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Weighted average least squares estimation with nonspherical disturbances and an application to the Hong Kong housing market

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  • Magnus, Jan R.
  • Wan, Alan T.K.
  • Zhang, Xinyu

Abstract

The recently proposed 'weighted average least squares' (WALS) estimator is a Bayesian combination of frequentist estimators. It has been shown that the WALS estimator possesses major advantages over standard Bayesian model averaging (BMA) estimators: the WALS estimator has bounded risk, allows a coherent treatment of ignorance and its computational effort is negligible. However, the sampling properties of the WALS estimator as compared to BMA estimators are heretofore unexamined. The WALS theory is further extended to allow for nonspherical disturbances, and the estimator is illustrated with data from the Hong Kong real estate market. Monte Carlo evidence shows that the WALS estimator performs significantly better than standard BMA and pretest alternatives.

Suggested Citation

  • Magnus, Jan R. & Wan, Alan T.K. & Zhang, Xinyu, 2011. "Weighted average least squares estimation with nonspherical disturbances and an application to the Hong Kong housing market," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1331-1341, March.
    • Handle: RePEc:eee:csdana:v:55:y:2011:i:3:p:1331-1341
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    Cited by:

    1. Magnus, J.R. & Wang, W. & Zhang, Xinyu, 2012. "WALS Prediction," Discussion Paper 2012-043, Tilburg University, Center for Economic Research.
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    4. Schomaker, Michael & Heumann, Christian, 2014. "Model selection and model averaging after multiple imputation," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 758-770.
    5. Poghosyan, K., 2012. "Structural and reduced-form modeling and forecasting with application to Armenia," Other publications TiSEM ad1a24c3-15e6-4f04-b338-3, Tilburg University, School of Economics and Management.
    6. Alan T. K. Wan & Shangyu Xie & Yong Zhou, 2017. "A varying coefficient approach to estimating hedonic housing price functions and their quantiles," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(11), pages 1979-1999, August.
    7. Zhao, Shangwei & Zhou, Jianhong & Li, Hongjun, 2016. "Model averaging with high-dimensional dependent data," Economics Letters, Elsevier, vol. 148(C), pages 68-71.
    8. Afonso, António & Huart, Florence & Tovar Jalles, João & Stanek, Piotr, 2022. "Twin deficits revisited: A role for fiscal institutions?," Journal of International Money and Finance, Elsevier, vol. 121(C).
    9. Berger, Michael & Pock, Markus & Reiss, Miriam & Röhrling, Gerald & Czypionka, Thomas, 2023. "Exploring the effectiveness of demand-side retail pharmaceutical expenditure reforms: cross-country evidence from weighted-average least squares estimation," LSE Research Online Documents on Economics 116928, London School of Economics and Political Science, LSE Library.
    10. Aman Ullah & Alan T. K. Wan & Huansha Wang & Xinyu Zhang & Guohua Zou, 2017. "A semiparametric generalized ridge estimator and link with model averaging," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 370-384, March.
    11. Michael Berger & Markus Pock & Miriam Reiss & Gerald Röhrling & Thomas Czypionka, 2023. "Exploring the effectiveness of demand-side retail pharmaceutical expenditure reforms," International Journal of Health Economics and Management, Springer, vol. 23(1), pages 149-172, March.
    12. Shangwei Zhao & Aman Ullah & Xinyu Zhang, 2018. "A Class of Model Averaging Estimators," Working Paper series 18-11, Rimini Centre for Economic Analysis.
    13. Jan R. Magnus & Wendun Wang & Xinyu Zhang, 2016. "Weighted-Average Least Squares Prediction," Econometric Reviews, Taylor & Francis Journals, vol. 35(6), pages 1040-1074, June.
    14. Sufrauj, Shamnaaz & Schiavo, Stefano & Riccaboni, Massimo, 2014. "The Structure and Growth of World Trade, and the Role of Europe in the Global Economy," MPRA Paper 54122, University Library of Munich, Germany.
    15. Mark F. J. Steel, 2020. "Model Averaging and Its Use in Economics," Journal of Economic Literature, American Economic Association, vol. 58(3), pages 644-719, September.
    16. Giuseppe De Luca & Jan R. Magnus, 2011. "Bayesian model averaging and weighted-average least squares: Equivariance, stability, and numerical issues," Stata Journal, StataCorp LP, vol. 11(4), pages 518-544, December.
    17. Zhao, Shangwei & Ullah, Aman & Zhang, Xinyu, 2018. "A class of model averaging estimators," Economics Letters, Elsevier, vol. 162(C), pages 101-106.
    18. Karen Poghosyan & Jan R. Magnus, 2012. "WALS Estimation and Forecasting in Factor-based Dynamic Models with an Application to Armenia," International Econometric Review (IER), Econometric Research Association, vol. 4(1), pages 40-58, April.
    19. De Luca, Giuseppe & Magnus, Jan R. & Peracchi, Franco, 2022. "Sampling properties of the Bayesian posterior mean with an application to WALS estimation," Journal of Econometrics, Elsevier, vol. 230(2), pages 299-317.
    20. Christopher F. Parmeter & Alan T. K. Wan & Xinyu Zhang, 2019. "Model averaging estimators for the stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 51(2), pages 91-103, June.
    21. Aedın Doris & Donal O’Neill & Olive Sweetman, 2011. "GMM estimation of the covariance structure of longitudinal data on earnings," Stata Journal, StataCorp LP, vol. 11(3), pages 439-459, September.
    22. Xinyu Zhang & Alan T. K. Wan & Sherry Z. Zhou, 2011. "Focused Information Criteria, Model Selection, and Model Averaging in a Tobit Model With a Nonzero Threshold," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 132-142, June.
    23. Yin-Wong Cheung & Wenhao Wang, 2020. "A Jackknife Model Averaging Analysis of RMB Misalignment Estimates," Journal of International Commerce, Economics and Policy (JICEP), World Scientific Publishing Co. Pte. Ltd., vol. 11(02), pages 1-45, June.
    24. Judith Anne Clarke, 2017. "Model Averaging OLS and 2SLS: An Application of the WALS Procedure," Econometrics Working Papers 1701, Department of Economics, University of Victoria.
    25. Magnus, J.R. & Wang, W. & Zhang, Xinyu, 2012. "WALS Prediction," Other publications TiSEM 7715e942-b446-4985-8216-f, Tilburg University, School of Economics and Management.

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