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Bootstrapping econometric models (in Russian)

Author

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  • Russell Davidson

    (McGill University, Canada
    GREQAM, France)

Abstract

The bootstrap is a statistical technique used more and more widely in econometrics. While it is capable of yielding very reliable inference, some precautions should be taken in order to ensure this. Two “Golden Rules” are formulated that, if observed, help to obtain the best the bootstrap can offer. Bootstrapping always involves setting up a bootstrap data-generating process (DGP). The main types of bootstrap DGP in current use are discussed, with examples of their use in econometrics. The ways in which the bootstrap can be used to construct confidence sets differ somewhat from methods of hypothesis testing. The relation between the two sorts of problem is discussed.

Suggested Citation

  • Russell Davidson, 2007. "Bootstrapping econometric models (in Russian)," Quantile, Quantile, issue 3, pages 13-36, September.
    • Handle: RePEc:qnt:quantl:y:2007:i:3:p:13-36
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    References listed on IDEAS

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    1. Childers, Terry L. & Kaufman-Scarborough, Carol, 2009. "Expanding opportunities for online shoppers with disabilities," Journal of Business Research, Elsevier, vol. 62(5), pages 572-578, May.
    2. Davidson, Russell & Flachaire, Emmanuel, 2008. "The wild bootstrap, tamed at last," Journal of Econometrics, Elsevier, vol. 146(1), pages 162-169, September.
    3. Brown, Bryan W & Newey, Whitney K, 2002. "Generalized Method of Moments, Efficient Bootstrapping, and Improved Inference," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 507-517, October.
    4. Foster, James & Greer, Joel & Thorbecke, Erik, 1984. "A Class of Decomposable Poverty Measures," Econometrica, Econometric Society, vol. 52(3), pages 761-766, May.
    5. Giulia Galera, 2009. "The ‘Re-Emergence’ of Social Enterprises in CEE and the CIS," AIEL Series in Labour Economics, in: Marco Musella & Sergio Destefanis (ed.), Paid and Unpaid Labour in the Social Economy. An International Perspective, edition 1, chapter 14, pages 245-262, AIEL - Associazione Italiana Economisti del Lavoro.
    6. Juan Alberto à valos, 2015. "Principales Variables Para La Gestiã“N De Cadenas De Valor Agroalimentaria," Observatorio de la Economía Latinoamericana, Servicios Académicos Intercontinentales SL. Hasta 31/12/2022, issue 214, December.
    7. Blake D. Ratner & Edward H. Allison, 2012. "Wealth, Rights, and Resilience: An Agenda for Governance Reform in Small-scale Fisheries," Development Policy Review, Overseas Development Institute, vol. 30(4), pages 371-398, July.
    8. Pradhan, Jaya Prakash, 2008. "Indian Direct Investment in Developing Countries: Emerging Trends and Development Impacts," MPRA Paper 12323, University Library of Munich, Germany.
    9. Engelmann, Dirk, 2005. "Auctions: Theory and practice, by Klemperer, P., Princeton University Press, Princeton, NJ, 2004, pp. 246, ISBN: 0-691-11925-2, (5 figures, 1 Table), $29.95 (Paperback)," Journal of Economic Psychology, Elsevier, vol. 26(1), pages 155-157, February.
    10. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    11. Jean-Marie Dufour, 1997. "Some Impossibility Theorems in Econometrics with Applications to Structural and Dynamic Models," Econometrica, Econometric Society, vol. 65(6), pages 1365-1388, November.
    12. Rafael Ranieri & Raquel Almeida Ramos, 2013. "After All, What is Inclusive Growth?," One Pager 188, International Policy Centre for Inclusive Growth.
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    Cited by:

    1. Davidson, Russell, 2017. "A discrete model for bootstrap iteration," Journal of Econometrics, Elsevier, vol. 201(2), pages 228-236.
    2. Mazzutti, Caio Cícero Toledo Piza da Costa, 2016. "Three essays on the causal impacts of child labour laws in Brazil," Economics PhD Theses 0616, Department of Economics, University of Sussex Business School.
    3. Barbara Hutniczak & Niels Vestergaard & Dale Squires, 2019. "Policy Change Anticipation in the Buyback Context," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 73(1), pages 111-132, May.
    4. Yang, Zhenlin, 2015. "LM tests of spatial dependence based on bootstrap critical values," Journal of Econometrics, Elsevier, vol. 185(1), pages 33-59.
    5. Russell Davidson & Victoria Zinde‐Walsh, 2017. "Advances in specification testing," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 50(5), pages 1595-1631, December.
    6. Russell Davidson, 2010. "Innis Lecture: Inference on income distributions," Canadian Journal of Economics, Canadian Economics Association, vol. 43(4), pages 1122-1148, November.
    7. Hounyo, Ulrich & Varneskov, Rasmus T., 2017. "A local stable bootstrap for power variations of pure-jump semimartingales and activity index estimation," Journal of Econometrics, Elsevier, vol. 198(1), pages 10-28.

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    More about this item

    Keywords

    Bootstrap; hypothesis test; confidence set;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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