Looking into the black box of boosting: the case of Germany

Robert Lehmann and Klaus Wohlrabe

Munich Reprints in Economics from University of Munich, Department of Economics

Abstract: This article looks into the fine print' of boosting for economic forecasting. By using German industrial production for the period from 1996 to 2014 and a data set consisting of 175 monthly indicators, we evaluate which indicators get selected by the boosting algorithm over time and four different forecasting horizons. It turns out that a number of hard indicators like turnovers, as well as a small number of survey results, get selected frequently by the algorithm and are therefore important to forecasting the performance of the German economy. However, there are indicators such as money supply that never get chosen by the boosting approach at all.

Date: 2016
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Citations: View citations in EconPapers (18)

Published in Applied Economics Letters 17 23(2016): pp. 1229-1233

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Related works:
Journal Article: Looking into the black box of boosting: the case of Germany (2016)
Working Paper: Looking into the Black Box of Boosting: The Case of Germany (2015)
Working Paper: Looking into the Black Box of Boosting: The Case of Germany (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:lmu:muenar:43525

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