Recession Prediction with OptimalUse of Leading Indicators

Heikki Kauppi
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Heikki Kauppi: University of Turku

No 125, Discussion Papers from Aboa Centre for Economics

Abstract: We use the gradient boosting estimation technique and the ROC curveto non-parametrically measure and exploit the maximal predictive powerof leading indicators for the future state of the business cycle. We de-velop novel procedures for finding the best performing transformationsof individual indicators, for combining them to form an optimal reces-sion prediction model and for assessing which predictors are contribut-ing in the model. Among our empirical findings with US data are thatthe predictive impact of various indicators is non-monotone and thatrecession predictions based on our nonparametric procedures clearlyoutperform the ones based on a conventional probit model.

Keywords: gradient boosting; leading indicators; non-parametric esti-mation; optimal binary prediction; recession prediction (search for similar items in EconPapers)
JEL-codes: C22 C25 C53 E37 (search for similar items in EconPapers)
Pages: 53
Date: 2019-04
New Economics Papers: this item is included in nep-mac
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