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Bootstrap Specification Tests with Dependent Observations and Parameter Estimation Error


  • Valentina Corradi

    () (Department of Economics, University of Exeter)

  • Norman R. Swanson

    () (Texas A&M University)


This paper introduces a parametric specification test for dissusion processes which is based on a bootstrap procedure that accounts for data dependence and parameter estimation error. The proposed bootstrap procedure additionally leads to straightforward generalizations of the conditional Kolmogorov test of Andrews (1997) and the conditional mean test of Whang (2000) to the case of dependent observations. The bootstrap hinges on a twofold extension of the Politis and Romano (1994) stationary bootstrap. First we provide an empirical process version of this bootstrap, and second, we account for parameter estimation error. One important feature of this new bootstrap is that one need not specify the conditional distribution given the entire history of the process when forming conditional Kolmogorov tests. Hence, the bootstrap, when used to extend Andrews (1997) conditional Kolmogorov test to the case of data dependence, allows for dynamic misspecification under both hypotheses. An example based on a version of the Cox, Ingersol and Ross square root process is outlined and related Monte Carlo experiments are carried out. These experiments suggest that the boostrap has excellent finite sample properties, even for samples as small as 500 observations when tests are formed using critical values constructed with as few as 100 bootstrap replications. .

Suggested Citation

  • Valentina Corradi & Norman R. Swanson, 2001. "Bootstrap Specification Tests with Dependent Observations and Parameter Estimation Error," Discussion Papers 0101, Exeter University, Department of Economics.
  • Handle: RePEc:exe:wpaper:0101

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    References listed on IDEAS

    1. Myerson, Roger B, 1983. "Mechanism Design by an Informed Principal," Econometrica, Econometric Society, vol. 51(6), pages 1767-1797, November.
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    3. Gorton, Gary, 1985. "Bank suspension of convertibility," Journal of Monetary Economics, Elsevier, vol. 15(2), pages 177-193, March.
    4. Ted Temzelides & Bernandino Adao, 1995. "Beliefs, Competition, and Bank Runs," Finance 9511001, EconWPA.
    5. V.V. Chari & Ravi Jagannathan, 1984. "Banking Panics," Discussion Papers 618, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    6. Chari, V V & Jagannathan, Ravi, 1988. " Banking Panics, Information, and Rational Expectations Equilibrium," Journal of Finance, American Finance Association, vol. 43(3), pages 749-761, July.
    7. Neil Wallace, 1988. "Another attempt to explain an illiquid banking system: the Diamond and Dybvig model with sequential service taken seriously," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall, pages 3-16.
    8. Bernardino Adao & Ted Temzelides, 1998. "Sequential Equilibrium and Competition in a Diamond-Dybvig Banking Model," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 1(4), pages 859-877, October.
    9. S. Rao Aiyagari, 1988. "Banking panics, information, and rational expectations equilibrium," Working Papers 320, Federal Reserve Bank of Minneapolis.
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    Cited by:

    1. Xiaohong Chen & Yanqin Fan, 2002. "Evaluating Density Forecasts via the Copula Approach," Vanderbilt University Department of Economics Working Papers 0225, Vanderbilt University Department of Economics, revised Sep 2003.

    More about this item


    Diffusion process; parameter estimation error; specification test; stationary bootstrap.;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes


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