Using Scanner Data to Construct CPI Basic Component Indexes
Bibliographic Data
| ID | 19417455 |
|---|---|
| Authors | Marshall B Reinsdorf, Marshall Reinsdorf (0000-0002-3866-6591, corresponding author) |
| Year | 1999 |
| Volume | 17 |
| Issue | 2 |
| Pages | 152 |
| Publication date | 1999-04-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Business and Economic Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0735-0015 • E-ISSN: 1537-2707 |
| Publisher | JSTOR (PUBLISHER) |
| DOI | 10.2307/1392470 |
| OpenAlex | W4255469829 |
| Language | EN |
| Citations received | 6 |
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
Econometrics · Economics · Statistics · Computer Science · Mathematics · Neural Networks and Applications
Comparing Price Indices of Clothing and Footwear for Scanner Data and Web Scraped Data
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Introduction – The Value Chain of Scanner and Web Scraped Data
Inflation Measurement with Scanner Data and an Ever-Changing Fixed Basket
Scanner Data
Sampling Frequency and the Comparison Between Matched-Model and Hedonic Regression Price Indexes
| Unique citing works | 6 |
|---|---|
| Citations per year | 0,27 |
| Citation span | 2004 - 2019 (16) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 1 |