Hostname: page-component-586b7cd67f-dlnhk Total loading time: 0 Render date: 2024-11-23T16:56:35.293Z Has data issue: false hasContentIssue false

Modelling Cyclical Asymmetry in a Production Series Using Threshold Autoregressive Models

Published online by Cambridge University Press:  17 August 2016

Horst Kräger*
Affiliation:
Universität Mannheim
Get access

Summary

In recent years there is evidence in the literature that various time series like GNP or production may be nonlinear. In this paper the question is examined whether there are non-linearities in the net production index for the producing sector of the FRG. Three different non-linearity tests are applied on the stationary series and two exhibit clear nonlinearities. Therefore a SETAR-model was estimated and it was able to capture all the previous inherent non-linearities.

Résumé

Résumé

Ces dernières années ont vu apparaître dans la littérature de nombreuses preuves de la non-linéarité des séries temporelles telles que celles du PNB ou de la production. Dans cet article, nous cherchons à savoir s'il existe des non-linéarités dans l'indice de la production nette du secteur productif de la RFA. On applique 3 tests différents de non-linéarité sur les séries stationnaires et deux de celles-ci s'avèrent clairement non-linéaires. Un recours à l'estimation d'un modèle SETAR, permet de saisir différemment ces non-linéairités détectées à l'étape précédente.

Keywords

Type
Part IV: Time Series Analysis of Output and Employment
Copyright
Copyright © Université catholique de Louvain, Institut de recherches économiques et sociales 1992 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

(*)

Helpful comments of three anonymous referees are gratefully acknowledged.

References

REFERENCES

Ashley, R. A. and Patterson, D. M. (1989), Linear Versus Nonlinear Macroeconomics: A Statistical Test, International Economic Review, 30, pp. 685704.Google Scholar
Brock, W. A., Dechert, W. D. and Scheinkman, J. (1987), A Test for Independence Based on the Correlation Dimension, Working Paper, The University of Chicago, Department of Economics.Google Scholar
Brock, W. A. and Dechert, W. D. (1988), A General Test of Specification Tests: The Scaler Case, Proceedings of the Business and Economic Statistics Section of the American Statistical Association, pp. 7079.Google Scholar
Brock, W. A. and Sayers, C. L. (1988), Is the Business Cycle Characterized by Deterministic Chaos?, Journal of Monetary Economics, 22, pp. 7190.Google Scholar
Brock, W. A. and Malliaris, A. G. (1989), Differential Equations. Stability and Chaos in Dynamic Economics, Amsterdam, North Holland.Google Scholar
Chan, K. S. (1990), Percentage Points of Likelihood Ratio Tests for Threshold Autoregression, Technical Report No. 272, Department of Statistics, University of Chicago.Google Scholar
Chan, K. S. and Tong, H. (1990), On Likelihood Ratio Test for Threshold Autoregression, Journal of the Royal Statistical Society, B.Google Scholar
Fuller, W. A. (1976), Introduction to statistical times series, New York, Wiley.Google Scholar
Gabisch, G. and Lorenz, A. W. (1987), Business Cycle Theory. A Survey of Methods and Concepts, Berlin, Springer Verlag.Google Scholar
Hamilton, J. D. (1989), A new approach to the economic analysis of nonstationary time series and the business cycle, Econometrica, 57, pp. 357384.Google Scholar
Hsieh, D. (1989), Testing for Nonlinear Dependence in Daily Foreign Exchange Rates, Journal of Business, 62, No. 3, pp. 339369.Google Scholar
Hsieh, D. and Lebaron, B. (1990), Finite Sample Properties of the BDS-Statistic, Duke University, mimeo.Google Scholar
Keynes, J. M. (1936) The General Theory of Employment. Interest and Money, London, Macmillan.Google Scholar
Kräger, H. and Kugler, P. (1990), Non-Linearities in Foreign Exchange Markets: A Different Perspective, Paper presented at the European Meeting of the Econometric Society, Cambridge 1991.Google Scholar
Luukkonen, R., Saikkonen, P. and Terasvirta, T. (1988), Testing linearity against smooth transition autoregressive models, Biometrica, 75, pp. 491499.Google Scholar
R., Luukkonen and Teräsvirta, T. (1991), Testing Linearity of Economic Time Series against Cyclical Asymmetry, Annales d'Economie et de Statistique, 20/21, pp. 125142.Google Scholar
Neftci, S. N. (1984), Are Economic Time Series Asymmetric over the Business cycle?, Journal of Political Economy, 92, pp. 307328.Google Scholar
Petrucelli, J. D. (1990), A Comparison of Tests for SETAR-type Non-Linearity in Time Series, Journal of Forecasting, 9, pp. 2536.Google Scholar
Scheinkman, J. (1990), Nonlinearities in Economic Dynamics, The Economic Journal, 100 (Conference 1990), pp. 3348.Google Scholar
Teräsvirta T. and H. M. Anderson (1991), Modelling Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models, Discussion Paper 91-124, Department of Economics, University of California, San Diego.Google Scholar
Tong, H. and Lim, K. S. (1980), Threshold autoregression, limit cycles and cyclical data, Journal of Royal Statistical Society, B 42, pp. 245292.Google Scholar
Tong, H. (1983), Threshold models in non-linear time series analysis, Lecture Notes in Statistics, No 21, Heidelberg, Springer.Google Scholar
Tong, H. (1990), Nonlinear Time Series. A Dynamical System Approach, Oxford, Oxford University Press.Google Scholar