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

  • David F. Layton

    (University of California)

  • Klaus Moeltner

    (University of Washington)

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.

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Paper provided by Econometric Society in its series Econometric Society World Congress 2000 Contributed Papers with number 0912.

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Date of creation: 01 Aug 2000
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Handle: RePEc:ecm:wc2000:0912
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