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Easy Bootstrap-Like Estimation of Asymptotic Variances

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Listed:
  • Bo E. Honore
  • Luojia Hu

Abstract

The bootstrap is a convenient tool for calculating standard errors of the parameter estimates of complicated econometric models. Unfortunately, the bootstrap can be very time-consuming. In a recent paper, Honor and Hu (2017), we propose a ?Poor (Wo)man's Bootstrap? based on one-dimensional estimators. In this paper, we propose a modified, simpler method and illustrate its potential for estimating asymptotic variances.

Suggested Citation

  • Bo E. Honore & Luojia Hu, 2018. "Easy Bootstrap-Like Estimation of Asymptotic Variances," Working Paper Series WP-2018-11, Federal Reserve Bank of Chicago.
  • Handle: RePEc:fip:fedhwp:wp-2018-11
    DOI: 10.21033/wp-2018-11
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    References listed on IDEAS

    as
    1. Bo E. Honoré & Luojia Hu, 2017. "Poor (Wo)man's Bootstrap," Econometrica, Econometric Society, vol. 85, pages 1277-1301, July.
    2. Powell, James L., 1984. "Least absolute deviations estimation for the censored regression model," Journal of Econometrics, Elsevier, vol. 25(3), pages 303-325, July.
    3. Newey, Whitney K., 1984. "A method of moments interpretation of sequential estimators," Economics Letters, Elsevier, vol. 14(2-3), pages 201-206.
    4. Hahn, Jinyong, 1996. "A Note on Bootstrapping Generalized Method of Moments Estimators," Econometric Theory, Cambridge University Press, vol. 12(1), pages 187-197, March.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    standard error; bootstrap; inference; censored regression; two-step estimation;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General

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