Recent advances in social science surveys include collection of biological samples. Although biomarkers offer a large potential for social science and economic research, they impose a number of statistical challenges, often being distributed asymmetrically with heavy tails. Using data from the...

We use a set of biomarkers to measure inequality of opportunity (IOp) in health in the UK. Applying a direct ex ante IOp approach, we find that inequalities in health attributed to circumstances account for a non-trivial part of the total health variation. For example, observed circumstances...

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 monthly data from the Understanding Society (UKHLS) COVID-19 Survey we analyse the evolution of unmet need and assess how the UK health care system performed against the norm of horizontal equity in health care access during the first wave of COVID-19 wave. Unmet need was most evident for...

We develop an empirical approach to analyse, measure and decompose Inequality of Opportunity (IOp) in health, based on a latent class model. This addresses some of the limitations that affect earlier work in this literature concerning the definition of types, such as partial observability, the...

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...

This paper extends the earlier work of Davillas and Jones (2021) on socioeconomic inequality in mental health, measured by the General Health Questionnaire (GHQ), to include the second national lockdown up to March 2021.

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...

Using monthly data from the Understanding Society (UKHLS) COVID-19 Survey we analyse the evolution of unmet need and assess how the UK health care system performed against the norm of horizontal equity in health care access during the first wave of COVID-19 wave. Unmet need was most evident for...

Using administrative DVLA data matched with micro-data from Understanding Society – the UK Household Longitudinal Study we estimate income-related inequalities in ownership of vehicles with a set of safety features and we apply a regression-based decomposition method for rank-dependent...