Stochastic Panel Frontiers : A Semiparametric Approach

This paper complements the results of Hausman and Taylor (1981) and Cornwell, Schmidt and Sickles (1990) and generalizes Park and Simar (1994) by examining the semiparametric efficient estimation of panel models in which the random effects and the regressors have certain patterns of correlation. A model in which the estimator may have particular promise is the stochastic panel frontier model. In that model inefficiency may be correlated with certain determinants of technology or proxies for heterogeneity in the application of that technology. Generalized least squares or other estimators that fail to address this dependency structure are inconsistent. We examine semiparametric efficient estimation for three different models based on differing dependency structures. Efficiency of the slope parameters and the asymptotic proper- ties of the level of the frontier function are explored. We illustrate our new estimator in an analysis of productive efficiency between selected North American and European airline firms after domestic deregulation in the U.S. and prior to recent European reforms implemented in the course of EC integration.