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Modeling Macro-Financial Linkages: Combined Impulse Response Functions in SVAR Models

Author

Listed:
  • Dobromił Serwa

    (Narodowy Bank Polski
    Warsaw School of Economics)

  • Piotr Wdowiński

    (Narodowy Bank Polski
    University of Łódź)

Abstract

We estimated a structural vector autoregressive (SVAR) model describing the links between a banking sector and a real economy. We proposed a new method to verify robustness of impulse-response functions to the ordering of variables in an SVAR model. This method applies permutations of orderings of variables and uses the Cholesky decomposition of the error covariance matrix to identify parameters. Impulse response functions are computed and combined for all permutations. We explored the method in practice by analyzing the macro-financial linkages in the Polish economy. Our results indicate that the combined impulse response functions are more uncertain than those from a single model specification with a given ordering of variables, but some findings remain robust. It is evident that macroeconomic aggregate shocks and interest rate shocks have a significant impact on banking variables.

Suggested Citation

  • 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.
  • Handle: RePEc:psc:journl:v:9:y:2017:i:4:p:323-357
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    as
    1. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, vol. 79(4), pages 655-673, September.
    2. Uhlig, Harald, 2005. "What are the effects of monetary policy on output? Results from an agnostic identification procedure," Journal of Monetary Economics, Elsevier, vol. 52(2), pages 381-419, March.
    3. Lown, Cara & Morgan, Donald P., 2006. "The Credit Cycle and the Business Cycle: New Findings Using the Loan Officer Opinion Survey," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(6), pages 1575-1597, September.
    4. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    5. Markku Lanne & Helmut Lütkepohl, 2008. "Identifying Monetary Policy Shocks via Changes in Volatility," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(6), pages 1131-1149, September.
    6. Helmut Lütkepohl, 1985. "Comparison Of Criteria For Estimating The Order Of A Vector Autoregressive Process," Journal of Time Series Analysis, Wiley Blackwell, vol. 6(1), pages 35-52, January.
    7. Gonzalo, Jesus & Ng, Serena, 2001. "A systematic framework for analyzing the dynamic effects of permanent and transitory shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 25(10), pages 1527-1546, October.
    8. Renée Fry & Adrian Pagan, 2011. "Sign Restrictions in Structural Vector Autoregressions: A Critical Review," Journal of Economic Literature, American Economic Association, vol. 49(4), pages 938-960, December.
    9. Stefan Klößner & Sven Wagner, 2014. "Exploring All Var Orderings For Calculating Spillovers? Yes, We Can!—A Note On Diebold And Yilmaz (2009)," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(1), pages 172-179, January.
    10. Haroon Mumtaz & Gabor Pinter & Konstantinos Theodoridis, 2018. "What Do Vars Tell Us About The Impact Of A Credit Supply Shock?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(2), pages 625-646, May.
    11. Gilchrist, Simon & Yankov, Vladimir & Zakrajsek, Egon, 2009. "Credit market shocks and economic fluctuations: Evidence from corporate bond and stock markets," Journal of Monetary Economics, Elsevier, vol. 56(4), pages 471-493, May.
    12. Iacoviello, Matteo & Minetti, Raoul, 2008. "The credit channel of monetary policy: Evidence from the housing market," Journal of Macroeconomics, Elsevier, vol. 30(1), pages 69-96, March.
    13. Bassett, William F. & Chosak, Mary Beth & Driscoll, John C. & Zakrajšek, Egon, 2014. "Changes in bank lending standards and the macroeconomy," Journal of Monetary Economics, Elsevier, vol. 62(C), pages 23-40.
    14. Pagan, A.R. & Pesaran, M. Hashem, 2008. "Econometric analysis of structural systems with permanent and transitory shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 32(10), pages 3376-3395, October.
    15. Walentin, Karl, 2014. "Business cycle implications of mortgage spreads," Journal of Monetary Economics, Elsevier, vol. 67(C), pages 62-77.
