation approach in different countries. Rahji et al.,
(2008) rice supply response in Nigeria, Niamatullah and Zaman (2009) wheat and cotton
response in Pakistan, Nosheen and Iqbal (2008) acreage response of wheat in Pakistan,
Begum et al., (2002) wheat supply response in Bangladesh and Dorosh et al., (2001) price
responsiveness of food grain supply in Bangladesh used the Nerlovian adjustment model. But
it often occurred spurious regression problem with time series data. The annual time series
data for the period 1980-2009 have been used in the analysis. Since the study employs time
series data, statistical tests of time series were employed to establish the validity of the
model. Most well known Engle-Granger co-integration approach was employed and test for
possible long-run equilibrium relationship was carried out to overcome the problem often
occurred due to time series properties of data.
3.8
2.1
2.4 2.4
2.92.67
2.35
1.73
2.11
2.50
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
1971/72-79/80 1980/81-89/90 1990/91-1999/2000 2000/01-2008/09 1971/72-2008/09
Gro
wth
rat
e (
%)
Periods
Total food grain production growth rate Population growth rate
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5.2.2.1 Unit root tests
Before preceding the supply response analysis, a unit root test of each of the time series were
undertaken to determine whether the variables are stationary or not and also order of
integration. A very well known unit root test, the ADF test was employed to test the
hypothesis that all the variables contain a unit root cannot be rejected at the 5 % percent level.
Table 5.7 The ADF test results for the variables of supply response analysis
Series Level series First differences
No trend Trend No trend Trend
Logarithm of rice yield -0.371 -2.576 -3.391 -3.32
Logarithm of rice
production
-0.010 -2.130 -4.111 -4.121
Logarithm of real rice price -1.609 -2.028 -5.960 -6.014
Logarithm of irrigated area -1.984 -1.152 -4.193 -4.581
Logarithm of wheat area -1.266 -1.066 -3.08 -3.647
Logarithm of wheat yield -2.962 -3.013 -4.581 -4.493
Logarithm of wheat relative
price
-1.437 -3.646 -5.622 -5.632
Logarithm of wheat
irrigated area
-0.556 -2.439 -5.024 -5.087
5 % level critical values -3.00 -3.600 -3.00 -3.600
The econometric package STATA 11 was used and the critical values are the Mackinon
approximate value for rejection of the null hypothesis of a unit root
The results of the ADF tests with and without deterministic trend are presented in table 5.7.
The results of the ADF test indicate that all the variables are non-stationary in the level series
even in deterministic trend. Thus, the study proceeded to first order differentiated of each
series and the results showed all time series become stationary at 5 % significance level.
Therefore, the model is specified after having known the order of integration.
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5.2.2.2 Empirical results of the rice supply response model
As mentioned earlier that rice is the most strategic commodity in the economy of Bangladesh
and it is the main staple food of country‘s 160 million people. The share of rice in the
agricultural GDP was 35 percent in 2000 (Ahmed, 2004). So, the pace of growth in
production of rice sector determines the pace of agricultural growth in the country. Rice
constitutes above 90 percent of the domestic food grain production. Therefore, self-
sufficiency in food grain implies primarily an autarky in rice production. Recently, the yield/
production response function are used by the researcher to analyze the supply response.
Nowadays, land becomes a secondary factor of production, because of land saving advanced
technology. Bangladesh is highly densely populated country and land becoming very scarce
and fragmented day by day, because of high population growth rate. The overall growth rate
of rice production is largely dominated by the growth rate of yield (table 5.6). Thus, this
study was estimated production response function of rice at aggregate level with respect to
price and non-price factors. The price variable used in this equation is the weighted average
of harvest prices of Aus, Aman and Boro, using output weights. The rice price was deflated
by non-food consumer price index (base 1995-96 = 100), because for rice crop it is difficult
to find highly competitive crops in Bangladesh and also agricultural input index are not
available. Dorosh et al., (2001) also used non-food consumer price index as a deflator for rice
price.
The results of the ADF test showed that all the variables are weak stationary after first order
difference (table 5.7). That means they are all integrated in order one, i.e. I (1). Then the co-
integration was employed to establish long-run equilibrium relationships between the
variables. However, for co-integration two conditions must be hold, first one is each variable
should be integrated of the same order. Secondly, the linear combination of these variables
must be integrated of an order one less than the original order of the variable (Engle
&Granger, 1987). In other words, if the variables are integrated in order one I (1), then the
residual from the co-integrating relationship should be integrated in zero order or I (0). If the
long-run equilibrium relationships among the variable are co-integrated (Engle & Granger,
1987) show that the variables can be represented in a dynamic error correction model.
