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Sieve bootstrap t-tests on long-run average parameters

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  • Fuertes, Ana-Maria

Abstract

Panel estimators can provide consistent measures of a long-run average parameter even if the individual regressions are spurious. However, the t-test on this parameter is fraught with problems because the limit distribution of the test statistic is non-standard and rather complicated, particularly in panels with mixed (non-)stationary errors. A sieve bootstrap framework is suggested to approximate the distribution of the t-statistic. An extensive Monte Carlo study demonstrates that the bootstrap is quite useful in this context.

Suggested Citation

  • Fuertes, Ana-Maria, 2008. "Sieve bootstrap t-tests on long-run average parameters," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3354-3370, March.
  • Handle: RePEc:eee:csdana:v:52:y:2008:i:7:p:3354-3370
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    Cited by:

    1. Di Iorio, Francesca & Fachin, Stefano, 2012. "A note on the estimation of long-run relationships in panel equations with cross-section linkages," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 6, pages 1-18.
    2. Stephan Smeekes & Jean-Pierre Urbain, 2014. "On the Applicability of the Sieve Bootstrap in Time Series Panels," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(1), pages 139-151, February.
    3. Marian Vavra, 2015. "On a Bootstrap Test for Forecast Evaluations," Working and Discussion Papers WP 5/2015, Research Department, National Bank of Slovakia.
    4. Urbain, J.R.Y.J. & Westerlund, J., 2008. "Spurious Regression in Nonstationary Panels time Series with Cross-Member Cointegration," Research Memorandum 044, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    5. Trapani, Lorenzo, 2021. "Inferential theory for heterogeneity and cointegration in large panels," Journal of Econometrics, Elsevier, vol. 220(2), pages 474-503.
    6. Trapani, Lorenzo, 2012. "On the asymptotic t-test for large nonstationary panel models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3286-3306.

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