Inflation Factors 
The unexpected surge in global inflation in 2021, driven by the COVID-19 pandemic, exposed weaknesses in traditional inflation forecasting models. Accurate forecasts and a sounder real-time understanding of inflation’s driving forces allow central banks to calibrate the scope and timing of monetary policy more effectively. In turn, this helps monetary authorities maintain their credibility, which is vital for managing inflation expectations and maintaining public trust. To this end, this paper introduces a sign-restricted dynamic factor model (SiR-DFM) that decomposes inflation into its underlying common supply and demand components by leveraging the co-movement of prices and quantities across various personal consumption expenditures (PCE) categories. Importantly, the paper’s SiR-DFM distinguishes between common supply and demand drivers within the goods and services sectors and incorporates features such as time-varying volatility, outliers, and long-term inflation expectations.
Key Findings
- By decomposing total PCE inflation into six components—common demand for goods, common demand for services, common supply of goods, common supply of services, long-term inflation expectations, and idiosyncratic, or category-specific, demand and supply contributions—the paper’s SiR-DFM provides a significantly enhanced understanding of pandemic-era inflation dynamics.
- The paper’s validation exercises demonstrate the SiR-DFM’s effectiveness in accurately identifying key inflation drivers.
- Including the SiR-DFM’s estimated supply and demand inflation factors in a standard inflation forecasting framework leads to a notable improvement in the accuracy of medium-term inflation forecasts.
Implications
The model presented in this paper offers an improved understanding of inflation dynamics that can inform monetary-policy decisions in real time, helping to ensure macroeconomic stability in the face of complex and evolving economic conditions.
Abstract
This paper develops an econometric framework for identifying latent factors that provide real-time estimates of supply and demand conditions shaping goods- and services-related price pressures in the U.S. economy. The factors are estimated using category-specific personal consumption expenditures (PCE) data on prices and quantities, using a sign-restricted dynamic factor model that imposes theoretical predictions of the effects of fluctuations in supply and demand on prices and associated quantities through factor loadings. The resulting estimates are used to decompose total PCE inflation into contributions from common factors—goods demand, goods supply, services demand, services supply, and inflation expectations—and category-specific idiosyncratic components. Validation exercises demonstrate that the estimated factors provide an informative and coherent narrative of inflation dynamics over time and can be effectively used for forecasting and policy analysis.