The World Bank Group-LinkedIn partnership pilots the use of private company data for generating insights on development trends. This partnership is a three-year effort between the WBG and LinkedIn to investigate the extent to which LinkedIn's data can inform policy. The first phase of the partnership evaluates LinkedIn data covering 100 countries with at least 100,000 LinkedIn members, distributed across 148 industries and 50,000 skills categories. The second and third phase focus on automating and scaling insights, and expanding joint research. This methodology report describes the construction and validation of metrics on skills, industry employment, and talent migration in over 100 countries. This report has three objectives: (1) document the characteristics and coverage of LinkedIn data; (2) report the methods used to develop new metrics; and (3) showcase examples of policy questions that can be answered with this non-traditional data. Because this is the first time that LinkedIn has shared a non-traditional dataset with a third-party organization globally as a public good (strictly unremunerated), it is important that we make these methodology and validation results available so that researchers and policy-makers can build on this initial effort by the WBG and LinkedIn.
Details
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Author
Zhu,Tingting Juni, Fritzler,Alan, Orlowski,Jan Alexander Kazimierz
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Document Date
2018/11/13
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Document Type
Working Paper
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Report Number
132009
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Volume No
1
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Total Volume(s)
2
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Country
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Region
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Disclosure Date
2018/11/13
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Disclosure Status
Disclosed
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Doc Name
World Bank Group-LinkedIn Data Insights : Jobs, Skills and Migration Trends Methodology and Validation Results
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Keywords
source of inflow; arts and craft; tradable sector; compulsory social security; Private Sector Growth; labor market outcome; comments and feedback; Executive Offices; labor force data; labor market information; external data; employment growth; skill need; penetration rate; public good; skill group; net migration; policy question; work experience; migration trend; motion picture; management consulting; work history; migration datum; panel data; migration flow; government statistics; validation exercises; significant correlation; disruptive technology; Digital Literacy; innovative application; Real estate; web development; social network; dramatic change; qualitative analysis; energy company; data structure; digital economy; cognitive skill; interpersonal communication; official statistic; statistical technique; business service; skill category; government indicator; statistical significance; oral communication; employment size; productivity data; small sample; consumer goods; social work; consequential damages; data quality; insurance activity; public safety; retail trade; economic research; government administrative; survey data; Food Services; user feedback; technological change; industry growth; future research; business management; Open Data; entrepreneurial spirit; insurance sector; software engineer; job description; external migration; global coverage; limited coverage; technology industry; random sample; education experience; big data; administrative datum; agriculture sector; index data; work routine; artificial intelligence; business growth; financial service; statistical method; empirical research; economic census; human capital; employment data; private company; raw data; real time; technological advancement; comparable data; sectoral employment; data connections; representative sample; Global Industries; communications technology; relative value; digital market; skilled labor; geographic region; Occupation
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Citation
Zhu,Tingting Juni Fritzler,Alan Orlowski,Jan Alexander Kazimierz
World Bank Group-LinkedIn Data Insights : Jobs, Skills and Migration Trends Methodology and Validation Results (English). Washington, D.C. : World Bank Group. http://documents.worldbank.org/curated/en/827991542143093021/World-Bank-Group-LinkedIn-Data-Insights-Jobs-Skills-and-Migration-Trends-Methodology-and-Validation-Results