Unpacking trend inflation: Evidence from a factor correlated unobserved components model of sticky and flexible prices

We propose a factor correlated unobserved components (FCUC) model to analyze the sticky and flexible components of U.S. inflation. The proposed FCUC framework estimates trend inflation and component cycles in a flexible stochastic environment with time-varying volatility, factor loadings, and cross-frequency (trend-cycle) correlations, thus capturing how structural heterogeneity in price adjustment shapes the evolution of aggregate trend inflation over time. Using Bayesian estimation methods, we show that the FCUC model substantially reduces the uncertainty surrounding estimates of trend inflation and improves both point and density forecast accuracy. Our findings reveal that, particularly following the Global Financial Crisis and more markedly since the COVID-19 recession, transitory price shocks originating from flexible inflation have become a major driver of trend inflation, whereas sticky inflation explains only part of the variation. These results indicate that temporary price movements can have persistent effects, highlighting important policy implications regarding the cyclical dynamics of disaggregated inflation components amid evolving macroeconomic conditions.