Post on 23-Dec-2015
transcript
Analysis of the environmental services provided by selected farming systems in
Ghana
Module 2: Environmental externalities II
(site specific study)
A. Wayo SeiniGeorge Botchie
andLawrence Damnyag
outline
Introduction Characterization of the farming systems
and their environmental implications Variables and functional model Sample characteristics and attitude on
payment Determinants of willingness to pay for agro
forestry attributes Replacement cost evaluation of
environmental externalities Conclusion
1.1 Purpose of the study
The report focuses on the analysis on the environmental services provided by selected farming systems in Ghana
The main purpose is to obtain the micro-economic analysis of major environmental externalities
Semi-deciduous forest & Sudan savannah farming systems are selected
1.2 Evaluation of physical/Biological impact
Major attributes of the semi-deciduous forest zone farming systems comprise;
• permanent tree crops and rational bush fallow of food crop farming systems
The permanent tree crops such as cocoa are usually intercropped with timber trees, fruit trees and medicinal plants
In the interior savannah zone, mixed farming & livestock farming are important attributes of farming systems
• Another important attribute of this zone is the compound farming system
1.2 Evaluation of Physical/Biological impact(cont’d)
Externalities produced by the characteristics of the selected farming system vary
In the semi-deciduous forest zone, the agro forest farms generate positive environmental externalities in terms of
• Soil erosion prevention• Groundwater retention & recharge• Restoration of water quality due to eutrophication• Biodiversity preservation• Watershed and catchment area protection• Carbon sequestration and • Beautification of rural landscapes
In the interior zone, the farming system operates under harsh environmental conditions characterized by
• Flooding of rivers, soil erosion, deforestation etc
1.3 Rationale for farming systems selection
The two alternative systems selected present contrasting system characteristics in terms of;
• Agro-ecological setting• Farming practices• Crops cultivated and• Externalities generated
Semi-deciduous forest agro-ecological zone is characterized by agro-forestry farming systems
• This generates positive environmental externalities
The interior savannah agro-ecological zone experiences rotational bush fallow systems that generates negative externalities
1.4 Methodology for measurement & evaluation
1.4.1 Contingent valuation method Contingent valuation method was used to
analyze the survey CVM is a survey technique It is used to place monetary values on
products & services for which market prices do not exist or
CVM can measure a larger proportion of the total economic value associated with agro-forestry attributes the study investigates
1.4.2 Replacement cost method
Replacement cost method (RCM) uses the cost of replacing an ecosystem or
• Its services as an estimate of the value of the ecosystem or its services
The cost of restoring a river or wetland can be used as estimates of the cost of environmental damage of these natural assets
In RCM, goods & services traded in the market are used instead of the functions to be evaluated
In this study the aim is to estimate the annual replacement cost per hectare of the most relevant environmental functions in study area
1.5 Questionnaire design
Questionnaire was structured to capture the maximum amount of money the respondent is willing to pay for the overall benefits from agro-forestry farm
1.6 Method of data collection
Convenient sampling method was used All qualified farmers who turned up
were willing to be interviewed and In some cases those who exceeded our
target were number disappointed Convenient sampling allows the
researcher to meet the target sample size without compromising too much on the randomness of the sample
1.7 Value elicitation
This study employed the double bounded, followed up with open ended format
This format involves a straight forward estimation and the maximum willingness to pay obtained
It does not preclude the problem of starting point bias
It is not suited for mail survey, face to face interview was conducted
