A Simple Framework to Monitor Inflation

This paper proposes a simple framework to help monitor and understand movements in PCE inflation in real time. The approach is to decompose inflation using simple categorical-level regressions or systems of equations. The estimates are then used to group categories into components of PCE inflation. I review some applications of the methodology, and show how it can help explain inflation dynamics over recent episodes. The methodology shows that inflation remained low in the mid-2010s primarily because of factors unrelated to aggregate economic conditions. I also apply the methodology to the Covid-19 pandemic. The decomposition reveals that a majority of elevated inflation in core PCE inflation in the 2021 2022 period was due to "Covid-sensitive" categories, that is, those categories where prices and quantities moved the most at the onset of the pandemic. Finally, I show how the methodology can be applied in a dynamic fashion, labeling categories as either supply- or demand-driven by month. This decomposition allows one to assess the extent to which supply and demand factors are impacting inflation.