Unemployment Rates Forecasts – Unobserved Component Models Versus SARIMA Models In Central And Eastern European Countries

• Authors: Barbara Będowska-Sójka

Title variants

Prognozowanie stop bezrobocia – porównanie modeli SARIMA i modeli nieobserwowanych komponentów dla wybranych krajów Europy Środkowej i Wschodniej

• Languages of publication: EN

Abstracts

EN

In this paper we compare the accuracy of unemployment rates forecasts of eight Central and Eastern European countries. The unobserved component models and seasonal ARIMA models are used within a rolling short-term forecast experiment as an out-of-sample test of forecast accuracy. We find that unemployment rates present clear unconditional asymmetry in three out of eight countries. Half the cases there is no difference between forecasting accuracy of the methods used in the study. In the remaining, a proper specification of seasonal ARIMA model allows to generate better forecasts than from unobserved component models. The forecasting accuracy deteriorates in periods of rapid upward and downward movement and improves in periods of gradual change in the unemployment rates.

PL

W artykule porównano prognozy wskaźników stóp bezrobocia w ośmiu krajach Europy Środkowej i Wschodniej. Zastosowano modele nieobserwowanych komponentów i sezonowe modele ARIMA w przesuwanym oknie i postawiono prognozy krótkoterminowe weryfikowane na podstawie trafności prognozy spoza próby. Wykazano, że w przypadku trzech krajów stopa bezrobocia charakteryzuje się bezwarunkową asymetrią. Generalnie w przypadku stosowanych metod, dla połowy badanych szeregów nie znaleziono statystycznie istotnej różnicy w dokładności stawianych prognoz. W pozostałych przypadkach odpowiednio dobrany sezonowy model ARIMA pozwalał na postawienie lepszych prognoz. Ponadto wykazano, że trafność prognoz pogarsza się w okresach gwałtownych wzrostów i spadków stóp bezrobocia, a poprawia się w okresach nieznacznych zmian wielkości tego wskaźnika.

Keywords

EN

unemployment rate; unobserved component; SARIMA models; forecasting accuracy

PL

stopa bezrobocia; modele nieobserwowanych komponentów; modele SARIMA; trafność prognoz; stopa bezrobocia; modele nieobserwowanych komponentów; modele SARIMA; trafność prognoz

• Publisher: Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
• Journal: Comparative Economic Research. Central and Eastern Europe
• Year: 2017
• Volume: 20
• Issue: 2
• Pages: 91-107

Dates

published

2017-06-30

Contributors

author

Barbara Będowska-Sójka

• Poznan University of Economics and Business, Department of Econometrics

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Identifiers

DOI

10.1515/cer-2017-0014