Therefore, the Engle-Granger con-integration approach was carried out to test the existence
of long-run equilibrium among the variables in equation (5). The result showed that there is
no long-run unique relationship among the variables (Appendix A5.7). The possible
explanation can be that in the actual data there was some structural break, because of
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occurred floods in several years and fertilizer crisis, and rice crop was mostly affected by
flood. Another reason might be the inadequate data and short period of time series. Thus, the
equation (5) was estimated using first order difference logarithmic functional form. Tey et al.,
(2010) used first order difference logarithmic function for acreage response of paddy in
Malaysia. Several equations were estimated with various explanatory variables, only the
equations with meaningful explanatory variables and appropriate lags are presented here.
The estimated coefficients of the rice output response function with related statistics are
presented in table 5.8.
Table 5.8 Estimates of rice output response in Bangladesh
Variables Coefficient t-Statistic
Constant -0.01935 -0.8696
Logarithm of price lag 1 0.1125*
1.7746
Logarithm of output lag 1 0.0547 0.3168
Log. of irrigated area 0.4633*
1.9377
DD 90 0.0388**
2.1732
D 95 -0.1071**
-2.6276
R2
0.43
F-statistic 3.41**
Durbin-Watson 1.895
Statistically significant: ***
at 1%, **
at 5 % and * at 10 % level
Di is define as; Di = 1 if year = i, Otherwise Di = 0
DDi is define as follows; DDi = 1if year > = i, Otherwise DDi = 0
The explanatory power of the equation indicates that the variables included in the model
explained around 43 percent of total variation. The F-ratio shows that all the estimated
coefficients are jointly significance. The Durbin-Watson statistic indicates that there is no
serial auto correlation. For further confirmation, the Durbin h statistic was calculated and it‘s
also support the evidence of no auto correlation. Others diagnostic tests result, like Jarque
Bera for normality, RESET test for functional misspecification form and heteroscedasticity
test in table 5.9 shows that the estimated equation was correct functional form, normally
distributed and no evidence of heteroscedasticity.
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Table 5.9 Diagnostic tests for rice output response function
Durbin h statistic .6777(.498)
Jarque Bera Normality test 2.3612 (.307)
RESET test .0556 (.813)
Heteroscedasticity test .8463 (.358)
Figure in the parentheses are the probability level
The coefficient of real price was positive and statistically significant at 10 percent level,
which indicates the positive influence of price on the rice output response. That means if the
farmers got higher price in the previous year then they are motivated to increase production
using HYV seeds, other agricultural inputs and technology. The coefficient of area under
irrigation was also statistically significant and positive. Irrigation water is important input for
rice production. Generally rice consumed more water three to four times than other crops. In
the dry season the Boro rice and HYV‘s are completely depends on the ground water and
surface water irrigation in Bangladesh. Even sometime drought occurred during the Aman
rice harvesting period due to high impact of natural calamities in Bangladesh. The coefficient
of lagged output was positive but not significant. The coefficients of dummy variables were
highly statistically significant, which indicates the inclusion of these variables have
significant influence on rice production response. The dummy 90 variable capture the
continuous increase of rice production. This is impact of market liberalization. After market
liberalization in 1992 the private sectors were largely allowed to import agricultural inputs
like, HYV seeds, fertilizer, irrigation equipment and machineries etc. which were largely
increased the productivity of rice. Consequently, in 2001 first time in history Bangladesh
exceeds the minimum requirement of food grain production. On the other hand, in 1995 rice
production was decreased in area and productivity compare to previous year. Because in the
year 1995, Bangladesh has experienced with fertilizer crisis at the farmers level in the rice
cultivation period. In Bangladesh, almost all farmers used fertilizer and chemical fertilizer
accounted for 18 to 20 percent of total expenditure on HYV crop production (Begum and
Manos, 2005).
5.2.2.3 Empirical results of the estimated wheat area response model
Wheat is the second most important food grain after rice in Bangladesh. The actual data
showed the yield is almost stagnant. Wheat production is highly competitive with Boro rice,
Mustard and Lentils production. There is a possibility to increase area under wheat
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production if HYV seed and other inputs are available in Bangladesh. Thus, for wheat only
the area response model was estimated. The price used for estimation is the relative price,
which was obtained deflated the wheat harvested price by competitive crops (Boro rice,
Mustard and Lentils) prices.
The ADF test indicates all the variables in equation (4) are non-stationary in the level series.
