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Purpose: This study on spatial analysis of child labour in India is a macro level analysis on child labour using the census data, 2011 of Government of India. The population census which is conducted once in 10 years only provides district level data on work-force distribution. The study has spatial analysis of child labour in the age group of 5–14 years in India. To assess the magnitude of the children in the labour force, district level data of Census 2011 has been used in the study. The study has made an attempt to identify the districts where there is high level of children in the labour force. This paper aims to estimate the magnitude and trends of children's workforce participation using the census data as it is the only data base, which is available at the district level since 1961 onwards. The study has made an attempt to identify the clustering of child labour across districts in India and how child labour is clustered by different background characteristics. Design/methodology/approach: The study has used ArcGIS software package, GeoDa software and local indicator of spatial association test. Findings: The findings of study reveal that the proportion of rural, total fertility rate (TFR) and poverty headcount ratio is positively associated, whereas female literacy and the pupil-teacher ratio are negatively associated with child labour. It suggests that in the hot-spot areas and areas where there is a high prevalence of child labour, there is need to increase the teacher's number at the school level to improve the teacher-pupil ratio and also suggested to promote the female education, promote family planning practices to reduce TFR in those areas for reducing the incidences of child labour. Research limitations/implications: The study also recommends that the incidences of child labour can be controlled by a comprehensive holistic action plan with the active participation of social workers. Practical implications: The promulgation of effective legislation, active involvement of judiciary and police, political will, effective poverty alleviation and income generation programmes, sensitisation of parents, corporates and media can play effective role in mitigating the incidences of child labour in India. To achieve the sustainable development goals (SDGs) adopted by world leaders in 2015 to eradicate child labour in all its forms by 2025. Social implications: The study aims to achieve the SDGs adopted by world leaders in 2015 to eradicate child labour in all its forms by 2025. Originality/value: The study is purely original and there are no such studies in Indian context by using the latest software. [ABSTRACT FROM AUTHOR]

• Multidimensional child poverty is notably more prevalent among STs and SCs. • Standard of living, ECD, and WASH are the dimensions that need committed thrust. • STs and SCs contribute more to the national MCP than their share of the population. • Head of household characterised by female gender, older age, and higher level of education is associated with a lower likelihood of MCP. • MCP tends to be more pronounced in nuclear families, households with 7+ members, rural areas, and central and eastern regions. Children are among the most vulnerable groups worldwide, bearing a disproportionate share of the burden of poverty. One-third of children, compared to one-sixth of adults, are multidimensionally poor. Experiencing poverty in childhood can have long-term negative consequences across generations. As a result, multidimensional poverty measures have recently been investigated in the child poverty literature. This study analysed multidimensional poverty among children (0–59 months) in India using the Alkire-Foster's counting approach and looked into how it differs across the country's well-known social stratification, the Caste system. The determinants of multidimensional child poverty (MCP) have been determined using multiple logistic regression. By using National Family Health Survey, 2019–21 data, the study revealed that the incidence of MCP in India is 32 %; highest among Scheduled Tribes (STs) (50 %), followed by Scheduled Castes (SCs) (37 %), Other Backward Classes (OBCs) (30 %) and 'Others' (22 %). Across all the Castes highest rates of deprivation were recorded in the indicators of standard of living and early childhood development (ECD) dimensions; together, they contribute more than 50 % to the MCP index (MCPI). The contribution of the water, sanitation, and hygiene (WASH) dimension in MCPI of STs is also noticeably higher (20.2 %). Of the 15 indicators considered, availability of TV/Radio, followed by immunisation, sanitation, cooking fuel, housing condition, and stunting, are the leading contributors with a combined contribution of more than 55 %. A child being a male, of higher birth order and born to a mother with higher years of schooling was more likely to experience multidimensional poverty. The household head's sex, age, and years of schooling were significantly associated with MCP. Across all castes, children from nuclear families, 7 + household members, higher number of children per woman, rural areas, central, eastern and north-eastern (except STs) regions were more likely to experience multidimensional poverty. [ABSTRACT FROM AUTHOR]