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

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.