A Censored Random Coefficients Model for Pooled Survey Data with Application to the Estimation of Power Outage Costs

David F. Layton and Klaus Moeltner
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David F. Layton: University of California

No 912, Econometric Society World Congress 2000 Contributed Papers from Econometric Society

Abstract: In 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.

Date: 2000-08-01
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Journal Article: A Censored Random Coefficients Model For Pooled Survey Data With Application To The Estimation Of Power Outage Costs (2002)
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