Title: Ex-ante industry-based uncertainty network and the business cycle
Authors: Mattia Bevilacqua - London School of Economics (United Kingdom) [presenting]
Jozef Barunik - UTIA AV CR vvi (Czech Republic)
Robert Faff - University of Queensland (Australia)
Abstract: A forward-looking measure of uncertainty network connectedness for the US industries is developed through a time-varying parameter VAR (TVP VAR) model. Our measure is constructed from options investors' expectations about the next month uncertainty of the US industries. We rank the dynamics of each industry uncertainty based on the contribution to the whole system and in relation to the business cycle in a dynamic way. We uncover a predominant role for communications, industrials and information technology industries in terms of uncertainty propagation mechanism throughout the cycles, being these denoted as "uncertainty hubs". Other industries such as materials, real estate and utilities are classifiable as "uncertainty not-hubs". We detect the ex-ante network of uncertainty as a useful predictor of business cycles and macroeconomic indicators, showing even greater predictive ability when extracted from uncertainty hubs only.