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PPS232S.01 Microeconomics of International Development Policy. 4. Market participation. Market Failure as a Household-Specific Phenomenon. de Janvry, Fafchamps, and Sadoulet (1991) develop a framework in which market failures are household-specific .

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market failure as a household specific phenomenon
Market Failure as a Household-Specific Phenomenon

de Janvry, Fafchamps, and Sadoulet (1991) develop a framework in which market failures are household-specific.

Households face transactions costs (TCs), which insert a wedge between the effective price received or paid by the household, thereby creating a “price band” around the market price.

The lower bound of the price band is the sales price (s), and the upper bound of the price band is the purchases price (b).


Market Failure as a Household-Specific Concept



If marginal utility falls within

price band, the household

remains autarkic, i.e., does

not participate in market.

“Price band”



the price band two types of transactions costs
The “Price Band”: Two Types of Transactions Costs

The TCs faced by the household come in two varieties:

  • Fixed transactions costs (FTCs): These are akin to fixed costs in production theory, i.e., they do not vary according to the number of units purchased or sold (e.g., licensing cost, fees, etc.)
  • Proportional transactions costs (PTCs): These are akin to variable costs in production theory, i.e., they are per unit costs (e.g., inspection fees, transportation costs, etc.)
two types of transactions costs
Two Types of Transactions Costs

Assume the FTCs are represented by fj and the VTCs are represented by vj, where j is in {s,b} and denotes sales or purchases. These TCs are household-specific.

Then we have


empirical evidence on market participation
Empirical Evidence on Market Participation

Much of the literature on market participation is empirical.

The theoretical bases for the econometric analyses of market participation are provided by the unitary AHM, which we discussed in the last module.

In other words, the unitary AHM is a suitable analytical tool for analyzing the market behavior of households, since market participation is a household-level phenomenon, typically.

goetz 1992
Goetz (1992)

The first significant study of market participation behavior is Goetz (1992), who studies participation in grain markets in Senegal.

The novelty of his approach is that he considers first the decision whether to participate or not (i.e., participants vs. non-participants) and, conditional on being a participant, he estimates a regression for buyers and one for sellers.

This allows controlling for selection bias. How so?

goetz 19921
Goetz (1992)

As regards market participation, Goetz finds that:

  • The variables that affect likelihood of participating as a buyer are the price of coarse grains (+), the price of rice (+), access to a grain transformation technology (-), number of persons in the household (+), age of the household head (-), the age of the household head squared (+), and whether the household owns a cart (-).
  • The variables that affect the likelihood of participating as a seller are the age of the household head (-), and the age of the household head squared (-).
goetz 19922
Goetz (1992)

As regards quantities purchased and sold:

  • The variables that affect the quantity purchased, conditional on having chosen to be a buyer: the price of grains (-), the price of rice (+), access to transformation technology (+), and the number of persons within the household (+).
  • The variables that affect the quantity sold, conditional on having chosen to be a seller: the price of grains (+), the price of rice (-), access to transformation technology (+), and the household’s dependency ratio (-).
key et al 2000
Key et al. (2000)

One problem with Goetz’ approach is that he does not explicitly take transactions costs into consideration. Given the simple theoretical framework we’ve seen above (i.e., the “price band”), that is a considerable omission.

Key, et al. (2000) develop a structural model of supply response which specifically takes into account FTCs and PTCs.

Their study looks at the maize market in Mexico.

key et al 20001
Key et al. (2000)

Key et al. conclude that both FTCs and PTCs matter in the supply of corn of Mexican households, with PTCs being more important in the selling rather than buying decision.

In terms of policy, their study empirically shows how pricing policies can have different effects for different households.

Additionally, they provide further evidence that policies aimed at reducing transactions costs can directly stimulate development via market access.

fafchamps and hill 2005
Fafchamps and Hill (2005)

Using data from Uganda, Fafchamps and Hill (2005) look at a slightly different aspect of market participation by studying the determinants of coffee sales at the farm gate instead of at market.

Including the relevant transaction costs, they find that market sales are more likely than farm-gate sales for large quantities and when the market is close by.

bellemare and barrett 2006
Bellemare and Barrett (2006)

In Bellemare and Barrett (2006) paper, we take Goetz’ (1992) analysis one step further by expanding the first-stage to explain the determinants of being a net buyer, autarkic, or a net seller. Our approach also incorporates FTCs and PTCs, unlike Goetz’.

bellemare and barrett 20061
Bellemare and Barrett (2006)

Net sales of livestock are equal to sales minus purchases (M = S – B).

  • If M > 0, a household is a net seller
  • If M = 0, a household is autarkic
  • If M < 0, a household is a net buyer

We first estimate the determinants of this ordered, categorical choice (negative, zero, or positive net sales).