1.7 Value elicitation(cont’d) The main valuation question was on the overall benefit arising
from an acre of agro forestry farm It was framed as follows:
“Agro forestry plays multifunctional roles. It enhances soil erosion prevention ; water retention and ground water recharge; provision of habitat for wild life, carbon sequestration and rural amenities preservation. Flooding is prevented by agro forestry. In view of all these benefits that agro forestry provides, are you willing to pay $ X to protect all these environmental benefits, arising from one hectare of agro forestry farm”
The bid selection proceeded the main question on the maximum amount the respondent was willing to pay for these agro forestry attributes
Variables and functional model
3.2 Dependent variable: willingness to pay (WTP)• WTP is defined as the maximum willingness to pay after
two bids(lower & higher)• With this method, straight forward estimation is done ,
using the maximum willingness to pay obtained 3.3 Independent variables
• Income(TMINCH)• The effect of income of the household is expected to be
positive• Age of respondent(AGER)• Young people tend to be more aggressive in seeking
information and• And are likely to adopt agro forestry practices and new
technologies due to their longer planning horizon
Variables and functional model (cont’d)
3.3.3 Gender of respondent(GENDER)• A dummy variable coded as 1 if respondent
is a male, or 0, otherwise• Males are more likely to own lands in the
study area than females• Male farmers will be more willing to pay for
total benefits from agro forestry3.3.4 Education of respondent(EDYR)• Education enhances people’s perception of
the advantages that a new technology or practice has
• The effect of education on WTP is therefore generally expected to be positive
Variables and functional model(cont’d)
3.3.5 Main occupation of household head (MECOR)
•Farmers are more likely to be more willing to pay for total of benefit from agro forestry
3.3.6 Initial bid (INITIALBID)•The value of the initial bid is tested for
starting point bias and•If this is significant it either negatively
or positively influences the final maximum WTP, & the estimations suffer from starting point bias
Variables and functional model(cont’d)
3.3.7 Protest bid (PROTEST)• A dummy variable, PROTEST is generated • It is expected to negatively impact the
maximum WTP3.3.8 Importance of agro forestry(LIAFAR)• LIAFAR measures the level of importance
of agro forestry to the respondent• The attributes are improve scenery,
prevent soil erosion, improve wildlife, etc• Each is taken as a variable &• its impact on the maximum WTP
examined
3.4 The functional form
The functional form assumes a utility function that is positive, but increasing at a decreasing rate
That is, WTP function is similarly shaped. That is;
Y )1(0 ii X Y = W i l l i n g n e s s t o p a y ( W T P ) , a n d X i = V e c t o r o f t h e i n d e p e n d e n t v a r i a b l e s .
)2(876
54321
i
sa va n n a h
LIAFARPROTESTDINITIALEBI
MECOREDYRGENDERAGERTMINCHWTP
)3(876
54321
i
d ecid u o u s
LIAFARPROTESTDINITIALEBI
MECOREDYRGENDERAGERTMINCHWTP
)4(876
54321
i
p o o led
LIAFARPROTESTDINITIALEBI
MECOREDYRGENDERAGERTMINCHWTP
4.0 Sample characteristics and attitudes on payment
4.2.1Gender of respondent 4.2.2 Age of respondents 4.2.3 Household size 4.2.4 Education of respondent 4.2.5Major occupation 4.2.6 Household income 4.3 Attitudes on payment
Table 4.7: Responses to some attitudinal questions
Percentage of respondents in each sample indicating that: Savannah Forest Combined 1. To pay for the overall benefits arising from a hectare of agro-forestry farm;
Government should be responsible 3.5 22.0 12.8 District Assembly should be responsible 5.0 5.0 5.0 Willing to pay but cannot afford 9.0 15.0 12.0 Others 0.5 0.3
2.Rate agro-forestry attributes in terms of importance a.improve scenery;
Indifferent 5.5 3.0 4.3 not important 10.0 9.5 9.8 important 47.5 59.0 53.3 very important 29.5 18.5 24.0 extremely important 6.5 10.0 8.3
b. Prevent soil erosion indifferent 4.3 not important 0.5 1.0 9.8 important 18.5 27.5 53.3 very important 60.0 62.5 24.0 extremely important 20.5 9.0 8.3
