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Price Measurement Using Scanner Data: Time‐Product Dummy Versus Time Dummy Hedonic Indexes
Author(s) -
Haan Jan,
Hendriks Rens,
Scholz Michael
Publication year - 2021
Publication title -
review of income and wealth
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.024
H-Index - 57
eISSN - 1475-4991
pISSN - 0034-6586
DOI - 10.1111/roiw.12468
Subject(s) - econometrics , overfitting , hedonic index , economics , index (typography) , hedonic regression , regression , statistics , price index , matching (statistics) , regression analysis , mathematics , computer science , machine learning , world wide web , artificial neural network
This paper compares two model‐based multilateral price indexes: the time‐product dummy (TPD) index and the time dummy hedonic (TDH) index, both estimated by expenditure‐share weighted least squares regression. The TPD model can be viewed as the saturated version of the underlying TDH model, and we argue that the regression residuals are “distorted toward zero” due to overfitting. We decompose the ratio of the two indexes in terms of average regression residuals of the new and disappearing items. The decomposition aims to explain the conditions under which the TPD index suffers from quality‐change bias or, more generally, lack‐of‐matching bias. An example using scanner data on packaged men's T‐shirts illustrates our framework.