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Better Confidence Intervals: The Double Bootstrap with No Pivot

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  • David Letson
  • B.D. McCullough

Abstract

The double bootstrap is an important advance in confidence interval generation because it converges faster than the already popular single bootstrap. Yet the usual double bootstrap requires a stable pivot that is not always available, e.g., when estimating flexibilities or substitution elasticities. A recently developed double bootstrap does not require a pivot. A Monte Carlo analysis with the Waugh data finds the double bootstrap achieves nominal coverage whereas the single bootstrap does not. A useful artifice dramatically decreases the computational time of the double bootstrap. Copyright 1998, Oxford University Press.

Suggested Citation

  • David Letson & B.D. McCullough, 1998. "Better Confidence Intervals: The Double Bootstrap with No Pivot," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(3), pages 552-559.
    • Handle: RePEc:oup:ajagec:v:80:y:1998:i:3:p:552-559
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    Citations

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    Cited by:

    1. Patrice Bertail & Christine Boizot & Pierre Combris, 2003. "Évaluation de la précision d’estimateurs de fonctionnelles : l’exemple de la consommation alimentaire," Post-Print hal-01201043, HAL.
    2. Kim, Jae H. & Fraser, Iain & Hyndman, Rob J., 2011. "Improved interval estimation of long run response from a dynamic linear model: A highest density region approach," Computational Statistics & Data Analysis, Elsevier, vol. 55(8), pages 2477-2489, August.
    3. Park, Seong C. & Brorsen, B. Wade & Stoecker, Arthur L. & Hattey, Jeffory A., 2012. "Forage Response to Swine Effluent: A Cox Nonnested Test of Alternative Functional Forms Using a Fast Double Bootstrap," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 44(4), pages 593-606, November.
    4. Patrice Bertail & Christine Boizot & Pierre Combris, 2003. "Évaluation de la précision d’estimateurs de fonctionnelles : l’exemple de la consommation alimentaire," Cahiers d'Economie et Sociologie Rurales, INRA Department of Economics, vol. 67, pages 71-102.
    5. Yoonsuk Lee & B. Wade Brorsen, 2017. "Permanent Breaks and Temporary Shocks in a Time Series," Computational Economics, Springer;Society for Computational Economics, vol. 49(2), pages 255-270, February.
    6. H. D. Vinod & B. D. McCullough, 1999. "The Numerical Reliability of Econometric Software," Journal of Economic Literature, American Economic Association, vol. 37(2), pages 633-665, June.
    7. McCullough, B D, 1999. "Econometric Software Reliability: EViews, LIMDEP, SHAZAM and TSP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(2), pages 191-202, March-Apr.
    8. Bertail, Patrice & Boizot, Christine & Combris, Pierre, 2003. "Évaluation de la précision d’estimateurs de fonctionnelles : l’exemple de la consommation alimentaire," Cahiers d'Economie et de Sociologie Rurales (CESR), Institut National de la Recherche Agronomique (INRA), vol. 67.
    9. Yoonsuk Lee & B. Wade Brorsen, 2017. "Permanent shocks and forecasting with moving averages," Applied Economics, Taylor & Francis Journals, vol. 49(12), pages 1213-1225, March.

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