Impact of Water Poverty Index on Human Capital Index: A Case Study of India

Abstract: This paper aims to investigate the impact of various dimensions of water poverty on human capital in India. In order to take into account, the multidimensional nature of water poverty, the Water Poverty Index (WPI) was constructed using five components: resource, access, capability, environment, and secondary source. Using weighted arithmetic mean, the final WPI was computed. Human capital Index (HCI) was developed according to World Bank methodology to account for human capital in India. Further, the impact of components of WPI on HCI was evaluated using structural equation modelling. The findings reveal that Bihar, Uttar Pradesh, and Jammu and Kashmir have the lowest human capital. At the same time, water poverty was found to be the highest in Jharkhand, Madhya Pradesh, and Bihar. The study also found that access to safe, uncontaminated water and sanitation significantly impacts human capital in India. This research contributes to the scant literature on the effects of water poverty on human capital in developing nations such as India. Keywords: Human Capital Index, Water Poverty Index, India, Structural Equation Modelling

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-20
DOI
https://doi.org/10.5281/zenodo.16225748
Primary Topic
Water Resources and Sustainability
Type
article
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article

Impact of Water Poverty Index on Human Capital Index: A Case Study of India

Zenodo (CERN European Organization for Nuclear Research)
Water Resources and Sustainability
article

Impact of Water Poverty Index on Human Capital Index: A Case Study of India

article en

Abstract

Abstract: This paper aims to investigate the impact of various dimensions of water poverty on human capital in India. In order to take into account, the multidimensional nature of water poverty, the Water Poverty Index (WPI) was constructed using five components: resource, access, capability, environment, and secondary source. Using weighted arithmetic mean, the final WPI was computed. Human capital Index (HCI) was developed according to World Bank methodology to account for human capital in India. Further, the impact of components of WPI on HCI was evaluated using structural equation modelling. The findings reveal that Bihar, Uttar Pradesh, and Jammu and Kashmir have the lowest human capital. At the same time, water poverty was found to be the highest in Jharkhand, Madhya Pradesh, and Bihar. The study also found that access to safe, uncontaminated water and sanitation significantly impacts human capital in India. This research contributes to the scant literature on the effects of water poverty on human capital in developing nations such as India. Keywords: Human Capital Index, Water Poverty Index, India, Structural Equation Modelling

Zenodo (CERN European Organization for Nuclear Research)
Indian Institute of Management Rohtak (IN), Birla Institute of Technology and Science, Pilani (IN)
No poverty
Openalex Percentile: Top 58%
Water Resources and Sustainability
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