Forecasting National Recessions Using State-Level Data

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Journal of Money, Credit and Banking


We investigate whether there is information useful for identifying U.S. business cycle phases contained in subnational measures of economic activity. Using a probit model to forecast the National Bureau of Economic Research 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.


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