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Money and prices in the Polish economy. Seasonal cointegration approach

  • Jacek Kotlowski

    ()

    (Department of Applied Econometrics, Warsaw School of Economics)

The paper presents the analysis of the long run causality behaviour between money and prices in the Polish economy during the transition period. The study makes use of the monetary inflation model known as the P-star model, originally developed by the FED economists at the end of 80-ties. The research on the relationship between money and prices in the Polish economy carried out to date indicates that some variables (GDP, prices) show the irregular seasonal pattern. For this reason we propose to analyse the long run relationship between money and prices in the Polish economy by means of seasonal cointegration, developed by Hylleberg, Engle, Granger and You in the beginning of 90-ties. The main hypothesis has been verified positively. The results of the research give the evidence that there exists a long-run causality relationship between money and prices (long-run cointegration relationship), which follows the assumptions of the P-star inflation model. The results also indicate that there are no seasonal cointegrating relationships in the P-star inflation model, which can be interpreted as the money demand equations. This means that the quality of the inflation forecasts cannot be improved by applying the additional seasonal cointegrating relationships to this model.

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File URL: http://kolegia.sgh.waw.pl/pl/KAE/struktura/IE/struktura/ZES/Documents/Working_Papers/aewp03-05.pdf
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Paper provided by Department of Applied Econometrics, Warsaw School of Economics in its series Working Papers with number 20.

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Length: 29 pages
Date of creation: 22 May 2005
Date of revision:
Handle: RePEc:wse:wpaper:20
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  1. Barassi, Marco R. & Caporale, Guglielmo Maria & Hall, Stephen G., 2005. "Interest rate linkages: a Kalman filter approach to detecting structural change," Economic Modelling, Elsevier, vol. 22(2), pages 253-284, March.
  2. Svensson, Lars E O, 1999. "Does the P* Model Provide Any Rationale for Monetary Targeting?," CEPR Discussion Papers 2198, C.E.P.R. Discussion Papers.
  3. Lee, Hahn Shik, 1992. "Maximum likelihood inference on cointegration and seasonal cointegration," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 1-47.
  4. Franses, Ph.H.B.F. & Kunst, R.M., 1998. "On the role of seasonal intercepts in seasonal cointegration," Econometric Institute Research Papers EI 9820, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  5. James G. MacKinnon, 1995. "Numerical Distribution Functions for Unit Root and Cointegration Tests," Working Papers 918, Queen's University, Department of Economics.
  6. Cubadda, Gianluca & Omtzigt, Pieter, 2003. "Small Sample Improvements in the Statistical Analysis of Seasonally Cointegrated Systems," Economics & Statistics Discussion Papers esdp03012, University of Molise, Dept. EGSeI.
  7. Greenslade, Jennifer V. & Hall, Stephen G. & Henry, S. G. Brian, 2002. "On the identification of cointegrated systems in small samples: a modelling strategy with an application to UK wages and prices," Journal of Economic Dynamics and Control, Elsevier, vol. 26(9-10), pages 1517-1537, August.
  8. Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, vol. 55(2), pages 251-76, March.
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