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Asymptotically Valid Bootstrap Inference for Proxy SVARs

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  • Carsen Jentsch
  • Kurt Graden Lunsford

Abstract

Proxy structural vector autoregressions identify structural shocks in vector autoregressions with external variables that are correlated with the structural shocks of interest but uncorrelated with all other structural shocks. We provide asymptotic theory for this identification approach under mild ?-mixing conditions that cover a large class of uncorrelated, but possibly dependent innovation processes, including conditional heteroskedasticity. We prove consistency of a residual-based moving block bootstrap for inference on statistics such as impulse response functions and forecast error variance decompositions. Wild bootstraps are proven to be generally invalid for these statistics and their coverage rates can be badly and persistently mis-sized.

Suggested Citation

  • Carsen Jentsch & Kurt Graden Lunsford, 2019. "Asymptotically Valid Bootstrap Inference for Proxy SVARs," Working Papers 19-08, Federal Reserve Bank of Cleveland.
    • Handle: RePEc:fip:fedcwq:190800
    DOI: 10.26509/frbc-wp-201908
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    Cited by:

    1. Giovanni Angelini & Luca Fanelli, 2019. "Exogenous uncertainty and the identification of structural vector autoregressions with external instruments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(6), pages 951-971, September.
    2. Karamysheva, Madina, 2022. "How do fiscal adjustments work? An empirical investigation," Journal of Economic Dynamics and Control, Elsevier, vol. 137(C).
    3. Giovanni Angelini & Luca Fanelli & Luca Neri, 2024. "Invalid proxies and volatility changes," Working Papers wp1193, Dipartimento Scienze Economiche, Universita' di Bologna.
    4. Bulat Gafarov & Madina Karamysheva & Andrey Polbin & Anton Skrobotov, 2024. "Policymaker meetings as heteroscedasticity shifters: Identification and simultaneous inference in unstable SVARs," Papers 2407.03265, arXiv.org.
    5. Angelini, Giovanni & Cavaliere, Giuseppe & Fanelli, Luca, 2024. "An identification and testing strategy for proxy-SVARs with weak proxies," Journal of Econometrics, Elsevier, vol. 238(2).
    6. Andreasen, Martin M. & Caggiano, Giovanni & Castelnuovo, Efrem & Pellegrino, Giovanni, 2024. "Does risk matter more in recessions than in expansions? Implications for monetary policy," Journal of Monetary Economics, Elsevier, vol. 143(C).
    7. Giovanni Caggiano & Efrem Castelnuovo & Gabriela Nodari, 2020. "Uncertainty and monetary policy in good and bad times: A Replication of the VAR investigation by Bloom (2009)," CAMA Working Papers 2020-74, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    8. Giovanni Angelini & Giovanni Caggiano & Efrem Castelnuovo & Luca Fanelli, 2023. "Are Fiscal Multipliers Estimated with Proxy‐SVARs Robust?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(1), pages 95-122, February.
    9. Key, Tomas & Lenney, Jamie, 2024. "The impact of aggregate fluctuations across the UK income distribution," Bank of England working papers 1083, Bank of England.
    10. Daniel Dzikowski & Carsten Jentsch, 2024. "Structural Periodic Vector Autoregressions," Papers 2401.14545, arXiv.org.
    11. repec:zbw:bofrdp:2020_013 is not listed on IDEAS
    12. Härtl, Tilmann, 2022. "Identifying Proxy VARs with Restrictions on the Forecast Error Variance," VfS Annual Conference 2022 (Basel): Big Data in Economics 264071, Verein für Socialpolitik / German Economic Association.
    13. Tomas Key & Jamie Lenney, 2024. "The Impact of Aggregate Fluctuations Across the UK Income Distribution," Discussion Papers 2430, Centre for Macroeconomics (CFM).
    14. Cesa-Bianchi, Ambrogio & Thwaites, Gregory & Vicondoa, Alejandro, 2020. "Monetary policy transmission in the United Kingdom: A high frequency identification approach," European Economic Review, Elsevier, vol. 123(C).
    15. Bruns, Martin & Lütkepohl, Helmut, 2024. "Heteroskedastic proxy vector autoregressions: An identification-robust test for time-varying impulse responses in the presence of multiple proxies," Journal of Economic Dynamics and Control, Elsevier, vol. 161(C).
    16. Fengler, Matthias & Polivka, Jeannine, 2021. "Proxy-identification of a structural MGARCH model for asset returns," Economics Working Paper Series 2103, University of St. Gallen, School of Economics and Political Science, revised Oct 2024.
    17. Montiel Olea, José L. & Stock, James H. & Watson, Mark W., 2021. "Inference in Structural Vector Autoregressions identified with an external instrument," Journal of Econometrics, Elsevier, vol. 225(1), pages 74-87.
    18. Fengler, Matthias & Polivka, Jeanine, 2022. "Identifying Structural Shocks to Volatility through a Proxy-MGARCH Model," VfS Annual Conference 2022 (Basel): Big Data in Economics 264010, Verein für Socialpolitik / German Economic Association.
    19. Maghyereh, Aktham & Abdoh, Hussein, 2021. "The effect of structural oil shocks on bank systemic risk in the GCC countries," Energy Economics, Elsevier, vol. 103(C).
    20. Giovanni Angelini & Giovanni Caggiano & Efrem Castelnuovo & Luca Fanelli, 2020. "Are Fiscal Multipliers Estimated with Proxy-SVARs Robust?," "Marco Fanno" Working Papers 0257, Dipartimento di Scienze Economiche "Marco Fanno".

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    More about this item

    Keywords

    Wild Bootstrap; Mixing; Proxy Variables; Residual-Based Moving Block Bootstrap; Structural Vector Autoregression; External Instruments;
    All these keywords.

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - 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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