Modelling and forecasting unemployment non-linear dynamics using spectral analysis

Abstract

Changes in the unemployment in Croatia are largely permanent. However, transitory movements account for most of the unemployment dynamics after 2008. Unemployment series is non-stationary but mean-reversing, non-linear with structural breaks and significant white and red-noise in the data. This paper estimates Multivariate singular spectrum model (MSSA) to explain overall fluctuations in unemployment registered during 1998–2013. Unemployment behaviour in Croatia shows evidence of cyclo-stationarity caused by seasonal employment effects. We use 88 time series (variable) to explain observed fluctuations with our MSSA model explaining 76 % of the total unemployment variance comprehensively. Evidence of this study demonstrates that unemployment phenomena should be modelled by using a non-linear model with multivariate singular spectrum models giving more robust and empirically valid results in relation to standard modelling techniques. A 5–6 years limit cycle for unemployment is isolated dominating unemployment behaviour in Croatia over the last two decades1.