Modelling and Forecasting Unemployment Non-linear Dynamics Using Spectral Analysis

  • Marinko Skare Juraj Dobrila University of Pula
  • Vesna Buterin
Keywords: Multivariate singular spectrum analysis, Unemployment, Nonlinear, Persistence, Causality, Croatian disease, Partial Hysteresis, Spectral methods


Movements in the unemployment in Croatia are largely permanent but transitory movements accounts 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 show evidence of cyclostationarity caused by seasonal employment effects.  We use 88 time series (variable) to comprehensively explain observed fluctuations with our MSSA model explaining 76% of the total unemployment variance. Evidence of this study points that unemployment phenomena should be modelled by using 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 in unemployment is isolated dominating unemployment behaviour in Croatia over last two decades.