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A Stochastic Frontier Model with short-run and long-run inefficiency random effects

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Author Info

  • Roberto Colombi

    ()

  • Gianmaria Martini

    ()

  • Giorgio Vittadini

    ()

Abstract

This paper presents a new stochastic frontier model for panel data. The model takes into account firm unobservable heterogeneity and short-run and long-run sources of inefficiency. Each of these features is modeled by a specific random effect. In this way, firms’ latent heterogeneity is not wrongly modeled as inefficiency, and it is possible to disentangle a time-persistent component from the total inefficiency. Under reasonable assumptions, we show that the closed-skew normal distribution allows us to derive both the log-likelihood function of the model and the posterior expected values of the random effects. The new model is compared with nested models by analyzing the efficiency of firms belonging to different sectors.

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File URL: http://hdl.handle.net/10446/842
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Bibliographic Info

Paper provided by Department of Economics and Technology Management, University of Bergamo in its series Working Papers with number 1101.

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Date of creation: 2011
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Handle: RePEc:brh:wpaper:1101

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Related research

Keywords: Closed-Skew Normal Distribution; Longitudinal Data Analysis; Mixed Models; Stochastic Frontiers;

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References

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  1. Berta, P & Callea, G & Martini, G & Vittadini, G, 2009. "The effects of upcoding, cream skimming and readmissions on the Italian hospitals efficiency: a population–based investigation," MPRA Paper 17671, University Library of Munich, Germany.
  2. Paolo Malighetti & Gianmaria Martini & Stefano Paleari & Renato Redondi, 2007. "An Empirical Investigation on the Efficiency, Capacity and Ownership of Italian Airports," Working Papers 0703, Department of Economics and Technology Management, University of Bergamo.
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Cited by:
  1. Subal Kumbhakar & Anatoly Peresetsky, 2013. "Cost efficiency of Kazakhstan and Russian banks: results from competing panel data models-super-1," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 6(1), pages 88-113, March.
  2. Subal Kumbhakar & Gudbrand Lien & J. Hardaker, 2014. "Technical efficiency in competing panel data models: a study of Norwegian grain farming," Journal of Productivity Analysis, Springer, vol. 41(2), pages 321-337, April.

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