IDEAS home Printed from https://ideas.repec.org/p/ptu/wpaper/w200110.html
   My bibliography  Save this paper

Identification with Averaged Data and Implications for Hedonic Regression Studies

Author

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
    as

    Download full text from publisher

    File URL: https://www.bportugal.pt/sites/default/files/anexos/papers/wp200110.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Reis, Hugo J. & Santos Silva, J.M.C., 2006. "Hedonic prices indexes for new passenger cars in Portugal (1997-2001)," Economic Modelling, Elsevier, vol. 23(6), pages 890-908, December.
    2. Alberto Abadie & Susan Athey & Guido W. Imbens & Jeffrey M. Wooldridge, 2020. "Sampling‐Based versus Design‐Based Uncertainty in Regression Analysis," Econometrica, Econometric Society, vol. 88(1), pages 265-296, January.
    3. Psaradakis, Zacharias & Sola, Martin, 1996. "On the power of tests for superexogeneity and structural invariance," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 151-175.
    4. Richard H. Spady & Sami Stouli, 2018. "Simultaneous Mean-Variance Regression," Bristol Economics Discussion Papers 18/697, School of Economics, University of Bristol, UK.
    5. Amavilah, Voxi & Asongu, Simplice A. & Andrés, Antonio R., 2017. "Effects of globalization on peace and stability: Implications for governance and the knowledge economy of African countries," Technological Forecasting and Social Change, Elsevier, vol. 122(C), pages 91-103.
    6. Joshua D. Angrist & Jörn-Steffen Pischke, 2010. "The Credibility Revolution in Empirical Economics: How Better Research Design Is Taking the Con out of Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 24(2), pages 3-30, Spring.
    7. Godfrey, Leslie G & McAleer, Michael & McKenzie, Colin R, 1988. "Variable Addition and LaGrange Multiplier Tests for Linear and Logarithmic Regression Models," The Review of Economics and Statistics, MIT Press, vol. 70(3), pages 492-503, August.
    8. Christian M. Hafner & Helmut Herwartz, 2009. "Testing for linear vector autoregressive dynamics under multivariate generalized autoregressive heteroskedasticity," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(3), pages 294-323, August.
    9. Joshua D. Angrist & Jörn-Steffen Pischke, 2017. "Undergraduate Econometrics Instruction: Through Our Classes, Darkly," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 125-144, Spring.
    10. Miguel A. Delgado & Thomas J. Kniesner, 1997. "Count Data Models With Variance Of Unknown Form: An Application To A Hedonic Model Of Worker Absenteeism," The Review of Economics and Statistics, MIT Press, vol. 79(1), pages 41-49, February.
    11. Packalen, Mikko & Wirjanto, Tony S., 2012. "Inference about clustering and parametric assumptions in covariance matrix estimation," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 1-14, January.
    12. Montes-Rojas, Gabriel & Sosa-Escudero, Walter, 2011. "Robust tests for heteroskedasticity in the one-way error components model," Journal of Econometrics, Elsevier, vol. 160(2), pages 300-310, February.
    13. Demos, Antonis & Sentana, Enrique, 1998. "Testing for GARCH effects: a one-sided approach," Journal of Econometrics, Elsevier, vol. 86(1), pages 97-127, June.
    14. Manabu Asai & Michael McAleer, 2005. "Dynamic Asymmetric Leverage in Stochastic Volatility Models," Econometric Reviews, Taylor & Francis Journals, vol. 24(3), pages 317-332.
    15. Alberto Abadie & Susan Athey & Guido W. Imbens & Jeffrey M. Wooldridge, 2017. "Sampling-based vs. Design-based Uncertainty in Regression Analysis," Papers 1706.01778, arXiv.org, revised Jun 2019.
    16. Bruce E. Hansen & Seojeong Lee, 2021. "Inference for Iterated GMM Under Misspecification," Econometrica, Econometric Society, vol. 89(3), pages 1419-1447, May.
    17. Davidson, R. & MacKinnon & J.G., 1999. "Artificial Regressions," G.R.E.Q.A.M. 99a04, Universite Aix-Marseille III.
    18. Amavilah, Voxi Heinrich, 2013. "The Love Aspects of Human Capital and the Economic Activity of Countries," MPRA Paper 52686, University Library of Munich, Germany.
    19. Audretsch, David B & Klomp, Luuk & Thurik, A R Roy, 1997. "Do Services Differ From Manufacturing? The Post-Entry Performance of Firms in Dutch Services," CEPR Discussion Papers 1718, C.E.P.R. Discussion Papers.
    20. Kim, Moshe & Vale, Bent, 2001. "Non-price strategic behavior: the case of bank branches," International Journal of Industrial Organization, Elsevier, vol. 19(10), pages 1583-1602, December.

    More about this item

    JEL classification:

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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ptu:wpaper:w200110. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: DEE-NTD (email available below). General contact details of provider: https://edirc.repec.org/data/bdpgvpt.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.