Unemployment Rates Forecasts - Unobserved Component Models Versus SARIMA Models in Central and Eastern European Countries

• Autorzy: Barbara Będowska-Sójka

Warianty tytułu

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

• Języki publikacji: EN

Abstrakty

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. (original abstract)

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. (abstrakt oryginalny)

Słowa kluczowe

EN

Unemployment rate; Forecasting; SARIMA models

PL

Stopa bezrobocia; Prognozowanie; Modele SARIMA

• Czasopismo: Comparative Economic Research
• Rocznik: 2017
• Tom: 20
• Numer: nr 2
• Strony: 91--107

Twórcy

autor

Barbara Będowska-Sójka

• Poznań University of Economics and Business, Poland

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Identyfikatory

DOI

https://doi.org/10.1515/cer-2017-0014