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International spillovers from Euro area and US credit and demand shocks: A focus on emerging Europe

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  • Fadejeva, Ludmila
  • Feldkircher, Martin
  • Reininger, Thomas

Abstract

In this paper, we examine the international effects of contractions in loan supply, loan demand and aggregate demand in the euro area and the USA. All three shocks have been at the forefront in spreading stress during the period of the global financial crisis and in particular so to countries that are strongly integrated with the euro area. We find that these shocks decrease international output and total credit to a varying degree. Loan demand and aggregate demand shocks in the euro area trigger significant negative spillovers on output in most other regions. Evidence for global negative output effects of euro area loan supply shocks is fraught with considerable estimation uncertainty. When these three types of shocks emanate from the USA, we find significant negative spillovers on output also for loan supply shocks. In general, international effects on total credit are an order of magnitude larger than those on output, with again more evidence that is significant for US than euro area shocks. Last, and taking a regional stance, our results indicate that economies from emerging Europe are most vulnerable to all shocks considered. Through their strong economic integration with the euro area, these economies are likewise exposed to euro area and US shocks, and spillover effects are often larger than the domestic response in the country of shock-origin.

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  • Fadejeva, Ludmila & Feldkircher, Martin & Reininger, Thomas, 2017. "International spillovers from Euro area and US credit and demand shocks: A focus on emerging Europe," Journal of International Money and Finance, Elsevier, vol. 70(C), pages 1-25.
  • Handle: RePEc:eee:jimfin:v:70:y:2017:i:c:p:1-25
    DOI: 10.1016/j.jimonfin.2016.08.001
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    as
    1. Alexander Chudik & M. Hashem Pesaran, 2016. "Theory And Practice Of Gvar Modelling," Journal of Economic Surveys, Wiley Blackwell, vol. 30(1), pages 165-197, February.
    2. 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.
    3. Mathias Lahnsteiner, 2011. "The Refinancing Structure of Banks in Selected CESEE Countries," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 1, pages 44-69.
    4. Eickmeier, Sandra & Ng, Tim, 2015. "How do US credit supply shocks propagate internationally? A GVAR approach," European Economic Review, Elsevier, vol. 74(C), pages 128-145.
    5. Dovern, Jonas & Feldkircher, Martin & Huber, Florian, 2015. "Does Joint Modelling of the World Economy Pay Off? Evaluating Multivariate Forecasts from a Bayesian GVAR," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112999, Verein für Socialpolitik / German Economic Association.
    6. 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.
    7. Hristov, Nikolay & Hülsewig, Oliver & Wollmershäuser, Timo, 2012. "Loan supply shocks during the financial crisis: Evidence for the Euro area," Journal of International Money and Finance, Elsevier, vol. 31(3), pages 569-592.
    8. Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2010. "Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(2), pages 665-696.
    9. Peter Backé & Martin Feldkircher & Tomáš Slacík, 2013. "Economic Spillovers from the Euro Area to the CESEE Region via the Financial Channel: A GVAR Approach," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 4, pages 50-64.
    10. Dovern, Jonas & Feldkircher, Martin & Huber, Florian, 2016. "Does joint modelling of the world economy pay off? Evaluating global forecasts from a Bayesian GVAR," Journal of Economic Dynamics and Control, Elsevier, vol. 70(C), pages 86-100.
    11. Peek, Joe & Rosengren, Eric S & Tootell, Geoffrey M B, 2003. "Identifying the Macroeconomic Effect of Loan Supply Shocks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 35(6), pages 931-946, December.
    12. Filippo di Mauro & L. Vanessa Smith & Stephane Dees & M. Hashem Pesaran, 2007. "Exploring the international linkages of the euro area: a global VAR analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 1-38.
    13. Fratzscher, Marcel & Chudik, Alexander, 2010. "Identifying the Global Transmission of the 2007-09 Financial Crisis in a GVAR Model," CEPR Discussion Papers 8093, C.E.P.R. Discussion Papers.
    14. Helbling, Thomas & Huidrom, Raju & Kose, M. Ayhan & Otrok, Christopher, 2011. "Do credit shocks matter? A global perspective," European Economic Review, Elsevier, vol. 55(3), pages 340-353, April.
    15. Fabio Fornari & Livio Stracca, 2012. "What does a financial shock do? First international evidence [Financial intermediaries, financial stability and monetary policy]," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 27(71), pages 407-445.
    16. Pesaran, Mohammad Hashem & Holly, Sean & Dees, Stephane & Smith, L. Vanessa, 2007. "Long Run Macroeconomic Relations in the Global Economy," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 1, pages 1-20.
