Computational Economics

, Volume 43, Issue 2, pp 183–197 | Cite as

Forecasting Spanish Unemployment Using Near Neighbour and Neural Net Techniques



In this paper, alternative non-parametric forecasting techniques are analysed, with emphasis placed on the difference between the reconstruction and learning approaches. The former is based on Takens’ Theorem, which recovers unknown dynamic properties of a system; it is appropriate in deterministic systems. The latter is a powerful instrument in noisy systems. Both techniques are applied to the forecasting of Spanish unemployment, first one step -forecasting and second using a longer time horizon of prediction. To assess the robustness and generality of the methods we have employed unemployment time series of different European countries.


Forecasting Neural networks Unemployment Nonlinearity 

JEL Classification

B41 C14 C32 C45 C51 C53 


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Departamento de Economía Aplicada IUniversidad de SevillaSevillaSpain

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