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Another Look at Swedish Business Cycles, 1861-1988

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  • J. SKALIN
  • T. TERÄSVIRTA

Abstract

This paper considers nine long Swedish macroeconomic time series whose business cycle properties were discussed by Englund, Persson, and Svensson (1992) using frequency domain techniques. It is found by testing that all but two of the logarithmed and difference series are non-linear. The observed nonlinearity is characterized by STAR models. The statistical and dynamic properties of the estimated STAR models are investigated using, among other things, parametrically estimated ‘local’ or ‘sliced’ spectra. Cyclical variation at business cycle frequencies does not seem to be constant over time for all series, and it is difficult to find a ‘Swedish business cycle’. Only two series may be regarded as having genuinely assymetric cyclical variation. Standard Granger non-causality tests are adapted to the nonlinear (STAR) case, and the null hypothesis of noncausality is tested for pairs of series. The results point at strong temporal interactions between series. They also indicate that the assumption of functional form (linear or STAR) strongly affects the outcome of these pairwise tests.

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Bibliographic Info

Paper provided by Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes in its series SFB 373 Discussion Papers with number 1996,96.

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Date of creation: 1996
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Handle: RePEc:zbw:sfb373:199696

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References

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  1. Sichel, Daniel E, 1993. "Business Cycle Asymmetry: A Deeper Look," Economic Inquiry, Western Economic Association International, vol. 31(2), pages 224-36, April.
  2. Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, number 9780198283164.
  3. Bell, David & Kay, Jim & Malley, Jim, 1996. "A non-parametric approach to non-linear causality testing," Economics Letters, Elsevier, vol. 51(1), pages 7-18, April.
  4. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
  5. Zivot, Eric & Andrews, Donald W K, 1992. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 251-70, July.
  6. Eitrheim, Øyvind & Teräsvirta, Timo, 1995. "Testing the Adequacy of Smooth Transition Autoregressive Models," Working Paper Series in Economics and Finance 56, Stockholm School of Economics.
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  8. Raj, Baldev, 1992. "International Evidence on Persistence in Output in the Presence of an Episodic Change," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(3), pages 281-93, July-Sept.
  9. Perron, P, 1988. "The Great Crash, The Oil Price Shock And The Unit Root Hypothesis," Papers 338, Princeton, Department of Economics - Econometric Research Program.
  10. Hiemstra, Craig & Jones, Jonathan D, 1994. " Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-64, December.
  11. Geweke, John, 1984. "Inference and causality in economic time series models," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 19, pages 1101-1144 Elsevier.
  12. Stock, James H, 1987. "Measuring Business Cycle Time," Journal of Political Economy, University of Chicago Press, vol. 95(6), pages 1240-61, December.
  13. Balke, Nathan S & Fomby, Thomas B, 1994. "Large Shocks, Small Shocks, and Economic Fluctuations: Outliers in Macroeconomic Time Series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(2), pages 181-200, April-Jun.
  14. Neftci, Salih N, 1984. "Are Economic Time Series Asymmetric over the Business Cycle?," Journal of Political Economy, University of Chicago Press, vol. 92(2), pages 307-28, April.
  15. John Hassler & Petter Lundvik & Torsten Persson & Paul Soderlind, 1992. "The Swedish business cycle: stylized facts over 130 years," Discussion Paper / Institute for Empirical Macroeconomics 63, Federal Reserve Bank of Minneapolis.
  16. Terasvirta, T & Anderson, H M, 1992. "Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages S119-36, Suppl. De.
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Cited by:
  1. van Dijk, D.J.C. & Franses, Ph.H.B.F., 1997. "Modelling Multiple Regimes in the Business Cycle," Econometric Institute Research Papers EI 9734/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  2. Pavlidis Efthymios G & Paya Ivan & Peel David A, 2010. "Specifying Smooth Transition Regression Models in the Presence of Conditional Heteroskedasticity of Unknown Form," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(3), pages 1-40, May.
  3. Tiwari, Aviral Kumar & Dar, Arif Billah & Bhanja, Niyati, 2013. "Oil price and exchange rates: A wavelet based analysis for India," Economic Modelling, Elsevier, vol. 31(C), pages 414-422.
  4. Nektarios Aslanidis, 2002. "Smooth Transition Regression Models in UK Stock Returns," Working Papers 0201, University of Crete, Department of Economics.
  5. van Dijk, D.J.C. & Terasvirta, T. & Franses, Ph.H.B.F., 2000. "Smooth transition autoregressive models - A survey of recent developments," Econometric Institute Research Papers EI 2000-23/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  6. Skalin, Joakim & Teräsvirta, Timo, 1998. "Modelling asymmetries and moving equilibria in unemployment rates," Working Paper Series in Economics and Finance 262, Stockholm School of Economics, revised 05 Oct 1998.
  7. Singh, Tarlok, 2014. "On the regime-switching and asymmetric dynamics of economic growth in the OECD countries," Research in Economics, Elsevier, vol. 68(2), pages 169-192.
  8. Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2012. "The Out-of-Sample Forecasting Performance of Non-Linear Models of Regional Housing Prices in the US," Working Papers 1209, University of Nevada, Las Vegas , Department of Economics.
  9. Escribano, A. & Franses, Ph.H.B.F. & van Dijk, D.J.C., 1998. "Nonlinearities and outliers: robust specification of STAR models," Econometric Institute Research Papers EI 9832, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  10. Nektarios Aslanidis, 2002. "Regime-switching behaviour in European," Working Papers 0202, University of Crete, Department of Economics.
  11. Q. Farooq Akram & Øyvind Eitrheim & Lucio Sarno, 2005. "Non-linear dynamics in output, real exchange rates and real money balances: Norway, 1830-2003," Working Paper 2005/2, Norges Bank.
  12. Chen, Yi-Ting, 2003. "Discriminating between competing STAR models," Economics Letters, Elsevier, vol. 79(2), pages 161-167, May.
  13. Andreas Röthig & Carl Chiarella, 2006. "Investigating Nonlinear Speculation in Cattle, Corn and Hog Futures Markets Using Logistic Smooth Transition Regression Models," Research Paper Series 172, Quantitative Finance Research Centre, University of Technology, Sydney.
  14. Sahin, Afsin, 2013. "Estimating Money Demand Function by a Smooth Transition Regression Model: An Evidence for Turkey," MPRA Paper 46851, University Library of Munich, Germany.
  15. Mark J.Holmes, 2002. "Are there non linearities in US: Latin American real exchange behavior," Estudios de Economia, University of Chile, Department of Economics, vol. 29(2 Year 20), pages 177-190, December.

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