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A New Dataset on Horizontal Structural Ethnic Inequalities in Thailand in Order to Address Sustainable Development Goal 10

  • John DraperEmail author
  • Joel Sawat Selway
Original Research
  • 24 Downloads

Abstract

Thailand is the world’s fourth most unequal country by wealth, but past research on this phenomenon has mainly been along individual or geographic lines as the census is insufficiently detailed to provide ethnic-based measures. This article introduces an innovative methodological solution to measure horizontal inequality in countries where the census excludes ethnicity. We investigate the roots of a structural ‘ethnic penalty’ by contextualising in some detail an ethnic gap in Thai public policies concerning poverty and inequality. Then, using data from the United Nations Development Programme’s ‘Human Achievement Index’ for Thailand, the Thai Office of the National Culture Commission’s Ethnolinguistic Maps of Thailand report, and Thai National Statistical Office population and poverty data, we compile the country’s first dataset on horizontal (between-group) inequality by ethnicity. Employing this novel approach, we then examine the eight sectors in the Human Achievement Index: health, education, employment, income, housing and living environment, transport and communication, family and community life, and participation. Describing how Thailand’s major ethnic groups fare in each sector and comparing inequality amongst sectors, this ethnolinguistics-based approach provides evidence of a significant ‘ethnic penalty’ in Thailand and makes initial recommendations for addressing the issue.

Keywords

Ethnic penalty Human development Inequality Poverty Southeast Asia Thailand 

Notes

Acknowledgements

The authors wish to acknowledge a grant of 4400 USD via Grant No. 14/2560 from the Research Group on Local Affairs Administration, College of Local Administration, Khon Kaen University, Thailand, for the research and article writing, and the assistance of Dr. Jay Goodliffe of the Department of Political Science of the Faculty of Humanities and Social Sciences at Brigham Young University for advice on ecological inferencing methodology. All and any errors are the authors’ own.

Supplementary material

11205_2019_2065_MOESM1_ESM.docx (42 kb)
Supplementary material 1 (DOCX 42 kb)

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Social Survey Center, Research Group on Local Affairs Administration and Smart City Development, College of Local AdministrationKhon Kaen UniversityKhon KaenThailand
  2. 2.Department of Political ScienceBrigham Young UniversityProvoUSA

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