Jihye Kim

My research has been focused on applying advanced statistical methods to analyse diverse socio-demographic topics, particularly examining a range of work and employment issues of children or young people in the Global South through the lenses of age, gender, social, cultural and institutional components. For example, my recent publication, ‘Harmful forms of child labour in India from a time-use perspective’ (Kim and Olsen, 2023, Development in Practice), has studied the indecent and extreme work conditions of Indian children and their disaggregated patterns by age and industrial areas based on socio-economic and gender approaches. I published ‘Predicting child-labour risks by norms in India’ in Work, Employment and Society (Kim et al., 2022), a prominent sociology journal on employment and industrial relations. In this paper, a child-labour risk model based on integrating two datasets incorporate the norms and socio-economic variables in the estimation of child labour. It provides a way to predict the risks of child labour according to households’ socio-economic backgrounds and locations. Another previously published work, ‘A Bayesian estimation of child labour in India’ (Child Indicators Research, Kim et al., 2020), investigates methods to enhance the estimation of child labour. The study demonstrates that Bayesian data integration could address uncertainty or underestimation regarding child labour. I have also been involved in several projects, making significant contributions to publishing papers such as the analysis of cumulative COVID-19-related deaths in India, the study of women’s work and time-use in India, hospital length of stay of Covid-19 patients in England, and future migration scenarios for Europe.

Methodologically, my research has extensively employed Bayesian statistics, and I have developed expertise in utilising a data-combining approach through Bayesian hierarchical models. During my PhD studies, I acquired a thorough understanding of Bayesian inference and applied various statistical models, such as multi-level analysis, data synthesis, structural equation modelling, and longitudinal data analysis. For data analysis, I primarily use R, STAN, JAGS, and STATA, for which I possess a good level of knowledge and skills.