电力公司面板数据与管理监控的广义估计方程

H. Vinod, R. Geddes
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引用次数: 0

摘要

Vinod(1997,1998)讨论了估计函数(EFs)的Godambe-Durbin理论及其在计量经济学中的潜力。在这里,我们考虑一个流行的应用称为广义估计方程(GEE)。它通常应用于面板数据,其中异方差与回归参数分析相关,并且因变量是二元的。Geddes(1997)研究了具有独家地理特许经营权的受监管电力公司的面板数据,以及首席执行官或首席执行官(CEO)在职期间的流失率。我们的GEE估计扭转了他有些违反直觉的结果,即三个绩效变量不影响首席执行官的更替。我们测试了(i)监管松弛、(ii)寻租和(iii)政治压力假设预测的经验有效性,并拒绝了其他假设。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Generalized Estimating Equations For Panel Data And Managerial Monitoring In Electric Utilities
Vinod (1997, 1998) discuss the Godambe-Durbin theory of estimating functions (EFs) and its potential in econometrics. Here we consider a popular application of EFs called generalized estimating equations (GEE). It is typically applied to panel data, where the heteroscedasticity is analytically related to , the regression parameter, and where the dependent variable is binary. Geddes (1997) studies panel data on regulated electric utilities with exclusive geographic franchises, and the turnover of the chief executive o cer (CEO) on the job. Our GEE estimates reverse his somewhat counterintuitive result that rm performance variables do not a ect the turnover of the CEO. We test the empirical validity of predictions of (i) regulatory slack, (ii) rent seeking, and (iii) political pressure hypotheses, and reject the rst.
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