Assessing the Real-Time Informational Content of Macroeconomic Data Releases for Now-/Forecasting GDP
Open access
Date
2010-01Type
- Working Paper
ETH Bibliography
yes
Altmetrics
Abstract
This study utilizes the dynamic factor model of Giannone et al. (2008) in order to make now-/forecasts of GDP quarter-on-quarter growth rates in Switzerland. It also assesses the informational content of macroeconomic data releases for forecasting of the Swiss GDP. We find that the factor model offers a substantial improvement in forecast accuracy of GDP growth rates compared to a benchmark naïve constant-growth model at all forecast horizons and at all data vintages. The largest forecast accuracy is achieved when GDP nowcasts for an actual quarter are made about three months ahead of the official data release. We also document that both business tendency surveys as well as stock market indices possess the largest informational content for GDP forecasting although their ranking depends on the underlying transformation of monthly indicators from which the common factors are extracted. Show more
Permanent link
https://doi.org/10.3929/ethz-a-005975867Publication status
publishedJournal / series
KOF Working PapersVolume
Publisher
KOF Swiss Economic Institute, ETH ZurichSubject
Real-time data; ECONOMETRICS AND ECONOMETRIC MODELS (OPERATIONS RESEARCH); GROSS NATIONAL PRODUCT; Dynamic factor model; BUSINESS FORECASTS; Nowcasting; BETRIEBSWIRTSCHAFTLICHE PROGNOSE; BRUTTONATIONALEINKOMMEN; SCHWEIZ (MITTELEUROPA). SCHWEIZERISCHE EIDGENOSSENSCHAFT; SWITZERLAND (CENTRAL EUROPE). SWISS CONFEDERATION; ÖKONOMETRIE UND ÖKONOMETRISCHE MODELLE (OPERATIONS RESEARCH); Forecasting; Business tendency surveysOrganisational unit
02525 - KOF Konjunkturforschungsstelle / KOF Swiss Economic Institute
More
Show all metadata
ETH Bibliography
yes
Altmetrics