Skip to main content
×
×
Home

ON THE RELATIONSHIP BETWEEN FINANCIAL INSTABILITY AND ECONOMIC PERFORMANCE: STRESSING THE BUSINESS OF NONLINEAR MODELING

  • David Ubilava (a1)
Abstract

The recent global financial crisis and the subsequent recession have revitalized the discussion on causal interactions between financial and economic sectors. In this study, I apply the financial stress and the national activity indices–respectively developed by Federal Reserve Banks of Kansas City and Chicago–to investigate the impact of financial uncertainty on an overall economic performance. I examine nonlinear dynamics in a vector smooth transition autoregressive framework, and illustrate regime-dependent asymmetries in the financial and economic indices using the generalized impulse-response functions. The results reveal more amplified dynamics during the stressed conditions. I further evaluate benefits of nonlinear modeling in an out-of-sample setting. The forecasting exercise brings out the important advantages that nonlinear modeling provides in the identification of the causal effect of financial instability on overall economic performance.

Copyright
Corresponding author
Address correspondence to: David Ubilava, School of Economics, The University of Sydney, Merewether Building, NSW 2006, Australia; e-mail: david.ubilava@sydney.edu.au.
Footnotes
Hide All

This paper greatly benefited from many useful comments and suggestions from Edward Nelson, as well as those of two anonymous referees.

