Introducing Environmental Variables in Nonparametric Frontier Models: a Probabilistic Approach
This paper proposes a general formulation of a nonparametric frontier model introducingexternal environmental factors that might influence the production process butare neither inputs nor outputs under the control of the producer. A representation isproposed in terms of a probabilistic model which defines the data generating process.Our approach extends the basic ideas from Cazals, Florens and Simar (2002) to thefull multivariate case. We introduce the concepts of conditional efficiency measure andof conditional efficiency measure of order-m. Afterwards we suggest a practical wayfor computing the nonparametric estimators. Finally, a simple methodology to investigatethe influence of these external factors on the production process is proposed.Numerical illustrations through some simulated examples and through a real data seton Mutual Funds show the usefulness of the approach.
|Date of creation:||19 Dec 2003|
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- Simar, L. & Wilson, P.W., 1999.
"Statistical Inference in Nonparametric Frontier Models: the State of the Art,"
9904, Catholique de Louvain - Institut de statistique.
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- Léopold Simar, 2003. "Detecting Outliers in Frontier Models: A Simple Approach," Journal of Productivity Analysis, Springer, vol. 20(3), pages 391-424, November.
- repec:cor:louvrp:-571 is not listed on IDEAS
- Fare, Rolf, et al, 1989. "Multilateral Productivity Comparisons When Some Outputs Are Undesirable: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 90-98, February.
- Cazals, Catherine & Florens, Jean-Pierre & Simar, Leopold, 2002. "Nonparametric frontier estimation: a robust approach," Journal of Econometrics, Elsevier, vol. 106(1), pages 1-25, January.
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