Forecasting National Recessions Using State Level Data
Federal Reserve Bank of St. Louis Working Paper No. 2012-013B
33 Pages Posted: 13 Jun 2012 Last revised: 16 Nov 2013
Date Written: November 8, 2013
A large literature studies the information contained in national-level economic indicators, such as financial and aggregate economic activity variables, for forecasting and nowcasting U.S. business cycle phases (expansions and recessions.) In this paper, we investigate whether there is additional information useful for identifying business cycle phases contained in subnational measures of economic activity. Using a probit model to forecast the NBER expansion and recession classification, we assess the incremental information content of state-level employment growth over a commonly used set of national-level predictors. As state-level data adds a large number of predictors to the model, we employ a Bayesian model averaging procedure to construct forecasts. Based on a variety of forecast evaluation metrics, we find that including state-level employment growth substantially improves nowcasts and very short-horizon forecasts of the business cycle phase. The gains in forecast accuracy are concentrated during months of national recession.
Keywords: turning points, probit, covariate selection
JEL Classification: C52, C53, E32, E37
Suggested Citation: Suggested Citation