Reassessment and Determinants of Multidimensional Poverty: Evidence from Cross-Country Analysis

This 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. F...

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Main Authors: Kalandi Charan Pradhan, Guru Dayal Kumar, Bhuvesh Sharma
Format: Article
Language:English
Published: World Scientific Publishing 2025-03-01
Series:International Journal of Empirical Economics
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Online Access:https://www.worldscientific.com/doi/10.1142/S2810943024500148
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author Kalandi Charan Pradhan
Guru Dayal Kumar
Bhuvesh Sharma
author_facet Kalandi Charan Pradhan
Guru Dayal Kumar
Bhuvesh Sharma
author_sort Kalandi Charan Pradhan
collection DOAJ
description This 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.
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spelling doaj-art-afe514b676734892a8d9c8f7f5bd92f82025-08-20T03:39:57ZengWorld Scientific PublishingInternational Journal of Empirical Economics2810-94302810-94492025-03-01040110.1142/S2810943024500148Reassessment and Determinants of Multidimensional Poverty: Evidence from Cross-Country AnalysisKalandi Charan Pradhan0Guru Dayal Kumar1Bhuvesh Sharma2School of Humanities and Social Sciences, Indian Institute of Technology Indore, Simrol, Khandwa Road, Indore 453552, Madhya Pradesh, IndiaSchool of Humanities and Social Sciences, Indian Institute of Technology Indore, Simrol, Khandwa Road, Indore 453552, Madhya Pradesh, IndiaIndian Institute of Management Amritsar, Punjab Institute of Technology Building, Polytechnic Road, Chheharta, GT Road, Amritsar 143105, Punjab, IndiaThis 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.https://www.worldscientific.com/doi/10.1142/S2810943024500148Healtheducationliving standardease of doing businessmultidimensional poverty indexregression analysis
spellingShingle Kalandi Charan Pradhan
Guru Dayal Kumar
Bhuvesh Sharma
Reassessment and Determinants of Multidimensional Poverty: Evidence from Cross-Country Analysis
International Journal of Empirical Economics
Health
education
living standard
ease of doing business
multidimensional poverty index
regression analysis
title Reassessment and Determinants of Multidimensional Poverty: Evidence from Cross-Country Analysis
title_full Reassessment and Determinants of Multidimensional Poverty: Evidence from Cross-Country Analysis
title_fullStr Reassessment and Determinants of Multidimensional Poverty: Evidence from Cross-Country Analysis
title_full_unstemmed Reassessment and Determinants of Multidimensional Poverty: Evidence from Cross-Country Analysis
title_short Reassessment and Determinants of Multidimensional Poverty: Evidence from Cross-Country Analysis
title_sort reassessment and determinants of multidimensional poverty evidence from cross country analysis
topic Health
education
living standard
ease of doing business
multidimensional poverty index
regression analysis
url https://www.worldscientific.com/doi/10.1142/S2810943024500148
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AT bhuveshsharma reassessmentanddeterminantsofmultidimensionalpovertyevidencefromcrosscountryanalysis