The results of ADF test in table 5.7 showed that there are stationary after first order
difference. That means, they are all integrated in the first order, i.e. I(1). Therefore, the well
known Engle-Granger co-integration approach was carried out to test the existence of the
long-run relationship among the variables. The result indicates that there is no long-run
equilibrium among the variables (AppendixA5.8). Possible explanation for no co movement
can be that the actual area under wheat production is continuously decreasing after 2001,
while the harvested price is in increasing trend, and also inadequacy of data. Since all the
variables are stationary after first order difference, thus the equation (4) of the wheat area
response function was estimated using first order difference logarithmic form. The estimated
coefficients of the wheat area response model with related statistics are presented in table
5.10. Several equations were estimated with various explanatory variables. Only the equation
gave minimum error sum of square with relevant explanatory variables and appropriate lags
are presented here.
Table 5.10 Estimates of the area response function of wheat in Bangladesh
Variables Coefficient t-Statistic
Constant 0.0116 0.449
Logarithm of price lag 1 -0.3756***
-3.516
Logarithm of area lag 1 0.2785*
1.754
Logarithm of yield 0.1853*
1.770
Logarithm of irrigated area -0.3193**
-2.248
R2
0.56
F-statistic 7.112***
Durbin-Watson 2.037
Statistically significant: ***
at 1%, **
at 5 % and * at 10 % level.
The explanatory power of the estimated equation is 0.56 i.e. R2 56 %, which indicates that the
variables included in the model explain around 56% of variation of wheat area. All the related
tests in the model gave satisfactory results. The F- ratio is statistically significance at 1
percent probability level, which indicates the overall significance of the model. The
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calculated Durbin-Watson statistic is 2.037, which suggests that there is no serial correlation
in the residuals. Nevertheless, the Durbin (h) statistics have calculated to further confirm
absence of serial correlation, because lagged dependent variable has also been included as an
independent variable. The calculated Durbin (h) statistic in the table 5.11 also suggests that
there is no serial correlation in the residuals. The RESET test for functional form miss-
specification was confirming the acceptance of the null hypothesis of a correct functional
form. The Jarque Bera test for normality in the residuals was not statistically significant,
which indicates that the residuals of the model are normally distributed. And the
heteroscedasticity test also suggests that there was no evidence of the presence of
heteroscedasticity. The estimated coefficients of the regression equation (table 5.10) are in
fact the short-run elasticities of area with respect to the specific variables. Most of the
coefficients of the explanatory variables are statistically significant. The coefficient of lagged
relative prices was found to be negative and significant at 1 percent level. The lagged relative
price of wheat was -0.37 and statistically significant at 1 percent level. The inverse
relationship between relative price and area implies that the relative price of wheat decreased
the farmers‘ response to area. That was not expected; it was happened may be due to higher
price of the competing crops.
Table 5.11 Diagnostic tests of estimated wheat response function
D. h Statistic -0.173(.862)
Jarque Bera Normality test 0.3582(.836)
RESET Test 0.1160(.732)
Heteroscedasticity test 0.026 (.871)
Figure in the parentheses are the probability level
The estimated coefficient of wheat lagged area is 0.27 and positively significant. The
adjustment coefficient is the pace at which the farmers adjust the area under a crop in
response to the movement of the other factors and which is one minus the coefficient of
lagged dependent variable. The calculated area adjustment coefficient is 0.73 represents that
the farmers‘ are adjust highly toward the desired wheat planted area. The coefficient of yield
was 0.18 and significantly positive, which indicates that wheat planted area increased with
the increase of yield. So, there is possibility to increase wheat area, if it is possible to increase
yield using HYV seed, modern technology and agricultural inputs.
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CHAPTER VI
SUMMARY, CONCLUSION AND POLICY IMPLICATION
In this chapter, the summary of the dissertation and conclusions on the basis of the study are
briefly discussed. In the summary, the justification and objective of the study are
recapitulated and the findings of the study are briefly discussed. After that some policy
implications are made on the basis of the findings. Finally, limitations of the study and
possibility for further research are mentioned in this chapter.
