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

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  • 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.

Suggested Citation

  • Roberto Colombi & Gianmaria Martini & Giorgio Vittadini, 2011. "A Stochastic Frontier Model with short-run and long-run inefficiency random effects," Working Papers 1101, Department of Management, Information and Production Engineering, University of Bergamo.
    • Handle: RePEc:brh:wpaper:1101
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    File URL: http://hdl.handle.net/10446/842
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    References listed on IDEAS

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    3. Subal C. Kumbhakar & Almas Heshmati, 1995. "Efficiency Measurement in Swedish Dairy Farms: An Application of Rotating Panel Data, 1976–88," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(3), pages 660-674.
    4. Berta, Paolo & Callea, Giuditta & Martini, Gianmaria & Vittadini, Giorgio, 2010. "The effects of upcoding, cream skimming and readmissions on the Italian hospitals efficiency: A population-based investigation," Economic Modelling, Elsevier, vol. 27(4), pages 812-821, July.
    5. Paolo Malighetti & Gianmaria Martini & Stefano Paleari & Renato Redondi, 2007. "An Empirical Investigation on the Efficiency, Capacity Ownership of Italian Airports," Rivista di Politica Economica, SIPI Spa, vol. 97(1), pages 157-188, January-F.
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    More about this item

    Keywords

    Closed-skew normal distribution; longitudinal data analysis; mixed models; stochastic frontiers;
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