Prague Economic Papers 2003, 12(1):68-83 | DOI: 10.18267/j.pep.207

Forecasting with leading economic indicators - a non-linear approach

Timotej Jagric
Faculty of Economics and Business, University of Maribor, Slovenia, Razlagova 14, 2000 Maribor, Slovenia (e-mail: timotej.jagric@uni-mb.si).

Leading economic indicators have a long tradition in forecasting future economic activity. Recent developments, however, suggest that there is scope for adding extensions to the methodology of forecasting major economic fluctuations. In this paper, the author tries to develop a new model, which would outperform the forecast accuracy of classical leading indicators model. The use of artificial neural networks is proposed here. For demonstration a case study for Slovene economy is included. The main finding is that, at the twelve months forecasting horizon, a stable and improved forecast accuracy could be achieved for in- and out-of-sample data.

Keywords: leading economic indicators, neural network, forecasting, aggregate economic activity
JEL classification: C45, E37

Published: January 1, 2003  Show citation

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Jagric, T. (2003). Forecasting with leading economic indicators - a non-linear approach. Prague Economic Papers, 12(1), 68-83. doi: 10.18267/j.pep.207
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