Skip to:
  1. Main navigation
  2. Main content
  3. Footer
Working Paper

Lessons for Forecasting Unemployment in the U.S.: Use Flow Rates, Mind the Trend

This paper evaluates the ability of autoregressive models, professional forecasters, and models that leverage unemployment flows to forecast the unemployment rate. We pay particular attention to flows-based approaches—the more reduced form approach of Barnichon and Nekarda (2012) and the more structural method in Tasci (2012)—to generalize whether data on unemployment flows is useful in forecasting the unemployment rate. We find that any approach that leverages unemployment inflow and outflow rates performs well in the near term. Over longer forecast horizons, Tasci (2012) appears to be a useful framework, even though it was designed to be mainly a tool to uncover long-run labor market dynamics such as the “natural” rate. Its usefulness is amplified at specific points in the business cycle when unemployment rate is away from the longer-run natural rate. Judgmental forecasts from professional economists tend to be the single best predictor of future unemployment rates. However, combining those guesses with flows-based approaches yields significant gains in forecasting accuracy.

Working Papers of the Federal Reserve Bank of Cleveland are preliminary materials circulated to stimulate discussion and critical comment on research in progress. They may not have been subject to the formal editorial review accorded official Federal Reserve Bank of Cleveland publications. The views expressed in this paper are those of the authors and do not represent the views of the Federal Reserve Bank of Cleveland or the Federal Reserve System.


Suggested Citation

Meyer, Brent, and Murat Tasci. 2015. “Lessons for Forecasting Unemployment in the U.S.: Use Flow Rates, Mind the Trend.” Federal Reserve Bank of Cleveland, Working Paper No. 15-02. https://doi.org/10.26509/frbc-wp-201502