A large Bayesian VAR of the United States Economy - Richard K. Crump; Stefano Eusepi; Domenico Giannone; Eric Qian; Argia M. Sbordone (Federal Reserve Bank of New York, 2021)
We model the United States macroeconomic and financial sectors using a formal and unified econometric model. Through shrinkage, our Bayesian VAR provides a flexible framework for modeling the dynamics of thirty-one variables, many of which are tracked by the Federal Reserve. We show how the model can be used for understanding key features of the data, constructing counterfactual scenarios, and evaluating the macroeconomic environment both retrospectively and prospectively. Considering its breadth and versatility for policy applications, our modeling approach gives a reliable, reduced form alternative to structural models.
Keywords: C11; C32; C53; C54; E32; E37; 330; bayesian vector autoregressions; conditional forecasts; scenario analyses; financial conditions index