Work in Progress
"Identifying Macro and Financial Uncertainty in a Long-Run Risk Framework."
Abstract: This paper analyzes the different roles of real economic and financial market volatility in driving asset prices. By extending the Long-Run Risk (LRR) framework into a Bayesian state-space model, I decompose aggregate uncertainty into two components: Macro Uncertainty, derived from industrial production dynamics; and Financial Uncertainty, derived from excess market returns. Using a Bayesian estimation strategy via Hamiltonian Monte Carlo (HMC) on monthly U.S. data from 1994 to 2024, I find evidence that these uncertainty sources are distinguishable. Macro uncertainty tracks real business cycles, whereas financial uncertainty shows independent spikes during periods of high financial stress. The estimation results also show that asset valuations are mainly affected by financial uncertainty, while the direct impact of macro uncertainty on asset valuations is statistically insignificant.