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Error covariance matrix correction based approach to functional coefficient regression models with generated covariates

  • Li, XiaoLi
  • You, JinHong
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    In this paper, we are concerned with the estimating problem of functional coefficient regression models with generated covariates. A new local polynomial estimation is proposed, which is based on error covariance matrix correction. It is shown that the resulting estimators are consistent, asymptotically normal and avoid the problem of undersmoothing. We estimate the error covariance matrix by difference based method. Therefore, the proposed new estimation avoids calibrating the covariate nonparametrically. Our difference based error covariance matrix estimator allows the order of difference to tend to be infinite and is asymptotically equivalent to the residual based estimator. In addition, we construct the simultaneous confidence bands for the underlying coefficient functions. The finite sample performance of our procedure is investigated in a simulation study and a real data set is analyzed to illustrate the usefulness of our procedure as well.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0047259X12000243
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    Article provided by Elsevier in its journal Journal of Multivariate Analysis.

    Volume (Year): 107 (2012)
    Issue (Month): C ()
    Pages: 263-281

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    Handle: RePEc:eee:jmvana:v:107:y:2012:i:c:p:263-281
    DOI: 10.1016/j.jmva.2012.01.023
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    1. Colin Wu & Kai Yu & Chin-Tsang Chiang, 2000. "A Two-Step Smoothing Method for Varying-Coefficient Models with Repeated Measurements," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 52(3), pages 519-543, September.
    2. Whitney Newey & James Powell & Francis Vella, 1998. "Nonparametric Estimation of Triangular Simultaneous Equations Models," Working papers 98-16, Massachusetts Institute of Technology (MIT), Department of Economics.
    3. Jinyong Hahn & Geert Ridder, 2010. "The Asymptotic Variance of Semi-parametric Estimators with Generated Regressors," Textos para discussão 575, Department of Economics PUC-Rio (Brazil).
    4. Jianqing Fan, 2000. "Simultaneous Confidence Bands and Hypothesis Testing in Varying-coefficient Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 27(4), pages 715-731.
    5. Newey, W.K., 1989. "Efficient Instrumental Variables Estimation Of Nonlinear Models," Papers 341, Princeton, Department of Economics - Econometric Research Program.
    6. Jianhua Z. Huang, 2002. "Varying-coefficient models and basis function approximations for the analysis of repeated measurements," Biometrika, Biometrika Trust, vol. 89(1), pages 111-128, March.
    7. Oxley, Les & McAleer, Michael, 1993. " Econometric Issues in Macroeconomic Models with Generated Regressors," Journal of Economic Surveys, Wiley Blackwell, vol. 7(1), pages 1-40.
    8. Rilstone, Paul, 1996. "Nonparametric Estimation of Models with Generated Regressors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 37(2), pages 299-313, May.
    9. Pagan, Adrian, 1984. "Econometric Issues in the Analysis of Regressions with Generated Regressors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 25(1), pages 221-47, February.
    10. Zhang, Wenyang & Lee, Sik-Yum, 2000. "Variable Bandwidth Selection in Varying-Coefficient Models," Journal of Multivariate Analysis, Elsevier, vol. 74(1), pages 116-134, July.
    11. Zongwu Cai & Jianqing Fan & Qiwei Yao, 2000. "Functional-coefficient regression models for nonlinear time series," LSE Research Online Documents on Economics 6314, London School of Economics and Political Science, LSE Library.
    12. Jinyong Hahn & Geert Ridder, 2010. "The asymptotic variance of semi-parametric estimators with generated regressors," CeMMAP working papers CWP23/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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