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Inference for Impulse Responses

Author

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  • Oscar Jorda

    (Department of Economics, University of California Davis)

Abstract

Poor identification of individual impulse response coefficients does not necessarily mean that an impulse response is imprecisely estimated. This paper introduces a three-pronged approach on how to communicate uncertainty of impulse response estimates: (1) withWald tests of joint significance; (2) with conditional t-tests of individual marginal coefficient significance; and (3) with fan charts based on the percentiles of the joint Wald statistics. The paper also shows how to anchor the impulse response analysis with a priori economic restrictions that can be formally tested and used to tighten structural identification. These methods are universal and do not depend on how the impulse responses are estimated. An empirical application illustrates the techniques in practice.

Suggested Citation

  • Oscar Jorda, 2007. "Inference for Impulse Responses," Working Papers 77, University of California, Davis, Department of Economics.
  • Handle: RePEc:cda:wpaper:07-7
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    File URL: http://wp.econ.ucdavis.edu/07-7.pdf
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    References listed on IDEAS

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    4. Òscar Jordà, 2005. "Estimation and Inference of Impulse Responses by Local Projections," American Economic Review, American Economic Association, vol. 95(1), pages 161-182, March.
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    8. Silvia Goncalves & Lutz Kilian, 2007. "Asymptotic and Bootstrap Inference for AR(∞) Processes with Conditional Heteroskedasticity," Econometric Reviews, Taylor & Francis Journals, vol. 26(6), pages 609-641.
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    Citations

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    Cited by:

    1. María Dolores Gadea & Laura Mayoral, 2006. "The Persistence of Inflation in OECD Countries: A Fractionally Integrated Approach," International Journal of Central Banking, International Journal of Central Banking, vol. 2(1), March.
    2. Kremer, Manfred & Lo Duca, Marco & Holló, Dániel, 2012. "CISS - a composite indicator of systemic stress in the financial system," Working Paper Series 1426, European Central Bank.
    3. Cai, Xiaoming & Den Haan, Wouter, 2009. "Predicting recoveries and the importance of using enough information," CEPR Discussion Papers 7508, C.E.P.R. Discussion Papers.
    4. Furceri, Davide & Zdzienicka, Aleksandra, 2012. "How costly are debt crises?," Journal of International Money and Finance, Elsevier, vol. 31(4), pages 726-742.
    5. Davide Furceri & Lorenzo E. Bernal-Verdugo & Dominique M. Guillaume, 2012. "Crises, Labor Market Policy, and Unemployment," IMF Working Papers 12/65, International Monetary Fund.
    6. Alan J. Auerbach & Yuriy Gorodnichenko, 2012. "Fiscal Multipliers in Recession and Expansion," NBER Chapters,in: Fiscal Policy after the Financial Crisis, pages 63-98 National Bureau of Economic Research, Inc.

    More about this item

    Keywords

    impulse response function; local projections; vector autoregressions;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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