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Forecasting GDP All Over the World Using Leading Indicators Based on Comprehensive Survey Data A Service of Leibniz-Informationszentrum econstor Wirtschaft Leibniz Information Centre Make Your Publications Visible. zbw for Economics Garnitz, Johanna; Lehmann, Robert; Wohlrabe, Klaus Article — Published Version Forecasting GDP all over the world using leading indicators based on comprehensive survey data Applied Economics Provided in Cooperation with: Ifo Institute – Leibniz Institute for Economic Research at the University of Munich Suggested Citation: Garnitz, Johanna; Lehmann, Robert; Wohlrabe, Klaus (2019) : Forecasting GDP all over the world using leading indicators based on comprehensive survey data, Applied Economics, ISSN 1466-4283, Routledge, London, Vol. 51, Iss. 54, pp. 5802-5816, http://dx.doi.org/10.1080/00036846.2019.1624915 This Version is available at: http://hdl.handle.net/10419/224966 Standard-Nutzungsbedingungen: Terms of use: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Documents in EconStor may be saved and copied for your Zwecken und zum Privatgebrauch gespeichert und kopiert werden. personal and scholarly purposes. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle You are not to copy documents for public or commercial Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich purposes, to exhibit the documents publicly, to make them machen, vertreiben oder anderweitig nutzen. publicly available on the internet, or to distribute or otherwise use the documents in public. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, If the documents have been made available under an Open gelten abweichend von diesen Nutzungsbedingungen die in der dort Content Licence (especially Creative Commons Licences), you genannten Lizenz gewährten Nutzungsrechte. may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc-nd/4.0/ www.econstor.eu APPLIED ECONOMICS 2019, VOL. 51, NO. 54, 5802–5816 https://doi.org/10.1080/00036846.2019.1624915 Forecasting GDP all over the world using leading indicators based on comprehensive survey data Johanna Garnitza, Robert Lehmann a,b and Klaus Wohlrabe a,b aifo Institute – Leibniz-Institute for Economic Research at the University of Munich e.V., Munich, Germany; bCESifo, Munich, Germany ABSTRACT KEYWORDS Comprehensive and international comparable leading indicators across countries and continents World economic survey; are rare. In this paper, we use a free and instantaneous available source of leading indicators, the Economic Climate; ifo World Economic Survey (WES), to forecast growth of Gross Domestic Product (GDP) in 44 Forecasting GDP countries and three country aggregates separately. We come up with three major results. First, for JEL CLASSIFICATION more than three-fourths of the countries or country-aggregates in our sample, a model contain- E17; E27; E37 ing one of the major WES indicators produces on average lower forecast errors compared to a benchmark model. Second, the most important WES indicators are either the economic climate or the expectations on future economic development for the next six months. And third, adding the WES indicators of the main trading partners leads to a further increase in forecast accuracy in more than 50% of the countries. It seems therefore reasonable to incorporate economic signals from the domestic economy’s main trading partners. I. Introduction the European Commission’s Joint Harmonised EU Programme of Business and Consumer Surveys Macroeconomic projections based on leading indica- (BCS) and the Composite Leading Indicator tors is a widely accepted approach when it comes to (CLI) of the OECD. Whereas the first two are practical forecasting or by looking at the correspond- solely business or consumer surveys, the CLIs of ing scientific literature. Especially survey indicators the OECD are also based on several hard indica- have often been proved to be very good predictors tors. The PMI covers more than 30 advanced and for the real economy (see, among others, Girardi, emerging economies using an identical question- Gayer, and Reuter 2016). Leading indicators, how- naire. The BCS ensures harmonized questions ever, crucially differ between countries, which makes across business and consumer surveys among a general statement on the usefulness of a specific almost all European countries. Unfortunately, group of leading indicators between countries nearly PMIs are not freely accessible for almost all coun- impossible. One freely available source of comparable tries and the CLIs have a publication lag of two qualitative indicators