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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
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
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- 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. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May.
- 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.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (DEE-NTDD).
If references are entirely missing, you can add them using this form.