Farm Household Misallocation

Agricultural markets often fail to allocate resources efficiently across farm households in developing countries. However, policymakers require knowledge of which markets fail and how the distortions they generate are correlated. Using data from rural Thailand, I characterize how distortions in land, labor, credit, and insurance markets each contribute to misallocation. I use moments in household consumption and production data to separately identify these distortions and develop a novel method using them to structurally estimate the production function. I find that the efficient allocation would increase aggregate productivity by 11.3% relative to the status quo, while only 3.5% (3.3%) gains could be achieved by eliminating financial (input) distortions in isolation. Positive interaction effects from addressing multiple distortions simultaneously account for the remaining 4.5% TFP gains. Meanwhile, other common methods would produce larger estimates of misallocation and suggest that a financial market intervention would decrease aggregate productivity. Accounting for multiple correlated distortions is therefore crucial for measuring misallocation and designing policies to address it.