IDEAS home Printed from https://ideas.repec.org/p/bol/bodewp/wp1122.html
   My bibliography  Save this paper

Identification and estimation issues in Structural Vector Autoregressions with external instruments

Author

Listed:
  • G. Angelini
  • L. Fanelli

Abstract

In this paper we discuss general identification results for Structural Vector Autoregressions (SVARs) with external instruments, considering the case in which r valid instruments are used to identify g ? 1 structural shocks, where r ? g. We endow the SVAR with an auxiliary statistical model for the external instruments which is a system of reduced form equations. The SVAR and the auxiliary model for the external instruments jointly form a `larger' SVAR characterized by a particularly restricted parametric structure, and are connected by the covariance matrix of their disturbances which incorporates the `relevance' and `exogeneity' conditions. We discuss identification results and likelihood-based estimation methods both in the `multiple shocks' approach, where all structural shocks are of interest, and in the `partial shock' approach, where only a subset of the structural shocks is of interest. Overidentified SVARs with external instruments can be easily tested in our setup. The suggested method is applied to investigate empirically whether commonly employed measures of macroeconomic and financial uncertainty respond on-impact, other than with lags, to business cycle uctuations in the U.S. in the period after the Global Financial Crisis. To do so, we employ two external instruments to identify the real economic activity shock in a partial shock approach.

Suggested Citation

  • G. Angelini & L. Fanelli, 2018. "Identification and estimation issues in Structural Vector Autoregressions with external instruments," Working Papers wp1122, Dipartimento Scienze Economiche, Universita' di Bologna.
  • Handle: RePEc:bol:bodewp:wp1122
    as

