FRED-MD: A Monthly Database for Macroeconomic Research

Abstract

This article describes a large, monthly frequency, macroeconomic database with the goal of establishing a convenient starting point for empirical analysis that requires “big data.” The dataset mimics the coverage of those already used in the literature but has three appealing features. First, it is designed to be updated monthly using the Federal Reserve Economic Data (FRED) database. Second, it will be publicly accessible, facilitating comparison of related research and replication of empirical work. Third, it will relieve researchers from having to manage data changes and revisions. We show that factors extracted from our dataset share the same predictive content as those based on various vintages of the so-called Stock–Watson dataset. In addition, we suggest that diffusion indexes constructed as the partial sum of the factor estimates can potentially be useful for the study of business cycle chronology. Supplementary materials for this article are available online.

KEY WORDS:

• Big data
• Diffusion index
• Factors
• Forecasting

ACKNOWLEDGMENTS

The authors thank Kenichi Shimizu and Joseph McGillicuddy for excellent research assistance. This project could not have occurred without the enormous assistance of the FRED staff—especially that of Yvetta Fortova. For that assistance the authors are very grateful. Financial support to the second author is provided by the National Science Foundation, SES-0962431. The views expressed here are those of the individual authors and do not necessarily reflect official positions of the Federal Reserve Bank of St. Louis, the Federal Reserve System, or the Board of Governors.