EconPapers    
Economics at your fingertips  
 

Using Scanner Data to Construct CPI Basic Component Indexes

Marshall B Reinsdorf

Journal of Business & Economic Statistics, 1999, vol. 17, issue 2, 152-60

Abstract: This article considers how scanner data could be used in constructing component indexes for the U.S. Consumer Price Index. One product, coffee, in two cities generates over 1.8 million observations in just over two years, so coping with the sheer volume of data would be a challenge. Some other findings are (1) some aggregation of prices into 'unit-value' averages is necessary for practical reasons and to avoid bias, (2) chained Laspeyres indexes are very high, (3) 'modified' Laspeyres indexes have some upward bias but much less than a true Laspeyres index, (4) Fisher ideal or modified Edgeworth indexes perform well, and (5) aggregating prices across outlets to form city-level unit values reduces the discrepancies between index-number formulas.

Date: 1999
References: Add references at CitEc
Citations: View citations in EconPapers (23)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:bes:jnlbes:v:17:y:1999:i:2:p:152-60

Ordering information: This journal article can be ordered from
http://www.amstat.org/publications/index.html

Access Statistics for this article

Journal of Business & Economic Statistics is currently edited by Jonathan H. Wright and Keisuke Hirano

More articles in Journal of Business & Economic Statistics from American Statistical Association
Bibliographic data for series maintained by Christopher F. Baum ().

 
Page updated 2025-03-19
Handle: RePEc:bes:jnlbes:v:17:y:1999:i:2:p:152-60