Proxy expenditure weights for Consumer Price Index: Audit sampling inference for big data statistics

Li-Chun Zhang

Papers from arXiv.org

Abstract: Purchase data from retail chains provide proxy measures of private household expenditure on items that are the most troublesome to collect in the traditional expenditure survey. Due to the sheer amount of proxy data, the bias due to coverage and selection errors completely dominates the variance. We develop tests for bias based on audit sampling, which makes use of available survey data that cannot be linked to the proxy data source at the individual level. However, audit sampling fails to yield a meaningful mean squared error estimate, because the sampling variance is too large compared to the bias of the big data estimate. We propose a novel accuracy measure that is applicable in such situations. This can provide a necessary part of the statistical argument for the uptake of big data source, in replacement of traditional survey sampling. An application to disaggregated food price index is used to demonstrate the proposed approach.

Date: 2019-06
New Economics Papers: this item is included in nep-big
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://arxiv.org/pdf/1906.11208 Latest version (application/pdf)

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:arx:papers:1906.11208

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().