FRED-SD: A Real-Time Database for State-Level Data with Forecasting Applications

Kathryn Bokun, Laura E. Jackson, Kevin Kliesen and Michael Owyang
Authors registered in the RePEc Author Service: Laura Jackson Young and Laura Jackson

No 2020-031, Working Papers from Federal Reserve Bank of St. Louis

Abstract: We construct a real-time dataset (FRED-SD) with vintage data for the U.S. states that can be used to forecast both state-level and national-level variables. Our dataset includes approximately 28 variables per state, including labor market, production, and housing variables. We conduct two sets of real-time forecasting exercises. The first forecasts state-level labor-market variables using five different models and different levels of industrially-disaggregated data. The second forecasts a national-level variable exploiting the cross-section of state data. The state-forecasting experiments suggest that large models with industrially-disaggregated data tend to have higher predictive ability for industrially-diversified states. For national-level data, we find that forecasting and aggregating state-level data can outperform a random walk but not an autoregression. We compare these real-time data experiments with forecasting experiments using final-vintage data and find very different results. Because these final-vintage results are obtained with revised data that would not have been available at the time the forecasts would have been made, we conclude that the use of real-time data is essential for drawing proper conclusions about state-level forecasting models.

Keywords: factor models; Bayesian VARs; space-time autoregression (search for similar items in EconPapers)
JEL-codes: C33 R11 (search for similar items in EconPapers)
Pages: 44 pages
Date: 2020-08-14, Revised 2021-08-01
New Economics Papers: this item is included in nep-for, nep-geo and nep-ure
Note: Publisher DOI: https://doi.org/10.1016/j.ijforecast.2021.11.008
References: View references in EconPapers View complete reference list from CitEc
Citations:

Published in International Journal of Forecasting

Downloads: (external link)
https://s3.amazonaws.com/real.stlouisfed.org/wp/2020/2020-031.pdf Full Text (application/pdf)

Related works:
Journal Article: FRED-SD: A real-time database for state-level data with forecasting applications (2023)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:fip:fedlwp:88720

Ordering information: This working paper can be ordered from

DOI: 10.20955/wp.2020.031

Access Statistics for this paper

More papers in Working Papers from Federal Reserve Bank of St. Louis Contact information at EDIRC.
Bibliographic data for series maintained by Scott St. Louis ().