In refereed journals
Davillas, A., Jones, A. Regional inequalities in adiposity in England: Distributional analysis of the contribution of individual-level characteristics and the small area obesogenic environment. Economics & Human Biology - Accepted (in press).
Carrieri, V., Davillas, A., Jones, A. A latent class approach to inequity in health using biomarker data. Health Economics. https://doi.org/10.1002/hec.4022.
Davillas, A., Jones, A. (2020). Ex ante inequality of opportunity in health, decomposition and distributional analysis of biomarkers. Journal of Health Economics, 102251. https://doi.org/10.1016/j.jhealeco.2019.102251
Davillas, A., Pudney, S. (2019). Biomarkers as precursors of disability. Economics & Human Biology, 100814.
Davillas A, Jones AM. (2018). Parametric models for biomarkers based on flexible size distributions. Health Economics. 1–8. https://doi.org/10.1002/hec.3787
Davillas, A., Pudney, S. (2017). Concordance of health states in couples: Analysis of self-reported, nurse administered and blood-based biomarker data in the UK Understanding Society panel. Journal of Health Economics, 56, 87-102.
Davillas, A., Benzeval, M., Kumari, M. (2017). Socio-economic inequalities in C-reactive protein and fibrinogen across the adult age span: Findings from Understanding Society. Scientific Reports, 7(1), 2641.
Davillas, A., Benzeval, M. (2016). Alternative measures to BMI: Exploring income-related inequalities in adiposity in Great Britain. Social Science & Medicine, 166, 223-232.
Davillas, A., Benzeval, M., Kumari, M. (2016). Association of Adiposity and Mental Health Functioning across the Lifespan: Findings from Understanding Society (The UK Household Longitudinal Study). PloS one, 11(2), e0148561.
Daouli, J., Davillas, A., Demoussis, M., Giannakopoulos, N. (2014). Obesity persistence and duration dependence: evidence from a cohort of US adults (1985–2010). Economics & Human Biology, 12, 30-44.
Peer-reviewed book chapters
Davillas, A., Jones, A.,Benzeval, M. (2019). The income-health gradient: Evidence from self-reported health and biomarkers using longitudinal data on income. In Panel Data Econometrics: Empirical Applications, Elsevier - In press.
Davillas, A., Pudney, S. Baseline health and public healthcare costs five years on: a predictive analysis using biomarker data in a prospective household panel. R&R requested by the Journal of Health Economics
Davillas, A., Pudney, S. (2020). Biomarkers, Disability and Health Care Demand.
Benzeval, M., Davillas, A., Kumari, M., & Lynn, P. (2014). Understanding Society: The UK Household Longitudinal Study: Biomarker User Guide and Glossary. Colchester, University of Essex.