Mathews Madola [email protected] University of Greenwich Natural Resources Institute.
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Transcript of Mathews Madola [email protected] University of Greenwich Natural Resources Institute.
Mathews [email protected]
University of GreenwichNatural Resources Institute
OutlineBackground and MotivationProblem StatementKey Research QuestionsConceptual Framework (Institutional
Analysis) Methodology and Data CollectionPreliminary Results Emerging Conclusions
BackgroundThere is a growing trend towards the promotion
of farmer organisations as a poverty reduction strategy to improve smallholders access to inputs, extension services and output markets.
It is therefore important understand benefits and effects of this institutional arrangement.
Most studies have concentrated on the effects of contract farming
Problem StatementFarmers no longer assured of ready markets
for their products.Face volatile market prices in place of a
previous system of stable markets (state-guaranteed prices)
Decreased access to credit and inputs.Negatively affecting output and productivity
Research QuestionsThe Key research questions are:
What are the determinants of participation in farmer organisations?
What is the impact of participation on household income (performance ) ?
Conceptual Framework and Institutional Analysis
We develop the conceptual framework following Williamson (1991) and link it to an institutional analysis to identify the factors determining the current organisational form of production and marketing in the cotton sub-sector in Malawi.
The analytical model follows the ones used in applied work in transaction costs (e.g. Doward, 2001)
The likelihood of observing a particular market institution is a function of certain properties of the underlying transaction
Can be expressed as Y=Ω[X], where Y is a vector of alternative marketing arrangements i.e. spot marketing, contract marketing and collective marketing (farmer organisations)
Conceptual Framework (cont’d)
X is a vector of transaction characteristics that affect transaction costs i.e. asset specificity, uncertainty, complexity and frequency of transactions.
The level of X is influenced by production, marketing characteristics, and the economic and political environment.
Framework the used to explain how these factors affect transaction costs and choice of organisational form
Transaction Costs and Marketing Institutional Arrangements
Factor Effect on Transaction Costs Type of Marketing Institutional Arrangement Most Favoured
Spot Marketing Contract Marketing
Collective Marketing
Production Characteristics
Economies of scale
High returns to inputs
Requires high initial investment and high cash flow & not feasible for smallholders
Requires effective research and extension and timely availability of inputs
X
X
X
X
Marketing/Processing characteristics
High economies of scale in processing
High Quality standards
Many potential buyers
The need for complimentarily creates a strong incentive for a stable supply of raw materials through more coordinated arrangements
Increases returns to close vertical coordination
Increases costs and risk of default (side selling) X
X
X
X
X
Endogenous economic & political factors
Poorly integrated output markets
Missing input/factor markets
Poor communication
Low literacy levels/education levels
among farmers
Weak contract enforcement
Increases the costs of procurement and marketing. Increases returns to coordination.
Increases returns to vertical coordination
Raises the costs of vertical coordination
Raises the costs of ensuring the adoption of new technologies and raises the costs of collective action
Increases uncertainty and increases risk of default
X
X
X
X
X
X
X
X
X
Methodology & Data CollectionUsed a structured questionnaireInterviewed smallholder farmers growing
cotton 170 respondents (83 participants and 87 non participants).
Also did some key informant interviews
Distribution of the SampleDistrict EPA/Chapters MACS Villages Households
Balaka Bazale 3 3 40
Utale 2 3 35
Ulongwe 3 3 40
Ntcheu Manjawira - 3 30
Bilira - 3 25
Methodology : Determinants of Participation
We will estimate the following probit model : m
PARTi = φ0 + ∑φjxj +e2
j=1
xj is a vector of exogenous variables assumed to influence the participation decision; φjs represents estimated marginal effects of the determinants of participation; PART is a dummy variable that takes a value of one or zero
Impact of Participation on Incomes (Performance) We will use propensity score matching methods
applied in programme evaluation. Use four matching methods to enhance the
robustness of our comparisonsNearest Neighbor RadiusKernelStratification matching
Our aim is to determine whether participating households have significantly higher crop and household incomes than non-participants.
Endogenous Switching Regression We also estimate the endogenous switching
regression model to take into account selection biasWe use this model to examine how farmers
characteristics affect their decisions to participate in a farmer organisations and their income (performance) with or without the farmer organisation.
We will also compare farmers expected performance (income) with the farmer organisation and without the farmer organisation
The following model describes farmers’ choices about participating in a farmer organisations and their performance with and without a farmer organisation
Impact of Participation (cont’d)
If δZi + ut > 0 , farmer i chooses to join a farmer organisation, described by Ii =1 (A)
If δZi + ut ≤ 0 , farmer i chooses not to join a farmer organisation, described by Ii =0
Then income (performance) equations associated with each alternative can be expressed as
Participants :ln y1i = x1ß1 + et0 if j = 1 (B)
Non-participants :ln y0i = x0ß0 + et1 if j = 0 (C)
Zi is a vector of farmers characteristics that affect decisions to participate in farmer organisation
ln y01 and ln y0i are natural logs of income (performance) for participants and non-participants, respectively; δ, ß’s are unknown parameters
Assume that ut , et0 and et1 are three random terms that follow a trivariate normal distribution
The methodology involves estimating system of equations (A), (B) and (C) equations by FIML as suggested by (Loskin and Sajaia, 2004)
Results-Comparison of Means
Selected Variable Type of Farmer
Participants Non-ParticipantsDemographic Variables
Female Headed households (%)
Education Household Head
Age of the Household Head
Household Size
Dependency Ratio
Farm Assets
Total Area (Acres)
Value of Manual tools (MK)
Use of Hired Labour
Permanent Labour (% using)
Casual labour (% using)
Income Diversification (%)
Livestock Ownership
Grows other cash crops
Small business
Household Income (MK)
Net Household Income
Net Agricultural Incomes
Net Cotton Incomes
Business Income
Livestock Income
Social Capital
Past Group Experience (1)
Friends in a FO (1)
18.29
2.819
44.386
5.264*
0.367
4.012
2, 759.40
2.41
43.37*
80.72
72.29*
80.72
41,874.40**
35,608.72***
26,665.12**
3,748.19
1,966.27***
0.928***
0.940***
11.49
2.598
41.598
6.217*
0.313
4.597
2, 908.20
2.30
22.99*
85.06
52.87*
70.11
30,935.28**
25,875.52***
18,361.71**
4,080.46
505.75***
0.448
0.414
Number of Observations 82 87
Initial Results from Probit ModelThe availability of alternative sources of income reduces
the likelihood of participation. Other cash crops income that are more lucrative and business income are negatively related to the likelihood of participation although the business income is not statistically significant
Household size is positively related to participation in a farmer organisation
Households with more educated household heads are less likely to participate in farmer organisations.
The ownership of assets value of agricultural tools is positively related to probability of participation while land is negatively related to participation.
Having a friend who is a member of a farmer organisation (social capital), the more likely the household will participate.
Emerging ConclusionsInitial analysis indicates that FO leads to
higher income (performance of participants) .
Other benefits of participation include reliable markets, stable prices and reduced
uncertainty
The social capital in farmer organisations has reduced the problems of writing, enforcing contracts prevalent in Malawi (culture of wilful default)
Thank you for your attention!