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Measuring Inflation: It’s All About Minding Your P’s and Q’s

Paper Session

Saturday, Jan. 3, 2026 10:15 AM - 12:15 PM (EST)

Philadelphia Convention Center, 202-A
Hosted By: American Economic Association & Committee on Economic Statistics
  • Chair: Carol Corrado, Georgetown University

Quality-Adjusted Unit Value Index: Are Changes in Average Prices Inflation or Quality Change?

John C. Haltiwanger
,
University of Maryland
Ron Jarmin
,
U.S. Census Bureau
R. Benjamin Rodriguez
,
University of Maryland
Matthew Shapiro
,
University of Michigan

Abstract

Digitized item-level transactions data allow for the calculation of the average sale price for the universe of items within a product group. Such measures, referred to as unit value indices (UVI), are often used by retail companies and information aggregators to monitor market changes across a wide variety of product groups. Items classified within the same product groups often differ in quality, making the change in the average unit values a combination of changing prices, quality, and product mix. This paper develops a decomposition of the change in unit values into price, quality, and product mix components. It applies hedonic and alternative methods to scanner data from Circana for consumer-technology products to compute quality-adjusted unit value indices (QUVIs) and to implement the decomposition into inflation, quality-change, and product mix.

Do Price Deflators for High-Tech Goods Overstate Quality Change?

Ana Aizcorbe
,
Bureau of Economic Analysis
Daniel Ripperger-Suhler
,
Bureau of Economic Analysis

Abstract

This paper studies chained price indexes for goods in high-tech sectors, how they handle quality change and whether they will likely suffer from chain drift issues. We argue that chained indexes do not handle quality change properly; though the underlying bilateral indexes hold quality constant just fine, the chained index does not, a problem we call comingling. When we explored multilateral methods as alternatives to chained indexes, we found that the GEKS index that is often used to deal with the chain drift problem does not fix the comingling problem. Thus, the comingling issue is not just the chain drift problem in another guise; it can also exist in indexes that do not suffer from chain drift. Using the Weighted Time Product Dummy (WTPD) index as a benchmark, we show that, the changes in prices and expenditure shares over the product cycle that are typically exhibited by these high-tech goods can generate numerically important chain drift problems. Moreover, we show that the gap is negative: that is, the chained index will show faster price declines than the WTPD index. We illustrate these points using scanner data for six categories of consumer
electronic goods.

Look Within: Demographic Grouping Masks Inflation Inequality

Kelsey O'Flaherty
,
Federal Reserve Board

Abstract

The recent inflation surge prompted renewed assessments of inflation inequality. Examinations of inflation by income or other demographic groups point to a shrinking or stable inflation gap between high- and low-income households in 2022. At the same time, research using scanner data shows grocery inflation becoming much more disparate with rising inflation. I show that aggregating households into demographic groups not only masks the majority of heterogeneity, but fails to capture important dynamics between that heterogeneity and the level of inflation.

Lack of Uniform Prices or Lack of Uniform Retailers?

Michael Navarrete
,
Federal Reserve Bank of Atlanta and NBER
Seula Kim
,
Pennsylvania State University and IZA Institute of Labor Economics

Abstract

Standard models assume that food retail chains set uniform prices across stores, following the evidence in DellaVigna and Gentzkow (2019). We first show that the extent of uniform pricing varies across products within food categories. Second, even if prices were nearly uniform at the product–chain level, systematic cross-market differences in product and chain composition could still generate spatial variation in effective price levels. We find substantial heterogeneity in retailer composition and characteristics across MSAs: poorer MSAs are served by fewer retail chains while having a disproportionately larger share of big (national) retailers. Furthermore, we show that poorer MSAs have less product variety because they have fewer retailers overall and because the same retailer offers fewer products in those markets. Failing to account for this heterogeneity in retailer composition leads to understating differences in effective price levels between poor and rich areas. These results complement Kim and Navarrete (2025), who document spatial heterogeneity in food inflation, and highlight cross-market differences in retail market structure as a key channel accounting for this variation.

Discussant(s)
David M. Byrne
,
Federal Reserve Board
Louise Sheiner
,
Brookings Institution
JEL Classifications
  • E3 - Prices, Business Fluctuations, and Cycles
  • C8 - Data Collection and Data Estimation Methodology; Computer Programs