Inferring Prices from Quantities

David Argente, Chang-Tai Hsieh and Munseob Lee ()
Additional contact information
David Argente: Yale University
Chang-Tai Hsieh: University of Chicago
Munseob Lee: University of California, San Diego

No 18423, IZA Discussion Papers from IZA Network @ LISER

Abstract: Measuring aggregate inflation is subject to two opposing biases: unobserved quality and variety growth, and the use of incorrect weights when new varieties are misclassified. We show that it is possible to measure an aggregate price index free of these biases when we have a subset of products where these two errors average to zero. This procedure does not require us to distinguish new from existing goods, measure quality attributes directly, or classify new varieties into the appropriate category. We implement this approach using BEA data from 1959 to 2019, approximating the official PCE price index with a CES aggregate of BEA prices at the product level. Our estimate of the inflation rate exceeds the CES aggregate of BEA prices by 0.3 to 1.0 percentage points per year on average. The aggregate bias was close to zero prior to the BLS introducing hedonic adjustments, which suggests that only adjusting for quality bias can lead to an underestimation of overall inflation, particularly in quality-adjusted categories.

Keywords: price index; inflation (search for similar items in EconPapers)
JEL-codes: D11 D12 E01 E31 (search for similar items in EconPapers)
Date: 2026-03
References: Add references at CitEc
Citations:

Downloads: (external link)
https://docs.iza.org/dp18423.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:iza:izadps:dp18423

Access Statistics for this paper

More papers in IZA Discussion Papers from IZA Network @ LISER Contact information at EDIRC.
Bibliographic data for series maintained by Mark Fallak ().