Amer. J. Agr. Econ. 94(5): 1136–1153; doi: 10.1093/ajae/aas065
Farmers have to make key decisions, such as which crops to plant or whether to prepare the soil, before knowing how much water they will get.They face losses if they make costly decisions but do not receive water, and they may forego profits if they receive water without being prepared.We consider the coordination of farmers’ decisions, such as which crops to plant or whether to prepare the soil when farmers must divide an uncertain water supply. We compare ex-ante queues (pre-decision) to an ex-post spot market (post-decision & post-rain) in experiments in rural Brazil and a university in England. Queues have greater coordination success than does the spot market.
Oxford Review of Economic Policy, Volume 28, Number 1, 2012, pp. 164–179
Policies must balance forest conservation’s local costs with its benefits—local to global—in terms of biodiversity, the mitigation of climate change, and other eco-services such as water quality. The trade-offs with development vary across forest locations. We argue that considering location in three ways helps to predict policy impact and improve policy choice: (i) policy impacts vary by location because baseline deforestation varies with characteristics (market distances, slopes, soils, etc.) of locations in a landscape; (ii) different mixes of political-economic pressures drive the location of different policies; and (iii) policies can trigger ‘second-order’ or ‘spillover’ effects likely to differ by location. We provide empirical evidence that suggests the importance of all three considerations, by reviewing highquality evaluations of the impact of conservation and development on forest. Impacts of well-enforced conservation rise with private clearing pressure, supporting (i). Protection types (e.g. federal/state) differ in locations and thus in impacts, supporting (ii). Differences in development process explain different signs for spillovers, supporting (iii).
Journal of Development Economics 97 (2012) 427–436
We estimate neighbor interactions in deforestation in Costa Rica. To address simultaneity and the presence of spatially correlated unobservables, we measure for neighbors’ deforestation using the slopes of neighbors’ and neighbors’ neighbors’ parcels. We find that neighboring deforestation significantly raises the probability of deforestation. Policies for agricultural development or forest conservation in one area will affect deforestation rates in non-targeted neighboring areas. Correct estimation of the interaction reverses the naive estimate’s prediction of multiple equilibria.