{"title":"Generalized Estimating Equations For Panel Data And Managerial Monitoring In Electric Utilities","authors":"H. Vinod, R. Geddes","doi":"10.1201/9780203493212.ch33","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":113421,"journal":{"name":"Advances on Methodological and Applied Aspects of Probability and Statistics","volume":"101 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances on Methodological and Applied Aspects of Probability and Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1201/9780203493212.ch33","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
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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