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Bootstrap Methods in Econometrics

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  • James G. MacKinnon

    () (Queen's University)

Abstract

There are many bootstrap methods that can be used for econometric analysis. In certain circumstances, such as regression models with independent and identically distributed error terms, appropriately chosen bootstrap methods generally work very well. However, there are many other cases, such as regression models with dependent errors, in which bootstrap methods do not always work well. This paper discusses a large number of bootstrap methods that can be useful in econometrics. Applications to hypothesis testing are emphasized, and simulation results are presented for a few illustrative cases.

Suggested Citation

  • James G. MacKinnon, 2006. "Bootstrap Methods in Econometrics," Working Papers 1028, Queen's University, Department of Economics.
    • Handle: RePEc:qed:wpaper:1028
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    File URL: http://qed.econ.queensu.ca/working_papers/papers/qed_wp_1028.pdf
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    References listed on IDEAS

    as
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    9. Jeff Racine & James G. MacKinnon, 2004. "Simulation-based Tests that Can Use Any Number of Simulations," Working Papers 1027, Queen's University, Department of Economics.
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    More about this item

    Keywords

    bootstrap; Monte Carlo test; wild bootstrap; sieve bootstrap; moving block bootstrap;

    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

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