6.1 Summary of the study
There is an important role of agriculture sector in the developing countries which can
accelerate the rate of growth. Most of the national policies and planning of the developing
countries are reflected by the agriculture sector. Both developed and developing countries
(Islam, 2010) pursued different policy to protect agriculture, to obtained self-sufficiency in
food production, to attain food security, to ensure reasonable price of food for domestic
consumer, price support and protect the producer from the global competition etc. Ensuring a
balance between consumer demand and supply of food is a crucial issue in economic
development programme and policy making, because in general the demand for food is
inelastic and production or supply somewhat variable. In the developing countries markets
are highly imperfect and supply does not co-relate with actual demand. Thus the estimation
of demand and supply are important for national price stabilization, trade, storage, production
and other policies (Hassan and Johnson, 1976). Estimation of food demand is also interest of
policy makers for designing effective price and income support policy. Likewise other
developing country, agriculture sector is the main driving force in the economy of
Bangladesh. It is the most significant source for food supply, income generation and
employment opportunities for majority rural peoples. Agriculture sector is dominated by food
grains production. Among all the commodities, rice and wheat are the main staple food and
foodgrains in Bangladesh. The food security situation is closely linked with production,
import and price stabilization of foodgrains. Bangladesh government has pursued different
policy for achieving self-sufficiency in foodgrains production like input subsidy, price
support to producer and stable price for consumer. Rice and wheat are the major foodgrains
and the consumption demand of these grains determines the government policy and producer
positions. Thus an analysis of demand estimation and supply response with respect to price
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change needed to make an appropriate price and income support policy for the government to
attain food security.
Keeping this in view, the present study made an attempt to estimate demand and supply
response of major food grains of Bangladesh with the following objectives:
i) To study the consumption pattern and estimate the demand elasticities for rice and
wheat.
ii) To analyze the growth of rice and wheat over the years and the supply responses to
changes in price and non-price factors.
This study mainly based on secondary data, which were collected HIES, BBS and FAOSTAT
online data base and from various published and unpublished sources by the researcher
himself. This study is comprises in two parts, first part try to fulfill the first objective i.e.
consumption pattern and demand elasticity of rice and wheat using LA/AIDS model and
second part try to analyze the rate of growth in area, production, productivity of rice and
wheat, and their production responses using supply response function.
In chapter two, we discussed the foodgrains (rice and wheat) in the economy of Bangladesh
as well as food policy taken by the government. It shows that agriculture sector contributed
about 20 percent to the gross domestic product in the year 2009-2010, within agriculture; the
share of crop-sub sector is 56.25 percent which is mainly dominated by food grain
production. Bangladesh has made considerable progress in food grain production likely to the
world production trend. After green revolution and trade liberalization Bangladesh did a
tremendous success in food grain production, especially rice production. Despite this, every
year Bangladesh imported rice and wheat to meet the requirement of the growing population
and tackling unavoidable circumstance (e.g. flood and other natural calamities). After market
liberalization in 1992 large number of private importers have involved in this sector. The
food policy scenario shows that for efficient and sustainable increase in food production the
government has different strategies like agricultural diversification, developed modern
agricultural systems and extension service, provide subsidies in fertilizer, fuel and electricity
for irrigation water. Non-distortionary food grain market intervention for price stabilization
by price incentives for domestic food grain production, public grain stock and consumer price
support. The government of Bangladesh has intervention in the foodgrain market by
maintaining food grain stock considering the interest of consumer and producer.
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Chapter three is mainly theoretical concepts and model on the basis of different literatures
related to demand estimation and supply response function. For demand analysis different
literature related to single equation and systems demand equation were reviewed. It shows
that the single equation model is convenient for policy analysis but the prediction or quantity
projection do not satisfy the restriction of demand theory. Then Richard Stone (1954) first
estimated a system of demand equations which specified a particular utility function and used
directly derive the demand of his linear expenditure system, which explicitly derives from the
consumer theory(Deaton and Muellbauer, 1980) and implied all the restrictions of demand
theory. Thei (1965) and Barten (1969) developed Rotterdam model to test all the restrictions
but question arise about the true functional forms of the demand equations (Thomas, 1987). A
complete demand system using flexible functional form for describing utility function
developed by Deaton and Muellbauer (1980) based on the duality of consumer decision
making called Almost Ideal Demand System (AIDS). For analyzing cereals demand in Kenya
Nzuma and Sarker (2010) used AIDS model for estimates demand elasticity. They also
argued that the properties of homogeneity and symmetry of AIDS model can be explored
with simple parametric restrictions and the results derive from the model are consistent with
consumer demand theory, and the model are more flexible functional forms than the other
commonly used demand systems. For consumption pattern the present study focused the
household expenditure share for different food items and per capita food intake using HIES
data. For consumption demand elasticity a complete demand system will be estimated. It
concludes from different empirical studies that LA/AIDS model is more flexible for food
grain demand system analysis. Thus, the study used LA/AIDS model for estimating
consumption demand of foodgrain in Bangladesh.
