Micro to Macro: Causal Micro Evidence for Macro Prevention Models
PhD Projects in Economics
Project Summary
The aim is to generate robust causal evidence on the economic consequences of better health. This will be achieved by exploiting rich, linked administrative health and earnings records to obtain quasi-experimental estimates of how medical interventions and major health events affect workers鈥 employment, earnings trajectories, and firm-switching decisions over time. The focus is on credible identification: natural policy roll-outs, clinical eligibility thresholds, and diagnostic timing shocks will isolate causal effects that standard cross-sectional studies miss. These high-resolution estimates will form the empirical backbone for evidence-based decisions on prevention subsidies, workplace policy, and social insurance design, and will inform the calibration of macro-prevention models.
naction.
- Governments require reliable numbers on the economic cost of chronic disease and the payoff to prevention, yet most existing figures rely on correlations or aggregate averages.
- Accurate micro parameters are essential inputs for agencies such as finance ministries and healthcare technology assessment bodies when assessing the fiscal and welfare implications of health spending.
Why EITis the place
EIT holds secure access to a portfolio of rich data assets that link health and labour鈥憁arket histories. Daily interaction with EIT鈥檚 prevention, clinical and data鈥憇cience teams fosters methodological innovation and rapid policy translation. Oxford鈥檚 economics and public鈥憄olicy departments add a world鈥慶lass setting for labour鈥慹conomics training and debate.
鈥Potential Supervisors鈥
- Supervisors are to be confirmed
Skills Recommended
- Graduate econometrics, particularly causal inference methods
- Proficiency in Python, R or Stata for large鈥憇cale data analysis
- Interest in labour鈥 and health鈥慹conomics questions
Skills to be Developed
- Advanced quasi鈥慹xperimental techniques (difference鈥慽n鈥慸ifferences, event studies, regression discontinuity, instrumental variables) applied to administrative micro鈥慸ata
- Translation of empirical findings into policy recommendations and model calibration
- Communication of results to interdisciplinary audiences in health, economics and public finance
University DPhil Courses鈥
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