Measuring Financial Conditions using Equal Weights Combination
Simone Arrigoni,
Alina Bobasu () and
Fabrizio Venditti
Additional contact information
Alina Bobasu: European Central Bank
IMF Economic Review, 2022, vol. 70, issue 4, No 2, 668-697
Abstract:
Abstract In this paper, we assess the merits of financial condition indices (FCIs) constructed using equal weights averaging versus alternatives that use data reduction techniques, like principal components, or that allow for time-varying parameters. Our analysis is based on data for 18 advanced and emerging economies at the monthly frequency covering about 70% of the world’s GDP. We study the performance of these indicators based on their ability to capture tail risk for economic activity and to predict banking and currency crises. We find that averaging with equal weights produces FCIs that are not inferior to, and often perform better than, those constructed with more sophisticated statistical methods. For the USA and for the euro area, based on the same evaluation criteria, they also work better than two popular alternatives that receive wide attention in policy discussions, namely the Chicago Fed National Financial Conditions Index and the Composite Index of Systemic Stress.
JEL-codes: C11 C55 E32 E44 (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://link.springer.com/10.1057/s41308-022-00170-y Abstract (text/html)
Access to full text is restricted to subscribers.
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:pal:imfecr:v:70:y:2022:i:4:d:10.1057_s41308-022-00170-y
Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/41308/PS2
DOI: 10.1057/s41308-022-00170-y
Access Statistics for this article
More articles in IMF Economic Review from Palgrave Macmillan, International Monetary Fund
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().