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<p>Women’s participation in the workforce is a cornerstone of gender equity and socioeconomic development. Despite India’s economic growth, women’s unemployment remains persistently high, with significant geographical and socioeconomic disparities. This study identifies high-risk areas and associated factors by examining the spatial and multilevel determinants of women’s unemployment. Data from the National Family Health Survey (NFHS-5, 2019–2021) involving 108,014 women aged 15–49 years across 707 districts were analysed. A mixed-effects multilevel logistic regression model examined individual, household, and regional factors. Spatial analysis techniques, including Moran’s I and LISA, identified clustering patterns and high-risk zones of unemployment. The result shows significant spatial dependence in women’s unemployment in India (Moran’s I = 0.529; p&lt; 0.001). The spatial analysis identified 186 districts as hot-spot areas, primarily located in the northern, eastern, and central parts of India. Additionally, 102 districts were found to be cold-spot areas, mainly covering the southern and northeastern regions. Socioeconomic factors, such as marital status, education level, and wealth index, significantly influenced unemployment. The study suggests that targeted interventions should prioritise high-risk areas characterised by high unemployment rates, aiming to encourage skill development, entrepreneurship, promote women’s education, and flexible work opportunities. This geographical analysis facilitates the reduction of implementation time and aids in the customisation of programmes according to various risk zones. This work contributes to enhancing gender equity and economic inclusion in India.</p>

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Spatial Disparities and Multilevel Analysis of Factors Associated with Women Unemployment in India: Evidence from Nationally Representative Data

  • 期刊论文

  • 发表日期：

    2025年8月28日

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  • Ramajayam Anbazhagan,
  • Bagavandas Mappillairaju

摘要

Women’s participation in the workforce is a cornerstone of gender equity and socioeconomic development. Despite India’s economic growth, women’s unemployment remains persistently high, with significant geographical and socioeconomic disparities. This study identifies high-risk areas and associated factors by examining the spatial and multilevel determinants of women’s unemployment. Data from the National Family Health Survey (NFHS-5, 2019–2021) involving 108,014 women aged 15–49 years across 707 districts were analysed. A mixed-effects multilevel logistic regression model examined individual, household, and regional factors. Spatial analysis techniques, including Moran’s I and LISA, identified clustering patterns and high-risk zones of unemployment. The result shows significant spatial dependence in women’s unemployment in India (Moran’s I = 0.529; p< 0.001). The spatial analysis identified 186 districts as hot-spot areas, primarily located in the northern, eastern, and central parts of India. Additionally, 102 districts were found to be cold-spot areas, mainly covering the southern and northeastern regions. Socioeconomic factors, such as marital status, education level, and wealth index, significantly influenced unemployment. The study suggests that targeted interventions should prioritise high-risk areas characterised by high unemployment rates, aiming to encourage skill development, entrepreneurship, promote women’s education, and flexible work opportunities. This geographical analysis facilitates the reduction of implementation time and aids in the customisation of programmes according to various risk zones. This work contributes to enhancing gender equity and economic inclusion in India.