Footnotes
References
Hide All
Anderson, H. M., Athanasopoulos, G. and Vahid, F. (2007) Nonlinear autoregressive leading indicator models of output in G-7 countries. Journal of Applied Econometrics 22 (1), 6387.
Anderson, H. M. and Vahid, F. (1998) Testing multiple equation systems for common nonlinear components. Journal of Econometrics 84 (1), 136.
Arestis, P., Demetriades, P. O. and Luintel, K. B. (2001) Financial development and economic growth: The role of stock markets. Journal of Money Credit and Banking 33 (1), 1641.
Ashley, R., Granger, C. W. and Schmalensee, R. (1980) Advertising and aggregate consumption: An analysis of causality. Econometrica 48 (5), 11491167.
Bacon, D. and Watts, D. (1971) Estimating the transition between two intersecting straight lines. Biometrika 58 (3), 525534.
Brunnermeier, M. K. and Sannikov, Y. (2014) A macroeconomic model with a financial sector. American Economic Review 104 (2), 379421.
Burns, A. F. and Mitchell, W. C. (1946) Measuring Business Cycles. National Bureau of Economic Research.
Calderón, C. and Liu, L. (2003) The direction of causality between financial development and economic growth. Journal of Development Economics 72 (1), 321334.
Camacho, M. (2004) Vector smooth transition regression models for US GDP and the composite index of leading indicators. Journal of Forecasting 23 (3), 173196.
Chan, K. and Tong, H. (1986) On estimating thresholds in autoregressive models. Journal of Time Series Analysis 7 (3), 179190.
Clark, T. and McCracken, M. (2001) Tests of equal forecast accuracy and encompassing for nested models. Journal of Econometrics 105 (1), 85110.
Clark, T. and West, K. (2007) Approximately normal tests for equal predictive accuracy in nested models. Journal of Econometrics 138 (1), 291311.
Davies, R. (1977) Hypothesis testing when a nuisance parameter is present only under the alternative. Biometrika 64 (2), 247254.
Davies, R. (1987) Hypothesis testing when a nuisance parameter is present only under the alternative. Biometrika 74 (1), 3343.
Davig, T. and Hakkio, C. S. (2010) What is the effect of financial stress on economic activity?. Federal Reserve Bank of Kansas City, Economic Review 95 (2), 3562.
De Gregorio, J. and Guidotti, P. E. (1995) Financial development and economic growth. World Development 23 (3), 433448.
Diebold, F. and Mariano, R. (1995) Comparing predictive accuracy. Journal of Business & Economic Statistics 13 (3), 253263.
Diebold, F. X. and Rudebusch, G. D. (1991) Forecasting output with the composite leading index: A real-time analysis. Journal of the American Statistical Association 86 (415), 603610.
Diebold, F. X. and Rudebusch, G. D. (1996) Measuring business cycles: A modern perspective. Review of Economics and Statistics 78 (1), 6777.
Ferrara, L., Marcellino, M. and Mogliani, M. (2015) Macroeconomic forecasting during the great recession: The return of non-linearity?. International Journal of Forecasting 31 (3), 664679.
Fisher, I. (1933) The debt-deflation theory of great depressions. Econometrica 1 (4), 337357.
Franses, P. H. and van Dijk, D. (2005) The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production. International Journal of Forecasting 21 (1), 87102.
Gertler, M. and Kiyotaki, N. (2010) Financial intermediation and credit policy in business cycle analysis. In Friedman, B. M. and Woodford, M. (eds.), Handbook of Monetary Economics, vol. 3, pp. 547599. Amsterdam, The Netherlands: Elsevier.
Giacomini, R. and Rossi, B. (2013) Forecasting in macroeconomics. In Hashimzade, N. and Thornton, M. A. (eds.), Handbook of Research Methods and Applications on Empirical Macroeconomics. Cheltenham, UK: Edward Elgar Publishing.
Gilchrist, S., Yankov, V., and Zakrajşek, E. (2009) Credit market shocks and economic fluctuations: Evidence from corporate bond and stock markets. Journal of Monetary Economics 56 (4), 471493.
Granger, C. and Teräsvirta, T. (1993) Modelling Nonlinear Economic Relationships. New York, USA: Oxford University Press.
Granger, C. W. (1969) Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37 (3), 424438.
Hakkio, C. S. and Keeton, W. R. (2009) Financial stress: What is it, how can it be measured, and why does it matter?. Federal Reserve Bank of Kansas City, Economic Review 94 (2), 550.
Hubrich, K. and Teräsvirta, T. (2013) Thresholds and Smooth Transitions in Vector Autoregressive Models. Research paper 13, CREATES.
Hubrich, K. and Tetlow, R. (2015) Financial stress and economic dynamics: The transmission of crises. Journal of Monetary Economics 70, 100115.
Hyndman, R. J. (1995) Highest-density forecast regions for nonlinear and non-normal time series models. Journal of Forecasting 4 (5), 431441.
Hyndman, R. J. (1996) Computing and graphing highest density regions. American Statistician 50 (2), 120126.
Jermann, U. and Quadrini, V. (2012). Macroeconomic effects of financial shocks. American Economic Review 102 (1), 238271.
Jones, P. M. and Enders, W. (2016) The asymmetric effects of uncertainty on macroeconomic activity. Macroeconomic Dynamics forthcoming 1–28.
