Five-dimensional unequally weighted mapping methodology for measuring the level of human development: an application in Bagmati Province, Nepal

Ishwari Prasad Banjade () and Srijan Lal Shrestha ()
Additional contact information
Ishwari Prasad Banjade: Tribhuvan University
Srijan Lal Shrestha: Tribhuvan University

Asia-Pacific Journal of Regional Science, 2024, vol. 8, issue 4, No 7, 1135-1161

Abstract: Abstract Human development index (HDI) was estimated based on an alternative and modified methodology. We considered five components to be relatively more rational and representative of the HDI: income, education, health, social governance, and technological adaptation. Reviews suggested for the formulation of hypotheses that the present HDI fails to address many factors included in SDGs and hence is insufficient in its representativeness. In addition, the components need not necessarily be equally weighted. The validity of HDI was improved by inclusion of social governance and technological adaptation. The method of mapping between SDGs and HDI components was used along with the Laplace rule of probability to determine the component weights, and HDI was estimated by weighted geometric mean. The modified methodology was applied by conducting a sample household survey in Bagmati Province, Nepal, in 2023, based on three-stage stratified random sampling that covered mountain to Terai regions of the province including 17 rural and urban municipalities with a sample size of 569 households. The estimated weights of the components differed notably (0.16–0.26), which implied varied levels of importance and could be crucial in development planning. Survey results quantified sub-indices of HDI as income = 0.341 (95% CI 0.337, 0.345), education = 0.650 (95% CI 0.645, 0.655), health = 0.807 (95% CI 0.806, 0.807), social governance = 0.678 (95% CI 0.674, 0.681), and technological adaptation = 0.462 (95% CI 0.454, 0.469). These figures suggest a high priority for economic progress and technological support for the people of Bagmati Province. Finally, the estimated HDI of the province was found to be 0.559 (95% CI 0.555, 0.564), which is substantially lower than the current UNDP-estimated HDI value (0.661) and warrants more focused development policies than those based on the UNDP HDI value. Moreover, the inequality adjusted HDI was found to be substantially lower by 13.4% compared to HDI and demonstrates the existence of considerable inequalities in the province. Overall, the comprehensively modified HDI is useful to enhance policy implications, particularly in developing countries like Nepal and results suggested that Bagmati Province would suffer from inappropriate development policies due to overestimated UNDP-adopted HDI.

Keywords: Human development; Inequality adjusted human development; Laplace probability; Mapping; Sustainable development goals; Weighted geometric mean and standard error (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s41685-024-00359-1 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:apjors:v:8:y:2024:i:4:d:10.1007_s41685-024-00359-1

Ordering information: This journal article can be ordered from
https://www.springer ... cience/journal/41685

DOI: 10.1007/s41685-024-00359-1

Access Statistics for this article

Asia-Pacific Journal of Regional Science is currently edited by Yoshiro Higano

More articles in Asia-Pacific Journal of Regional Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().