Skip to main content
×
Home
    • Aa
    • Aa

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
Linked references
Hide All

This list contains references from the content that can be linked to their source. For a full set of references and notes please see the PDF or HTML where available.

H. M. Anderson , G. Athanasopoulos and F. Vahid (2007) Nonlinear autoregressive leading indicator models of output in G-7 countries. Journal of Applied Econometrics 22 (1), 6387.

H. M. Anderson and F. Vahid (1998) Testing multiple equation systems for common nonlinear components. Journal of Econometrics 84 (1), 136.

P. Arestis , P. O. Demetriades and K. B. Luintel (2001) Financial development and economic growth: The role of stock markets. Journal of Money Credit and Banking 33 (1), 1641.

R. Ashley , C. W. Granger and R. Schmalensee (1980) Advertising and aggregate consumption: An analysis of causality. Econometrica 48 (5), 11491167.

D. Bacon and D. Watts (1971) Estimating the transition between two intersecting straight lines. Biometrika 58 (3), 525534.

C. Calderón and L. Liu (2003) The direction of causality between financial development and economic growth. Journal of Development Economics 72 (1), 321334.

M. Camacho (2004) Vector smooth transition regression models for US GDP and the composite index of leading indicators. Journal of Forecasting 23 (3), 173196.

K. Chan and H. Tong (1986) On estimating thresholds in autoregressive models. Journal of Time Series Analysis 7 (3), 179190.

T. Clark and M. McCracken (2001) Tests of equal forecast accuracy and encompassing for nested models. Journal of Econometrics 105 (1), 85110.

T. Clark and K. West (2007) Approximately normal tests for equal predictive accuracy in nested models. Journal of Econometrics 138 (1), 291311.

R. Davies (1987) Hypothesis testing when a nuisance parameter is present only under the alternative. Biometrika 74 (1), 3343.

F. Diebold and R. Mariano (1995) Comparing predictive accuracy. Journal of Business & Economic Statistics 13 (3), 253263.

F. X. Diebold and G. D. Rudebusch (1991) Forecasting output with the composite leading index: A real-time analysis. Journal of the American Statistical Association 86 (415), 603610.

L. Ferrara , M. Marcellino and M. Mogliani (2015) Macroeconomic forecasting during the great recession: The return of non-linearity?. International Journal of Forecasting 31 (3), 664679.

P. H. Franses and D. van Dijk (2005) The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production. International Journal of Forecasting 21 (1), 87102.

M. Gertler and N. Kiyotaki (2010) Financial intermediation and credit policy in business cycle analysis. In B. M. Friedman and M. Woodford (eds.), Handbook of Monetary Economics, vol. 3, pp. 547599. Amsterdam, The Netherlands: Elsevier.

S. Gilchrist , V. Yankov , and E. Zakrajşek (2009) Credit market shocks and economic fluctuations: Evidence from corporate bond and stock markets. Journal of Monetary Economics 56 (4), 471493.

C. W. Granger (1969) Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37 (3), 424438.

R. J. Hyndman (1996) Computing and graphing highest density regions. American Statistician 50 (2), 120126.

U. Jermann and V. Quadrini (2012). Macroeconomic effects of financial shocks. American Economic Review 102 (1), 238271.

R. G. King and R. Levine (1993) Finance and growth: Schumpeter might be right. Quarterly Journal of Economics 108 (3), 717737.

K. Lahiri and J. G. Wang (1994) Predicting cyclical turning points with leading index in a markov switching model. Journal of Forecasting 13 (3), 245263.

R. Luukkonen , P. Saikkonen and T. Teräsvirta (1988) Testing linearity against smooth transition autoregressive models. Biometrika 75 (3), 491499.

M. Marcellino , J. H. Stock and M. W. Watson (2006) A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series. Journal of Econometrics 135 (1), 499526.

S. Mittnik and W. Semmler (2013) The real consequences of financial stress. Journal of Economic Dynamics and Control 37 (8), 14791499.

F. Schleer and W. Semmler (2015) Financial sector and output dynamics in the euro area: Non-linearities reconsidered. Journal of Macroeconomics 46, 235263.

J. Skalin and T. Teräsvirta (2002) Modeling asymmetries and moving equilibria in unemployment rates. Macroeconomic Dynamics 6 (2), 202241.

J. H. Stock and M. W. Watson (1989) New Indexes of Coincident and Leading Economic Indicators. NBER macroeconomics annual 4, 351409.

J. H. Stock and M. W. Watson (1999a) Business cycle fluctuations in US macroeconomic time series. In J. B. Taylor and M. Woodford (eds.), Handbook of Macroeconomics, vol. 1, pp. 364. Amsterdam, The Netherlands: Elsevier.

J. H. Stock and M. W. Watson (1999b) Forecasting inflation. Journal of Monetary Economics 44 (2), 293335.

T. Teräsvirta (1994) Specification, estimation, and evaluation of smooth transition autoregressive models. Journal of the American Statistical Association 89 (425), 208218.

T. Teräsvirta (1995) Modelling nonlinearity in US gross national product 1889–1987. Empirical Economics 20 (4), 577597.

T. Teräsvirta and H. Anderson (1992) Characterizing nonlinearities in business cycles using smooth transition autoregressive models. Journal of Applied Econometrics 7 (S1), S119S136.

C. Weise (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: 7 *
Loading metrics...

Abstract views

Total abstract views: 61 *
Loading metrics...

* Views captured on Cambridge Core between 9th June 2017 - 22nd July 2017. This data will be updated every 24 hours.