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Using newspapers for tracking the business cycle: a comparative study for Germany and Switzerland

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  • David Iselin
  • Boriss Siliverstovs

Abstract

The use of news-based data for tracking the real economy has gained popularity recently as newspapers archives have become accessible and the need for timely information has soared. In this article, on the basis of keyword searches in newspaper articles we construct several versions of the so-called Recession-word Index (RWI) for Germany and Switzerland and exploit its use for forecasting. Our main findings are the following. First, we show that augmenting benchmark autoregressive models with the RWI leads to improvement in accuracy of one-step-ahead forecasts of GDP growth compared with those obtained by benchmark models. Second, the accuracy of out-of-sample forecasts obtained with models augmented with the RWI is comparable to that of models augmented with established economic indicators, such as the Ifo Business Climate Index and the ZEW Indicator of Economic Sentiment for Germany, and the KOF Economic Barometer and the Purchasing Managers Index in manufacturing for Switzerland. Our results are robust to changes in estimation/forecast samples, the use of rolling versus expanding estimation windows and the inclusion of a web-based recession indicator from Google Trends. As our indices are timely and simple to construct, they could be replicated in countries or regions where no reliable economic indicators exist or their provision is very costly.

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  • David Iselin & Boriss Siliverstovs, 2016. "Using newspapers for tracking the business cycle: a comparative study for Germany and Switzerland," Applied Economics, Taylor & Francis Journals, vol. 48(12), pages 1103-1118, March.
  • Handle: RePEc:taf:applec:v:48:y:2016:i:12:p:1103-1118
    DOI: 10.1080/00036846.2015.1093085
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    References listed on IDEAS

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    1. Nikolaos Askitas & Klaus F. Zimmermann, 2009. "Google Econometrics and Unemployment Forecasting," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 55(2), pages 107-120.
    2. David Iselin & Boriss Siliverstovs, 2013. "The R-word index for Switzerland," Applied Economics Letters, Taylor & Francis Journals, vol. 20(11), pages 1032-1035, July.
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    Cited by:

    1. Radoslaw Sobko & Maria Klonowska-Matynia, 2021. "The Relationship between the Purchasing Managers’ Index (PMI) and Economic Growth: The Case for Poland," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 198-219.
    2. Petar Soric & Ivana Lolic, 2017. "Economic uncertainty and its impact on the Croatian economy," Public Sector Economics, Institute of Public Finance, vol. 41(4), pages 443-477.
    3. Claveria, Oscar & Monte, Enric & Torra, Salvador, 2020. "Economic forecasting with evolved confidence indicators," Economic Modelling, Elsevier, vol. 93(C), pages 576-585.
    4. Heilemann Ullrich & Schnorr-Bäcker Susanne, 2017. "Could the start of the German recession 2008–2009 have been foreseen? Evidence from Real-Time Data," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 237(1), pages 29-62, February.
    5. Oscar Claveria & Enric Monte & Salvador Torra, 2021. "“Nowcasting and forecasting GDP growth with machine-learning sentiment indicators”," AQR Working Papers 202101, University of Barcelona, Regional Quantitative Analysis Group, revised Feb 2021.

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