frontier: Stochastic Frontier Analysis. Maximum Likelihood Estimation of Stochastic Frontier Production and Cost Functions. Two specifications are available: the error components specification with time-varying efficiencies (Battese and Coelli, 1992) and a model specification in which the firm effects are directly influenced by a number of variables (Battese and Coelli, 1995).

References in zbMATH (referenced in 11 articles )

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  1. Anaya, Karim L.; Pollitt, Michael G.: Using stochastic frontier analysis to measure the impact of weather on the efficiency of electricity distribution businesses in developing economies (2017)
  2. Badunenko, Oleg; Kumbhakar, Subal C.: When, where and how to estimate persistent and transient efficiency in stochastic frontier panel data models (2016) ioport
  3. Coto-Millán, Pablo; Fernández, Xose Luís; Pesquera, Miguel Ángel; Agüeros, Manuel: Impact of logistics on technical efficiency of world production (2007--2012) (2016)
  4. Ortega, Francisco J.; Gavilan, Jose M.: Bayesian estimation of the half-normal regression model with deterministic frontier (2016)
  5. Lampe, Hannes W.; Hilgers, Dennis: Trajectories of efficiency measurement: a bibliometric analysis of DEA and SFA (2015)
  6. Lin, Winston T.; Chen, Yueh H.; Shao, Benjamin B.M.: Assessing the business values of information technology and e-commerce independently and jointly (2015)
  7. Macedo, Pedro; Scotto, Manuel: Cross-entropy estimation in technical efficiency analysis (2014)
  8. Bogetoft, Peter; Otto, Lars: Benchmarking with DEA, SFA, and R. (2011)
  9. Simar, Léopold; Wilson, Paul W.: Inferences from cross-sectional, stochastic frontier models (2010)
  10. Castano, Mary Caroline N.; Cabanda, Emilyn C.: Performance evaluation of the efficiency of Philippine Private Higher Educational Institutions: application of frontier approaches (2007)
  11. Coelli, Tim; Prasada Rao, D.S.; Battese, George E.: An introduction to efficiency and productivity analysis (1998)