Sell Low and Buy High: Arbitrage and Local Price Effects in Kenyan Markets (with Marshall Burke and Edward Miguel)

Forthcoming, Quarterly Journal of Economics

Large and regular seasonal price fluctuations in local grain markets appear to offer African farmers substantial inter-temporal arbitrage opportunities, but these opportunities remain largely unexploited: small-scale farmers are commonly observed to “sell low and buy high” rather than the reverse.  In a field experiment in Kenya, we show that credit market imperfections limit farmers’ abilities to move grain inter-temporally.  Providing timely access to credit allows farmers to buy at lower prices and sell at higher prices, increasing farm revenues and generating a return on investment of 28%. To understand general equilibrium effects of these changes in behavior, we vary the density of loan offers across locations. We document significant effects of the credit intervention on seasonal price fluctuations in local grain markets, and show that these GE effects shape individual level profitability estimates.  In contrast to existing experimental work, the results indicate a setting in which microcredit can improve firm profitability, and suggest that GE effects can substantially shape microcredit’s effectiveness.  In particular, failure to consider these GE effects could lead to underestimates of the social welfare benefits of microcredit interventions.

Working Papers

Pass-Through, Competition, and Entry in Agricultural Markets: Experimental Evidence from Kenya

Revise and resubmit, American Economic Review

African agricultural markets are characterized by low revenues for smallholder farmers and high food prices for consumers.  There has long been concern that this price wedge between farmers and consumers — and the resulting loss in producer and consumer welfare — are driven in part by imperfect competition among the intermediaries that connect them.  In this paper, I implement three randomized control trials that are tightly linked to a model of market competition in order to estimate key parameters governing the competitive environment of Kenyan agricultural markets.  First, I reduce the marginal costs of traders in randomly selected markets, and find that only 22% of this cost reduction is passed through to consumers.  Second, to elicit the shape of consumer demand that these traders face, I randomize price discounts and measure the quantities that customers purchase at these prices.  Taken together, these estimates reveal a high degree of collusion among intermediaries, with large implied losses to consumer welfare and overall market efficiency.  Third, given that a natural policy response to limited competition is to encourage greater firm entry, I randomly incentivize the entry of new traders into markets.  By capturing the resulting effect on local market prices, I identify the implied change in the competitive environment due to entry. I find that the estimates are consistent with a model in which entrants are able to easily join collusive agreements with incumbents. Taken together, the results suggest that agricultural traders in Kenya have considerable market power, and that marginal changes in market entry are unlikely to induce significant changes in competition. These findings have implications for the incidence of technological and infrastructure changes in African agriculture and for the policy responses aimed at improving the market environment.

Works in Progress

Market Linkages for Smallholder Farmers in Uganda (with Craig McIntosh)

Trade frictions in developing country food markets can have tremendous welfare costs because of the dual role of crops as the dominant income generator and the primary source of nutrition.  In this paper, we utilize a multi-pronged experiment to assess the role of three potential barriers that may impede market depth: search costs, contractual risk, and credit constraints.  We partner with one of Uganda’s largest private-sector brokerage companies to introduce a mobile trading platform designed to reduce search costs by linking buyers and sellers of agricultural commodities. Trading credit and transport cost guarantees are then randomized across traders and contracts to disentangle the role of contractual risk and credit constraints in hampering efficient exchange.  We further collect biweekly market price information from 260 markets across Uganda and disseminate this information to farmers, intermediaries, and buyers.  We exploit these prices surveys to estimate the impact of the platform on price dispersion and market efficiency.  Large-scale farmer and trader surveys shed light on the distribution of welfare effects from this intervention.

Scaling Up RCTs: Theory and Evidence from Ugandan Agriculture (with Benjamin Faber, Matthias Hoelzlein, Edward Miguel, and Andres Rodriguez-Clare)

Policy evaluations based on model simulations frequently face three important challenges: i) the preference and technology parameters may not be well identified; ii) even when well identified, they may not have been estimated in the particular policy context in question; and iii) the model’s functional form and other assumptions may be misspecified. On the other hand, policy evaluations based on randomized control trials (RCTs) frequently face two important challenges: a) the estimated treatment effects by themselves may be insufficient to evaluate the general equilibrium effects of scaling up the intervention to the regional or national levels, and b) the estimated treatment effects may reflect spillovers on the control group. In this paper, we combine the empirical results from an RCT in Uganda with a quantitative model of farm production and trade to evaluate alternative policy scenarios. This approach allows us to address i), ii) and iii) by assessing the validity of the model’s structure using the reduced form effects of the intervention. In turn, we address a) and b) by interpreting the observed effects through the lens of the model, and by assessing the extent to which general equilibrium forces may reinforce or diminish the treatment effects when scaling up the intervention.