Input Demands and Inefficiency in U.S. Agriculture

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

American Journal of Agricultural Economics, 1999, vol. 81, issue 4, 865-880

Abstract: 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. Copyright 1999, Oxford University Press.

Date: 1999
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Persistent link: https://EconPapers.repec.org/RePEc:oup:ajagec:v:81:y:1999:i:4:p:865-880

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