caa a22 4500 378868462 CHVBK 20180305123403.0 cr unu---uuuuu 161128e20030701xx s 000 0 eng 10.2202/1558-3708.1135 doi (NATIONALLICENCE)gruyter-10.2202/1558-3708.1135 Jagric Timotej 1 timotej.jagric@uni-mb.si A Nonlinear Approach to Forecasting with Leading Economic Indicators [Elektronische Daten] [Timotej Jagric] The classical NBER leading indicators model was built solely within a linear framework. With recent developments in nonlinear time-series analysis, several authors have begun to examine the forecasting properties of nonlinear models in the field of forecasting business cycles. The research presented in this paper focuses on the development of a new approach to forecasting with leading indicators based on neural networks. Empirical results are presented for forecasting the Index of Industrial Production. The results demonstrate that a superior performance can be obtained relative to the classical model. ©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston Studies in Nonlinear Dynamics & Econometrics De Gruyter 7/2(2003-07-01) 7:2 2003 7 snde https://doi.org/10.2202/1558-3708.1135 text/html Onlinezugriff via DOI 1 research article jats NATIONALLICENCE 856 40 https://doi.org/10.2202/1558-3708.1135 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Jagric Timotej 1 timotej.jagric@uni-mb.si NATIONALLICENCE 773 0- Studies in Nonlinear Dynamics & Econometrics De Gruyter 7/2(2003-07-01) 7:2 2003 7 snde CC0 http://creativecommons.org/publicdomain/zero/1.0 nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-gruyter