    17. 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.
    18. Pesaran M.H. & Schuermann T. & Weiner S.M., 2004. "Modeling Regional Interdependencies Using a Global Error-Correcting Macroeconometric Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 129-162, April.
    19. Feldkircher, Martin & Huber, Florian, 2016. "The international transmission of US shocks—Evidence from Bayesian global vector autoregressions," European Economic Review, Elsevier, vol. 81(C), pages 167-188.
    20. Garratt, Anthony & Lee, Kevin & Pesaran, M. Hashem & Shin, Yongcheol, 2012. "Global and National Macroeconometric Modelling: A Long-Run Structural Approach," OUP Catalogue, Oxford University Press, number 9780199650460, Decembrie.
    21. Busch, Ulrike & Scharnagl, Michael & Scheithauer, Jan, 2010. "Loan supply in Germany during the financial crisis," Discussion Paper Series 1: Economic Studies 2010,05, Deutsche Bundesbank.
    22. Feldkircher, Martin, 2015. "A global macro model for emerging Europe," Journal of Comparative Economics, Elsevier, vol. 43(3), pages 706-726.
    23. Atif Mian & Amir Sufi, 2009. "The Consequences of Mortgage Credit Expansion: Evidence from the U.S. Mortgage Default Crisis," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 124(4), pages 1449-1496.
    24. M. Hashem Pesaran & L. Vanessa Smith & Ron P. Smith, 2007. "What if the UK or Sweden had joined the euro in 1999? An empirical evaluation using a Global VAR," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 12(1), pages 55-87.
    25. Pesaran, M. Hashem & Schuermann, Til & Smith, L. Vanessa, 2009. "Forecasting economic and financial variables with global VARs," International Journal of Forecasting, Elsevier, vol. 25(4), pages 642-675, October.
    26. Cesa-Bianchi, Ambrogio, 2013. "Housing cycles and macroeconomic fluctuations: A global perspective," Journal of International Money and Finance, Elsevier, vol. 37(C), pages 215-238.
    27. Lombardi, Marco J. & Galesi, Alessandro, 2009. "External shocks and international inflation linkages: a global VAR analysis," Working Paper Series 1062, European Central Bank.
    28. 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.
    29. Chudik, Alexander & Fratzscher, Marcel, 2011. "Identifying the global transmission of the 2007-2009 financial crisis in a GVAR model," European Economic Review, Elsevier, vol. 55(3), pages 325-339, April.
    30. 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.
    31. Mauricio Calani C. & Pablo García S. & Daniel Oda Z., 2010. "Supply and Demand Identification in the Credit Market," Working Papers Central Bank of Chile 571, Central Bank of Chile.
    32. Dovern, Jonas & van Roye, Björn, 2014. "International transmission and business-cycle effects of financial stress," Journal of Financial Stability, Elsevier, vol. 13(C), pages 1-17.
    33. Fratzscher, Marcel & Saborowski, Christian & Straub, Roland, 2009. "Monetary Policy Shocks and Portfolio Choice," Working Paper Series 1122, European Central Bank.
    34. Canova, Fabio & Paustian, Matthias, 2011. "Business cycle measurement with some theory," Journal of Monetary Economics, Elsevier, vol. 58(4), pages 345-361.
    35. Pesaran, M. Hashem & Schuermann, Til & Smith, L. Vanessa, 2009. "Rejoinder to comments on forecasting economic and financial variables with global VARs," International Journal of Forecasting, Elsevier, vol. 25(4), pages 703-715, October.
    36. Paustian Matthias, 2007. "Assessing Sign Restrictions," The B.E. Journal of Macroeconomics, De Gruyter, vol. 7(1), pages 1-33, August.
    37. Helmut Lütkepohl, 2013. "Vector autoregressive models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 6, pages 139-164, Edward Elgar Publishing.
    38. Castrén, Olli & Dées, Stéphane & Zaher, Fadi, 2010. "Stress-testing euro area corporate default probabilities using a global macroeconomic model," Journal of Financial Stability, Elsevier, vol. 6(2), pages 64-78, June.
    39. repec:onb:oenbwp:y:2013:i:4:b:1 is not listed on IDEAS
    40. di Mauro, Filippo & Pesaran, M. Hashem (ed.), 2013. "The GVAR Handbook: Structure and Applications of a Macro Model of the Global Economy for Policy Analysis," OUP Catalogue, Oxford University Press, number 9780199670086.
    41. Burbidge, John & Harrison, Alan, 1985. "An historical decomposition of the great depression to determine the role of money," Journal of Monetary Economics, Elsevier, vol. 16(1), pages 45-54, July.
    42. Meeks, Roland, 2012. "Do credit market shocks drive output fluctuations? Evidence from corporate spreads and defaults," Journal of Economic Dynamics and Control, Elsevier, vol. 36(4), pages 568-584.
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    More about this item

    Keywords

    Credit shock; Global vector autoregressions; Emerging Europe; Sign restrictions;
    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
    • F44 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - International Business Cycles
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • O54 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Latin America; Caribbean

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