Forecasting Inflation Components – Does it Help to Predict Polish Inflation?

Paweł Baranowski; Małgorzata Mazurek; Maciej Nowakowski; Marek Raczko

doi:https://doi.org/10.59139/ps.2010.01.2

Paweł Baranowski Uniwersytet Łódzki , Małgorzata Mazurek Uniwersytet Łódzki , Maciej Nowakowski Uniwersytet Łódzki , Marek Raczko Uniwersytet Łódzki Przegląd Statystyczny. Statistical Review, vol. 57, 2010, 1, pages: 17-33 Published online: 31 March 2010 DOI https://doi.org/10.59139/ps.2010.01.2

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ARTICLE

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ABSTRACT

This paper examines whether forecasting CPI components improves CPI forecast. We exploit quarterly data for Poland, disaggregated into 12 components. We follow methodology used in previous studies for Euro Area (Hubrich, 2005; Reijer and Vlaar, 2006). AR, MA, TAR and unrestricted VAR models are estimated using recursive sample and aggregated into CPI. Using out-of-sample forecasts, these models are evaluated and compared to the benchmark -- equivalents for aggregate CPI. The evidence is mixed. VAR component-forecast outperform benchmark. Contrary to VAR, for AR and TAR models we do not find substantial gain from using disaggregated data. Results for MA models are not robust. Moreover, it seems that results for AR- and VAR-based forecasts are comparable to consensus forecast.

KEYWORDS

forecasting, inflation, inflation components, sectoral aggregation, Poland

REFERENCES

[1] Akerlof G.A., [1970], The Market for “Lemons”: Quality Uncertainty and the Market Mechanism, „Quarterly Journal of Economics”, Vol. 84, No. 3.

[2] Aron J., Muelbauer J., [2008], New methods for forecasting inflation and its sub-components: application to the USA, „Department of Economics Discussion Paper”, No. 406, University of Oxford, http://www.economics.ox.ac.uk

[3] Basher S., Westerlund J., [2008], Is there really a unit root in the inflation rate? More evidence from panel data models, „Applied Economics Letters”, Vol. 15.

[4] Bates J., Granger C.W.J., [1969], On comparing macroeconomic forecast using forecast encompassing test, „Operational Research Quarterly”, Vol. 20.

[5] Blanchard O.J., Kiyotaki N., [1987], Monopolistic Competition and the Effects of Aggregate Demand, „American Economic Review”, Vol. 77, No. 4.

[6] Budnik K., Greszta M., Hulej M., Kolasa M., Murawski K., Rot M., Rybaczyk B., Tarnicka M., [2008], NECMOD: Presentation of the new forecasting model, NBP, www.nbp.pl

[7] Calvo G., [1983], Staggered Prices in a Utility Maximizing Framework, „Journal of Monetary Economics”, Vol. 12, No. 3.

[8] Cheung Y.-W., Lai K.S., [1995], Lag Order and Critical Values of the Augmented Dickey-Fuller Test, „Journal of Business and Economic Statistics”, Vol. 13, No. 3.

[9] Chien-Chang L., Chun-Ping Ch., [2007], Trend Stationary of Inflation Rates: Evidence from LM Unit Root Testing with a Long Span of Historical data, „Applied Economics”, Vol. 39.

[10] Diebold F.X., Mariano R.S., [1995], Comparing Predictive Accuracy, „Journal of Business and Economic Statistics”, Vol. 13, No. 3.

[11] Dhyne E., Alvarez L., Le Bihan H., Veronese G., Dias D., Hoffmann J., Jonker N., Lünnemann P., Rumler F., Vilmunen J., [2006], Price Changes in the Euro Area and the United States: Some Facts from Individual Consumer Price Data, „Journal of Economic Perspectives”, Vol. 20, No. 2.

[12] Enders W., [2004], Applied Econometric Time Series, John Wiley and Sons.

[13] Gregoriou A., Kontonikas A., [2006], Inflation targeting and the stationarity of inflation: new results from an ESTAR unit root test, „Bulletin of Economic Research”, Vol. 58, No. 4.

[14] Grajek M., [2002], Prognozy łączone, „Przegląd Statystyczny”, t. 49, nr 1.

[15] Greszta M., Maciejewski W., [2005], Kombinowanie prognoz gospodarki Polski, „Gospodarka Narodowa”, nr 5-6.

[16] Halunga A.G., Osborn D.R., Sensier M., [2009], Changes in order of integration of US and UK inflation, „Economic Letters”, Vol. 102, No. 1.

[17] Hendry D.F., Clements M.P., [2004], Pooling of forecasts, „Econometrics Journal”, Vol. 7.

[18] Hubrich K., [2005], Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?, „International Journal of Forecasting”, Vol. 21, No. 1.

[19] Jankiewicz Z., Kołodziejczyk D., [2008], Mechanizmy kształtowania cen w przedsiębiorstwach polskich na tle zachowań firm ze strefy euro, „Bank i Kredyt”, luty.

[20] Kokocińska M., Strzała K., [2007], Zintegrowany system oceny aktywności przedsiębiorstw i prognozowania kategorii makroekonomicznych, Wydawnictwo Akademii Ekonomicznej w Poznaniu, Poznań.

[21] Leith C., Malley J., [2007], A Sectoral Analysis of Price-Setting Behavior in U.S. Manufacturing Industries, „Review of Economics and Statistics”, Vol. 89, No. 2.

[22] Lütkepohl H., [2005], New Introduction to Multiple Time Series Analysis, Springer, Berlin etc.

[23] Lütkepohl H., (2009), Forecasting Aggregated Time Series Variables: A Survey, EUI Working Paper, No. 17.

[24] Marcellino M., Stock J.H., Watson M.W., [2003], Macroeconomic forecasting in the Euro area: Country specific versus area-wide information, „European Economic Review”, Vol. 47, No. 1.

[25] Narayan P.K., Narayan S., [2008], Is there a unit root in the inflation rate? New evidence from panel data models with multiple structural break, „Applied Economics”, Vol. 40.

[26] Reijer A., Vlaar P., [2006], Forecasting inflation: An art as well as science, „De Economist”, Vol. 154.

[27] Sztaudynger J.J., [2002], Prognozowanie cen, [w:] Milo W. (red.), Prognozowanie cen, Wydawnictwo UŁ, Łódź.

[28] Timmermann A., [2006], Forecast combination, [w:] Elliot G., Gragner C.W.J., Timmermann A. (red.), Handbook in Economic Forecasting, Elseiver.