IDEAS home Printed from https://ideas.repec.org/p/qed/wpaper/1027.html
   My bibliography  Save this paper

Simulation-based Tests That Can Use Any Number Of Simulations

Author

Listed:
  • James G. MacKinnon

    (Queen's University)

  • Jeff Racine

    (McMaster University)

Abstract

Conventional procedures for Monte Carlo and bootstrap tests require that B, the number of simulations, satisfy a specific relationship with the level of the test. Otherwise, a test that would instead be exact will either overreject or underreject for finite B. We present expressions for the rejection frequencies associated with existing procedures and propose a new procedure that yields exact Monte Carlo tests for any positive value of B. This procedure, which can also be used for bootstrap tests, is likely to be most useful when simulation is expensive.

Suggested Citation

  • James G. MacKinnon & Jeff Racine, 2004. "Simulation-based Tests That Can Use Any Number Of Simulations," Working Paper 1027, Economics Department, Queen's University.
    • Handle: RePEc:qed:wpaper:1027
    as

    Download full text from publisher

    File URL: https://www.econ.queensu.ca/sites/econ.queensu.ca/files/qed_wp_1027.pdf
    File Function: First version 2004
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Russell Davidson & James MacKinnon, 2000. "Bootstrap tests: how many bootstraps?," Econometric Reviews, Taylor & Francis Journals, vol. 19(1), pages 55-68.
    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. James G. MacKinnon, 2012. "Thirty Years Of Heteroskedasticity-robust Inference," Working Paper 1268, Economics Department, Queen's University.
    2. Rand R. Wilcox, 2018. "Robust regression: an inferential method for determining which independent variables are most important," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(1), pages 100-111, January.
    3. Rand Wilcox & Florence Clark, 2014. "Comparing robust regression lines associated with two dependent groups when there is heteroscedasticity," Computational Statistics, Springer, vol. 29(5), pages 1175-1186, October.
    4. JAMES G. MacKINNON, 2006. "Bootstrap Methods in Econometrics," The Economic Record, The Economic Society of Australia, vol. 82(s1), pages 2-18, September.
    5. James G. MacKinnon, 2007. "Bootstrap Hypothesis Testing," Working Paper 1127, Economics Department, Queen's University.
    6. Racine, Jeffrey S. & MacKinnon, James G., 2007. "Inference via kernel smoothing of bootstrap P values," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5949-5957, August.
    7. Francisco J. Ruge-Murcia, 2013. "Generalized Method of Moments estimation of DSGE models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 20, pages 464-485, Edward Elgar Publishing.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. M.L. Nores & M.P. Díaz, 2016. "Bootstrap hypothesis testing in generalized additive models for comparing curves of treatments in longitudinal studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(5), pages 810-826, April.
    2. Johannesson Magnus & Östling Robert & Ranehill Eva, 2010. "The Effect of Competition on Physical Activity: A Randomized Trial," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 10(1), pages 1-31, September.
    3. Wen Shi & Xi Chen & Jennifer Shang, 2019. "An Efficient Morris Method-Based Framework for Simulation Factor Screening," INFORMS Journal on Computing, INFORMS, vol. 31(4), pages 745-770, October.
    4. repec:ebl:ecbull:v:30:y:2010:i:1:p:55-66 is not listed on IDEAS
    5. Dong Ding & Axel Gandy & Georg Hahn, 2020. "A simple method for implementing Monte Carlo tests," Computational Statistics, Springer, vol. 35(3), pages 1373-1392, September.
    6. Davidson, Russell, 2009. "Reliable inference for the Gini index," Journal of Econometrics, Elsevier, vol. 150(1), pages 30-40, May.
    7. Sarlin, Peter & von Schweinitz, Gregor, 2021. "Optimizing Policymakers’ Loss Functions In Crisis Prediction: Before, Within Or After?," Macroeconomic Dynamics, Cambridge University Press, vol. 25(1), pages 100-123, January.
    8. Strikholm, Birgit & Teräsvirta, Timo, 2005. "Determining the Number of Regimes in a Threshold Autoregressive Model Using Smooth Transition Autoregressions," SSE/EFI Working Paper Series in Economics and Finance 578, Stockholm School of Economics, revised 11 Feb 2005.
    9. Emmanuel Flachaire, 2000. "Les méthodes du bootstrap dans les modèles de régression," Économie et Prévision, Programme National Persée, vol. 142(1), pages 183-194.
    10. Francis, Bill B. & Mougoué, Mbodja & Panchenko, Valentyn, 2010. "Is there a symmetric nonlinear causal relationship between large and small firms?," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 23-38, January.
    11. Priscila Espinosa & Jose M. Pavía, 2023. "Automation in Regional Economic Synthetic Index Construction with Uncertainty Measurement," Forecasting, MDPI, vol. 5(2), pages 1-19, April.
    12. Dufour, Jean-Marie & Khalaf, Lynda, 2002. "Simulation based finite and large sample tests in multivariate regressions," Journal of Econometrics, Elsevier, vol. 111(2), pages 303-322, December.
    13. Dang, Rey & Houanti, L'Hocine & Sahut, Jean-Michel & Simioni, Michel, 2021. "Do women on corporate boards influence corporate social performance? A control function approach," Finance Research Letters, Elsevier, vol. 39(C).
    14. Chiu, Sung Nok & Wang, Ling, 2009. "Homogeneity tests for several Poisson populations," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4266-4278, October.
    15. Fleissig, Adrian R. & Whitney, Gerald A., 2007. "Testing additive separability," Economics Letters, Elsevier, vol. 96(2), pages 215-220, August.
    16. Makram El-Shagi & Axel Lindner & Gregor von Schweinitz, 2016. "Real Effective Exchange Rate Misalignment in the Euro Area: A Counterfactual Analysis," Review of International Economics, Wiley Blackwell, vol. 24(1), pages 37-66, February.
    17. Judith Clarke & Nilanjana Roy & Marsha Courchane, 2009. "On the robustness of racial discrimination findings in mortgage lending studies," Applied Economics, Taylor & Francis Journals, vol. 41(18), pages 2279-2297.
    18. Görtz, Christoph & Yeromonahos, Mallory, 2022. "Asymmetries in risk premia, macroeconomic uncertainty and business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 137(C).
    19. Ghassan, Hassan B. & Alhajhoj, Hassan R., 2009. "اختبار أثر مزاحمة الإنفاق الحكومي للإستثمار الخاص في الاقتصاد السعودي عبر المعاينة المعادة [Crowding out Test of Government Expenditures to Private Investment in Saudi Arabia using Bootstrapping]," MPRA Paper 54453, University Library of Munich, Germany, revised 2009.
    20. Therese Lindahl & Magnus Johannesson, 2009. "Bargaining over a Common Good with Private Information," Scandinavian Journal of Economics, Wiley Blackwell, vol. 111(3), pages 547-565, September.
    21. Joachim Jarreau, 2015. "The Impact of Naturalizations on Job Mobility and Wages: Evidence from France," AMSE Working Papers 1508, Aix-Marseille School of Economics, France.

    More about this item

    Keywords

    resampling; Monte Carlo test; bootstrap test; percentiles;
    All these keywords.

    JEL classification:

    • 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

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:qed:wpaper:1027. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mark Babcock (email available below). General contact details of provider: https://edirc.repec.org/data/qedquca.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.