Journal of Productivity Analysis

, Volume 23, Issue 1, pp 7–32 | Cite as

Fixed and Random Effects in Stochastic Frontier Models

  • Willam Greene


Received stochastic frontier analyses with panel data have relied on traditional fixed and random effects models. We propose extensions that circumvent two shortcomings of these approaches. The conventional panel data estimators assume that technical or cost inefficiency is time invariant. Second, the fixed and random effects estimators force any time invariant cross unit heterogeneity into the same term that is being used to capture the inefficiency. Inefficiency measures in these models may be picking up heterogeneity in addition to or even instead of inefficiency. A fixed effects model is extended to the stochastic frontier model using results that specifically employ the nonlinear specification. The random effects model is reformulated as a special case of the random parameters model. The techniques are illustrated in applications to the U.S. banking industry and a cross country comparison of the efficiency of health care delivery.


panel data fixed effects random effects random parameters computation Monte Carlo maximum simulated likelihood technical efficiency stochastic frontier 


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Copyright information

© Springer Science+Business Media, Inc. 2005

Authors and Affiliations

  1. 1.Department of Economics, Stern School of BusinessNew York University New YorkUSA

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