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Forecasting Inflation: Phillips Curve Effects on Services Price Measures


We estimate an empirical model of inflation that exploits a Phillips curve relationship between a measure of unemployment and a subaggregate measure of inflation (services). We generate an aggregate inflation forecast from forecasts of the goods subcomponent separate from the services subcomponent, and compare the aggregated forecast to the leading time-series univariate and standard Phillips curve forecasting models. Our results indicate marked improvements in point and density forecasting accuracy statistics for models that exploit relationships between services inflation and the unemployment rate.

Keywords: Inflation forecasting, Phillips curve, disaggregated inflation forecasting models, trend-cycle model, density combinations.

JEL Codes: C22, C53, E31, E37.

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Suggested citation: Tallman, Ellis W., and Saeed Zaman, 2016. “Forecasting Inflation: Phillips Curve Effects on Services Price Measures,” Federal Reserve Bank of Cleveland, working paper no. 15-19R.

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