Evaluating Uncertainty Measures: An Empirical Analysis

Evaluating Uncertainty Measures: An Empirical Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Evaluating Uncertainty Measures: An Empirical Analysis Jesús Vázquez, Luis Herrera This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6589297/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This paper contributes to the literature on economic uncertainty by evaluating and comparing structural uncertainty indices, derived from estimated DSGE models, with a wide array of popular non-structural uncertainty measures. Specifically, we estimate seven structural uncertainty indicators from medium-scale DSGE models and assess their empirical properties relative to commonly used non-structural uncertainty metrics such as forecast dispersion, conditional volatility of forecast errors, news-based indices, and affine-model term premiums. We document strong countercyclicality and persistence across most uncertainty measures, with structural DSGE-based indices effectively capturing patterns seen in non-structural measures but also providing valuable insights into the underlying sources of uncertainty, particularly regarding financial frictions and expectation-driven distortions. Our findings underscore the complementary roles of structural and non-structural measures in macroeconomic uncertainty assessment, highlighting the potential of DSGE-based uncertainty indicators to inform policy analysis and deepen our understanding of uncertainty dynamics. JEL classification: D84, E30, E40 Uncertainty measures term premiums bounded rationality DSGE models Bayesian estimation. Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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