Fred-Sd: A Real-Time Database for State-Level Data with Forecasting Applications

47 Pages Posted: 23 Sep 2020 Last revised: 15 Jan 2023

See all articles by Kathryn Bokun

Kathryn Bokun

affiliation not provided to SSRN

Laura E. Jackson

Bentley University - Department of Economics

Kevin L. Kliesen

Federal Reserve Bank of St. Louis - Research Division

Michael Owyang

Federal Reserve Bank of St. Louis - Research Division

Date Written: August, 2020

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

JEL Classification: C33, R11

Suggested Citation

Bokun, Kathryn and Jackson Young, Laura and Kliesen, Kevin L. and Owyang, Michael T., Fred-Sd: A Real-Time Database for State-Level Data with Forecasting Applications (August, 2020). FRB St. Louis Working Paper No. 2020-31, Available at SSRN: https://ssrn.com/abstract=3696733 or http://dx.doi.org/10.20955/wp.2020.031

Kathryn Bokun

affiliation not provided to SSRN

Laura Jackson Young (Contact Author)

Bentley University - Department of Economics ( email )

175 Forest Street
Waltham, MA 02452-4705
United States

Kevin L. Kliesen

Federal Reserve Bank of St. Louis - Research Division ( email )

411 Locust St
Saint Louis, MO 63011
United States

Michael T. Owyang

Federal Reserve Bank of St. Louis - Research Division ( email )

411 Locust St
Saint Louis, MO 63011
United States

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