Diverging signals from economic uncertainty measures: Uncovering coherence through news narratives

The proliferation of economic uncertainty indicators —ranging from text-based indices like the Economic Policy Uncertainty (EPU) index to market-based measures such as the VIX and the ECB’s Country-Level Index of Financial Stress (CLIFS)— has enriched the analytical toolkit of economists and policymakers. Yet these indicators often diverge, sending conflicting signals about the state of uncertainty in the economy. This paper argues that such divergence is not a flaw but a feature: each indicator captures a distinct dimension of uncertainty. Using topic modeling techniques applied to national news corpora, we construct a taxonomy of uncertainty narratives across five European countries and classify episodes of divergence between the EPU and CLIFS indicators. Our findings reveal systematic patterns: EPU peaks are predominantly driven by political and institutional developments, CLIFS peaks by financial market stress and joint peaks by systemic crises. These results underscore the multidimensional nature of uncertainty and highlight the need for structured interpretative frameworks. By linking narrative content to indicator behavior, our approach offers a novel lens for understanding uncertainty dynamics and provides practical tools for researchers and policymakers navigating an increasingly complex informational environment.