In this paper, we explore the roles of migration frictions, land constraints, and international agricultural trade in uneven wage growth across districts in India. To answer this question, the paper combines reduced-form econometric methods with a quantitative spatial equilibrium model calibrated to a district-level monthly panel for 2010–2022. There are two stages to the empirical strategy. First, we estimate a Spatial Durbin model (SDM) to quantify the effects of local and neighboring districts’ conditions on district-level agricultural wages. These reduced-form estimates provide evidence of spatial spillovers and give elasticities that will be used in calibrations in the next step. In the second stage, we calibrate a quantitative spatial equilibrium model with costly labor migration, fixed land endowments, and heterogeneous productivity across districts. The calibration is performed using a simulated method of moments to match observed wage dispersion, spatial autocorrelation, and the responsiveness of wages to weather and trade shocks. This approach helps decompose the relative contributions of migration frictions, land scarcity, climate variability, and trade exposure to the divergence in wages. Finally, we also conduct counterfactual simulations measuring how changes in mobility barriers, export demand, or climate risk could alter the distribution of agricultural wages in India.
