Measurement and Determinants of Multidimensional Poverty: Evidence from Taiwan

  • Ke-Mei ChenEmail author
  • Chao-Hsien Leu
  • Te-Mu Wang


Poverty is multifaceted. In this study, multiple data sources and analytical approaches were used to analyze multidimensional poverty profiles in Taiwan. The Alkire–Foster method and a multilevel modeling technique were applied to examine multidimensional poverty and multilevel factors, respectively. The resulting estimates of multidimensional poverty indicated disparate multidimensional poverty profiles for the four districts of Taiwan. This study’s findings on the multilevel determinants of multidimensional poverty demonstrate that the levels of multiple dimensions of deprivation vary across cities and counties according to microlevel factors including age, socioeconomic status, marital status, household income, and household size. At the macrolevel, level of urbanization and service-to-manufacturing ratio were found to significantly correlate with level of multidimensional poverty. Finally, the study presents the implications of these findings for antipoverty policy and provides suggestions for future research.


Multidimensional poverty Deprivation Capability poverty Multilevel analysis Taiwan 



This work was supported by the Ministry of Science and Technology in Taiwan (Grant Nos. MOST 104-2420-H-194-008-DR and MOST 107-2410-H-020-001-). The study used the data from the National Health Interview Survey Original Database provided by the Health Promotion Administration, Ministry of Health and Welfare, National Health Research Institutes and Food and Drug Administration, and the Ministry of Health and Welfare. Finally, we appreciate the anonymous reviewers for valuable comments.


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Authors and Affiliations

  1. 1.Department of Social WorkNational Pingtung University of Science and TechnologyNeipuTaiwan, ROC
  2. 2.Department of Social WorkTunghai UniversityTaichungTaiwan, ROC
  3. 3.Department of Social WelfareNational Chung Cheng UniversityMinhsiung TownshipTaiwan, ROC

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