Semiparametric Efficient Estimation of AR(1) Panel Data Models∗

نویسندگان

  • Byeong U. Park
  • Robin C. Sickles
چکیده

This study focuses on the semiparametric efficient estimation of random effect panel models containing AR(1) disturbances. We also consider such estimators when the effects and regressors are correlated (Hausman and Taylor, 1981). We introduce two semiparametric efficient estimators that make minimal assumptions on the distribution of the random errors, effects, and the regressors and that provide semiparametric efficient estimates of the slope parameters and of the effects. Our estimators extend the previous work of Park and Simar (1994), Park, Sickles, and Simar (1998), and Adams, Berger, and Sickles (1999). Theoretical derivations are supplemented by Monte Carlo ∗The authors are very grateful for the helpful comments of three referees and an associate editor. The authors also would like to thank Wonho Song for his valuable research assistance and Jean-Marie Rolin for his help in revising the paper. †Research support by KOSEF through Statistical Research Center for Complex Systems at Seoul National University. ‡Corresponding author. §Research support from “Projet d’Actions de Recherche Concertées” (No. 98/03—217) and from the “Interuniversity Attraction Pole”, Phase V (No. P5/24) from the Belgian Government are also acknowledged.

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تاریخ انتشار 2003