Dynamic Crop Rotation with Field-Level Heterogeneity: Estimating Yields and Profits
Crop rotation shapes agricultural productivity and environmental outcomes, yet estimating its effects is complicated by the fact that farmers select crops based on unobserved field-level productivity. This selection creates endogeneity in observed yields and means that marginal fields responding to policy incentives are systematically different from average fields. We develop and estimate a dynamic structural model of crop rotation that jointly identifies three distinct policy-relevant margins: how many fields switch crops, how productive switchers are relative to non-switchers, and how yields change when fields switch. Using satellite-derived, field-level data on crop choices and yields for approximately one million fields in Illinois, Iowa, and Indiana over 2005–2019, we estimate yield equations with field fixed effects alongside a dynamic discrete choice model of profit-maximizing farmers. We derive and empirically verify conditions under which selection on comparative advantage also implies selection on absolute advantage, a result with direct implications for predicting supply responses to rotation subsidies and conservation programs. Our estimates reveal economically significant rotation yield effects, substantial heterogeneity in field productivity, and a large share of fields that maintain strict corn-soy rotations regardless of price signals. The structural framework enables coherent counterfactual policy analysis that reduced-form or aggregate approaches cannot support.