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Inflation at the Household Level

Listed author(s):
  • Schulhofer-Wohl, Sam

    (Federal Reserve Bank of Minneapolis)

  • Kaplan, Greg

    (Princeton University)

We use scanner data to estimate inflation rates at the household level. Households' inflation rates are remarkably heterogeneous, with an interquartile range of 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.

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Paper provided by Federal Reserve Bank of Minneapolis in its series Working Papers with number 731.

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Length: 35 pages
Date of creation: 11 Apr 2016
Handle: RePEc:fip:fedmwp:731
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  1. Reis, Ricardo, 2006. "Inattentive consumers," Journal of Monetary Economics, Elsevier, vol. 53(8), pages 1761-1800, November.
  2. Gianluca Violante & Benjamin Moll & Greg Kaplan, 2015. "Monetary Policy According to HANK," 2015 Meeting Papers 1507, Society for Economic Dynamics.
  3. Sims, Christopher A., 2003. "Implications of rational inattention," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 665-690, April.
  4. Liran Einav & Ephraim Leibtag & Aviv Nevo, 2010. "Recording discrepancies in Nielsen Homescan data: Are they present and do they matter?," Quantitative Marketing and Economics (QME), Springer, vol. 8(2), pages 207-239, June.
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