We measure unfair health inequality in the UK using a novel data-driven empirical approach. We explain health variability as the result of circumstances beyond individual control and health-related behaviours. We do this using model-based recursive partitioning, a supervised machine learning...

We use data from Wave 9 of UK Household Longitudinal Study (UKHLS) and the April 2020 Wave of the UKHLS COVID-19 survey to compare measures of ex ante inequality of opportunity (IOp) in psychological distress, as measured by the General Health Questionnaire (GHQ), before (Wave 9) and at the...

Using the 2011 and 2015 waves of the China Health and Retirement Longitudinal Study (CHARLS) linked with the 2014 CHARLS Life History Survey, we provide a comprehensive analysis on inequality of opportunity (IOp) in both body mass index (BMI) and waist circumference (WC) among middle-aged and...

We use data from Wave 9 of UK Household Longitudinal Study (UKHLS) and the April 2020 Wave of the UKHLS COVID-19 survey to compare measures of ex ante inequality of opportunity (IOp) in psychological distress, as measured by the General Health Questionnaire (GHQ), before (Wave 9) and at the...

We present a comprehensive analysis of ex ante inequality of opportunity (IOp) in health among Chinese adults aged 60+ and decompose the contributions of different sets of circumstances. Data are drawn from the 2011 and 2015 waves of the China Health and Retirement Longitudinal Study (CHARLS)...