The theoretical idea behind supply response model is that it is dynamic and different from
supply function; it indicates the changes in output with the changes in price as well as non-
price factors. In agriculture normally price of outputs are known after production has
occurred but cultivation decision based on the expected price. In the developing countries
farmers are rely on adaptive expectation i.e. what will happened in future based on what was
happened in the past. There are two approaches to estimate agricultural output supply
response but most of the empirical studies in the developing countries are used direct
approach i.e. Nerlovian partial adjustment and adaptive expectation, because for indirect
approach need to more details input price information which is difficult to get in the
developing countries. Since all the variables used in the model are time series and time series
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are trended over time, thus the regression between trended time series may produce spurious
results. Co-integration analysis with stationary time series data can avoid the problem of
spurious regression results (Banerjee et al., 1993). Empirical studies show that co-integration
analysis is better than Nerlovian model. For this purpose, study used simple Engle-Granger
co-integration test to estimate short-run and long-run dynamic of supply response function.
Chapter IV discusses the data sources and the specification of empirical model. Based on the
secondary, study conducted the consumption demand analysis for the period 1980 to 2006
and for the period 1980 t0 2009 for supply response analysis. The yearly time series data of
food consumption, consumer price, area under production, production, yield, irrigated area,
annual rainfall and harvested price of rice and wheat were used to study demand elasticity
and supply response using Microfit 4.0 and STATA 11 software.
The empirical results and discussion of findings are discusses in chapter V. The whole
discussion of this chapter distinguish in two sections, the first section discusses the
consumption pattern and demand elasticity of food grain. The consumption patterns of
different food items were examined using HIES data 2005. Monthly food expenditure shows
around 40 percent expenditure for foodgrains per household. Per capita consumption levels
were different between income groups in rural and urban area. Consumption of rice was
higher for high income groups in rural area and middle income groups in urban area. Per
capita consumption of wheat was higher in urban areas than rural area. Per capita per day
calorie intake from food grain has decreased in 2005 compare to the year 2000,which
indicates the changes in food consumption pattern. Before proceeding the demand elasticity
estimates using LA/AIDS model, the presence of unit roots of each budget share, consumer
price and total expenditure were tested by ADF test. Since all the variables used in the study
were time series. The ADF test results showed that all the variables are non-stationary in the
level series and stationary after first order difference at 5 percent significance level. That
means each of the series are first order integrated and suitable for further co-integration test
to examine the existence of long-term dynamics. The residual based conventional co-
integration technique suggested by Engle and Granger (1987) was used to determine the
long-run dynamic among the variables of the LA/AIDS model. The ADF and PP tests results
showed that there are no long-run dynamic of the demand system. This is may be the
problem of short period of time series data. Therefore, the LA/AIDS model was estimated in
first order difference (Klinsukon, 2001; Taljaard et al, 2004) form by means of restricted
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seemingly unrelated regression method. Before estimates the final LA/AIDS model different
tests were conducted to test the restriction of demand theory. The structural stability of the
data was tested using residuals two standard error band (Newbold, Rayner and Kellard
(2000). The results showed that in the year 1986 there was a structural break in rice and
wheat share equations. Thus study used a dummy variable for that specific year. Then the
restriction of empirical demand function; adding-up, homogeneity and symmetry were tested.
For adding-up property, the other grain share equation whose budget share is the lowest was
dropped for estimation to avoid a singular residual variance or co-variance matrix.
The Wald test were used to test the hypothesis of liners homogeneity, symmetry and both
linear homogeneity and symmetry. To implements these test, the LA/AIDS model was
estimated without imposing homogeneity and symmetry. The results showed that the null
hypothesis of valid homogeneity, symmetry and jointly homogeneity and symmetry are
accepted at 5 percent significance level, which indicates the data are consistent with
consumer utility maximizing theory. The acceptance of homogeneity conditions also can be
interpreted as acceptance of the exogeneity of expenditures (Attfield, 1985). Positive budget
share also satisfied the monotonicity in prices, which indicates the estimated parameters
satisfy the monotonicity of the underlying cost function. Since all computed own-price
Hicksian elasticities from the estimated LA/AIDS model were negative, thus the concavity of
the cost at the sample mean is ensured. The coefficient of real expenditure for rice was
negative sign and statistically significant at 10 percent level, which indicates rice is a
necessity good in Bangladesh. The expenditure elasticity for rice was 0.91 that is inelastic,
while for wheat was 1.48 and elastic that is ambiguous. Marshallian uncompensated own-
price elasticities were computed to measures the responsiveness of a particular grain to
changes with its own price. All the sign of the Marshallian own-price elasticities were
negative which satisfied the law of demand i.e. the demand decreases with the increase of
price. The Marshallian own-price elasticity for rice was -0.81 and for wheat was -0.48.
