Parametric stochastic frontier models yield firm-level conditional distributions of inefficiency that are truncated normal. Given these distributions, how should one assess and rank firm-level efficiency? This study compares the techniques of estimated (a) the conditional means of inefficiency and (b) probabilities that firms are most or least efficient. Monte Carlo experiments suggest that the efficiency probabilities are more reliable in terms of mean absolute percent error when inefficiency has large variation across firms. Along the way we tackle some interesting problems associated with simulating and assessing estimator performance in the stochastic frontier environment
A fundamental property of a progressive income tax is that it provides implicit insurance against sh...
Our research fleshes out econometric details of examining possible social interactions in labor supp...
This paper gives a brief survey of forecasting with panel data. Starting with a simple error compone...
Parametric stochastic frontier models yield firm-level conditional distributions of inefficiency tha...
This note analyzes the asymptotic distribution for instrumental variables regression for panel data ...
This paper considers various estimators using panel data seemingly unrelated regressions (SUR) with ...
Deconvolution is a useful statistical technique for recovering an unknown density in the presence of...
This paper focuses on inference based on the usual panel data estimators of a one-way error componen...
This paper studies estimation of panel cointegration models with cross-sectional dependence generate...
This paper examines the consequences of model misspecification using a panel data model with spatial...
This paper establishes that regressors in the models with censored dependent variables need not be b...
In the stochastic frontier model we extend the multivariate probability statements of Horrace (2005)...
We consider fixed-effect estimation of a production function where inputs and outputs vary over time...
A widely relied upon but a formally untested consideration is the issue of stability in actors under...
A panel data regression model with heteroskedastic as well as spatially correlated disturbance is co...
A fundamental property of a progressive income tax is that it provides implicit insurance against sh...
Our research fleshes out econometric details of examining possible social interactions in labor supp...
This paper gives a brief survey of forecasting with panel data. Starting with a simple error compone...
Parametric stochastic frontier models yield firm-level conditional distributions of inefficiency tha...
This note analyzes the asymptotic distribution for instrumental variables regression for panel data ...
This paper considers various estimators using panel data seemingly unrelated regressions (SUR) with ...
Deconvolution is a useful statistical technique for recovering an unknown density in the presence of...
This paper focuses on inference based on the usual panel data estimators of a one-way error componen...
This paper studies estimation of panel cointegration models with cross-sectional dependence generate...
This paper examines the consequences of model misspecification using a panel data model with spatial...
This paper establishes that regressors in the models with censored dependent variables need not be b...
In the stochastic frontier model we extend the multivariate probability statements of Horrace (2005)...
We consider fixed-effect estimation of a production function where inputs and outputs vary over time...
A widely relied upon but a formally untested consideration is the issue of stability in actors under...
A panel data regression model with heteroskedastic as well as spatially correlated disturbance is co...
A fundamental property of a progressive income tax is that it provides implicit insurance against sh...
Our research fleshes out econometric details of examining possible social interactions in labor supp...
This paper gives a brief survey of forecasting with panel data. Starting with a simple error compone...