Then, conditional on the category (negative or positive net sales), we study the determinants of the extent of market participation.

bellemare and barrett 2006 decision tree
Bellemare and Barrett (2006): Decision Tree

y1 = 0 if M < 0

y1 = 2 if M > 0

y2 > 0 if y1= 0

y1 = 1 if M = 0

y3 > 0 if y1= 2



beyond spot markets agricultural value chains
Beyond Spot Markets: Agricultural Value Chains

The remainder of this module looks at market participation, but at market participation defined more broadly than just spot market participation.

We will be discussing participation in (agricultural) value chains, a mechanism that allows households to grow cash crops and which integrates them into a more industrialized sector of the economy, i.e., agribusiness.

The institution of contract farming allows a firm to delegate its production of agricultural commodities to (many) small producers. It is a step towards vertical integration. away from spot markets.

beyond spot markets agricultural value chains1
Beyond Spot Markets: Agricultural Value Chains

The typical agricultural value chains is structured as follows:

Agricultural households (“growers,” the agents in these contracts)

→ Agribusiness firm (“processor,” the principal in these contracts)

→ Distributors, if they are necessary

→ Stores and supermarkets, either in-country or foreign

→ Consumers

Although there is a small literature on supermarkets in developing countries, we will look at the first link in those value chains – grower-processor contracts, or contract farming arrangements.

typical contract farming arrangement
The sequence for a typical contract is:

1. The grower and the processor agree on the amount of land contracted upon, and (usually) on the price at which the processor buys the commodity.

2. The grower undertakes production using his own inputs and (usually) inputs provided by the processor.

3. The grower experiences a shock i.e., realization of agro-climactic uncertainty.)

Typical Contract Farming Arrangement
typical contract farming arrangement1
4. The processor supervises the agent (traditional “policing” and extension services.)

5. The grower harvests and chooses how much to “leak” (i.e., side-sell on the local market.)

6. The grower reimburses the processor in crop for the input advance and sells the remainder of the crop to the processor at (possibly pre-agreed in stage 1) price.

It should thus be obvious that there is ample scope for moral hazard and for things to go wrong in general.

Typical Contract Farming Arrangement
sustainability of contract farming
Although contract farming may seem like yet another “silver bullet” for development (much like microfinance), these contracts are extremely difficult to sustain in practice.

Example: Minten et al. (2009) and inflation. In 2004, everything went well with a (fixed) price written in the contract. In 2005, after a year of rampant inflation, the written price became ridiculously low, and almost every grower decided to renege on their contracts and sell on the local market.

Sustainability of Contract Farming
sustainability of contract farming1
Moreover, it’s not all that obvious that contract farming actually makes people better off.

Indeed, participation in contract farming is usually endogenous to welfare (people select into it based on an expected boost in welfare, or wealthier people are the ones who can afford to participate), and the instruments used so far in the literature have been less than satisfactory.

Example: Using trustworthiness as an instrument for participation when trying to study the impact of contract farming on. Why is this a bad IV?

Sustainability of Contract Farming
sustainability of contract farming2
Still, if a contract farming arrangement is well-crafted and includes mechanisms to prevent moral hazard, these contracts have the potential to:

1. Disseminate technical knowledge.

2. Encourage new technologies (e.g., composting).

3. Increase welfare and reduce vulnerability.

4. Create employment in the agricultural services sector, depending on the level of vertical integration.

Sustainability of Contract Farming
empirical evidence
Above and beyond welfare impacts, many other questions are still unanswered by empirical work:

1) Who actually participates in these contracts?

2) How does the match between grower and processor occur?

3) How do processing firms choose where to locate their contracting activities?

4) Etc.

Empirical Evidence
empirical evidence1
Little and Watts (1994) have an edited volume (i.e., a collection of essays on contract farming) that presents case studies of

- Horticulture in Kenya,

- Sugar, tea, and cotton contracts in Zimbabwe ,

- Rice in the Gambia, and

- Palm oil in Côte d'Ivoire and in Ghana.

But given the book title (Living under Contract), you can imagine what kind of ideological bent it might have.

Empirical Evidence
empirical evidence2
Grosh (JAfrEcon, 1994)

She presents a discussion of contract farming viewed through the lens of the New Institutional Economics (NIE).

New Institutional Economics: An economic perspective that attempts to extend economics by focusing on the social and legal norms and rules that underlie economic activity; NIE has its roots in Coase’s insights about the role of institutional frameworks and transaction cost. The approach was rewarded with several Nobel prizes – Coase in 1991; North in 1993; Ostrom and Williamson in 2009; and the 2010 laureates, to some extent.

Empirical Evidence
empirical evidence3
Grosh (1994)

She provides extensive background on the nature and scope of contract farming by explaining how it can serve as a response to common market failures.

Moreover, she presents a case study of Kenyan contract farming.

Empirical Evidence
empirical evidence4
Grosh (1994)

Market failures that can be remedied through contract farming:

1. Risk and uncertainty: Missing insurance markets; portfolio diversification.

2. Imperfect factor markets: Especially for certain inputs such as credit, seeds, pesticides, fertilizer, etc.

3. Coordination failures: Technology adoption, private agricultural extension services.

Empirical Evidence
empirical evidence5
Key and Runsten (World Dev, 1999)

They study frozen vegetable contracts in Mexico. They identify three different types of contract farming arrangement, which are not necessarily mutually exclusive:

1. Market Specification: Forward contracts between growers and processors which usually specify price, quality, and timing.

