Polish macroeconomic indicators correlated-prediction with indicators of selected countries
Monika Hadas-Dyduch ()
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Monika Hadas-Dyduch: University of Economics in Katowice, Poland
A chapter in Proceedings of the 9th Professor Aleksander Zelias International Conference on Modelling and Forecasting of Socio-Economic Phenomena, 2015, vol. 1, pp 68-76 from Institute of Economic Research
The aim of this article is to provide an estimate of the unemployment rate on the basis of copyright model. Polish unemployment rate forecast, based on a model based on multiresolution analysis and selected macroeconomic indicators of different countries. A characteristic feature of the model is to divide the ranks into sub-series with the corresponding time-shifted and dependence prediction depend on other macroeconomic indicators of selected countries. The algorithm for the prediction of time series presenting macroeconomic indicators, based on neural networks and the wavelet analysis, wavelets Daubechies. However, the main feature of the algorithm is to divide the analyzed series into several partial under-series and prediction dependence of a number of other economic series with the appropriate sliding window of time.
Keywords: macroeconomic indicators; wavelets; unemployment rate (search for similar items in EconPapers)
JEL-codes: G10 G19 E00 (search for similar items in EconPapers)
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Persistent link: http://EconPapers.repec.org/RePEc:pes:ecchap:22
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