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.
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