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An empirical study of credit shock transmission in a small open economy

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  • Nathan Bedock
  • Dalibor Stevanović

Abstract

In this paper, we identify and estimate the dynamic effects of foreign (US) and national (Canadian) credit shocks in a small open economy. We use standard credit spreads as proxies to the external finance premium. Our first result suggests that the US and Canadian credit spreads contain substantial forecasting power for several measures of the Canadian real economic activity, especially during the recent financial crisis and its aftermath. Secondly, an adverse US credit shock generates a significant and persistent economic slowdown in Canada: the national external finance premium rises immediately while interest rates, credit aggregates, output and employment indicators decline. Variance decomposition reveals that credit shocks have a sizeable effect on real activity measures, leading indicators and credit spreads. Yet, the unexpected shocks in domestic credit spreads are not able to generate any significant dynamic response of the real activity once we control for the US credit market conditions. Une étude empirique de la transmission de chocs de crédit dans une petite économie ouverte. Dans ce texte, les auteurs identifient et estiment les effets dynamiques de chocs de crédit étranger (US) et domestique (Canada) dans une petite économie ouverte. On utilise les écarts de crédit standard en tant qu'approximation de la prime du financement externe. Premièrement, les résultats suggèrent que les écarts de crédit US/Canada ont un pouvoir de prédiction substantiel pour plusieurs mesures de l'activité économique réelle au Canada, en particulier au cours de la récente crise financière et son après. Deuxièmement, un choc négatif de crédit aux États‐Unis déclenche un ralentissement économique significatif et persistant au Canada : alors que la prime nationale du financement externe s'accroît immédiatement, les taux d'intérêt, et les indicateurs du niveau de crédit agrégé, de la production et de l'emploi déclinent. La décomposition de la variance montre que les chocs de crédit ont un effet important sur les mesures d'activité économique réelle, les indicateurs avancés et les écarts de crédit. D'autre part, les chocs non‐anticipés dans les écarts de crédit domestiques n'engendrent pas de réponse dynamique significative dans le niveau d'activité économique réelle quand on tient compte des conditions sur le marché du crédit aux États‐Unis.

