Abstract
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.
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Notes
See Alkire et al. (2015c) for a more detailed discussion.
This study is based in part on 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. The interpretation and conclusions herein do not represent those of the Health Promotion Administration, Ministry of Health and Welfare, National Health Research Institutes and Food and Drug Administration, or the Ministry of Health and Welfare.
The northern district comprises Taipei City, Taipei County, Yilan City, Taoyuan County, Hsinchu City, Hsinchu County, and Keelung City. The central district comprises Miaoli County, Taichung City*, Taichung County*, Changhua County, Nantou County, and Nantou County. The southern district consists of Chiayi City, Chiayi County, Tainan City*, Tainan County*, Kaohsiung City*, Kaohsiung County*, and Pingtung County. The eastern and outlying island district comprises Hualien County, Taitung County, and Penghu County. Penghu County comprises the outlying islands. An asterisk indicates that the city and county have been merged. Several city and county governments have been merged since 2010.
See Alkire et al. (2015b) for a more detailed discussion.
Socioeconomic status was recorded according to the International Standard Classification of Occupations (ISCO-88).
The proportion of variance explained was computed as [\(\tau_{00}\) (baseline model) − \(\tau_{00}\) (comparison model)]/\(\tau_{00}\) (baseline model) (see Raudenbush and Bryk 2002).
The formula used to calculate the range of values was \(0.797 \pm 1.96 \times 0.008^{1/2} = (0.622,0.972)\).
Only one panel survey, the “Taiwan Database of Children and Youth in Poverty,” has been conducted. The nonprofit organization Taiwan Fund for Children and Families conducted this survey, which followed children and the young in low- and middle-income families. Data were collected every 2 years for a total of four waves of data.
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Acknowledgements
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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About the multidimensional poverty measures, part of the data and deprivation indicators are rewritten from the first author’s PhD thesis named “Multidimensional Poverty Measurement and Analysis in Taiwan”. The PhD thesis was supported by a research scholarship from the Ministry of Science and Technology (Grant No. MOST 104-2420-H-194-008-DR).
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Chen, KM., Leu, CH. & Wang, TM. Measurement and Determinants of Multidimensional Poverty: Evidence from Taiwan. Soc Indic Res 145, 459–478 (2019). https://doi.org/10.1007/s11205-019-02118-8
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DOI: https://doi.org/10.1007/s11205-019-02118-8