Accounting for Unobserved Heterogeneity in Micro-econometric Agricultural Production Models: a Random Parameter Approach
Résumé
In this paper we rely on a random parameter approach to account for the unobserved heterogeneity of farms/farmers in the estimation of production choices model. We use a Stochastic Expectation-Maximization algorithm to estimate a Nested Multinomial Logit model of yield and acreage choices and perform some simulations using this model. This approach allows accounting for farms’ and farmers’ heterogeneity in a flexible way. Our results show that heterogeneity significantly matters in agricultural production choice models and that ignoring the heterogeneous determinants of farmers’ choices can have important impacts on estimation and simulation outcomes of micro econometric models. Estimates of random parameter models such as the one presented here can be used for, at least, two purposes: for the calibration of simulation models accounting for farm unobserved heterogeneity and to investigate the potential explanations of this unobserved heterogeneity.
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