There is a new and very important paper on this topic by Greg Kaplan and Sam Schulhofer-Wohl (pdf), emanating from the Minneapolis Fed:
We use scanner data to estimate inflation rates at the household level. Households’ inflation rates are remarkably heterogeneous, with an interquartile range between 6.2 to 9.0 percentage points on an annual basis. Most of the heterogeneity comes not from variation in broadly defined consumption bundles but from variation in prices paid for the same types of goods — a source of variation that previous research has not measured. The entire distribution of household inflation rates shifts in parallel with aggregate inflation. Deviations from aggregate inflation exhibit only slightly negative serial correlation within each household over time, implying that the difference between a household’s price level and the aggregate price level is persistent. Together, the large cross-sectional dispersion and low serial correlation of household-level inflation rates mean that almost all of the variability in a household’s inflation rate over time comes from variability in household-level prices relative to average prices for the same goods, not from variability in the aggregate inflation rate. We provide a characterization of the stochastic process for household inflation that can be used to calibrate models of household decisions.
For the pointer I thank David Levey. One wonders of course what this means for various propositions in macroeconomics, such as the Fisher effect, or the use of monetary stimulus to alter the meaning of a given nominal reservation wage. This is also of note: “…observable household characteristics have little power overall to predict household inflation rates.” By the way, note that the data measure recorded prices, and not prices plus search costs, so the bargain hunters are paying higher net prices than these results would indicate, thus narrowing the differences in inflation rates across persons.