Big Data in Official Statistics

Big Data in Official Statistics

Kees Zeelenberg (Statistics Netherlands, The Netherlands) and Barteld Braaksma (Statistics Netherlands, The Netherlands)
Copyright: © 2017 |Pages: 23
DOI: 10.4018/978-1-5225-2512-7.ch011
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Abstract

Big data come in high volume, high velocity and high variety. Their high volume may lead to better accuracy and more details, their high velocity may lead to more frequent and more timely statistical estimates, and their high variety may give opportunities for statistics in new areas. But there are also many challenges: there are uncontrolled changes in sources that threaten continuity and comparability, and data that refer only indirectly to phenomena of statistical interest. Furthermore, big data may be highly volatile and selective: the coverage of the population to which they refer, may change from day to day, leading to inexplicable jumps in time-series. And very often, the individual observations in these big data sets lack variables that allow them to be linked to other datasets or population frames. This severely limits the possibilities for correction of selectivity and volatility. In this chapter, we describe and discuss opportunities for big data in official statistics.
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Big Data And Official Statistics

There are nowadays three types of sources for official statistics:

  • Survey Data: Data collected by interviewing persons, households and enterprises,

  • Administrative Data: Data from official registrations, such as the population register and the tax registrations,

  • Big Data: Data generated by digital activities, e.g., activities on the internet, communications between devices or between devices and their operators (internet of things).

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