In this paper we consider estimation of models popular in efficiency and productivity analysis (such as the stochastic frontier model, truncated regression model, etc.) via the local maximum likelihood method, generalizing this method here to allow for not only continuous but also discrete...

This paper generalizes the results of Hausman and Taylor (1981), Schmidt and Sickles (1984), Cornwell, Schmidt and Sickles (1990) and Park and Simar (1992) to the efficient IV estimation of panel models in which the random effects are correlated with a subset of the regressors. The model in...

This paper considers the semiparametric stochastic frontier model with panel data which arises in the problem of measuring technical inefficiency in production processes. We assume a parametric form for the frontier function, which is linear in production inputs. The density of the individual...

When analyzing the productivity of firms, one may want to compare how the firms transform a set of inputs x (typically labor, energy or capital) into an output y (typically a quantity of goods produced). The economic efficiency of a firm is then defined in terms of its ability of operating close...

This paper complements the results of Hausman and Taylor (1981) and Cornwell, Schmidt and Sickles (1990) and generalizes Park and Simar (1994) by examining the semiparametric efficient estimation of panel models in which the random effects and the regressors have certain patterns of correlation....

A way for measuring the efficiency of enterprises is via the estimation of the so-called production frontier, which is the upper boundary of the support of the population density in the input and output space. It is reasonable to assume that the production frontier is a concave monotone...