Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/15784
Full metadata record
DC FieldValueLanguage
dc.contributor.authorPradhan, Kalandi Cen_US
dc.contributor.authorKumar, Guru Dayalen_US
dc.date.accessioned2025-03-18T06:56:41Z-
dc.date.available2025-03-18T06:56:41Z-
dc.date.issued2024-
dc.identifier.citationPradhan, K. C., Kumar, G. D., & Sharma, B. (2024). Reassessment and Determinants of Multidimensional Poverty: Evidence from Cross-Country Analysis. International Journal of Empirical Economics. https://doi.org/10.1142/S2810943024500148en_US
dc.identifier.issn2810-9430-
dc.identifier.otherEID(2-s2.0-85219743363)-
dc.identifier.urihttps://doi.org/10.1142/S2810943024500148-
dc.identifier.urihttps://dspace.iiti.ac.in/handle/123456789/15784-
dc.description.abstractThis paper aims to reassess multidimensional poverty measurement including the ease of doing business as an additional indicator with the existing measurements for 81 countries by human development, and identify how multidimensional poverty has changed during a very short period from 2014 to 2017. Further, using the tobit regression model, this study reveals the determinants of multidimensional poverty and its major indicators for both the periods. Results reveal that low human development countries are likely to be exposed to the highest multidimensional poverty as compared to moderate, high and very high human development countries. Surprisingly, we found that reduction of multidimensional poverty between 2014 and 2017 was the highest in moderate human development countries (8.18%), followed by high (5.27%), very high (3.94%) and low (2.67%) human development countries. Further, the findings from the regression results suggest that variables such as Global Climatic Risk index, Total Natural Resource Rents, Age Dependency Ratio and Urban Population Growth have a significant and positive impact on inducing multidimensional poverty irrespective of any group of countries. Contrastingly, Labour Force Participation Rate, higher score of Food Production Index, Personal Remittances Received and Volume of Trade significantly and negatively influence multidimensional poverty across the group of countries. As per the regression results, agricultural and external sectors (Food Production Index, Agricultural Land, Personal Remittances Received and Trade Volume) play a major role in reducing multidimensional poverty. This study will be helpful for the policy purpose to achieve the Sustainable Development Goals (SDGs) for the specific group of countries (SDGs 1–4, 6 and 7). Policy measures must focus largely on investment in the human capital along with prioritising climate risk reduction, proper planned urbanisation and strengthening legal rights for the vulnerable section of the people. © Sogang University Nam Duck-Woo Economic Research Institute.en_US
dc.language.isoenen_US
dc.publisherWorld Scientificen_US
dc.sourceInternational Journal of Empirical Economicsen_US
dc.subjectease of doing businessen_US
dc.subjecteducationen_US
dc.subjectHealthen_US
dc.subjectliving standarden_US
dc.subjectmultidimensional poverty indexen_US
dc.subjectregression analysisen_US
dc.titleReassessment and Determinants of Multidimensional Poverty: Evidence from Cross-Country Analysisen_US
dc.typeJournal Articleen_US
dc.rights.licenseAll Open Access-
dc.rights.licenseGold Open Access-
Appears in Collections:School of Humanities and Social Sciences

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetric Badge: