A NEW PANEL DATA TREATMENT FOR HETEROGENEITY IN TIME TRENDS

被引：50

作者：

Kneip, Alois ^{[2
]}

Sickles, Robin C. ^{[1
]}

Song, Wonho ^{[3
]}

机构：

[1] Rice Univ, Dept Econ, Houston, TX 77005 USA

[2] Univ Bonn, Bonn, Germany

[3] Chung Ang Univ, Ansong, South Korea

来源：

ECONOMETRIC THEORY | 2012年 / 28卷 / 03期

关键词：

SEMIPARAMETRIC-EFFICIENT ESTIMATION; FRONTIERS; MODELS; IDENTIFICATION; REDUCTION; INFERENCE; SERIES; NUMBER;

D O I：

10.1017/S026646661100034X

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This paper introduces a new estimation method for arbitrary temporal heterogeneity in panel data models. The paper provides a semiparametric method for estimating general patterns of cross-sectional specific time trends. The methods proposed in the paper are related to principal component analysis and estimate the time-varying trend effects using a small number of common functions calculated from the data. An important application for the new estimator is in the estimation of time-varying technical efficiency considered in the stochastic frontier literature. Finite sample performance of the estimators is examined via Monte Carlo simulations. We apply our methods to the analysis of productivity trends in the U.S. banking industry.

引用

页码：590 / 628

页数：39

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