Quality Adjustment, Hedonic Regressions and the Extension Problem

W. Erwin Diewert and Chihiro Shimizu

No DP26-7, RCESR Discussion Paper Series from Research Center for Economic and Social Risks, Institute of Economic Research, Hitotsubashi University

Abstract: High technology products are characterized by the rapid introduction of new models and the corresponding disappearance of older models. The paper addresses the quality adjustment problem associated with the construction of price indexes for these products. A main method for dealing with this problem is the use of hedonic regression models. Hedonic regressions use either product characteristics as explanatory variables (Time Dummy Characteristics regressions) or the product itself as the ultimate characteristic (Time Product Dummy regressions). The paper considers weighted and unweighted Time Product Dummy regressions. The indexes which were generated by the hedonic regressions are compared to traditional index numbers that did not make any special adjustments for quality change. The Expanding Window variant of a Weighted Time Product Dummy regression was used to address the chain drift problem and the problems associated with extending a series that cannot be revised. Finally, the estimation of systems of inverse demand functions was also used to generate various price indexes. Seventeen alternative approaches were implemented using Japanese price and quantity data on laptop sales in Japan for the 24 months over the years 2020-2021.

Keywords: Quality adjustment; scanner data; hedonic regressions; predicted share similaritylinking; expanding window approach to multilateral indexes; the chain drift problem; economic approach to index number theory; the estimation of systems of inverse demand functions (search for similar items in EconPapers)
JEL-codes: C32 C43 D20 D57 E31 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2026-03
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