In this paper we compare two flexible estimators of technical efficiency in a cross-sectional setting: the nonparametric kernel SFA estimator of Fan, Li and Weersink (1996) to the nonparametric bias corrected DEA estimator of Kneip, Simar and Wilson (2008). We assess the finite sample...

We use nonparametric production-frontier methods to decompose the growth of labor productivity of Chinese provinces in the post-reform period. These techniques, combined with kernel density estimates, allow us to decompose the shift in the distribution of labor productivity without the need for...

We employ data envelopment analysis (DEA) methods to construct the world production frontier, which is in turn used to decompose (labor) productivity growth into components attributable to technological change (shift of the production frontier), efficiency change (movements toward or away from...