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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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    1. Hélène Rey, 2016. "International Channels of Transmission of Monetary Policy and the Mundellian Trilemma," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 64(1), pages 6-35, May.
    2. Sims, Christopher A, 1980. "Comparison of Interwar and Postwar Business Cycles: Monetarism Reconsidered," American Economic Review, American Economic Association, vol. 70(2), pages 250-257, May.
    3. Evgenia Passari & Hélène Rey, 2015. "Financial Flows and the International Monetary System," Economic Journal, Royal Economic Society, vol. 0(584), pages 675-698, May.
    4. Michele Piffer & Maximilian Podstawski, 2018. "Identifying Uncertainty Shocks Using the Price of Gold," Economic Journal, Royal Economic Society, vol. 128(616), pages 3266-3284, December.
    5. Mark Gertler & Peter Karadi, 2015. "Monetary Policy Surprises, Credit Costs, and Economic Activity," American Economic Journal: Macroeconomics, American Economic Association, vol. 7(1), pages 44-76, January.
    6. Marek Jarociński & Peter Karadi, 2020. "Deconstructing Monetary Policy Surprises—The Role of Information Shocks," American Economic Journal: Macroeconomics, American Economic Association, vol. 12(2), pages 1-43, April.
    7. J. B. Taylor & Harald Uhlig (ed.), 2016. "Handbook of Macroeconomics," Handbook of Macroeconomics, Elsevier, edition 1, volume 2, number 2.
    8. Karel Mertens & Morten O. Ravn, 2013. "The Dynamic Effects of Personal and Corporate Income Tax Changes in the United States," American Economic Review, American Economic Association, vol. 103(4), pages 1212-1247, June.
    9. Marek Jarocinski & Peter Karadi, 2017. "Central Bank Information Shocks," 2017 Meeting Papers 1193, Society for Economic Dynamics.
    10. Dario Caldara & Edward Herbst, 2019. "Monetary Policy, Real Activity, and Credit Spreads: Evidence from Bayesian Proxy SVARs," American Economic Journal: Macroeconomics, American Economic Association, vol. 11(1), pages 157-192, January.
    11. Jentsch, Carsten & Lunsford, Kurt G., 2016. "Proxy SVARs : asymptotic theory, bootstrap inference, and the effects of income tax changes in the United States," Working Papers 16-10, University of Mannheim, Department of Economics.
    12. Kurt Graden Lunsford, 2015. "Identifying Structural VARs with a Proxy Variable and a Test for a Weak Proxy," Working Papers (Old Series) 1528, Federal Reserve Bank of Cleveland.
    13. Cesa-Bianchi, Ambrogio & Sokol, Andrej, 2022. "Financial shocks, credit spreads, and the international credit channel," Journal of International Economics, Elsevier, vol. 135(C).
    14. Lutz Kilian, 1999. "Finite-Sample Properties of Percentile and Percentile-t Bootstrap Confidence Intervals for Impulse Responses," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 652-660, November.
    15. Mark Kerssenfischer, 2019. "The puzzling effects of monetary policy in VARs: Invalid identification or missing information?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(1), pages 18-25, January.
    16. Kilian,Lutz & Lütkepohl,Helmut, 2018. "Structural Vector Autoregressive Analysis," Cambridge Books, Cambridge University Press, number 9781107196575, September.
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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. "Wild inference for wild SVARs with application to heteroscedasticity-based IV," Papers 2407.03265, arXiv.org, revised Nov 2024.
    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. Luca Eduardo Fierro & Mario Martinoli, 2024. "An Empirical Inquiry into the Distributional Consequences of Energy Price Shocks," LEM Papers Series 2024/30, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    10. Key, Tomas & Lenney, Jamie, 2024. "The impact of aggregate fluctuations across the UK income distribution," Bank of England working papers 1083, Bank of England.
    11. Daniel Dzikowski & Carsten Jentsch, 2024. "Structural Periodic Vector Autoregressions," Papers 2401.14545, arXiv.org.
    12. repec:zbw:bofrdp:2020_013 is not listed on IDEAS
    13. 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.
    14. Tomas Key & Jamie Lenney, 2024. "The Impact of Aggregate Fluctuations Across the UK Income Distribution," Discussion Papers 2430, Centre for Macroeconomics (CFM).
    15. 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).
    16. 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).
    17. 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.
    18. 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.
    19. 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.
    20. 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).
    21. 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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