Forecasting with leading economic indicators - a non-linear approach

Timotej Jagric

Prague Economic Papers, 2003, vol. 2003, issue 1, 68-83

Abstract: 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 (search for similar items in EconPapers)
JEL-codes: C45 E37 (search for similar items in EconPapers)
Date: 2003
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Citations: View citations in EconPapers (4)

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DOI: 10.18267/j.pep.207

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