A Censored Random Coefficients Model For Pooled Survey Data With Application To The Estimation Of Power Outage Costs
AbstractIn many surveys, multiple observations on the dependent variable are collected from a given respondent. The resulting pooled data set is likely to be censored and to exhibit cross-sectional heterogeneity. We propose a model that addresses both issues by allowing regression coefficients to vary randomly across respondents and by using the GewekeHajivassiliou-Keane simulator and Halton sequences to estimate highorder probabilities. We show how this framework can be usefully applied to the estimation of power outage costs to firms using data from a recent survey conducted by a U.S. utility. Our results strongly reject the hypotheses of parameter constancy and cross-sectional homogeneity. © 2002 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology
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Bibliographic InfoArticle provided by MIT Press in its journal The Review of Economics and Statistics.
Volume (Year): 84 (2002)
Issue (Month): 3 (August)
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- David F. Layton & Klaus Moeltner, 2000. "A Censored Random Coefficients Model for Pooled Survey Data with Application to the Estimation of Power Outage Costs," Econometric Society World Congress 2000 Contributed Papers 0912, Econometric Society.
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