When stochastic errors are added to data from a distribution with a sharp boundary, such as a changepoint or a frontier, nonparametric estimation of the boundary can be interpreted as a problem of deconvolution. We argue that, rather than attempting to estimate the distribution of the...

This study focuses on the semiparametric efficient estimation of random effect panel models containing AR(1) disturbances. We also consider such estimators when the effects and regressors are correlated.

This paper complements the results of Hausman and Taylor (1981) and Cornewell, 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.

Efficiency scores of production units are measured by their distance to an estimated production forntier. Nonparametric DEA estimators are based on a finit sample of observed production units and radial distances are considered. We investigate the consistency and the speed of convergence of...