Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We estimate an empirical model of inflation that exploits a Phillips curve relationship between a measure of unemployment and a sub-aggregate measure of inflation (services). We generate an aggregate inflation forecast from forecasts of the goods sub-component, separate from the services sub-component, 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.