IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/16127.html
   My bibliography  Save this paper

A Score Based Approach to Wild Bootstrap Inference

Author

Listed:
  • Patrick M. Kline
  • Andres Santos

Abstract

We propose a generalization of the wild bootstrap of Wu (1986) and Liu (1988) based upon perturbing the scores of M-estimators. This "score bootstrap" procedure avoids recomputing the estimator in each bootstrap iteration, making it substantially less costly to compute than the conventional nonparametric bootstrap, particularly in complex nonlinear models. Despite this computational advantage, in the linear model, the score bootstrap studentized test statistic is equivalent to that of the conventional wild bootstrap up to order `O_p(n^(-1))`. We establish the consistency of the procedure for Wald and Lagrange Multiplier type tests and tests of moment restrictions for a wide class of M-estimators under clustering and potential misspecification. In an extensive series of Monte Carlo experiments we find that the performance of the score bootstrap is comparable to competing approaches despite its computational savings.

Suggested Citation

  • Patrick M. Kline & Andres Santos, 2010. "A Score Based Approach to Wild Bootstrap Inference," NBER Working Papers 16127, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:16127 Note: TWP LS
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w16127.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. White,Halbert, 1996. "Estimation, Inference and Specification Analysis," Cambridge Books, Cambridge University Press, number 9780521574464, December.
    2. Hiroaki Kaido & Andres Santos, 2014. "Asymptotically Efficient Estimation of Models Defined by Convex Moment Inequalities," Econometrica, Econometric Society, vol. 82(1), pages 387-413, January.
    3. Cavaliere, Giuseppe & Taylor, A.M. Robert, 2008. "Bootstrap Unit Root Tests For Time Series With Nonstationary Volatility," Econometric Theory, Cambridge University Press, vol. 24(01), pages 43-71, February.
    4. Chesher, Andrew, 1995. "A Mirror Image Invariance for M-Estimators," Econometrica, Econometric Society, vol. 63(1), pages 207-211, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Melvin Stephens, Jr. & Desmond J. Toohey, 2018. "The Impact of Health on Labor Market Outcomes: Experimental Evidence from MRFIT," NBER Working Papers 24231, National Bureau of Economic Research, Inc.
    2. Baumgarten, Daniel & Kvasnicka, Michael, 2017. "Temporary agency work and the Great Recession," Journal of Economic Behavior & Organization, Elsevier, vol. 136(C), pages 29-44.
    3. Hill, Jonathan B. & Aguilar, Mike, 2013. "Moment condition tests for heavy tailed time series," Journal of Econometrics, Elsevier, vol. 172(2), pages 255-274.
    4. Xiaohong Chen & Demian Pouzo, 2014. "Sieve Wald and QLR Inferences on Semi/nonparametric Conditional Moment Models," Papers 1411.1144, arXiv.org, revised Mar 2015.
    5. Federico Belotti & Edoardo Di Porto & Gianluca Santoni, 2016. "The Effect of Local Taxes on Firm Performance: Evidence from Geo-referenced Data," CEIS Research Paper 377, Tor Vergata University, CEIS, revised 13 Apr 2016.
    6. A. Belloni & V. Chernozhukov & I. Fernández‐Val & C. Hansen, 2017. "Program Evaluation and Causal Inference With High‐Dimensional Data," Econometrica, Econometric Society, vol. 85, pages 233-298, January.
    7. A. Colin Cameron & Douglas L. Miller, 2015. "A Practitioner’s Guide to Cluster-Robust Inference," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 317-372.
    8. repec:cup:etheor:v:33:y:2017:i:05:p:1218-1241_00 is not listed on IDEAS
    9. Kaido, Hiroaki, 2017. "Asymptotically Efficient Estimation Of Weighted Average Derivatives With An Interval Censored Variable," Econometric Theory, Cambridge University Press, vol. 33(05), pages 1218-1241, October.
    10. Xiaohong Chen & Demian Pouzo, 2013. "Sieve Wald and QLR Inferences on Semi/nonparametric Conditional Moment Models," Cowles Foundation Discussion Papers 1897R, Cowles Foundation for Research in Economics, Yale University, revised Apr 2014.
    11. repec:eee:jeeman:v:86:y:2017:i:c:p:121-140 is not listed on IDEAS
    12. Matei Demetrescu & Christoph Hanck, 2013. "Nonlinear IV panel unit root testing under structural breaks in the error variance," Statistical Papers, Springer, vol. 54(4), pages 1043-1066, November.
    13. Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2013. "Program evaluation with high-dimensional data," CeMMAP working papers CWP57/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    14. repec:eee:jeborg:v:142:y:2017:i:c:p:64-78 is not listed on IDEAS
    15. Armstrong, Timothy B. & Bertanha, Marinho & Hong, Han, 2014. "A fast resample method for parametric and semiparametric models," Journal of Econometrics, Elsevier, vol. 179(2), pages 128-133.
    16. Charles E. Gibbons & Juan Carlos Suárez Serrato & Michael B. Urbancic, 2014. "Broken or Fixed Effects?," NBER Working Papers 20342, National Bureau of Economic Research, Inc.
    17. Su, Liangjun & Hoshino, Tadao, 2016. "Sieve instrumental variable quantile regression estimation of functional coefficient models," Journal of Econometrics, Elsevier, vol. 191(1), pages 231-254.
    18. repec:eee:jeborg:v:141:y:2017:i:c:p:177-187 is not listed on IDEAS
    19. Linda Babcock & Maria P. Recalde & Lise Vesterlund & Laurie Weingart, 2017. "Gender Differences in Accepting and Receiving Requests for Tasks with Low Promotability," American Economic Review, American Economic Association, vol. 107(3), pages 714-747, March.
    20. Xiaohong Chen & Demian Pouzo, 2014. "Sieve Wald and QLR Inferences on Semi/nonparametric Conditional Moment Models," CeMMAP working papers CWP38/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    21. Xiaohong Chen & Demian Pouzo, 2013. "Sieve Wald and QLR Inferences on Semi/nonparametric Conditional Moment Models," Cowles Foundation Discussion Papers 1897RR, Cowles Foundation for Research in Economics, Yale University, revised Nov 2014.
    22. Keith Finlay & Leandro M. Magnusson, 2014. "Bootstrap Methods for Inference with Cluster-Sample IV Models," Economics Discussion / Working Papers 14-12, The University of Western Australia, Department of Economics.

    More about this item

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:16127. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (). General contact details of provider: http://edirc.repec.org/data/nberrus.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.