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...

In this paper we propose a very flexible estimator in the context of truncated regression that does not require parametric assumptions. To do this, we adapt the theory of local maximum likelihood estimation. We provide the asymptotic results and illustrate the performance of our estimator on...

In this study, we merge results of two recent directions in efficiency analysis research-aggregation and bootstrap-applied, as an example, to one of the most popular point estimators of individual efficiency: the data envelopment analysis (DEA) estimator. A natural context of the methodology...