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Abstract

We employ state panel data for the period 1961-2004 to identify the role of climate change on U.S. agricultural productivity growth using a stochastic production frontier method. We examine the patterns of productivity changes and weather variations across regions and over time. Climate variables are measured using temperature humidity index (THI) load and Oury index at both their means and the degree of deviation from their historical norm (shocks). We also incorporate irrigation ratio and local public goods—R&D, extension, and road infrastructure—to capture the effects of specific state characteristics and to check for the robustness of the estimates of climate variables’ impacts. Results indicate that higher THI load can drive farm production from its best performance using given inputs and best technology. On the other hand, a higher Oury index, irrigation ratio, local R&D, Extension, and road density can drive state overall farm production closer to the production frontier. In addition, weather “shock” variables seem to have more consistent and robust impacts in explaining technical inefficiency than do level variables.

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