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  • Nathan Bedock & Dalibor Stevanović, 2017. "An empirical study of credit shock transmission in a small open economy," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 50(2), pages 541-570, May.
  • Handle: RePEc:wly:canjec:v:50:y:2017:i:2:p:541-570
    DOI: 10.1111/caje.12269
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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. Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez & Thomas J. Sargent & Mark W. Watson, 2007. "ABCs (and Ds) of Understanding VARs," American Economic Review, American Economic Association, vol. 97(3), pages 1021-1026, June.
    3. 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.
    4. Pesaran, M. Hashem & Schuermann, Til & Treutler, Bjorn-Jakob & Weiner, Scott M., 2006. "Macroeconomic Dynamics and Credit Risk: A Global Perspective," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1211-1261, August.
    5. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    6. Jean Boivin & Marc P. Giannoni & Dalibor Stevanović, 2020. "Dynamic Effects of Credit Shocks in a Data-Rich Environment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 272-284, April.
    7. Ravenna, Federico, 2007. "Vector autoregressions and reduced form representations of DSGE models," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 2048-2064, October.
    8. James H. Stock & Mark W. Watson, 2005. "Implications of Dynamic Factor Models for VAR Analysis," NBER Working Papers 11467, National Bureau of Economic Research, Inc.
    9. Ivana Komunjer & Serena Ng, 2011. "Dynamic Identification of Dynamic Stochastic General Equilibrium Models," Econometrica, Econometric Society, vol. 79(6), pages 1995-2032, November.
    10. Thomas Philippon, 2009. "The Bond Market's q," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 124(3), pages 1011-1056.
    11. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    12. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    13. 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.
    14. Raphael Espinoza & Fabio Fornari & Marco J. Lombardi, 2012. "The Role of Financial Variables in predicting economic activity," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 31(1), pages 15-46, January.
    15. Dynan, Karen E. & Elmendorf, Douglas W. & Sichel, Daniel E., 2006. "Can financial innovation help to explain the reduced volatility of economic activity?," Journal of Monetary Economics, Elsevier, vol. 53(1), pages 123-150, January.
    16. Ben S. Bernanke & Mark Gertler, 1995. "Inside the Black Box: The Credit Channel of Monetary Policy Transmission," Journal of Economic Perspectives, American Economic Association, vol. 9(4), pages 27-48, Fall.
    17. Williamson, Stephen D, 1987. "Financial Intermediation, Business Failures, and Real Business Cycles," Journal of Political Economy, University of Chicago Press, vol. 95(6), pages 1196-1216, December.
    18. 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.
    19. Seung C. Ahn & Alex R. Horenstein, 2013. "Eigenvalue Ratio Test for the Number of Factors," Econometrica, Econometric Society, vol. 81(3), pages 1203-1227, May.
    20. Atta-Mensah, Joseph & Dib, Ali, 2008. "Bank lending, credit shocks, and the transmission of Canadian monetary policy," International Review of Economics & Finance, Elsevier, vol. 17(1), pages 159-176.
    21. Zhiwei Zhang, 2002. "Corporate Bond Spreads and the Business Cycle," Staff Working Papers 02-15, Bank of Canada.
    22. 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.
    23. Amengual, Dante & Watson, Mark W., 2007. "Consistent Estimation of the Number of Dynamic Factors in a Large N and T Panel," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 91-96, January.
    24. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 120(1), pages 387-422.
    25. Hallin, Marc & Liska, Roman, 2007. "Determining the Number of Factors in the General Dynamic Factor Model," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 603-617, June.
    26. Marco Lombardi & Mr. Raphael A Espinoza & Fabio Fornari, 2009. "The Role of Financial Variables in Predicting Economic Activity in the Euro Area," IMF Working Papers 2009/241, International Monetary Fund.
    27. repec:ulb:ulbeco:2013/13388 is not listed on IDEAS
    28. Jushan Bai & Serena Ng, 2006. "Confidence Intervals for Diffusion Index Forecasts and Inference for Factor-Augmented Regressions," Econometrica, Econometric Society, vol. 74(4), pages 1133-1150, July.
    29. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    30. Lutkepohl, Helmut, 1984. "Linear transformations of vector ARMA processes," Journal of Econometrics, Elsevier, vol. 26(3), pages 283-293, December.
    31. Gertler, Mark & Lown, Cara S, 1999. "The Information in the High-Yield Bond Spread for the Business Cycle: Evidence and Some Implications," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 15(3), pages 132-150, Autumn.
    32. Bai, Jushan & Ng, Serena, 2007. "Determining the Number of Primitive Shocks in Factor Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 52-60, January.
    33. Ben S. Bernanke, 1993. "Credit in the macroeconomy," Quarterly Review, Federal Reserve Bank of New York, vol. 18(Spr), pages 50-70.
    34. Jean-Marie Dufour & Dalibor Stevanović, 2013. "Factor-Augmented VARMA Models With Macroeconomic Applications," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(4), pages 491-506, October.
    35. Estrella, Arturo & Hardouvelis, Gikas A, 1991. "The Term Structure as a Predictor of Real Economic Activity," Journal of Finance, American Finance Association, vol. 46(2), pages 555-576, June.
    36. Alexei Onatski, 2010. "Determining the Number of Factors from Empirical Distribution of Eigenvalues," The Review of Economics and Statistics, MIT Press, vol. 92(4), pages 1004-1016, November.
    37. Meh, Césaire A. & Moran, Kevin, 2010. "The role of bank capital in the propagation of shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 34(3), pages 555-576, March.
    38. Tibor F. Liska, 2007. "The Liska model," Society and Economy, Akadémiai Kiadó, Hungary, vol. 29(3), pages 363-381, December.
    39. Ali Dib, 2010. "Banks, Credit Market Frictions, and Business Cycles," Staff Working Papers 10-24, Bank of Canada.
    40. J. Safaei & N. E. Cameron, 2003. "Credit channel and credit shocks in Canadian macrodynamics - a structural VAR approach," Applied Financial Economics, Taylor & Francis Journals, vol. 13(4), pages 267-277.
    41. Onatski, Alexei, 2012. "Asymptotics of the principal components estimator of large factor models with weakly influential factors," Journal of Econometrics, Elsevier, vol. 168(2), pages 244-258.
    42. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409, National Bureau of Economic Research, Inc.
    43. Bai, Jushan & Ng, Serena, 2008. "Large Dimensional Factor Analysis," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(2), pages 89-163, June.
    44. Diebold, Francis X. & Rudebusch, Glenn D. & Borag[caron]an Aruoba, S., 2006. "The macroeconomy and the yield curve: a dynamic latent factor approach," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 309-338.
    45. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    46. Alessi, Lucia & Barigozzi, Matteo & Capasso, Marco, 2010. "Improved penalization for determining the number of factors in approximate factor models," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1806-1813, December.
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    2. Chinara Azizova & Bruno Feunou & James Kyeong, 2023. "Forecasting Risks to the Canadian Economic Outlook at a Daily Frequency," Discussion Papers 2023-19, Bank of Canada.
    3. Kevin Moran & Dalibor Stevanovic & Adam Kader Touré, 2022. "Macroeconomic uncertainty and the COVID‐19 pandemic: Measure and impacts on the Canadian economy," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(S1), pages 379-405, February.
    4. Kevin Moran & Dalibor Stevanovic & Stephane Surprenant, 2024. "Risk Scenarios and Macroeconomic Forecasts," Working Papers 24-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Apr 2024.
    5. Dalibor Stevanovic & Rachidi Kotchoni & Maxime Leroux, 2017. "Forecasting economic activity in data-rich environment," CIRANO Working Papers 2017s-05, CIRANO.
    6. Maxime Leboeuf & Daniel Hyun, 2018. "Is the Excess Bond Premium a Leading Indicator of Canadian Economic Activity?," Staff Analytical Notes 2018-4, Bank of Canada.

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    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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