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...

In this article, we present one of the first real-world empirical applications of state-contingent production theory. Our state-contingent behavioural model allows us to analyse production under both inefficiency and uncertainty without regard to the nature of producer risk preferences. Using...