Outlier detection methodologies for alternative data sources: International review of current practices

Janine Boshoff (j.boshoff@niesr.ac.uk), Xuxin Mao and Garry Young

No 523, National Institute of Economic and Social Research (NIESR) Discussion Papers from National Institute of Economic and Social Research

Abstract: The construction of consumer price indexes (CPI) has historically relied on manually and centrally collected price data. As point of sale (POS) scanner data and web-scraped data become more accessible, these alternative data represent a rich new source of information to produce consumer price information. While outlier detection methodologies are well established for traditional data sources, more research is required to better understand the unique quality and format of the alternative data. Several national statistical institutions (NSIs) have already started to conduct research into alternative data source and the outlier detection methodologies that are necessary before these data can be incorporated into CPI calculations. This project reviews the outlier detection methodologies adopted by NSIs that have started to incorporate alternative data sources in their calculation of CPI.

Keywords: consumer price index; multilateral indices; outlier detection; scanner data; webscraped data (search for similar items in EconPapers)
JEL-codes: C43 E31 (search for similar items in EconPapers)
Date: 2020-11
New Economics Papers: this item is included in nep-mac
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Working Paper: Outlier detection methodologies for alternative data sources: International review of current practices (2020)
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