c. Improve wildlife indifferent 11.5 10.5 11.0 not important 32.0 11.0 21.5 important 37.0 41.5 39.3 very important 15.5 28.5 22.0 extremely important 3.5 7.5 5.5
Table 4.7: Responses to some attitudinal questions(cont’d)
d. Supply fuel wood indifferent 0.5 0.3 not important 0.5 10.5 5.5 important 8.5 48.0 28.3 very important 39.5 22.0 30.8 extremely important 51.5 19.0 35.3
e. Improve water retention indifferent 0.5 1.0 0.3 not important 1.5 5.0 5.0 important 44.0 23.0 33.5 very important 42.0 63.5 52.8 extremely important 10.0 7.5 8.8
f. Increase soil fertility indifferent 0.5 0.3 not important 0.5 1.0 0.8 important 10.0 13.0 11.5 very important 43.0 56.5 49.8 extremely important 46.0 29.5 37.8
g. Enhance carbon sequestration indifferent 5.0 10.0 7.5 not important 8.5 8.5 8.5 important 42.5 39.0 40.8 very important 30.0 35.5 32.8 extremely important 13.5 6.5 10.0
5.0 Determinants of willingness to pay for agro forestry attributes
Table 5.1: Semi-Deciduous Forest Table 5.2: Sudan Savannah System
*** Significant at 1%; **significant at 5% and * Significant at 10%
Dependent variable =
MWTP
Variable Estimated
Coefficient t-ratio
Constant 15741.88 0.62 Age -22.95*** -3.63
Gender 14.44** 2.25 Protest 23.98*** -6.99
Household income
867.24 1.25
Improve scenery 4769.40 0.98 Prevent soil
erosion -6679.68 -0.41
Supply fuel wood
-346.76 -0.62
Improve wildlife -0.35 -0.22 Improve water
retention -
19434.66**
-2.91
Enhance carbon sequestration
-1.77 -0.08
Increase soil fertility
9286.25 -0.60
R-squared Adjusted = 0.66 Mean of dependent variable = 54,780.75 Sample size = 200
Dependent variable =
MWTP
Variable Estimated
Coefficient t-ratio
Constant 5163.53 1.42 Age -13.18* -1.70
Initial bid 0.68*** 13.45 Protest -13.44*** -3.74
Household income
28.81** 2.23
Gender 7.00 0.84 Prevent soil
erosion 3.55 0.19
Increase soil fertility
1723.60 0.59
Supply fuel wood
-4367.47* 1.58
R-squared Adjusted = 0.57 Mean of dependent variable = 70,831.55 Sample size = 200
5.1 Semi-deciduous forest system
Factors influencing WTP for agro-forestry attributes are Improve scenery, increase soil fertility,
improve water retention, prevent soil erosion, gender & age of farmer
Age has a negative sign that coincides with what is in the literature
Improve water retention is significant at 5% level
5.2 Sudan Savannah System Factors determing WTP are;
• Supply of fuel wood, household income, & age
They all have the expected a priori signs There are differences in the valuation of
the determinants of WTP between 2 systems
Age is significant determinant in both systems
• but the level is lower in the Sudan savannah (10%) than in the forest system (1%)
• Farmers in the forest system are relatively younger than in the savannah system
• Gender is not significant in Sudan savannah, & is significant
6.0 Replacement cost valuation of environmental externalities
Table 6.1 Components of Costs for Cassia/Sorghum Agro-forestry Component Cost/Ha./
Year (¢)
% of Annual
Cost/Year
1. Cassia Seedlings 8,000 0.37
2. Sorghum Seeds 25,000 1.16
3. Capital Costs 60,000 2.77
4. Labour Costs 624,000 28.86
5. Fencing Costs 31,250 1.45
6. Irrigation Costs 4,000 0.18
7. Nutrient Replacement 1,210,000 55.96
8. Pest Control 200,000 9.25
TOTAL 2,162,250 100.00
Sudan savannah (RCM) Components of the RCM cost per hectare of
cassia/sorghum agro-forestry are indicated in table 6.1
Average yearly cost per hectare is ¢2,162,250• It is a sum of the components in the table 6.1• This amount is recurring cost to maintain agricultural
production in a hectare of cassia/sorghum agro-forestry farm &
• repair damages caused by soil erosion• RCM of soil erosion prevention thro’ agro forestry was
discounted over 15-yr period at • discount rate of 23% to obtain present value of
replacement• The PV of the RC for a hectare over 15-yr period is ¢ 8,879,080.35
6.2 Semi-deciduous forest The prevalent agro-forestry practiced is
teak intercropped with cocoa Trees planted in the teak/cocoa agro-
forestry to be replaced after 20yrs This based on the number of years it
takes for the teak & cocoa trees to mature
RC per hectare of teak/cocoa agro forestry included the following in Table 6.2
Table 6.2 Components of Costs for Teak/Cocoa Agro-forestry Component Cost/Hectare/
Year (¢)
% of Annual
Cost/Ha.