Hicksian compensated price elasticities were computed to known the substitution effects
among the goods. All the Hicksian own-price elasticities were also in negative sign. Hicksian
cross price elasticities are better for substitution effect because they only capture substitution
effect not income effect. The cross price elasticity for the demand of rice with respect to
wheat price was 0.03 and for the demand of wheat with respect to the change in rice price
was 0.20. In the second section of this chapter are discusses about the supply responses of
rice and wheat. Before estimates the supply function the annual growth rate on area,
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production and yield of rice and wheat were estimated using semi-logarithmic least square
method to know the overall trend in growth over the period. The results showed that the
growth rate of rice production was reflected by the growth rate of yield and for wheat largely
reflected by growth rate of area, and the overall growth rate of foodgrains is largely
dominated by rice production.
The ADF test was conducted for concluding about stationary of the variables and level of
integration before estimates the rice output response function. The results showed that the
variables are stationary after first order difference. But the result of the Engle-Granger co-
integration test for long-run equilibrium relationship showed that there are no unique long –
run relationships among the variables of rice output response model. Possible reason for no
co integration can be that there was structural break in several years due to natural calamities
like floods, and another reason might be inadequacy of data. Thus, supply function was
estimated with first order difference form of variables. The coefficient of real price one year
lagged was 0.11 and statistically significant, which indicates influence of price on rice
production, i.e. if the price increases then next year the farmers are trying to increase
production through advanced technology and other inputs. The coefficient of irrigated area
under rice production was positively significant, which indicates the positive influence of
irrigation water for increasing rice production. Generally, rice consumed more water than
other crops. The Boro rice is produced in the dry season and completely depends on ground
water irrigation. The productivity of Boro rice is higher than the Aus and Aman rice. Thus,
irrigation water is an important factor to increase rice production in Bangladesh. On the other
hand, wheat is the second most food grain after rice. The actual area under wheat production
is in decreasing trend and the yield is almost stagnant. Thus, for wheat area response
function was estimated to know the supply response of wheat. Before estimate the final
model the ADF test was conducted to check the time series properties of data. All the
variables are stationary after first order difference. Then the Engle-Granger residual based co-
integration test was carried out to test the long-run equilibrium relationships among the
variables. The results showed that there was no long-run unique co movement between the
variables of supply response function. The possible reason can be that the actual area under
wheat production is continuously decreasing after 2001, while the producer price is in
increasing trend, and also inadequacy of data. Thus, wheat area response function was
estimated using first order difference form of the variables with appropriate lags. The
coefficient of lagged relative price was negative and statistically significant, which indicates
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the inverse relation between price and area of wheat. The coefficient of lagged area was 0.27
and positively significant. The coefficient of area adjustment was 0.73, which indicates that
farmers‘ are highly adjusted to desire planted area. The coefficient of yield was 0.18 and
significantly positive. That means wheat area under cultivation can be increases with the
increase of yield.
6.2 Conclusion and policy implication
The broad object of this study is to estimate consumption demand and supply response of
major foodgrain (rice and wheat) in Bangladesh. To fulfill the objective the study is divided
in two parts, i.e. foodgrain demand system using LA/AIDS model and secondly supply
response function of rice and wheat. From the first part it can be concluded that the
consumption of grains is decreasing while the consumption of other non-grains is increasing.
The estimated LA/AIDS model supported the theoretical properties of homogeneity and
symmetry. Moreover, the other conditions for monotonicity and concavity of the cost
function were satisfactory. Thus, the calculated elasticities from the estimated model are
theoretical consistent and reliable. The positive income elasticity of foodgrains shows that
they are normal goods. Expenditure elasticity of rice was inelastic indicating that rice is a
necessity good in Bangladesh, while the expenditure elasticity for wheat was high and elastic.
The Marshallian uncompensated and Hicksian compensated own price elasticity indicated
that rice and wheat are price inelastic. The cross price effect shows the relatively low
substitution effects of price and no clear direction. From the supply analysis it can be
concluded that the growth of foodgrains is largely dominated by the growth rate of
production and especially rice production. Price and irrigated area under production have
positively significant influence for rice production in Bangladesh. Therefore, effective price
and irrigation policy can be increase desired output level of rice. For wheat the yield has
significant influence to increase the supply response of area.
