The product life cycle and sample representativity bias in price indexes

Daniel Melser and Iqbal Syed ()

Applied Economics, 2017, vol. 49, issue 6, 573-586

Abstract: Official price indexes are usually calculated using matched samples of products. If products exhibit systematic price trends at different points in their life cycle then matched sample methods may introduce bias if the life cycle movement in the sample does not adequately reflect that in the population. This article explores the extent of these life cycle pricing effects and then examines the bias it can introduce in measured inflation. A large US supermarket scanner data set for six cities and six products over 12 years is used. Using hedonic methods we find that the life cycle component of price change is important across a range of products and cities. To explore the bias introduced by these movements, we use simulations that construct indexes with different sample update frequency. For indexes that are never completely resampled, we find an annual absolute bias of 0.88 and 0.59 percentage points depending upon whether we use the actual prices or prices imputed from our hedonic model. This compares with absolute biases of 0.34 and 0.10 percentage points for the corresponding cases for samples, which are re-selected annually. Thus our results provide strong support for more frequently updating index samples.

Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/10.1080/00036846.2016.1203060 (text/html)
Access to full text is restricted to subscribers.

Related works:
Working Paper: The Product Life Cycle and Sample Representativity Bias in Price Indexes (2016)
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:taf:applec:v:49:y:2017:i:6:p:573-586

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEC20

DOI: 10.1080/00036846.2016.1203060

Access Statistics for this article

Applied Economics is currently edited by Anita Phillips

More articles in Applied Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().