Journal Article

Input Demands and Inefficiency in U.S. Agriculture

Christopher J. O'Donnell, C. Richard Shumway and V. Eldon Ball

in American Journal of Agricultural Economics

Published on behalf of Agricultural and Applied Economics Association

Volume 81, issue 4, pages 865-880
Published in print November 1999 | ISSN: 0002-9092
Published online November 1999 | e-ISSN: 1467-8276 | DOI:
Input Demands and Inefficiency in U.S. Agriculture

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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.

Keywords: Bayes; concavity; input demands; Markov Chain Monte Carlo; technical efficiency; Q110

Journal Article.  0 words. 

Subjects: Agricultural Economics

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