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What do VARs Tell Us about the Impact of a Credit Supply Shock? An Empirical Analysis

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  • Haroon Mumtaz

    (Queen Mary University of London)

  • Gabor Pinter

    (Bank of England)

  • Konstantinos Theodoridis

    (Bank of England)

Abstract

This paper evaluates the performance of structural VAR models in estimating the impact of credit supply shocks. In a simple Monte-Carlo experiment, we generate data from a DSGE model that features bank lending and credit supply shocks and use SVARs to try and recover the impulse responses to these shocks. The experiment suggests that a proxy VAR that uses an instrumental variable procedure to estimate the impact of the credit shock performs well and is relatively robust to measurement error in the instrument. A structural VAR with sign restrictions also performs well under some circumstances. In contrast, VARs of the narrative variety, i.e. VAR models that include measures of the credit shock as endogenous variables are highly sensitive to ordering and measurement error. An application of the proxy VAR model and the VAR with sign restrictions to US data suggests, however, that the credit supply shock is hard to identify in practice.

Suggested Citation

  • Haroon Mumtaz & Gabor Pinter & Konstantinos Theodoridis, 2014. "What do VARs Tell Us about the Impact of a Credit Supply Shock? An Empirical Analysis," Working Papers 716, Queen Mary University of London, School of Economics and Finance.
  • Handle: RePEc:qmw:qmwecw:wp716
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    3. Abbate, Angela & Eickmeier, Sandra & Prieto, Esteban, 2016. "Financial shocks and inflation dynamics," Discussion Papers 41/2016, Deutsche Bundesbank.
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    6. George J. Bratsiotis & Konstantinos Theodoridis, 2020. "Precautionary Liquidity Shocks, Excess Reserves and Business Cycles," Economics Discussion Paper Series 2014, Economics, The University of Manchester.
    7. Kanngiesser Derrick & Martin Reiner & Maurin Laurent & Moccero Diego, 2020. "The macroeconomic impact of shocks to bank capital buffers in the Euro Area," The B.E. Journal of Macroeconomics, De Gruyter, vol. 20(1), pages 1-17, January.
    8. Jelena Zivanovic, 2019. "What Does Structural Analysis of the External Finance Premium Say About Financial Frictions?," Staff Working Papers 19-38, Bank of Canada.
    9. Dobromił Serwa & Piotr Wdowiński, 2017. "Modeling Macro-Financial Linkages: Combined Impulse Response Functions in SVAR Models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(4), pages 323-357, December.
    10. Altavilla, Carlo & Pariès, Matthieu Darracq & Nicoletti, Giulio, 2019. "Loan supply, credit markets and the euro area financial crisis," Journal of Banking & Finance, Elsevier, vol. 109(C).
    11. 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.
    12. Breitenlechner, Max & Mathy, Gabriel P. & Scharler, Johann, 2021. "Decomposing the U.S. Great Depression: How important were loan supply shocks?," Explorations in Economic History, Elsevier, vol. 79(C).
    13. Daniel Kaufmann, 2020. "Is deflation costly after all? The perils of erroneous historical classifications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 614-628, August.
    14. Herwartz, Helmut & Rohloff, Hannes & Wang, Shu, 2020. "Proxy SVAR identification of monetary policy shocks: MonteCarlo evidence and insights for the US," Center for European, Governance and Economic Development Research Discussion Papers 404, University of Goettingen, Department of Economics.
    15. Kwon, Dohyoung, 2020. "Risk Shocks and Credit Spreads," Journal of Macroeconomics, Elsevier, vol. 64(C).
    16. Bartoletto, Silvana & Chiarini, Bruno & Marzano, Elisabetta & Piselli, Paolo, 2019. "Business cycles, credit cycles, and asymmetric effects of credit fluctuations: Evidence from Italy for the period of 1861–2013," Journal of Macroeconomics, Elsevier, vol. 61(C), pages 1-1.
    17. Olli Palm'en, 2020. "Inflation Dynamics of Financial Shocks," Papers 2006.03301, arXiv.org.
    18. 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.
    19. Guevara, Carlos & Rodríguez, Gabriel, 2020. "The role of credit supply shocks in pacific alliance countries: A TVP-VAR-SV approach," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    20. Garreth Rule, 2015. "Understanding the central bank balance sheet," Handbooks, Centre for Central Banking Studies, Bank of England, number 32, March.
    21. Helmut Herwartz & Christian Ochsner & Hannes Rohloff, 2021. "Global Credit Shocks and Real Economies," MAGKS Papers on Economics 202116, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    22. Bańbura, Marta & Albani, Maria & Ambrocio, Gene & Bursian, Dirk & Buss, Ginters & de Winter, Jasper & Gavura, Miroslav & Giordano, Claire & Júlio, Paulo & Le Roux, Julien & Lozej, Matija & Malthe-Thag, 2018. "Business investment in EU countries," Occasional Paper Series 215, European Central Bank.

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    More about this item

    Keywords

    Credit supply shocks; Proxy SVAR; Sign restrictions; DSGE models;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: 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
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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