Journal
JOURNAL OF BUSINESS & ECONOMIC STATISTICS
Volume 34, Issue 4, Pages 574-589Publisher
AMER STATISTICAL ASSOC
DOI: 10.1080/07350015.2015.1086655
Keywords
Big data; Diffusion index; Factors; Forecasting
Funding
- National Science Foundation [SES-0962431]
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available