Assessing the External Demand of the Czech Economy: Nowcasting Foreign GDP Using Bridge Equations

Tomas Adam and Filip Novotný

Working Papers from Czech National Bank, Research and Statistics Department

Abstract: We propose an approach to nowcasting foreign GDP growth rates for the Czech economy. For presentational purposes, we focus on three major trading partners: Germany, Slovakia and France. We opt for a simple method which is very general and which has proved successful in the literature: the method based on bridge equation models. A battery of models is evaluated based on a pseudo-real-time forecasting exercise. The results for Germany and France suggest that the models are more successful at backcasting, nowcasting and forecasting than the naive random walk benchmark model. At the same time, the various models considered are more or less successful depending on the forecast horizon. On the other hand, the results for Slovakia are less convincing, possibly due to the stability of the GDP growth rate over the evaluation period and the weak relationship between GDP growth rates and monthly indicators in the training sample.

Keywords: Bayesian model averaging; bridge equations; nowcasting; short-term forecasting (search for similar items in EconPapers)
JEL-codes: C53 E37 (search for similar items in EconPapers)
Date: 2018-12
New Economics Papers: this item is included in nep-for, nep-mac and nep-tra
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.cnb.cz/export/sites/cnb/en/economic-re ... wp/cnbwp_2018_18.pdf

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cnb:wpaper:2018/18

Access Statistics for this paper

More papers in Working Papers from Czech National Bank, Research and Statistics Department Contact information at EDIRC.
Bibliographic data for series maintained by Tomas Karhanek ().