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Identification with Averaged Data and Implications for Hedonic Regression Studies

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Abstract

In this estimation of models with averaged data, weighted least squares is often used and recommended as a way of improving the efficiency of the estimator. However, if the size of the different groups is not conditionally independent of the regressand, consistent estimation may not be possible at all. It is argued that in the case of some leading examples of averaged data regression, consistent estimation is possible using the usual weighted estimator.

Suggested Citation

  • José Ferreira Machado, 2001. "Identification with Averaged Data and Implications for Hedonic Regression Studies," Working Papers w200110, Banco de Portugal, Economics and Research Department.
    • Handle: RePEc:ptu:wpaper:w200110
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    References listed on IDEAS

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    1. White, Halbert, 1980. "Using Least Squares to Approximate Unknown Regression Functions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 21(1), pages 149-170, February.
    2. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    3. Wooldridge, Jeffrey M., 1991. "On the application of robust, regression- based diagnostics to models of conditional means and conditional variances," Journal of Econometrics, Elsevier, vol. 47(1), pages 5-46, January.
    4. Kenneth Brown, 2000. "Hedonic price indexes and the distribution of buyers across the product space: an application to mainframe computers," Applied Economics, Taylor & Francis Journals, vol. 32(14), pages 1801-1808.
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    Cited by:

    1. Hugo Reis & J.M.C.Santos Silva, . "Índices de Preços Hedónicos de Automóveis Ligeiros de Passageiros Novos em Portugal (1997-2001)," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.

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    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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