1. Seedlings 21,640 0.63
2. Plantation Establishment 174,190 5.06
3. Maintenance of Plantation 2,339,200 67.96
4. Capital Costs 289,000 11.30
5. Miscellaneous Costs (Fire
Belt, Patrolling, etc)
618,000 15.05
TOTAL 3,442,030 100.00
The replacement cost hectare of a teak/cocoa agro-
forestry farm is ¢3,442,030/hectare per year
The most important component of RC per hectare per annum is maintenance of plantation, that accounts for about 68% of costs
Construction of fire belt & patrolling is the 2nd most expensive item, accounting for over 15%
It shows the importance attached to the risk of an outbreak of fire on the teak/cocoa agro forestry farm
The replacement cost of soil erosion prevention thro’ teak/cocoa agro-forestry was discounted over a 20-yr period at a discount rate of 23% to obtain the present value replacement
The PV of the RC for a hectare of a teak/cocoa agro-forestry farm over a 20 year period is ¢14,548,687, in contrast to ¢8.8 million in the Sudan Savannah
6.0 Replacement cost valuation of environmental externalities(cont’d)
It is more expensive to replace damage caused by soil erosion in the forest system than in the savannah system
The value of replacing a hectare of positive environmental externalities thro’ agro-forestry is ¢ 5.7million (64.8%) higher in the semi-deciduous forest farming system than in the Sudan Savannah
6.0 Replacement cost valuation of environmental externalities(cont’d)
Another valuation is annual cost of a hectare of agro forestry in the Sudan Savannah thro’ small-scale irrigation dam
Given 15 years life span, average RC per hectare per year is ¢2,363,333
With trees planted on the land, RC of a hectare of agro-forest farm will have to be added to the RC of water conservation and retention to get ¢ 4,525,583 per hectare per year
The PV of RC of water conservation & retention that includes agro-forestry for a hectare of land in the Sudan savannah is ¢ 18,583,889.50
Table 6.3 Summary of valuation per hectare per year (cedis)
Method Forest Savannah Contingent valuation:
Average willingness to pay
54,780.75 70,831.55
Replacement cost valuation:
Without irrigation 3,442,030.00 2,162,250.00 With irrigation - 3,724,500.00
Conclusion Farmers are willing to pay for a wide range of
positive environmental externalities generated thro’ agro-forestry practices
The WTP differs between the 2 agro-ecological farming systems in Ghana
The WTP is much higher in the Sudan Savannah than in the semi-deciduous forest system
The plausible explanation is the very harsh environmental conditions confronting farmers in the Sudan savannah
Conclusion (cont’d) Supply of fuel wood & increase in soil fertility are
extremely important to farmers in the Sudan savannah
the most important attributes to the farmers in the semi-deciduous forest system are
improvement in water retention & prevention of soil erosion
Measures to generate positive environmental externalities add value to the farming systems
Policy makers are to regard these measures as additions to the quality of the environment in which farmers operate