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...

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...

The widespread consumer adoption of low-carbon technologies (LCTs) is a cornerstone of net zero targets worldwide, however LCTs may not be equally distributed across socioeconomic characteristics. Our paper contributes to the literature by exploring socioeconomic inequality in LCT adoption and...

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 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...

To reduce infection rates during the first UK wave of the COVID-19 outbreak, a first lockdown was announced on March 23, 2020, with a final easing of the restrictions on July 4, 2020. Among the most important public health costs of lockdown restrictions are the potential adverse effects on...

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...

We capitalise on an opportunity in the UK Household Longitudinal Study, which asks respondents the same SAH question with identical wording two times. This is done once with a self-completion and once with an open interview mode within the same household interview over four waves. We estimate...

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...