Keeping these entire things in view, the following policy can be made
i) Since the consumers have inelastic responses to price changes; and for rice inelastic
response to income changes. Thus, only the government price intervention may not
lead to considerable impact on the consumption. A combination of price and income
policy may induce more effective in food consumption pattern in Bangladesh.
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ii) In the developing country, it is hypothesis that producer‘s are react with harvest
price. Most of the producers in Bangladesh sell their product just after harvesting.
Farmers are faced many difficulties in marketing due to lack of market information,
high marketing cost and low price during harvesting period. Therefore, price
stabilization through market intervention in the harvesting period and efficient
market can be effective for increasing domestic foodgrains production.
iii) Policy related to technological advancement, improving varieties, extension services,
fertilizer distribution, HYV seeds and production management research may increase
the productivity of foodgrains in Bangladesh.
iv) Irrigation water is important for increasing rice production in Bangladesh. Policy
related to availability of irrigation equipment and subsidies on fuel and electricity
may be more effective for increasing productivity, although the government of
Bangladesh has a policy to give subsidy on fuel and electricity for irrigation water,
but not sufficient at the farmers‘ level.
[
6.3 Limitations and possibility for further research
This study has not been considered all the aspects of food consumption and supply responses
that limit the scope of the study due to time and data constraint. Thus, the discussion of
limitations of the findings resulted the scope for further research. For food consumption
demand the study used LA/AIDS model only for cereals for the period 1980 to 2006, because
of availability of data. Thus, inclusion of other food items and longer period of time series in
the analysis would have given better results for the short-term and long-term dynamic of
consumption pattern and price policy for the consumer as well as the welfare of the different
income groups of peoples in Bangladesh. So, in future if it is possible to use recent data set
then it will be more effective for pricing policy, because recently Bangladesh has experienced
with price hiking respect to world market price. For rice output response analysis we used
only the aggregate rice production and irrigated area as non-price factors due to time and data
constraint. In future, supply response analysis with different season and varieties such as Aus
rice, Aman rice, Boro rice, local varieties and HYV‘s with different non-price factors would
be possible. Also in future research on marketing efficiency through improving marketing
activities and demand-supply estimation within simultaneous equation model could be better
results for price policy for consumer as well as producers.
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Appendix A
Table A5.1: Changes in average per capita per day quantity of food intake (gram) by food items
Food items HIES 2005 HIES 2000 % Change
National Rural Urban National Rural Urban National
Total 947.7 946.3 952.1 893.1 898.7 870.7 6.11
Food grains 469.2 485.6 419.3 486.7 502.8 422.4 -3.60
Rice 439.6 459.7 378.5 458.5 478.8 377.7 -4.12
Wheat 12.1 8.0 24.5 17.2 14.0 30.1 -29.65
Others 17.5 17.9 16.3 11.0 10.0 14.6 59.09
Potato 63.3 61.9 67.5 55.0 54.7 58.4 15.09
Vegetables 157.0 156.5 158.7 140.5 141.1 137.9 11.74
Pulses 14.2 12.7 18.6 15.6 15.0 19.0 -8.97
Milk/milk product 32.4 31.0 36.6 29.7 29.0 32.6 9.09
Edible oil 16.5 14.3 22.9 12.8 11.3 19.1 28.90
Meat, poultry, egg 20.8 17.6 30.7 18.5 15.4 31.0 12.43
Fish 42.1 39.7 49.6 38.5 37.8 40.9 9.35
Condim & Spices 53.4 50.2 63.1 50.0 48.5 56.1 6.80
Fruits 32.5 32.4 32.9 28.4 26.5 35.6 14.43
Sugar/Gur 8.1 7.5 9.7 6.9 6.4 8.8 17.39
Miscellaneous 38.2 36.9 42.5 10.0 10.2 8.9 282
Source: using HIES 2005, BBS
Table A5.2: Changes in per capita consumption of rice and wheat in rural and urban area (Kg. per month)
Year National Rural Urban
Total food
grains
Rice Wheat Total food
grains
Rice Wheat Total food
grains
Rice Wheat
2000 14.6 13.8 0.5 15.1 14.4 0.4 12.7 11.3 0.9
2005 14.1 13.2 0.4 14.6 13.8 0.2 12.6 11.4 0.7
% Change
-3.42 -4.35 -20 -3.31 -4.17 -50 -0.79 0.88 -22.22
Source: using HIES 2005, BBS
Table A3: Per capita consumption of rice and wheat by income groups in rural and urban area (Kg. per month)
Income groups Rice Wheat
National Rural Urban National Rural Urban
Poor (Below 4000Tk.) 13.80 13.48 11.77 0.25 0.22 0.40
Middle (4000 -12499 Tk.)
