OECD Statistics Working Papers

The OECD Statistics Working Paper Series - managed by the OECD Statistics and Data Directorate – is designed to make available in a timely fashion and to a wider readership selected studies prepared by staff in the Secretariat or by outside consultants working on OECD projects. The papers included are of a technical, methodological or statistical policy nature and relate to statistical work relevant to the organisation. The Working Papers are generally available only in their original language - English or French - with a summary in the other.

Joint Working Papers:

Measuring Well-being and Progress in Countries at Different Stages of Development: Towards a More Universal Conceptual Framework (with OECD Development Centre)

Measuring and Assessing Job Quality: The OECD Job Quality Framework (with OECD Directorate for Employment, Labour and Social Affairs)

Forecasting GDP during and after the Great Recession: A contest between small-scale bridge and large-scale dynamic factor models (with OECD Economics Directorate)

Decoupling of wages from productivity: Macro-level facts (with OECD Economics Directorate)

Which policies increase value for money in health care? (with OECD Directorate for Employment, Labour and Social Affairs)

Compiling mineral and energy resource accounts according to the System of Environmental-Economic Accounting (SEEA) 2012 (with OECD Environment Directorate)


Diversity statistics in the OECD

How do OECD countries collect data on ethnic, racial and indigenous identity?

Data on ethnic, racial and indigenous identity can help render certain minorities statistically visible, and expose potential discrimination and inequalities. This paper systematically reviews diversity data collection practices in OECD countries and selected key partners and identifies three common challenges: the legal treatment of ‘sensitive’ data and concerns around privacy; the use of different data sources for different policy purposes; and issues of comparability over time since identities are dynamic and multiple constructs. When relevant, recommendations and best practices to improve diversity data are put forward. These include: expanding the collection of data on ethnic and racial identities where legal frameworks permit; ensuring the representation of hard-to-reach populations such as indigenous communities; developing national diversity statistical standards to standardise information and allow linking data across sources; raising the timeliness and policy relevance of diversity data by including questions in both regular sample surveys and population censuses; and involving communities in the data collection process.


Keywords: well-being, Data collection, race, ethnicity, indigenous peoples, migration
JEL: C80: Mathematical and Quantitative Methods / Data Collection and Data Estimation Methodology; Computer Programs / Data Collection and Data Estimation Methodology; Computer Programs: General; I3: Health, Education, and Welfare / Welfare, Well-Being, and Poverty; J15: Labor and Demographic Economics / Demographic Economics / Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination
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