Nonparametric and Stochastic Efficiency and Productivity Analysis

Nonparametric efficiency measurement and statistical inference via DEA type estimators (see Färe, Grosskopf, and Lovell (1994) , Kneip, Simar, and Wilson (2008) and Badunenko and Mozharovskyi (2020) ) 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) , Badunenko and Kumbhakar (2016) ). 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.


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install.packages("npsf")

0.7.1 by Oleg Badunenko, 4 months ago


Browse source code at https://github.com/cran/npsf


Authors: Oleg Badunenko [aut, cre] , Pavlo Mozharovskyi [aut] , Yaryna Kolomiytseva [aut]


Documentation:   PDF Manual  


GPL-2 license


Depends on Formula

Suggests snowFT, Rmpi

Linking to Rcpp


See at CRAN