Productive efficiency of French grain producers: A latent variable model

Abstract

In this article we propose to implement a covariance structure analysis to deal with the estimation of a stochastic frontier production function on panel data and the measurement of a time-varying technical efficiency. First, this method solves the potential problem of correlations between input quantities and individual effects. Second, individual effects and efficiency measures can be recovered as a byproduct of the analysis through the so-called factor scores. We implement this approach by fitting to a balanced panel of French grain producers, a parsimonious version of the Cornwell, Schmidt, and Sickles [1990]'s model where technical efficiencies are individual-specific linear functions of time. A specification search shows that this model is preferred to the traditional production function. Results shed light on the temporal pattern of efficiency in the French grain production sector.