"This book traces the role of money in the creation of the state. From US independence to the establishment of the EU and the breakup of the USSR and beyond, Wilson examines changing attitudes about monetary sovereignty, arguing for a more rational attitude toward money as a means of...

Stochastic frontier models are widely used to measure, e.g., technical efficiencies of firms. The classical stochastic frontier model often suffers from the empirical artefact that the residuals of the production function may have a positive skewness, whereas a negative one is expected under the...

Simar and Wilson (J. Econometrics, 2007) provided a statistical model that can rationalize two-stage estimation of technical efficiency in nonparametric settings. Two-stage estimation has been widely used, but requires a strong assumption: the second-stage environmental variables cannot affect...

The explanation of productivity differentials is very important to identify the economic conditions that create inefficiency and to improve managerial performance. In literature two main approaches have been developed: one-stage approaches and two-stage approaches. Daraio and Simar (2003)...

In a seminal paper, Racine and Li, (Journal of Econometrics, 2004) introduce a tool which admits discrete and categorical variables as regressors in nonparametric regres- sions. The method is similar to the smoothing techniques for continuous regressors but uses discrete kernels. In 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 (Hausman and Taylor, 1981). One motivation for such a model is the need to estimate a...

In this paper we extend the work of Simar (2007) introducing noise in nonparametric frontier models. We develop an approach that synthesizes the best features of the two main methods in the estimation of production efficiency. Specifically, our approach first allows for statistical noise,...