Artikel
Forecasting GDP all over the world using leading indicators based on comprehensive survey data
Comprehensive and international comparable leading indicators across countries and continents are rare. In this paper, we use a free and instantaneous available source of leading indicators, the ifo World Economic Survey (WES), to forecast growth of Gross Domestic Product (GDP) in 44 countries and three country aggregates separately. We come up with three major results. First, for more than three-fourths of the countries or country-aggregates in our sample, a model containing 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.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Applied Economics ; ISSN: 1466-4283 ; Volume: 51 ; Year: 2019 ; Issue: 54 ; Pages: 5802-5816 ; London: Routledge
- Klassifikation
-
Wirtschaft
General Aggregative Models: Forecasting and Simulation: Models and Applications
Macroeconomics: Consumption, Saving, Production, Employment, and Investment: Forecasting and Simulation: Models and Applications
Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications
- Thema
-
World economic survey
Economic Climate
Forecasting GDP
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Garnitz, Johanna
Lehmann, Robert
Wohlrabe, Klaus
- Ereignis
-
Veröffentlichung
- (wer)
-
Routledge
- (wo)
-
London
- (wann)
-
2019
- DOI
-
doi:10.1080/00036846.2019.1624915
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Garnitz, Johanna
- Lehmann, Robert
- Wohlrabe, Klaus
- Routledge
Entstanden
- 2019
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