Unemployment rates forecasts - Unobserved Component Models versus SARIMA Models in Central and Eastern European countries
AbstractIn 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.
|Journal series||Comparative Economic Research. Central and Eastern Europe, ISSN 1508-2008, e-ISSN 2082-6737, (B 15 pkt)|
|Publication size in sheets||0.8|
|Keywords in English||unemployment rate, unobserved component, SARIMA models, forecasting accuracy|
|Score||= 15.0, 11-03-2020, ArticleFromJournal|
|Publication indicators||= 1; : 2017 = 0.393|
|Citation count*||3 (2020-09-23)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.