Unemployment rates forecasts - Unobserved Component Models versus SARIMA Models in Central and Eastern European countries

Barbara Będowska-Sójka


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.
Author Barbara Będowska-Sójka (WIiGE / KE)
Barbara Będowska-Sójka,,
- Department of Econometrics
Journal seriesComparative Economic Research. Central and Eastern Europe, ISSN 1508-2008, e-ISSN 2082-6737, (B 15 pkt)
Issue year2017
Publication size in sheets0.8
Keywords in Englishunemployment rate, unobserved component, SARIMA models, forecasting accuracy
ASJC Classification2000 General Economics, Econometrics and Finance
URL https://www.degruyter.com/downloadpdf/j/cer.2017.20.issue-2/cer-2017-0014/cer-2017-0014.pdf
Languageen angielski
Score (nominal)15
Score sourcejournalList
ScoreMinisterial score = 15.0, 11-03-2020, ArticleFromJournal
Publication indicators WoS Citations = 1; Scopus SNIP (Source Normalised Impact per Paper): 2017 = 0.393
Citation count*3 (2020-09-23)
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