Keynes, J. M. (1936) The General Theory of Employment, Interest and Money. London: Macmillan.
King, R. G. and Levine, R. (1993) Finance and growth: Schumpeter might be right. Quarterly Journal of Economics 108 (3), 717737.
Koop, G., Pesaran, M. and Potter, S. (1996) Impulse response analysis in nonlinear multivariate models. Journal of Econometrics 74 (1), 119147.
Lahiri, K. and Wang, J. G. (1994) Predicting cyclical turning points with leading index in a markov switching model. Journal of Forecasting 13 (3), 245263.
Levine, R. (1997) Financial development and economic growth: Views and agenda. Journal of Economic Literature 35 (2), 688726.
Liu, Z., Waggoner, D. F. and Zha, T. (2011) Sources of macroeconomic fluctuations: A regime-switching DSGE approach. Quantitative Economics 2 (2), 251301.
Luukkonen, R., Saikkonen, P. and Teräsvirta, T. (1988) Testing linearity against smooth transition autoregressive models. Biometrika 75 (3), 491499.
Marcellino, M., Stock, J. H. and Watson, M. W. (2006) A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series. Journal of Econometrics 135 (1), 499526.
McCracken, M. W. (2007) Asymptotics for out of sample tests of Granger causality. Journal of Econometrics 140 (2), 719752.
Mittnik, S. and Semmler, W. (2013) The real consequences of financial stress. Journal of Economic Dynamics and Control 37 (8), 14791499.
Rothman, P., van Dijk, D. and Franses, P. H. (2001) Multivariate STAR analysis of money–output relationship. Macroeconomic Dynamics 5 (4), 506532.
Samuelson, P. A. (1966) Science and stocks. Newsweek, September 19, 1992.
Schleer, F. and Semmler, W. (2015) Financial sector and output dynamics in the euro area: Non-linearities reconsidered. Journal of Macroeconomics 46, 235263.
Schumpeter, J. A. (1934) The Theory of Economic Development: An Inquiry into Profits, Capital, Credit, Interest, and the Business Cycle. Cambridge, MA: Harvard University Press. Translated by Redvers Opie.
Skalin, J. and Teräsvirta, T. (2002) Modeling asymmetries and moving equilibria in unemployment rates. Macroeconomic Dynamics 6 (2), 202241.
Stock, J. H. and Watson, M. W. (1989) New Indexes of Coincident and Leading Economic Indicators. NBER macroeconomics annual 4, 351409.
Stock, J. H. and Watson, M. W. (1993) A procedure for predicting recessions with leading indicators: Econometric issues and recent experience. In Stock, J. H. and Watson, M. W. (eds.), Business Cycles, Indicators and Forecasting, pp. 95156. Chicago, IL: University of Chicago Press.
Stock, J. H. and Watson, M. W. (1999a) Business cycle fluctuations in US macroeconomic time series. In Taylor, J. B. and Woodford, M. (eds.), Handbook of Macroeconomics, vol. 1, pp. 364. Amsterdam, The Netherlands: Elsevier.
Stock, J. H. and Watson, M. W. (1999b) Forecasting inflation. Journal of Monetary Economics 44 (2), 293335.
Stock, J. H. and Watson, M. W. (2003) Forecasting output and inflation: The role of asset prices. Journal of Economic Literature 41 (3), 788829.
Teräsvirta, T. (1994) Specification, estimation, and evaluation of smooth transition autoregressive models. Journal of the American Statistical Association 89 (425), 208218.
Teräsvirta, T. (1995) Modelling nonlinearity in US gross national product 1889–1987. Empirical Economics 20 (4), 577597.
Teräsvirta, T. and Anderson, H. (1992) Characterizing nonlinearities in business cycles using smooth transition autoregressive models. Journal of Applied Econometrics 7 (S1), S119S136.
Teräsvirta, T., Tjøstheim, D. and Granger, C. W. J. (2010). Modelling Nonlinear Economic Time Series. Advanced Texts in Econometrics. New York: Oxford University Press.
Teräsvirta, T. and Yang, Y. (2014a) Linearity and misspecification tests for vector smooth transition regression models. Research paper 4, CREATES.
Teräsvirta, T. and Yang, Y. (2014b) Specification, estimation and evaluation of vector smooth transition autoregressive models with applications. Research paper 8, CREATES.
Tong, H. and Lim, K. S. (1980) Threshold autoregression, limit cycles and cyclical data. Journal of the Royal Statistical Society. Series B (Methodological) 42 (3), 245292.
van Dijk, D. and Franses, P. (1999) Modeling multiple regimes in the business cycle. Macroeconomic Dynamics 3 (3), 311340.
Weise, C. (1999). The asymmetric effects of monetary policy: A nonlinear vector autoregression approach. Journal of Money, Credit and Banking 31 (1), 85108.
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

Macroeconomic Dynamics
  • ISSN: 1365-1005
  • EISSN: 1469-8056
  • URL: /core/journals/macroeconomic-dynamics
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
×

Keywords:

Metrics

Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 18 *
Loading metrics...

Abstract views

Total abstract views: 316 *
Loading metrics...

* Views captured on Cambridge Core between 9th June 2017 - 24th April 2018. This data will be updated every 24 hours.