This news article discusses a method proposed by the authors to identify the anticipated components of macroeconomic shocks in a structural VAR (Vector Autoregression) model. The authors include empirical forecasts about each time series in the VAR, which helps identify each structural shock and further decompose them into “news” and “surprise” shocks. The authors applied this method to a VAR model using forecast data from various sources, such as the SPF, CBO, Federal Reserve, and asset prices. The shocks identified, including unanticipated fiscal stimulus and interest rate shocks, were found to have typical effects consistent with existing evidence.
In the news-surprise decomposition, the authors discovered that news, as opposed to surprise, drives approximately one quarter of the volatility in the US business cycle. When applying this decomposition to fiscal and monetary policy shocks, they found that news explains a larger share of the variance for fiscal shocks than for monetary policy shocks. Additionally, the authors used the news structure of the shocks to estimate counterfactual policy rules and compared the effectiveness of fiscal and monetary policy in moderating output and inflation. Their findings suggest that coordinated fiscal and monetary policy are significantly more effective in achieving desired outcomes than either tool used individually.
Overall, this research provides insights into the factors driving macroeconomic shocks and highlights the importance of considering news and surprise components in analyzing the effects of fiscal and monetary policy on the economy. The findings emphasize the potential benefits of coordinating fiscal and monetary policy for better economic outcomes.
