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Another Look at Swedish Business Cycles, 1861-1988

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  • Skalin, Joakim

    ()
    (Dept for Economic Affairs, Ministry of Finance)

  • Teräsvirta, Timo

    ()
    (Department of Economic Statistics)

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 Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 130.

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Length: 58 pages
Date of creation: Nov 1996
Date of revision:
Publication status: Published in Journal of Applied Econometrics, 1999, pages 359-378.
Handle: RePEc:hhs:hastef:0130

Note: This is the working paper version appearing in the References of the published version (Journal of Applied Econometrics 14, 359-378 (1999).
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Postal: The Economic Research Institute, Stockholm School of Economics, P.O. Box 6501, 113 83 Stockholm, Sweden
Phone: +46-(0)8-736 90 00
Fax: +46-(0)8-31 01 57
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Web page: http://www.hhs.se/
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Related research

Keywords: Granger causality; model spectrum; linearity test; time series model; nonlinearity; smooth transition autoregression;

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References

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  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
  6. 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.
  7. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
  8. Daniel E. Sichel, 1989. "Business cycle asymmetry: a deeper look," Working Paper Series / Economic Activity Section 93, Board of Governors of the Federal Reserve System (U.S.).
  9. 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.
  10. 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.
  11. 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.
  12. 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.
  13. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-38, July.
  14. 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.
  15. Stock, James H, 1987. "Measuring Business Cycle Time," Journal of Political Economy, University of Chicago Press, vol. 95(6), pages 1240-61, December.
  16. Stock, James H., 1987. "Measuring Business Cycle Time," Scholarly Articles 3425950, Harvard University Department of Economics.
  17. 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.
  18. Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, number 9780198283164, Octomber.
  19. Wesley Clair Mitchell, 1927. "Business Cycles: The Problem and Its Setting," NBER Books, National Bureau of Economic Research, Inc, number mitc27-1.
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Citations

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Cited by:
  1. 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.
  2. E Pavlidis & I Paya & D Peel, 2009. "Specifying Smooth Transition Regression Models in the Presence of Conditional Heteroskedasticity of Unknown Form," Working Papers 599040, Lancaster University Management School, Economics Department.
  3. Chen, Yi-Ting, 2003. "Discriminating between competing STAR models," Economics Letters, Elsevier, vol. 79(2), pages 161-167, May.
  4. Dijk, Dick van & Franses, Philip Hans, 1999. "Modeling Multiple Regimes in the Business Cycle," Macroeconomic Dynamics, Cambridge University Press, vol. 3(03), pages 311-340, September.
  5. 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.
  6. Nektarios Aslanidis, 2002. "Smooth Transition Regression Models in UK Stock Returns," Working Papers 0201, University of Crete, Department of Economics.
  7. 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.
  8. 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.
  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. 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.
  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. Röthig, Andreas & Chiarella, Carl, 2006. "Investigating nonlinear speculation in cattle, corn, and hog futures markets using logistic smooth transition regression models," Darmstadt Discussion Papers in Economics 36774, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute of Economics (VWL).
  13. Nektarios Aslanidis, 2002. "Regime-switching behaviour in European," Working Papers 0202, University of Crete, Department of Economics.
  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. 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.

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