EconPapers    
Economics at your fingertips  
 

Forecasting Baden‐Württemberg's GDP growth: MIDAS regressions versus dynamic mixed‐frequency factor models

Konstantin Kuck and Karsten Schweikert

Journal of Forecasting, 2021, vol. 40, issue 5, 861-882

Abstract: Germany's economic composition is heterogenous across regions, which makes regional economic projections based on German gross domestic product (GDP) growth unreliable. In this paper, we develop forecasting models for Baden‐Württemberg's economic growth, a regional economy that is dominated by small‐ and medium‐sized enterprises with a strong focus on foreign trade. For this purpose, we evaluate the backcasting and nowcasting performance of mixed data sampling (MIDAS) regressions with forecast combinations against an approximate dynamic mixed‐frequency factor model. Considering a wide range of regional, national, and global predictors, we find that our high‐dimensional models outperform benchmark time series models. Surprisingly, we also find that combined forecasts based on simple single‐predictor MIDAS regressions are able to outperform forecasts from more sophisticated dynamic factor models.

Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

Downloads: (external link)
https://doi.org/10.1002/for.2743

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:wly:jforec:v:40:y:2021:i:5:p:861-882

Access Statistics for this article

Journal of Forecasting is currently edited by Derek W. Bunn

More articles in Journal of Forecasting from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley Content Delivery ().

 
Page updated 2025-03-20
Handle: RePEc:wly:jforec:v:40:y:2021:i:5:p:861-882