Abstract
Production frontiers are often represented by distance, revenue, cost and/or profit functions. These functions can sometimes be written in the form of regression models in which the explanatory variables are deterministic (i.e., not random). This chapter explains how to estimate and draw inferences concerning the unknown parameters in so-called deterministic frontier models (DFMs). It then explains how the estimated parameters can be used to predict levels of efficiency and analyse productivity change. The focus is on least squares estimators and predictors.
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