13.78 14.84 12.10 0.45 0.32 0.76
High (12500 and above)
13.71 16.47 11.17 0.72 0.42 1.20
All groups 13.85 14.52 11.82 0.42 0.30 0.80
Source: using HIES 2005, BBS
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Table A5.4: Changes in average per capita per day protein (in gram) intake by food items
Food items HIES 2005 HIES 2000 % Change
National Rural Urban National Rural Urban National
Total 62.52 61.74 64.88 62.50 61.88 64.96 0.032
Food grains 33.73 34.70 30.77 36.39 37.41 32.30 -7.30
Rice 32.09 33.55 27.63 33.47 34.95 27.56 -4.12
Wheat 1.45 0.96 2.95 2.06 1.68 3.59 -29.61
Others 0.19 0.19 0.19 0.86 0.78 1.15 -77.90
Potato 1.89 1.85 2.02 1.66 1.64 1.75 13.85
Vegetables 4.67 4.67 4.68 3.75 3.71 3.90 24.53
Pulses 3.52 3.16 4.63 3.83 3.62 4.68 -8.09
Milk/milk
product
0.75 0.70 0.89 1.73 1.61 2.24 -56.64
Edible oil 0.00 0.00 0.00 0.90 1.03 0.38 -
Meat, poultry,
egg
4.37 3.66 6.50 3.76 3.09 6.44 16.22
Fish 8.50 8.06 9.86 7.93 7.81 8.39 7.18
Condim & Spices 1.45 1.34 1.77 1.43 1.36 1.70 1.39
Fruits 0.79 0.79 0.78 0.71 0.65 0.91 11.26
Sugar/Gur 0.01 0.01 0.00 0.00 0.00 0.00 -
Miscellaneous 2.84 2.80 2.98 0.27 0.29 0.20 951.85
Source: using HIES 2005, BBS
Table A5.5: Co-integration test for consumer demand series
Series Dickey-Fuller co integration
test
Philips-Perron co integration
test
No trend Trended No trend Trended
Budget share of rice -2.194 -2.145 -2.898 -2.837
Budget share of wheat -2.659 -2.623 -3.193 -3.240
Budget share of other
grain
-0.989 -1.147 -1.280 -1.217
5% critical value -3.00 -3.60 -2.99 -3.59
The econometric package STATA 11 was used and the critical values are the Mackinon
approximate value for rejection of the null hypothesis of no co- integration.
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Table A5.6 Population growth rate over the period
Time period Growth rate (%)
1971/72-1979/80 2.67
1980/81-1989/90 2.35
1990/91-1999/2000 1.73
2000/01-2008/09 2.11
1971/72-2008/09 2.50
Source: Begum and Haese (2010)
Table A5.7 Engle-Granger test for long-run equilibrium co integration of rice output response
model
Regressors Dependent variables
Log of output Log of real price
Logarithm of output n. a. -.1325
(-.3547)
Logarithm of real price 0.034
(0.349)
n. a
Logarithm of irrigated area 0.746
(11.577)
.0190
(.0639)
D90 -0.129
(-2.180)
-.2573
(-2.080)
D95 -0.139
(-2.009)
-.0451
(-.317)
Intercept 3.917
(5.557)
5.6028
(3.051)
ADF(-1) -2.839 -3.117
DW 0.962 1.071
Figure in parentheses are the t statistic. ADF is Augmented Dickey-Fuller statistic with
critical value -4.978 at 5 % significance level, n. a. = not available
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Table A5.8 Engle-Granger test for long-run equilibrium co integration of wheat area response
model
Regressors Dependent variables
Log of area Log of relative price Log of yield
Logarithm of area n. a. .1307
(.8210)
.1777
(1.3007)
Logarithm of relative
price
.1932
(.8210)
n. a. .0829
(.4859)
Logarithm of yield .3437
(1.3007)
.1085
(.4859)
n. a.
Logarithm of irrigated
area
-.4865
(-2.544)
.5772
(4.2937)
.0183
(.1191)
Intercept 8.0335
(10.497)
-3.067
(-2.342)
-.5661
(-.4512)
ADF(-1) -2.490 -3.208 -3.53
DW 0.318 1.86 1.287
Figure in parentheses are the t statistic. ADF is Augmented Dickey-Fuller statistic with
critical value -4.564 at 5 % significance level, n. a = not available
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Declaration
I do thereby earnestly declare that I have completed the preceding independently, and have
not used any other sources or aids apart from those listed
Date Signature