    Download full text from publisher

    File URL: http://amsacta.unibo.it/5867/1/WP1122.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Lawrence J. Christiano & Roberto Motto & Massimo Rostagno, 2014. "Risk Shocks," American Economic Review, American Economic Association, vol. 104(1), pages 27-65, January.
    4. Leduc, Sylvain & Liu, Zheng, 2016. "Uncertainty shocks are aggregate demand shocks," Journal of Monetary Economics, Elsevier, vol. 82(C), pages 20-35.
    5. Caggiano, Giovanni & Castelnuovo, Efrem & Pellegrino, Giovanni, 2017. "Estimating the real effects of uncertainty shocks at the Zero Lower Bound," European Economic Review, Elsevier, vol. 100(C), pages 257-272.
    6. Kilian,Lutz & Lütkepohl,Helmut, 2018. "Structural Vector Autoregressive Analysis," Cambridge Books, Cambridge University Press, number 9781107196575, May.
    7. Brüggemann, Ralf & Jentsch, Carsten & Trenkler, Carsten, 2016. "Inference in VARs with conditional heteroskedasticity of unknown form," Journal of Econometrics, Elsevier, vol. 191(1), pages 69-85.
    8. Karel Mertens & Morten O. Ravn, 2012. "Empirical Evidence on the Aggregate Effects of Anticipated and Unanticipated US Tax Policy Shocks," American Economic Journal: Economic Policy, American Economic Association, vol. 4(2), pages 145-181, May.
    9. Lutz Kilian, 2008. "The Economic Effects of Energy Price Shocks," Journal of Economic Literature, American Economic Association, vol. 46(4), pages 871-909, December.
    10. Michael Plante & Alexander W. Richter & Nathaniel A. Throckmorton, 2018. "The Zero Lower Bound and Endogenous Uncertainty," Economic Journal, Royal Economic Society, vol. 128(611), pages 1730-1757, June.
    11. Taisuke Nakata, 2017. "Uncertainty at the Zero Lower Bound," American Economic Journal: Macroeconomics, American Economic Association, vol. 9(3), pages 186-221, July.
    12. Susanto Basu & Brent Bundick, 2017. "Uncertainty Shocks in a Model of Effective Demand," Econometrica, Econometric Society, vol. 85, pages 937-958, May.
    13. Andrea Carriero & Haroon Mumtaz & Konstantinos Theodoridis & Angeliki Theophilopoulou, 2015. "The Impact of Uncertainty Shocks under Measurement Error: A Proxy SVAR Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(6), pages 1223-1238, September.
    14. 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.
    15. Hamilton, James D., 2003. "What is an oil shock?," Journal of Econometrics, Elsevier, vol. 113(2), pages 363-398, April.
    16. 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.
    17. 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.
    18. 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.
    19. Emanuele Bacchiocchi & Luca Fanelli, 2015. "Identification in Structural Vector Autoregressive Models with Structural Changes, with an Application to US Monetary Policy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(6), pages 761-779, December.
    20. Sydney C. Ludvigson & Sai Ma & Serena Ng, 2017. "Shock Restricted Structural Vector-Autoregressions," NBER Working Papers 23225, National Bureau of Economic Research, Inc.
    21. Chris Woolston, 2014. "Rice," Nature, Nature, vol. 514(7524), pages 49-49, October.
    22. Susanto Basu & Brent Bundick, 2015. "Endogenous volatility at the zero lower bound: implications for stabilization policy," Research Working Paper RWP 15-1, Federal Reserve Bank of Kansas City.
    23. Mertens, Karel & Ravn, Morten O., 2014. "A reconciliation of SVAR and narrative estimates of tax multipliers," Journal of Monetary Economics, Elsevier, vol. 68(S), pages 1-19.
    24. Hausman, Jerry A & Taylor, William E, 1983. "Identification in Linear Simultaneous Equations Models with Covariance Restrictions: An Instrumental Variables Interpretation," Econometrica, Econometric Society, vol. 51(5), pages 1527-1549, September.
    25. Giovanni Angelini & Emanuele Bacchiocchi & Giovanni Caggiano & Luca Fanelli, 2019. "Uncertainty across volatility regimes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 437-455, April.
    26. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    27. 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.
    28. 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.
    29. Dario Caldara & Christophe Kamps, 2017. "The Analytics of SVARs: A Unified Framework to Measure Fiscal Multipliers," Review of Economic Studies, Oxford University Press, vol. 84(3), pages 1015-1040.
    30. 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.
    31. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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. 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.
    3. Danilo Cascaldi-Garcia, 2022. "Forecast Revisions as Instruments for News Shocks," International Finance Discussion Papers 1341, Board of Governors of the Federal Reserve System (U.S.).
    4. Robin Braun & Ralf Brüggemann, 2017. "Identification of SVAR Models by Combining Sign Restrictions With External Instruments," Working Paper Series of the Department of Economics, University of Konstanz 2017-07, Department of Economics, University of Konstanz.
    5. Andrea Gazzani & Alejandro Vicondoa, 2020. "Bridge Proxy-SVAR: estimating the macroeconomic effects of shocks identified at high-frequency," Temi di discussione (Economic working papers) 1274, Bank of Italy, Economic Research and International Relations Area.
    6. Giacomini, Raffaella & Kitagawa, Toru & Read, Matthew, 2022. "Robust Bayesian inference in proxy SVARs," Journal of Econometrics, Elsevier, vol. 228(1), pages 107-126.
    7. Allan W. Gregory & James McNeil & Gregor W. Smith, 2022. "US Fiscal Policy Shocks: Proxy-SVAR Overidentification via GMM," Working Paper 1461, Economics Department, Queen's University.
    8. Caggiano, Giovanni & Castelnuovo, Efrem & Delrio, Silvia & Kima, Richard, 2021. "Financial uncertainty and real activity: The good, the bad, and the ugly," European Economic Review, Elsevier, vol. 136(C).
    9. Mirela Miescu, 2019. "Uncertainty shocks in emerging economies," Working Papers 277077821, Lancaster University Management School, Economics Department.
    10. Giovanni Pellegrino & Federico Ravenna & Gabriel Züllig, 2021. "The Impact of Pessimistic Expectations on the Effects of COVID‐19‐Induced Uncertainty in the Euro Area," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(4), pages 841-869, August.
    11. Rangan Gupta & Chi Keung Marco Lau & Mark E. Wohar, 2019. "The impact of US uncertainty on the Euro area in good and bad times: evidence from a quantile structural vector autoregressive model," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 353-368, May.
    12. Karamysheva, Madina, 2022. "How do fiscal adjustments work? An empirical investigation," Journal of Economic Dynamics and Control, Elsevier, vol. 137(C).
    13. Mirela Miescu & Haroon Mumtaz, 2019. "Proxy structural vector autoregressions, informational sufficiency and the role of monetary policy," Working Papers 280730188, Lancaster University Management School, Economics Department.
    14. Rivolta, Giulia & Trecroci, Carmine, 2020. "Measuring the effects of U.S. uncertainty and monetary conditions on EMEs' macroeconomic dynamics," MPRA Paper 99403, University Library of Munich, Germany.
    15. Piergiorgio Alessandri & Andrea Gazzani & Alejandro Vicondoa, 2021. "The real effects of financial uncertainty shocks: A daily identification approach," Working Papers 61, Red Nacional de Investigadores en Economía (RedNIE).
    16. 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.
    17. Herwartz, Helmut & Rohloff, Hannes & Wang, Shu, 2020. "Proxy SVAR identification of monetary policy shocks: MonteCarlo evidence and insights for the US," University of Göttingen Working Papers in Economics 404, University of Goettingen, Department of Economics.
    18. Pierdzioch Christian & Gupta Rangan, 2020. "Uncertainty and Forecasts of U.S. Recessions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(4), pages 1-20, September.
    19. Seneca, Martin, 2016. "Risk shocks close to the zero lower bound," Bank of England working papers 606, Bank of England.
    20. Helmut Lütkepohl & Thore Schlaak, 2020. "Heteroskedastic Proxy Vector Autoregressions," Discussion Papers of DIW Berlin 1876, DIW Berlin, German Institute for Economic Research.

    More about this item

    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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bol:bodewp:wp1122. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/sebolit.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dipartimento Scienze Economiche, Universita' di Bologna (email available below). General contact details of provider: https://edirc.repec.org/data/sebolit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.