Forecasting National Recessions Using State Level Data

Abstract

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