Do media data help to predict German industrial production?

Konstantin Kholodilin (), Tobias Thomas and Dirk Ulbricht

No 149, DICE Discussion Papers from Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE)

Abstract: In an uncertain world, decisions by market participants are based on expectations. Thus, sentiment indicators reflecting expectations are proven at predicting economic variables. However, survey respondents largely perceive the world through media reports. Typically, crude media information, like word-count indices, is used in the prediction of macroeconomic and financial variables. Here, we employ a rich data set provided by Media Tenor International, based on sentiment analysis of opinion-leading media in Germany from 2001 to 2014, transformed into several monthly indices. German industrial production is predicted in a real-time out-of-sample forecasting experiment using more than 17,000 models formed of all possible combinations with a maximum of 3 out of 48 macroeconomic, survey, and media indicators. Media data are indispensable for the prediction of German industrial production both for individual models and as a part of combined forecasts, particularly during the global financial crisis.

Keywords: forecast combination; media data; German industrial production; reliability index; R-word (search for similar items in EconPapers)
JEL-codes: C10 C52 C53 E32 (search for similar items in EconPapers)
Date: 2014
New Economics Papers: this item is included in nep-eur, nep-for and nep-mac
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Citations: View citations in EconPapers (8)

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Related works:
Journal Article: Do Media Data Help to Predict German Industrial Production? (2017)
Working Paper: Do Media Data Help to Predict German Industrial Production? (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:dicedp:149

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