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Periodic Cointegration: Representation and Inference

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  • Boswijk, H Peter
  • Franses, Philip Hans

Abstract

This paper considers a new approach to the analysis of stable relationships between nonstationary seasonal time series. The basis of this approach is an error correction model in which both long-run effects and adjustment parameters are allowed to vary per season. First, we discuss theoretical arguments for such a periodic error correction model. We define periodic cointegration and compare this to the concept of seasonal cointegration. Next, we analyze statistical inference in the periodic error correction model. A sequential procedure is proposed, consisting of a test for periodic cointegration, an estimator of the cointegration parameters and adjustment coefficients, and a class of tests for the hypothesis that some of the parameters are constant over the seasons. The finite sample behavior of the proposed test statistics is analyzed in a limited Monte Carlo exercise. We conclude the paper with an application to a model of aggregate Swedish consumption. Copyright 1995 by MIT Press.

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Bibliographic Info

Article provided by MIT Press in its journal Review of Economics & Statistics.

Volume (Year): 77 (1995)
Issue (Month): 3 (August)
Pages: 436-54

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Handle: RePEc:tpr:restat:v:77:y:1995:i:3:p:436-54

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Web page: http://mitpress.mit.edu/journals/

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Cited by:
  1. Tomas del Barrio Castro & Mariam Camarero & Cecilio Tamarit, 2013. "An analysis of the trade balance for OECD countries using periodic integration and cointegration," Working Papers 1320, Department of Applied Economics II, Universidad de Valencia.
  2. Wells, J. M., 1997. "Modelling seasonal patterns and long-run trends in U.S. time series," International Journal of Forecasting, Elsevier, vol. 13(3), pages 407-420, September.
  3. Christiano, Lawrence J. & Todd, Richard M., 2002. "The conventional treatment of seasonality in business cycle analysis: does it create distortions?," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 335-364, March.
  4. Svend Hylleberg, 2006. "Seasonal Adjustment," Economics Working Papers 2006-04, School of Economics and Management, University of Aarhus.
  5. Tomas del Barrio Castro & Mariam Camarero & Cecilio Tamarit, 2013. "The trade balance in euro countries: a natural case study of periodic integration with a changing mean," Working Papers 1321, Department of Applied Economics II, Universidad de Valencia.
  6. Löf, M. & Franses, Ph.H.B.F., 2000. "On forecasting cointegrated seasonal time series," Econometric Institute Research Papers EI 2000-04/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  7. David R. Bell & Ronald C. Griffin, 2011. "Urban Water Demand with Periodic Error Correction," Land Economics, University of Wisconsin Press, vol. 87(3), pages 528-544.
  8. Dr. Godwin Chukwudum Nwaobi, 2004. "Modelling Economic Fluctuations In Subsaharan Africa:A Vector Autoregressive Approach," Macroeconomics 0406008, EconWPA.
  9. Bohl, Martin T., 2000. "Nonstationary stochastic seasonality and the German M2 money demand function," European Economic Review, Elsevier, vol. 44(1), pages 61-70, January.
  10. Novales, Alfonso & de Fruto, Rafael Flores, 1997. "Forecasting with periodic models A comparison with time invariant coefficient models," International Journal of Forecasting, Elsevier, vol. 13(3), pages 393-405, September.
  11. Albertson, Kevin & Aylen, Jonathan, 1999. "Forecasting using a periodic transfer function: with an application to the UK price of ferrous scrap," International Journal of Forecasting, Elsevier, vol. 15(4), pages 409-419, October.
  12. Evans, Mark, 2006. "A study of the relationship between regional ferrous scrap prices in the USA, 1958-2004," Resources Policy, Elsevier, vol. 31(2), pages 65-77, June.

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