Essays in Bayesian macroeconometrics

The first chapter introduces a "theory-coherent" shrinkage prior for Time-Varying Parameters Vector Autoregressive (TVP-VAR) models. The Theory Coherent TVP-VAR (TC-TVP-VAR) significantly enhances inference precision and forecast accuracy over standard TVP-VAR models. This approach demonstrates superior predictive capabilities for GDP growth and inflation and provides more accurate impulse response analyses, especially in assessing the impacts of macroeconomic shocks during the Zero Lower Bound (ZLB) period. The second chapter proposes a VAR model with stochastic volatility and time-varying skewness, aimed at monitoring macroeconomic tail risks. It develops an MCMC sampler for Bayesian estimation of VARs with Skew-Normal and Skew-t shocks, featuring stochastic volatility and time-varying skewness. The chapter shows that these models often outperform semi-parametric methods like quantile regression in forecasting macroeconomic risks. The third chapter applies a Bayesian VAR model with stochastic volatility and time-varying skewness to assess labor risks in the euro area and the United States. It explores the asymmetry of the shocks to the unemployment rate in relation to real activity and financial risk factors. The model is also used to study stagflation risks, emphasizing labor market dynamics in the inflation-unemployment trade-off.