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 Geweke-Hajivassiliou-Keane simulator and Halton sequences to estimate high-order 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.
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Date of creation: 01 Aug 2000
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- Klaus Moeltner & David F. Layton, 2002. "A Censored Random Coefficients Model For Pooled Survey Data With Application To The Estimation Of Power Outage Costs," The Review of Economics and Statistics, MIT Press, vol. 84(3), pages 552-561, August.
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