2020
DOI: 10.48550/arxiv.2003.06797
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On new data sources for the production of official statistics

Abstract: In the past years we have witnessed the rise of new data sources for the potential production of official statistics, which, by and large, can be classified as survey, administrative, and digital data. Apart from the differences in their generation and collection, we claim that their lack of statistical metadata, their economic value, and their lack of ownership by data holders pose several entangled challenges lurking the incorporation of new data into the routinely production of official statistics. We argue… Show more

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Cited by 2 publications
(1 citation statement)
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“…Illustrative of these shifts is the increasing use of (and widening aspirations to use) digital data to assemble official statistics at national and international scales, nurtured by initiatives such as the Global Working Group on Big Data for Official Statistics created by the UN Statistical Commission in 2015 (Daas et al 2015). Data employed for this purpose-some experimentally and some, in the case of supermarket scanner data, for instance, quite routinely in certain countries (Melser 2018)-include anonymized mobile phone data to assemble migration and tourism statistics, supermarket scanner data to help generate inflation statistics, satellite surface reflectance data to assemble agriculture statistics, and social media data to infer levels of consumer confidence for economic reporting purposes (Salgado & Oancea 2020). In such settings, conventional statistical populations, such as those made up of national survey respondents, are problematized, with emphasis laid on the expense, respondent burden, and lack of timeliness associated with conducting surveys (Cakici & Ruppert 2020).…”
Section: Governance By Data Sublimates Populations Into Digital Aggre...mentioning
confidence: 99%
“…Illustrative of these shifts is the increasing use of (and widening aspirations to use) digital data to assemble official statistics at national and international scales, nurtured by initiatives such as the Global Working Group on Big Data for Official Statistics created by the UN Statistical Commission in 2015 (Daas et al 2015). Data employed for this purpose-some experimentally and some, in the case of supermarket scanner data, for instance, quite routinely in certain countries (Melser 2018)-include anonymized mobile phone data to assemble migration and tourism statistics, supermarket scanner data to help generate inflation statistics, satellite surface reflectance data to assemble agriculture statistics, and social media data to infer levels of consumer confidence for economic reporting purposes (Salgado & Oancea 2020). In such settings, conventional statistical populations, such as those made up of national survey respondents, are problematized, with emphasis laid on the expense, respondent burden, and lack of timeliness associated with conducting surveys (Cakici & Ruppert 2020).…”
Section: Governance By Data Sublimates Populations Into Digital Aggre...mentioning
confidence: 99%