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Identification with External Instruments in Structural VARs under Partial Invertibility

Author

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  • Miranda-Agrippino, Silvia

    (Northwestern University Bank of England and CFM (LSE))

  • Ricco, Giovanni

    (University of Warwick OFCE-SciencesPo and CEPR)

Abstract

This paper discusses the conditions for identification in SVAR-IVs when only the shock of interest or a subset of the structural shocks can be recovered as a linear combination of the VAR residuals. This condition of partial invertibility is very general, often of empirical relevance, and less stringent than the standard full invertibility that is routinely assumed in the SVAR literature. We show that, underpartial invertibility, the dynamic responsescan be correctly recoveredusing an external instrument even when this correlates with leads and lags of other invertible shocks. We call this a limited lead-lag exogeneity condition. We evaluate our results in a simulated environment, and provide an empirical application to the case of monetary policy shocks.

Suggested Citation

  • Miranda-Agrippino, Silvia & Ricco, Giovanni, 2019. "Identification with External Instruments in Structural VARs under Partial Invertibility," The Warwick Economics Research Paper Series (TWERPS) 1213, University of Warwick, Department of Economics.
  • Handle: RePEc:wrk:warwec:1213
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    File URL: https://warwick.ac.uk/fac/soc/economics/research/workingpapers/2019/twerp_1213_ricco.pdf
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    References listed on IDEAS

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    3. Silvia Miranda-Agrippino & Giovanni Ricco, 2021. "The Transmission of Monetary Policy Shocks," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(3), pages 74-107, July.
    4. Altavilla, Carlo & Brugnolini, Luca & Gürkaynak, Refet S. & Motto, Roberto & Ragusa, Giuseppe, 2019. "Measuring euro area monetary policy," Journal of Monetary Economics, Elsevier, vol. 108(C), pages 162-179.
    5. Kuttner, Kenneth N., 2001. "Monetary policy surprises and interest rates: Evidence from the Fed funds futures market," Journal of Monetary Economics, Elsevier, vol. 47(3), pages 523-544, June.
    6. Ryan Chahrour & Kyle Jurado, 2017. "Recoverability," Boston College Working Papers in Economics 935, Boston College Department of Economics.
    7. Ricco, Giovanni & Callegari, Giovanni & Cimadomo, Jacopo, 2016. "Signals from the government: Policy disagreement and the transmission of fiscal shocks," Journal of Monetary Economics, Elsevier, vol. 82(C), pages 107-118.
    8. V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2004. "A Critique of Structural VARs Using Real Business Cycle Theory," Levine's Bibliography 122247000000000518, UCLA Department of Economics.
    9. Miranda-Agrippino, Silvia & Hacıoglu Hoke, Sinem, 2018. "When creativity strikes: news shocks and business cycle fluctuations," LSE Research Online Documents on Economics 90381, London School of Economics and Political Science, LSE Library.
    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. Pascal Paul, 2020. "The Time-Varying Effect of Monetary Policy on Asset Prices," The Review of Economics and Statistics, MIT Press, vol. 102(4), pages 690-704, October.
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    Cited by:

    1. Martínez-Hernández, Catalina, 2020. "Disentangling the effects of multidimensional monetary policy on inflation and inflation expectations in the euro area," Discussion Papers 2020/18, Free University Berlin, School of Business & Economics.
    2. Leonardo N. Ferreira, 2020. "Forward Guidance Matters: disentangling monetary policy shocks," Working Papers Series 530, Central Bank of Brazil, Research Department.
    3. Mikkel Plagborg‐Møller & Christian K. Wolf, 2021. "Local Projections and VARs Estimate the Same Impulse Responses," Econometrica, Econometric Society, vol. 89(2), pages 955-980, March.
    4. Fabio Canova & Filippo Ferroni, 2018. "Mind the gap! Stylized dynamic facts and structural models," Working Papers No 13/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    5. Mirela S. Miescu & Haroon Mumtaz, 2019. "Proxy structural vector autoregressions, informational sufficiency and the role of monetary policy," Working Papers 894, Queen Mary University of London, School of Economics and Finance.

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    More about this item

    Keywords

    Identification with External Instruments ; Structural VAR ; Invertibility ; Monetary Policy Shocks;
    All these keywords.

    JEL classification:

    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation
    • 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
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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