2. Resource Provision: Contracts in which the processor provides certain inputs, credit, or extension services.

3. Production Management: Bind the grower to a certain production method or specifies specific input intensities, in exchange of which the processor promises to market the output for the grower.

Empirical Evidence
empirical evidence6
Key and Runsten (1999)

Conclusion: The scale of contract farming is limited by the transactions costs of contracting with a large number of heterogeneous (i.e., very different) growers, so that most processing firms find it more profitable to deal with fewer large growersrather than many small ones.

Empirical Evidence
empirical evidence7
Warning and Key (World Dev, 2002)

Case study of the arachide de bouche(a specific variety of peanut) program in Senegal.

Even though contract farming implies higher incomes for the households who choose to participate in these agreements, participants and non-participants are indistinguishable when it comes to wealth – i.e., contract farming does not make the wealthy households wealthier at the expense of poor households.

This is a question with important distributional implications, since it means that the institution of contract farming does not increase inequality, at least in that specific context.

Empirical Evidence
empirical evidence8
Bellemare (2011)

The problem with all the aforementioned studies, however, is that they fail to credibly estimate the causal impact of participation in agricultural value chains in general and of contract farming in particular.

Indeed, because participation is nonrandom, it is very difficult to isolate its effects (and only its effects) in a regression of some welfare outcome on participation. In other words, there is a classic selection bias problem in this literature.

Empirical Evidence
empirical evidence9
Bellemare (2011)

The identification strategies used range from no identification strategy (Singh, 2002) to using agent trustworthiness (Warning and Key, 2002), the number of organizations an agent belongs to (Simmons et al., 2005), the distance between an agent’s and the village chief’s farms (Miyata et al., 2007) as instrumental variables, and to simply asking respondents whether they think they’re better off than in the alternative (Minten et al., 2009).

What is wrong with all those approaches?

Empirical Evidence
empirical evidence10
Bellemare (2011)

In 2008, a colleague and I received a consulting offer from the Economic Development Board of Madagascar, who wanted to know what drove participation in contract farming, and whether participation in contract farming made people better off.

On top of receiving consulting honoraria (which ended up never being paid), this was going to allow us to write our own survey questionnaire, which meant that we could get the best IV we could think of.

Empirical Evidence
empirical evidence11
Bellemare (2011)

So we asked each respondent (i.e., both nonparticipants and participants in contract farming):

“Would you be willing to enter a contract farming arrangement that would increase your income by 10 percent but which would require an initial investment of $X?,”

where $X was randomly generated in the field via the throw of a die and ranged from $12.50 to $75.

Empirical Evidence
empirical evidence12
Bellemare (2011)

A digression: The method by which I estimated WTP is generally called the contingent valuation (CV) method.

It is commonly used by environmental economists to estimate people’s intrinsic valuation of goods for which there exist no markets per se.

For example, when we want to know the exact WTP of individuals for green spaces in their city, for clean air, for clean water, etc. This then allows levying the right taxes.

Empirical Evidence
empirical evidence13
Bellemare (2011)

This allowed me to estimate each respondent’s willingness-to-pay (WTP) to enter contract farming based on a fully exogenous source of variation (i.e., the randomly generated price).

I then use this as a variable that

Explains participation in contract farming (instrument strength assumption; easily testable);

Is independent from welfare (exogeneity assumption; not testable).

Empirical Evidence
empirical evidence14
Bellemare (2011)

Let’s look at the latter requirement. Why could this work as an IV?

Unobserved heterogeneity: WTP allows controlling for people’s preferences for risk, time, etc. as well as for their level of entrepreneurship and technical ability.

Measurement error: I assume that there is no systematic under- or over-reporting of people’s participation in contract farming.

Reverse causality/Simultaneity: This is the big weakness, especially given the question posed. Still, no evidence that this is actually happening in this context.

Empirical Evidence
empirical evidence15
Bellemare (2011)

Given that, and given the idea that WTP should not affect welfare except through participation in contract farming (what we refer to as the exclusion restriction for the IV), I estimate:

A selection equation, which is a function of WTP and the control variables, and

A welfare equation, which is a function of (instrumented) participation and the control variables.

I do this for about 1200 households across six regions, multiple crops, and multiple processing firms.

Empirical Evidence
empirical evidence16
Bellemare (2011)

I find that

A 1-percent increase in the likelihood of participation in contract farming translates into a 0.5-percent increase in household income, with similar results for household income per capita and per adult equivalent.

Participation in contract farming has spillover effects on other income sources, too. This is especially true of income from noncontracted crops and income from livestock.

Ignoring the endogeneity problem leads to underestimating the welfare impacts of contract farming.

Empirical Evidence