Working Paper: CEPR ID: DP16346
Authors: Massimiliano Marcellino; Andrea Carriero; Todd Clark
Abstract: We develop a structural vector autoregression with stochastic volatility in which one of the variables can impact both the mean and the variance of the other variables. We provide conditional posterior distributions for this model, develop an MCMC algorithm for estimation, and show how stochastic volatility can be used to provide useful restrictions for the identification of structural shocks. We then use the model with US data to show that some variables have a significant contemporaneous feedback effect on macroeconomic uncertainty, and overlooking this channel can lead to distortions in the estimated effects of uncertainty on the economy.
Keywords: endogeneity; causality; stochastic volatility; bayesian methods
JEL Codes: C11; C32; D81; E32
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| macroeconomic variables (E19) | macroeconomic uncertainty (D89) |
| macroeconomic uncertainty (D89) | macroeconomic variables (E19) |
| uncertainty shocks (D89) | economic variables (P42) |
| feedback effects of consumption on macroeconomic uncertainty (E21) | macroeconomic uncertainty (D89) |
| feedback effects of industrial production on macroeconomic uncertainty (E32) | macroeconomic uncertainty (D89) |
| feedback effects of federal funds rate on macroeconomic uncertainty (E52) | macroeconomic uncertainty (D89) |
| macroeconomic uncertainty (D89) | feedback effects of consumption on economic variables (E21) |
| macroeconomic uncertainty (D89) | feedback effects of industrial production on economic variables (E23) |
| macroeconomic uncertainty (D89) | feedback effects of federal funds rate on economic variables (E52) |