In the past ten years, researchers have explored the impact of data revisions in many different contexts. Researchers have examined the properties of data revisions, how structural modeling is affected by data revisions, how data revisions affect forecasting, the impact of data revisions on monetary policy analysis, and the use of real-time data in current analysis. This paper summarizes many of the questions for which real-time data analysis has provided answers. In addition, researchers and institutions have developed better real-time data sets around the world. Still, additional research is needed in key areas and research to date has uncovered even more fruitful areas worth exploring. (JEL C52, C53, C80, E01)

This paper examines fiscal policy forecasts prepared for the Federal Open Market Committee and its influence on U.S. monetary policy. The forecasts contain useful information beyond that in the CBO’s forecasts. Fiscal forecast errors are only weakly correlated with forecast errors for inflation and output growth, but those for the budget surplus are highly correlated with those for the unemployment rate and the output gap. Some fiscal variables can also account for a significant fraction of the “exogenous” changes in the federal funds rate target that Romer and Romer (2004) studied, consistent with the board’s statements on the importance of fiscal policy.

This paper uses a real-time data set to analyze data revisions and to test the robustness of published econometric results. The data set consists of vintages, or snapshots, of the major macroeconomic data available at quarterly intervals in real time. The paper illustrates why such data may matter, examines the properties of several of the variables in the data set across vintages, and examines key empirical papers in macroeconomics, investigating their robustness to different vintages.