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Balanced Bootstrap Joint Confidence Bands for Structural Impulse Response Functions

Author

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  • Stefan Bruder
  • Michael Wolf

Abstract

Constructing joint confidence bands for structural impulse response functions based on a VAR model is a difficult task because of the non‐linear nature of such functions. We propose new joint confidence bands that cover the entire true structural impulse response function up to a chosen maximum horizon with a pre‐specified probability (1−α), at least asymptotically. Such bands are based on a certain bootstrap procedure from the multiple testing literature. We compare the finite‐sample properties of our method with those of existing methods via extensive Monte Carlo simulations. We also investigate the effect of endogenizing the lag order in our bootstrap procedure on the finite‐sample properties. Furthermore, an empirical application to a real dataset is provided.

Suggested Citation

  • Stefan Bruder & Michael Wolf, 2018. "Balanced Bootstrap Joint Confidence Bands for Structural Impulse Response Functions," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(5), pages 641-664, September.
    • Handle: RePEc:bla:jtsera:v:39:y:2018:i:5:p:641-664
    DOI: 10.1111/jtsa.12289
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    Cited by:

    1. Jonas E. Arias & Juan F. Rubio‐Ramírez & Daniel F. Waggoner, 2025. "Uniform Priors for Impulse Responses," Econometrica, Econometric Society, vol. 93(2), pages 695-718, March.
    2. Atsushi Inoue & Lutz Kilian, 2020. "The Role of the Prior in Estimating VAR Models with Sign Restrictions," Working Papers 2030, Federal Reserve Bank of Dallas.
    3. Jochen Güntner & Magnus Reif & Maik Wolters, 2024. "Sudden stop: Supply and demand shocks in the German natural gas market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(7), pages 1282-1300, November.
    4. Jonas E. Arias & Juan F. Rubio-Ramirez & Daniel F. Waggoner, 2020. "Uniform Priors for Impulse Responses," Working Papers 22-30, Federal Reserve Bank of Philadelphia.
    5. Inoue, Atsushi & Kilian, Lutz, 2022. "Joint Bayesian inference about impulse responses in VAR models," Journal of Econometrics, Elsevier, vol. 231(2), pages 457-476.
    6. Inoue, Atsushi & Kilian, Lutz, 2020. "The uniform validity of impulse response inference in autoregressions," Journal of Econometrics, Elsevier, vol. 215(2), pages 450-472.
    7. Thomas F. P. Wiesen & Paul M. Beaumont, 2024. "A joint impulse response function for vector autoregressive models," Empirical Economics, Springer, vol. 66(4), pages 1553-1585, April.
    8. Lenard Lieb & Stephan Smeekes, 2017. "Inference for Impulse Responses under Model Uncertainty," Papers 1709.09583, arXiv.org, revised Oct 2019.
    9. Lütkepohl, Helmut & Staszewska-Bystrova, Anna & Winker, Peter, 2020. "Constructing joint confidence bands for impulse response functions of VAR models – A review," Econometrics and Statistics, Elsevier, vol. 13(C), pages 69-83.
    10. Micheli, Martin, 2019. "Labor market effects of minimum wage shocks," Ruhr Economic Papers 830, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    11. Diego Fresoli, 2022. "Bootstrap VAR forecasts: The effect of model uncertainties," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 279-293, March.

    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • 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

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