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Input Demands and Inefficiency in U.S. Agriculture

Christopher J. O'DonnellC. Richard ShumwayV. Eldon Ball

出版	SSRN, 2020
URL	http://books.google.com.hk/books?id=dZ3jzwEACAAJ&hl=&source=gbs_api

註釋Markov Chain Monte Carlo (MCMC) methods are used to estimate a seemingly unrelated regression (SUR) system of input demand functions for U.S. agriculture. Our demand functions have flexible forms and allow for nonrandom technical inefficiency. Concavity constraints are imposed at individual data points, and the distributions of measures of relative technical efficiency are constrained to the unit interval. Results are evaluated in terms of characteristics of the posterior distributions of parameters, measures of relative technical efficiency, and other nonlinear functions of the parameters.