Identification with Averaged Data and Implications for Hedonic Regression Studies
AbstractIn 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.
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Bibliographic InfoPaper provided by Banco de Portugal, Economics and Research Department in its series Working Papers with number w200110.
Date of creation: 2001
Date of revision:
Other versions of this item:
- J.A.F. Machado & J.M.C. Santos Silva, 2003. "Identification with averaged data and implications for hedonic regression studies," Econometrics 0303002, EconWPA.
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
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- 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.
- 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 149-70, February.
- 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.
- White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May.
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