Nonparametric and Stochastic Efficiency and Productivity Analysis
U.S. Commercial Banks Data
U.S. Commercial Banks Data
Program Follow Through at Primary Schools
'coef' method for class 'npsf'
'halton' method for class 'npsf'
Female labor force participation
'nobs' method for class 'npsf'
Introduction to Nonparametric and Stochastic Frontier Analysis
Nonparametric Test of Independence
Nonparametric Test of Returns to Scale
'primes' method for class 'npsf'
Penn World Tables 5.6 (compiled in 1995)
'rescale' method for class 'npsf'
Stochastic Frontier Models Using Cross-Sectional and Panel Data
'summary' method for class 'npsf'
Nonradial Measure of Technical Efficiency, the Russell Measure
Statistical Inference Regarding the Russell Measure of Technical Effic...
Radial Measure of Technical Efficiency, the Debrue-Farrell Measure
Statistical Inference Regarding the Radial Measure of Technical Effici...
Parametric truncated regression for cross-sectional data
US Manufacturing Industry Data
'vcov' method for class 'npsf'
Nonparametric efficiency measurement and statistical inference via DEA type estimators (see Färe, Grosskopf, and Lovell (1994) <doi:10.1017/CBO9780511551710>, Kneip, Simar, and Wilson (2008) <doi:10.1017/S0266466608080651> and Badunenko and Mozharovskyi (2020) <doi:10.1080/01605682.2019.1599778>) as well as Stochastic Frontier estimators for both cross-sectional data and 1st, 2nd, and 4th generation models for panel data (see Kumbhakar and Lovell (2003) <doi:10.1017/CBO9781139174411>, Badunenko and Kumbhakar (2016) <doi:10.1016/j.ejor.2016.04.049>). The stochastic frontier estimators can handle both half-normal and truncated normal models with conditional mean and heteroskedasticity. The marginal effects of determinants can be obtained.