Artur Prędki

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In the article we present the DEA+ method as a tool for estimation of production function and technical efficiency measures. We restrict the scope of the study only to the single-product case. Once the underlying, semiparametric frontier model is discussed, we proceed with demonstrating the very algorithm of DEA+, and provide some critique of its validity. Finally, the method is illustrated with an empirical analysis under certain choices of distributions for each of the random variables constituting the composed error.


DEA+, semiparametric frontier model, production function, technical efficiency


Aigner D., Lovell C. A. K., Schmidt P., (1977), F ormulation a nd Estimation of Stochastic Frontier Models, Journal of Econometrics, 6, 21–37.

Banker R. D., (1993), Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation, Management Science, 39 (10), 1265–1273.

Bierens H. J., (1994), Topics in Advanced Econometrics, Cambridge University Press, Cambridge.

Gstach D., (1998), Another Approach to Data Envelopment Analysis in Noisy Environments: DEA+, Journal of Productivity Analysis, 9, 161–176.

Gstach D., (1999), Technical Effi ciency in Noisy Multi-Output Settings, CEJOR 7, 93–110.

Kumbhakar S. C., Lovell C. A. K., (2000), Stochastic Frontier Analysis, Cambridge University Press, Cambridge.

Kuosmanen T., Kortelainen M., (2012), Stochastic Non-Smooth Envelopment of Data: Semi-Parametric Frontier Estimation Subject to Shape Constraints, Journal of Productivity Analysis, 38, 11–28.

Meeusen W., Van den Broeck J., (1977), Effi ciency Estimation from Cobb-Douglas Production Functions with Composed Error, International Economic Review, 18 (2), 435–444.

Osiewalski J., Wróbel-Rotter R., (2002), Bayesowski model efektów losowych w analizie efektywności kosztowej (na przykładzie elektrowni i elektrociepłowni polskich), Przegląd Statystyczny, 50 (2), 47–68.

Prędki A., (2012), Wybrane metody estymacji w semiparametrycznym modelu granicznym, Przegląd Statystyczny, 59 (3), 215–232.

Tate M. W., Brown S. M., (1970), Note on the Cochran Q test, Journal of the American Statistical Association, 65 (329), 155–160.

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