Distributional Vector Autoregression: Eliciting Macro and Financial Dependence

ABSTRACT This paper extends the vector autoregression framework by introducing a flexible distributional regression that models multivariate time series without imposing restrictive parametric distribution assumptions. We develop a distributional impulse response function that captures the future effect of distributional disturbances within the system, providing a more detailed view of dynamic heterogeneity. We propose a straightforward estimation method and establish its asymptotic properties under weak dependence assumptions. Our model, in an application to U.S. economic data, exhibits strong forecasting capabilities compared to existing alternatives. By examining distributional interactions and monetary policy impacts, particularly during the Great Recession, we uncover complex macroeconomic dynamics.