is the ifo World Economic months. The WES, in contrast, is freely available Survey (WES). In this paper, we use the main indica- to researchers1 and covers more than 100 coun- tors from this survey among economic experts to tries. Furthermore, the WES employs comparable evaluate their forecasting performance for gross questionnaires which allow us to formulate a domestic product (GDP) growth in 44 countries and statement on the WES forecasting performance three aggregates (EU-27, the Eurozone and a World across a large set of countries. aggregate). Up to date, a vast literature on country-specific There are only a few surveys with question- GDP forecasts exists that either focuses on methodo- naires that are comparable across countries. logical or data issues.2 A recent study for global GDP Three examples are the Purchasing Manager growth is the one by Ferrara and Marsilli (2019). Index (PMI) provided by Markit, indicators from CONTACT Robert Lehmann [email protected] ifo Institute – Leibniz-Institute for Economic Research at the University of Munich e.V., Poschingerstr. 5, D-81679, Munich, Germany 1Non-researchers, however, have to pay a small fee to access the data. 2See, for example, China: Zhou, Wang, and Tong (2013), France: Barhoumi, Darné, and Ferrara (2010), Germany: Drechsel and Scheufele (2012), Greece: Kiriakidis and Kargas (2013b), Spain: Pons-Novell (2006), Sweden: Österholm (2014), UK: Barnett, Mumtaz, and Theodoridis (2014), US: Banerjee and Marcellino (2006). © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc- nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. APPLIED ECONOMICS 5803 However, a comprehensive study for many countries economic situation, the expectations on future eco- using identical survey data to forecast national eco- nomic development for the next six months, and the nomic activity is missing. One exception is Fichtner, economic climate) and ask whether models contain- Rüffer, and Schnatz (2011) who investigate the fore- ing one of these indicators have a higher forecast casting properties of the OECD leading indicators for accuracy compared to an autoregressive benchmark. 11 countries. Lehmann (2015) and Lehmann and Our second contribution deals with the question Weyh (2016) use data from the BCS to forecast export whether national GDP forecasts can be improved by growth or employment growth for various European additionally using the WES survey results from the countries. country-specific most important trading partners. Despite the instantaneous and free availability, the Since business cycle synchronization between coun- WESsurveydatahaveonlybeenusedbyasmall tries rises the higher their trading intensity is (Inklaar, number of studies. Henzel and Wollmershäuser Jong-A-Pin, and de Haan 2008; Duval et al. 2016), one (2005) develop a new methodology to elicit inflation can suggest that country-specific forecast accuracy of expectations from the WES. For 43 countries and two GDP can be increased by adding WES indicators from country aggregates, the paper by Kudymowa, Plenk, economically important countries.3 Our results indi- and Wohlrabe (2013) assesses the in-sample perfor- cate that the WES indicators have a higher forecast mance of the WES economic climate as a business accuracy compared to the benchmark model in more cycle indicator. They find strong cross-correlations than three-fourths of countries or country-aggregates between the WES indicators and country-specific and forecast horizons; concerning the nowcast situa- year-on-year growth rates in real GDP. Thus, the tion, the WES indicators are better in 45 of our 47 climate indicator can be used to assess the state of countries or aggregates. Only for Switzerland and the economy or even upcoming future economic Indonesia the WES indicators cannot improve GDP development. The relevant literature for our purpose, forecasts over the benchmark. Adding the WES indi- namely the studies that focus on forecasting issues, is cators from a country’s main trading partners further also very scarce. For Euro Area real GDP, Hülsewig, increases the forecast accuracy in more than 50% of Mayr, and Wollmershäuser (2008)usethreebusiness countries and forecast horizons; the largest improve- cycle indicators and ask whether the optimal pooling ment – with more than 70% of the countries in the of nationwide information of these indicators help to sample – can again be observed by forecasting the increase forecast accuracy of the European aggregate. current quarter. Thus, relying on economic signals They find an improvement in their
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