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Bootstrapping Macroeconometric Models

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  • Ray Fair

Abstract

This paper outlines a bootstrapping approach to the estimation and analysis of macroeconometric models. It integrates for dynamic, nonlinear, simultaneous equation models the bootstrapping approach to evaluating estimators initiated by Efron (1979) and the stochastic simulation approach to evaluating models' properties initiated by Adelman and Adelman (1959). It also estimates for a particular model the gain in coverage accuracy from using bootstrap confidence intervals over asymptotic confidence intervals.

Suggested Citation

  • Ray Fair, 2002. "Bootstrapping Macroeconometric Models," Yale School of Management Working Papers ysm254, Yale School of Management, revised 01 Aug 2007.
    • Handle: RePEc:ysm:wpaper:ysm254
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    File URL: https://repec.som.yale.edu/icfpub/publications/2374.pdf
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    References listed on IDEAS

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    1. Runkle, David E, 1987. "Vector Autoregressions and Reality," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 437-442, October.
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    3. Bianchi, Carlo & Calzolari, Giorgio & Corsi, Paolo, 1976. "Divergences in the results of stochastic and deterministic simulation of an Italian non linear econometric model," MPRA Paper 21287, University Library of Munich, Germany.
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    6. Jeremy Berkowitz & Lutz Kilian, 2000. "Recent developments in bootstrapping time series," Econometric Reviews, Taylor & Francis Journals, vol. 19(1), pages 1-48.
    7. T. Muench & A. Rolnick & N. Wallace & W. Weiler, 1974. "Tests for Structural Change and Prediction Intervals for the Reduced Forms of Two Structural Models of the US: The FRB-MIT and Michigan Quarterly Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 3, pages 491-519, National Bureau of Economic Research, Inc.
    8. David E. Runkle, 1987. "Vector autoregressions and reality," Staff Report 107, Federal Reserve Bank of Minneapolis.
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    Keywords

    Bootstrapping; Stochastic Simulation;

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