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Bootstrap Methods For Covariance Structures

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  • Joel L. Horowitz

    (Univ. of Iowa)

Abstract

The optimal minimum distance (OMD) estimator for models of covariance structures is asymptotically efficient but has much worse finite-sample properties than does the equally-weighted minimum distance (EWMD) estimator. This paper shows how the bootstrap can be used to improve the finite-sample performance of the OMD estimator. The theory underlying the bootstrap's ability to reduce the bias of estimators and errors in the coverage probabilities of confidence intervals is summarized. The results of numerical experiments and an empirical example show that the bootstrap often essentially eliminates the bias of the OMD estimator. The finite-sample estimation efficiency of the bias-corrected OMD estimator often exceeds that of the EWMD estimator. Moreover, the true coverage probabilities of confidence intervals based on the OMD estimator with bootstrap critical values are very close to the nominal coverage probabilities.

Suggested Citation

  • Joel L. Horowitz, 1996. "Bootstrap Methods For Covariance Structures," Econometrics 9610003, EconWPA.
  • Handle: RePEc:wpa:wuwpem:9610003
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    References listed on IDEAS

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    1. Abowd, John M & Card, David, 1987. "Intertemporal Labor Supply and Long-term Employment Contracts," American Economic Review, American Economic Association, vol. 77(1), pages 50-68, March.
    2. Altonji, Joseph G & Segal, Lewis M, 1996. "Small-Sample Bias in GMM Estimation of Covariance Structures," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 353-366, July.
    3. Koenker, Roger & Machado, José A.F. & Skeels, Christopher L. & Welsh, Alan H., 1994. "Momentary Lapses: Moment Expansions and the Robustness of Minimum Distance Estimation," Econometric Theory, Cambridge University Press, vol. 10(01), pages 172-197, March.
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    8. Abowd, John M & Card, David, 1989. "On the Covariance Structure of Earnings and Hours Changes," Econometrica, Econometric Society, vol. 57(2), pages 411-445, March.
    9. Behrman, Jere R & Rosenzweig, Mark R & Taubman, Paul, 1994. "Endowments and the Allocation of Schooling in the Family and in the Marriage Market: The Twins Experiment," Journal of Political Economy, University of Chicago Press, vol. 102(6), pages 1131-1174, December.
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    Cited by:

    1. Victor Aguirregabiria & Victor Aguirregabiria & Aviv Nevo & Aviv Nevo, 2010. "Recent Developments in Empirical IO: Dynamic Demand and Dynamic Games," Working Papers tecipa-419, University of Toronto, Department of Economics.
    2. Rasmus Lentz & Dale T. Mortensen, 2008. "An Empirical Model of Growth Through Product Innovation," Econometrica, Econometric Society, vol. 76(6), pages 1317-1373, November.
    3. Gobillon, Laurent & Magnac, Thierry & Selod, Harris, 2007. "The Effect of Location on Finding a Job in the Greater Paris Area," IZA Discussion Papers 2848, Institute for the Study of Labor (IZA).
    4. Smith, Richard J., 2007. "Efficient information theoretic inference for conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 138(2), pages 430-460, June.
    5. James Heckman & Rosa Matzkin & Lars Nesheim, 2005. "Nonparametric estimation of nonadditive hedonic models," CeMMAP working papers CWP03/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Whitney K. Newey & Richard J. Smith, 2004. "Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators," Econometrica, Econometric Society, vol. 72(1), pages 219-255, January.
    7. Damba Lkhagvasuren, 2009. "Large Locational Differences in Unemployment Despite High Labor Mobility: Impact of Moving Cost on Aggregate Unemployment and Welfare," Working Papers 09009, Concordia University, Department of Economics, revised Mar 2010.
    8. Whitney K. Newey & Joaquim J. S. Ramalho Ramalho & Richard Smith, 2003. "Asymptotic bias for GMM and GEL estimators with estimated nuisance parameters," CeMMAP working papers CWP05/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Jeffrey M. Wooldridge, 2004. "Estimating average partial effects under conditional moment independence assumptions," CeMMAP working papers CWP03/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Louis-Philippe Morin, 2010. "Estimating the Benefit of High School for College-Bound Students," Working Papers 1002E, University of Ottawa, Department of Economics.
    11. Yuriy Gorodnichenko, 2007. "Using Firm Optimization to Evaluate and Estimate Returns to Scale," NBER Working Papers 13666, National Bureau of Economic Research, Inc.
    12. Joachim Inkmann, 2000. "Finite Sample Properties of One-Step, Two-Step and Bootstrap Empirical Likelihood Approaches to Efficient GMM Estimation," Econometric Society World Congress 2000 Contributed Papers 0332, Econometric Society.
    13. Yuriy Gorodnichenko, 2005. "Reduced-Rank Identification of Structural Shocks in VARs," Macroeconomics 0512011, EconWPA.
    14. Gorodnichenko, Yuriy & Ng, Serena, 2010. "Estimation of DSGE models when the data are persistent," Journal of Monetary Economics, Elsevier, vol. 57(3), pages 325-340, April.

    More about this item

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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