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Autor
Lenart Łukasz (Cracow University of Economics, Poland / Wydział Finansów i Prawa)
Tytuł
Examination of Seasonal Volatility in HICP for Baltic Region Countries : Non-Parametric Test versus Forecasting Experiment
Źródło
Central European Journal of Economic Modelling and Econometrics (CEJEME), 2017, vol. 9, nr 1, s. 29-67, rys., tab., aneks, bibliogr. 34 poz.
Słowa kluczowe
Wahania sezonowe w gospodarce, Statystyka nieparametryczna, Prognozowanie cen, Zharmonizowany wskaźnik cen konsumpcyjnych
Seasonal fluctuations in the economy, Nonparametric statistics, Prediction of prices, Harmonised Index of Consumer Prices (HICP)
Uwagi
summ.; Klasyfikacja JEL: C32, C53, E31, E37
Kraj/Region
Kraje bałtyckie
Baltic countries
Abstrakt
The aim of this paper is to examine the problem of existing seasonal volatility in total and disaggregated HICP for Baltic Region countries (Denmark, Estonia, Latvia, Finland, Germany, Lithuania, Poland and Sweden). Using nonparametric tests, we found that in the case of m-o-m prices, including fruit, vegetables, and total HICP, the homogeneity of variance during seasons is rejected. Based on these findings, we propose an exponential smoothing model with periodic variance of error terms that capture the repetitive seasonal variation (in conditional or unconditional second moments). In a pseudo-real data experiment, the short-term forecasts (nowcasting) for the considered components of inflation were determined using different specifications of considered models. The forecasting performance of the models was measured using one of the scoring rules for probabilistic forecasts called logarithmic score. We found instead that while the periodic phenomenon in variance was statistically significant, the models with a periodic phenomenon in variance of error terms do not significantly improve forecasting performance in disaggregated cases and in the case of total HICP. The simpler models with constant variance of error term have comparative forecasting (nowcasting) performance over the alternative model. (original abstract)
Dostępne w
Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie
Biblioteka Szkoły Głównej Handlowej w Warszawie
Biblioteka Główna Uniwersytetu Ekonomicznego w Poznaniu
Pełny tekst
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Bibliografia
Pokaż
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  11. Franses P.H., Ooms M., (1997), A periodic long-memory model for quarterly UKinflation. International Journal of Forecasting 13, 117-126.
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  22. Lenart Ł., (2016), Detecting the Periodicity of Autocovariance Function for M-dependent Time Series by Graphical Method. Folia Oeconomica Cracovoensia 57, 19-36.
  23. Lenart Ł., Leszczyńska-Paczesna A., (2016), Do market prices improve the accuracy of inflation forecasting in Poland? A disaaggregated approach. Bank & Credit 47(5), 365-394.
  24. Lenart Ł., Pipień M., (2013), Seasonality Revisited - statistical Testing for Almost Periodically Correlated Stochastic Processes. Central European Journal of Economic Modelling and Econometrics 5(2), 85-102.
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Cytowane przez
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ISSN
2080-0886
Język
eng
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