There is a concern that ordered responses on health questions may differ across populations or even across subgroups of a population. This reporting heterogeneity may invalidate group comparisons and measures of health inequality. This paper proposes a test for differential reporting in ordered...

Although there is a large gap between Black and White American life expectancies, the gap fell 48.9% between 1990-2018, mainly due to mortality declines among Black Americans. We examine age-specific mortality trends and racial gaps in life expectancy in rich and poor U.S. areas and with...

Large differences in mortality rates across those with different levels of education are a well- established fact. This association between mortality and education may partly be explained by confounding factors, including cognitive ability. Cognitive ability may also be affected by education so...

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.

Using nine waves of data from Understanding Society (UKHLS), we study the expansion of higher education in the UK, since the landmark Robbins Report in 1963, and its consequences for levels of and inequalities in household income, physical and mental health. We estimate fixed effects models...

We designed an experiment to explore the extent of measurement error in body mass index (BMI), when based on self-reported body weight and height. We find that there is a systematic age gradient in the reporting error in BMI, while there is limited evidence of systematic associations with...

The economics of obesity literature implicitly assumes that measured anthropometrics are error-free and they are often treated as a gold standard when compared to self-reported data. We use factor mixture models to analyse and characterize measurement error in both self-reported and measured...

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 the UK Household Longitudinal Study (UKHLS) to compare measures of socioeconomic inequality in psychological distress, measured by the General Health Questionnaire (GHQ), before (Waves 9 and the Interim 2019 Wave) and during the first wave of the COVID-19 pandemic (April to July...

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...