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The Impact of Financial Variables on Czech Macroeconomic Developments: An Empirical Investigation

Author

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  • Tomas Adam
  • Miroslav Plasil

Abstract

This paper investigates empirically to what extent financial variables can explain macroeconomic developments in the Czech Republic and how the results are sensitive to some (usually reasonable or routinely made) modeling choices. To this end, the dynamic model averaging/selection framework is applied to a universe of (potentially large) time-varying parameter VAR models, which allows one to assess the explanatory power of financial variables at each point in time. Based on a set of 27 competing models and an extensive ensemble of alternative specifications of those models, we find that financial variables were particularly relevant in explaining developments in the lead-up to and during economic downturns. By contrast, in tranquil times, models containing only traditional macroeconomic variables explained macroeconomic dynamics reasonably well. Within the broad set of financial variables considered, credit to the private sector, bank profitability, and leverage seem to be among the most relevant indicators.

Suggested Citation

  • Tomas Adam & Miroslav Plasil, 2014. "The Impact of Financial Variables on Czech Macroeconomic Developments: An Empirical Investigation," Working Papers 2014/11, Czech National Bank.
    • Handle: RePEc:cnb:wpaper:2014/11
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    References listed on IDEAS

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    1. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2003. "Do financial variables help forecasting inflation and real activity in the euro area?," Journal of Monetary Economics, Elsevier, vol. 50(6), pages 1243-1255, September.
    2. Tomas Konecny & Oxana Babecka Kucharcukova, 2013. "Evaluating the Links Between the Financial and Real Sectors in a Small Open Economy: The Case of the Czech Republic," Working Papers 2013/10, Czech National Bank.
    3. Markus K. Brunnermeier & Thomas M. Eisenbach & Yuliy Sannikov, 2012. "Macroeconomics with Financial Frictions: A Survey," Levine's Working Paper Archive 786969000000000384, David K. Levine.
    4. Vincenzo Quadrini, 2011. "Financial frictions in macroeconomic fluctations," Economic Quarterly, Federal Reserve Bank of Richmond, vol. 97(3Q), pages 209-254.
    5. Bernanke, Ben S. & Gertler, Mark & Gilchrist, Simon, 1999. "The financial accelerator in a quantitative business cycle framework," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 21, pages 1341-1393, Elsevier.
    6. Kremer, Manfred & Lo Duca, Marco & Holló, Dániel, 2012. "CISS - a composite indicator of systemic stress in the financial system," Working Paper Series 1426, European Central Bank.
    7. repec:ecb:ecbwps:20111426 is not listed on IDEAS
    8. repec:fip:fedreq:y:2011:i:3q:p:209-254:n:vol.97no.3 is not listed on IDEAS
    9. Koop, Gary & Korobilis, Dimitris, 2014. "A new index of financial conditions," European Economic Review, Elsevier, vol. 71(C), pages 101-116.
    10. Mathias Drehmann & Claudio Borio & Kostas Tsatsaronis, 2012. "Characterising the financial cycle: don't lose sight of the medium term!," BIS Working Papers 380, Bank for International Settlements.
    11. James H. Stock & Mark W. Watson, 2010. "Modeling inflation after the crisis," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 173-220.
    12. Michal Franta & Roman Horvath & Marek Rusnak, 2014. "Evaluating changes in the monetary transmission mechanism in the Czech Republic," Empirical Economics, Springer, vol. 46(3), pages 827-842, May.
    13. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 821-852.
    14. Koop, Gary & Korobilis, Dimitris, 2013. "Large time-varying parameter VARs," Journal of Econometrics, Elsevier, vol. 177(2), pages 185-198.
    15. Tomas Adam & Sona Benecka, 2013. "Financial Stress Spillover and Financial Linkages between the Euro Area and the Czech Republic," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(1), pages 46-64, March.
    16. James H. Stock & Mark W.Watson, 2003. "Forecasting Output and Inflation: The Role of Asset Prices," Journal of Economic Literature, American Economic Association, vol. 41(3), pages 788-829, September.
    17. Hartmann, Philipp & Hubrich, Kirstin & Kremer, Manfred & Tetlow, Robert J., 2013. "Melting down: Systemic financial instability and the macroeconomy," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 80487, Verein für Socialpolitik / German Economic Association.
    18. Jakub Rysanek & Jaromir Tonner & Stanislav Tvrz & Osvald Vasicek, 2012. "Monetary Policy Implications of Financial Frictions in the Czech Republic," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 62(5), pages 413-429, November.
    19. AfDB AfDB, . "Annual Report 2012," Annual Report, African Development Bank, number 461.
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    Cited by:

    1. Tomas Adam & Filip Novotny, 2018. "Assessing the External Demand of the Czech Economy: Nowcasting Foreign GDP Using Bridge Equations," Working Papers 2018/18, Czech National Bank.

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    More about this item

    Keywords

    Dynamic model averaging; macro-financial linkages; 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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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