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Avoiding Unintentionally Correlated Shocks in Proxy Vector Autoregressive Analysis

Author

Listed:
  • Martin Bruns

    (School of Economics, University of East Anglia)

  • Helmut Lutkepohl

    (DIW Berlin and Freie Universitat Berlin)

  • James McNeil

    (Dalhousie University)

Abstract

The shocks in structural vector autoregressive (VAR) analysis are typically assumed to be instantaneously uncorrelated. This condition may easily be violated in proxy VAR models if more than one shock is identified by a proxy variable. Correlated shocks may be obtained even if the proxies are uncorrelated and satisfy the usual relevance and exogeneity conditions individually. Examples from the recent proxy VAR literature are presented. It is shown that assuming uncorrelated proxies that satisfy the usual relevance and exogeneity conditions individually actually over-identifies the shocks of interest and a Generalized Method of Moments (GMM) algorithm is proposed that ensures orthogonal shocks and provides efficient estimators of the structural parameters. It generalizes an earlier GMM proposal that works only if at least K-1 shocks are identified by proxies in a VAR with K variables.

Suggested Citation

  • Martin Bruns & Helmut Lutkepohl & James McNeil, 2024. "Avoiding Unintentionally Correlated Shocks in Proxy Vector Autoregressive Analysis," University of East Anglia School of Economics Working Paper Series 2024-05, School of Economics, University of East Anglia, Norwich, UK..
    • Handle: RePEc:uea:ueaeco:2024-05
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    References listed on IDEAS

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    1. Boer, Lukas & Lütkepohl, Helmut, 2021. "Qualitative versus quantitative external information for proxy vector autoregressive analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).
    2. Crepon, Bruno & Kramarz, Francis & Trognon, Alain, 1997. "Parameters of interest, nuisance parameters and orthogonality conditions An application to autoregressive error component models," Journal of Econometrics, Elsevier, vol. 82(1), pages 135-156.
    3. Ramey, V.A., 2016. "Macroeconomic Shocks and Their Propagation," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 71-162, Elsevier.
    4. 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.
    5. James H. Stock & Mark W. Watson, 2012. "Disentangling the Channels of the 2007-09 Recession," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 43(1 (Spring), pages 81-156.
    6. 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.
    7. 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.
    8. James H. Stock & Mark W. Watson, 2018. "Identification and Estimation of Dynamic Causal Effects in Macroeconomics Using External Instruments," Economic Journal, Royal Economic Society, vol. 128(610), pages 917-948, May.
    9. Giacomini, Raffaella & Kitagawa, Toru & Read, Matthew, 2022. "Robust Bayesian inference in proxy SVARs," Journal of Econometrics, Elsevier, vol. 228(1), pages 107-126.
    10. 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.
    11. 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.
    12. Aeimit Lakdawala, 2019. "Decomposing the effects of monetary policy using an external instruments SVAR," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(6), pages 934-950, September.
    13. Jonathan H. Wright, 2012. "What does Monetary Policy do to Long‐term Interest Rates at the Zero Lower Bound?," Economic Journal, Royal Economic Society, vol. 122(564), pages 447-466, November.
    14. Arias, Jonas E. & Rubio-Ramírez, Juan F. & Waggoner, Daniel F., 2021. "Inference in Bayesian Proxy-SVARs," Journal of Econometrics, Elsevier, vol. 225(1), pages 88-106.
    15. Kilian,Lutz & Lütkepohl,Helmut, 2018. "Structural Vector Autoregressive Analysis," Cambridge Books, Cambridge University Press, number 9781107196575, November.
    16. Fanelli, Luca & Marsi, Antonio, 2022. "Sovereign spreads and unconventional monetary policy in the Euro area: A tale of three shocks," European Economic Review, Elsevier, vol. 150(C).
    17. 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.
    18. Carsten Jentsch & Kurt G. Lunsford, 2019. "The Dynamic Effects of Personal and Corporate Income Tax Changes in the United States: Comment," American Economic Review, American Economic Association, vol. 109(7), pages 2655-2678, July.
    19. Bruns, Martin & Lütkepohl, Helmut, 2022. "Comparison of local projection estimators for proxy vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    20. Martin Bruns & Helmut Lütkepohl, 2023. "An Alternative Bootstrap for Proxy Vector Autoregressions," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1857-1882, December.
    21. James H. Stock & Mark W. Watson, 2012. "Disentangling the Channels of the 2007-09 Recession," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 44(1 (Spring), pages 81-156.
    22. James H. Stock & Mark W. Watson, 2012. "Disentangling the Channels of the 2007-2009 Recession," NBER Working Papers 18094, National Bureau of Economic Research, Inc.
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    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
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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