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Forecasting Spanish Unemployment Using Near Neighbour and Neural Net Techniques

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Abstract

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.

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  1. Departamento de Economía Aplicada I, Universidad de Sevilla, Avda. Ramon y Cajal, Sevilla, 41018, Spain

    Elena Olmedo

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Olmedo, E. Forecasting Spanish Unemployment Using Near Neighbour and Neural Net Techniques. Comput Econ 43, 183–197 (2014). https://doi.org/10.1007/s10614-013-9371-1

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