Mathews Madolamm87@gre.ac.uk

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!