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A Simple Instrument for Proxy Vector Autoregressive Analysis

Author

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  • Lukas Boer
  • Helmut Lütkepohl

Abstract

A major challenge for proxy vector autoregressive analysis is the construction of a suitable instrument variable for identifying a shock of interest. We propose a simple proxy that can be constructed whenever the dating and sign of particular shocks are known. It is shown that the proxy can lead to impulse response estimates of the impact effects of the shock of interest that are nearly as efficient as or even more efficient than estimators based on a conventional, more sophisticated proxy.

Suggested Citation

  • Lukas Boer & Helmut Lütkepohl, 2020. "A Simple Instrument for Proxy Vector Autoregressive Analysis," Discussion Papers of DIW Berlin 1905, DIW Berlin, German Institute for Economic Research.
    • Handle: RePEc:diw:diwwpp:dp1905
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    References listed on IDEAS

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    1. Helmut Lütkepohl & Thore Schlaak, 2022. "Heteroscedastic Proxy Vector Autoregressions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 1268-1281, June.
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    5. 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.
    6. Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-529, October.
    7. 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.
    8. José Luis Montiel Olea & Carolin Pflueger, 2013. "A Robust Test for Weak Instruments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(3), pages 358-369, July.
    9. 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.
    10. 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.
    11. 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.
    12. 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).
    13. Kilian,Lutz & Lütkepohl,Helmut, 2018. "Structural Vector Autoregressive Analysis," Cambridge Books, Cambridge University Press, number 9781107196575, November.
    14. 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.
    15. 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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    Cited by:

    1. Michael Ryan, 2020. "A Narrative Approach to Creating Instruments with Unstructured and Voluminous Text: An Application to Policy Uncertainty," Working Papers in Economics 20/10, University of Waikato.

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    More about this item

    Keywords

    GMM; heteroskedastic VAR; instrumental variable estimation; proxy VAR; structural vector autoregression;
    All these keywords.

    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

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