    16. Karfakis, Costas, 2013. "Credit and business cycles in Greece: Is there any relationship?," Economic Modelling, Elsevier, vol. 32(C), pages 23-29.
    17. Alfred A.Haug & Tomasz Jędrzejowicz & Anna Sznajderska, 2013. "Combining monetary and fiscal policy in an SVAR for a small open economy," NBP Working Papers 168, Narodowy Bank Polski.
    18. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    19. Barnett, Alina & Thomas, Ryland, 2013. "Has weak lending and activity in the United Kingdom been driven by credit supply shocks?," Bank of England working papers 482, Bank of England.
    20. Roberto Rigobon & Brian Sack, 2003. "Measuring The Reaction of Monetary Policy to the Stock Market," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(2), pages 639-669.
    21. Hans‐Martin Krolzig, 2003. "General‐to‐Specific Model Selection Procedures for Structural Vector Autoregressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 769-801, December.
    22. Robert E. Hall, 2011. "The High Sensitivity of Economic Activity to Financial Frictions," Economic Journal, Royal Economic Society, vol. 121(552), pages 351-378, May.
    23. Halvorsen, Jørn I. & Jacobsen, Dag Henning, 2014. "How important can bank lending shocks be for economic fluctuations?," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 104-123.
    24. Michał Brzoza-Brzezina, 2002. "Estimating the Natural Rate of Interest: A SVAR Approach," NBP Working Papers 27, Narodowy Bank Polski.
    25. Matteo Ciccarelli & Angela Maddaloni & Jose Luis Peydro, 2015. "Trusting the Bankers: A New Look at the Credit Channel of Monetary Policy," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 18(4), pages 979-1002, October.
    26. Dag Tjøstheim & Jostein Paulsen, 1985. "Least Squares Estimates And Order Determination Procedures For Autoregressive Processes With A Time Dependent Variance," Journal of Time Series Analysis, Wiley Blackwell, vol. 6(2), pages 117-133, March.
    27. Lanne, Markku & Lütkepohl, Helmut & Maciejowska, Katarzyna, 2010. "Structural vector autoregressions with Markov switching," Journal of Economic Dynamics and Control, Elsevier, vol. 34(2), pages 121-131, February.
    28. Urban Jermann & Vincenzo Quadrini, 2012. "Erratum: Macroeconomic Effects of Financial Shocks," American Economic Review, American Economic Association, vol. 102(2), pages 1186-1186, April.
    29. Jesús Gonzalo & Jean‐Yves Pitarakis, 2002. "Lag length estimation in large dimensional systems," Journal of Time Series Analysis, Wiley Blackwell, vol. 23(4), pages 401-423, July.
    30. Lanne, Markku & Lütkepohl, Helmut, 2010. "Structural Vector Autoregressions With Nonnormal Residuals," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 159-168.
    31. Canova, Fabio & Nicolo, Gianni De, 2002. "Monetary disturbances matter for business fluctuations in the G-7," Journal of Monetary Economics, Elsevier, vol. 49(6), pages 1131-1159, September.
    32. Luca Gambetti & Alberto Musso, 2017. "Loan Supply Shocks and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(4), pages 764-782, June.
    33. Hans-Martin Krolzig, 2003. "General-to-Specific Model Selection Procedures for Structural Vector Autoregressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 769-801, December.
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    Cited by:

    1. Mariusz Kapuściński, 2022. "The short-term effects of changes in capital regulations in Poland," NBP Working Papers 350, Narodowy Bank Polski.
    2. Robert Socha & Piotr Wdowiński, 2018. "Tendencje zmian cen na światowym rynku ropy naftowej po 2000 roku," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 1, pages 103-135.
    3. Robert Socha & Piotr Wdowiński, 2018. "Crude oil price and speculative activity: a cointegration analysis," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 10(3), pages 263-304, September.

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    More about this item

    Keywords

    vector autoregression; Cholesky decomposition; combined impulse response; banking sector; real economy;
    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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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