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On Edgeworth Expansion and Moving Block Bootstrap for StudentizedM-Estimators in Multiple Linear Regression Models

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  • Lahiri, Soumendra Nath
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    Abstract

    This paper considers the multiple linear regression modelYi=xi'[beta]+[var epsilon]i,i=i, ..., n, wherexi's are knownp-1 vectors,[beta]is ap-1 vector of parameters, and[var epsilon]1,[var epsilon]2, ... are stationary, strongly mixing random variables. Let[beta]ndenote anM-estimator of[beta]corresponding to some score function[psi]. Under some conditions on[psi],xi's and[var epsilon]i's, a two-term Edgeworth expansion for Studentized multivariateM-estimator is proved. Furthermore, it is shown that the moving block bootstrap is second-order correct for some suitable bootstrap analog of Studentized[beta]n.

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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Multivariate Analysis.

    Volume (Year): 56 (1996)
    Issue (Month): 1 (January)
    Pages: 42-59

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    Handle: RePEc:eee:jmvana:v:56:y:1996:i:1:p:42-59

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    Related research

    Keywords: Edgeworth expansion moving block bootstrap M-estimators multiple linear regression stationarity strong mixing Studentization (null);

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    Cited by:
    1. Ching-Chuan Tsong, 2009. "Assessing the Accuracy of Event Forecasts," Journal of Economics and Management, College of Business, Feng Chia University, Taiwan, vol. 5(2), pages 219-240, July.
    2. Goncalves, Silvia & White, Halbert, 2000. "Maximum Likelihood and the Bootstrap for Nonlinear Dynamic Models," University of California at San Diego, Economics Working Paper Series qt1bj657ff, Department of Economics, UC San Diego.
    3. Inoue, Atsushi & Shintani, Mototsugu, 2006. "Bootstrapping GMM estimators for time series," Journal of Econometrics, Elsevier, vol. 133(2), pages 531-555, August.
    4. Janis J. Zvingelis, 2000. "On Bootstrap Coverage Probability with Dependent Data," Econometric Society World Congress 2000 Contributed Papers 1231, Econometric Society.
    5. Blaskowitz, Oliver & Herwartz, Helmut, 2014. "Testing the value of directional forecasts in the presence of serial correlation," International Journal of Forecasting, Elsevier, vol. 30(1), pages 30-42.
    6. Härdle, Wolfgang & Horowitz, Joel L. & Kreiss, Jens-Peter, 2001. "Bootstrap methods for time series," SFB 373 Discussion Papers 2001,59, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

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