PhD Projects in Economics

The Macroeconomics of Longevity

Apply Now

Project Summary

Economics has analysed in detail the consequences of an ageing society and a shift in the age structure towards an older population. However perhaps even more important is how individual’s and society adapt to longer lives. Increases in life expectancy will change a host of decisions around human capital – including health and education. They will also change attitudes towards risk seeking and demand changes in organizational structure. Just as technological progress has important and rich implications for macroeconomic models so too does longevity. Creating tractable analytical models that identify the mechanisms through which longevity and ageing impact the economy and how policies can adapt to longer lives to achieve better social and economic outcomes is of first order economic importance. This project aims to develop a range of different models linking together life cycle, health, knowledge and production to develop insights into a longevity economy.  

Why it matters

  • Enables more realistic macroeconomic models of longevity, ageing, and fiscal sustainability.
  • Provide insight into the behaviour of older and younger individuals in response to longevity gains.  
  • Identifies the most impactful stages in the life-course for health or skills interventions.
  • Provides policymakers with a narrative-shaping, decision-relevant metric that can drive macroeconomic policy in the face of demographic change.  

Why EIT Oxford is the place

EIT specialises in the economics of longevity and this topic builds on Oxford’s strength in macroeconomics, EIT’s emphasis on longevity and its links from academic practitioners through to policymakers.  

Potential Supervisors  

  • Supervisors are to be confirmed

Skills Recommended

  • Strong economic theory skills in modelling and equilibrium
  • Strong quantitative background (econometrics, statistics or applied maths)
  • Programming proficiency (Python/R)

Skills to be Developed  

  • Mathematical modelling
  • Translation of academic research into policy relevance
  • Bridging studies from other disciplines

University DPhil Courses 

Supervisors

We are bringing together experts from across the globe, with a shared drive to create lasting impact.

VP of AI Research & Principal Scientist

Dr Danilo Jimenez Rezende

VP of AI Research for AI & Robotics at EIT. Former Director at Google DeepMind.

VP of Applied Machine Learning

Dr Matej Macak

VP of Applied Machine Learning for AI & Robotics at EIT. Chief Technologist at Every Cure.

Principal Scientist & Executive Vice President - AI & Robotics Institute

Professor Cecilia Lindgren

Co-Director of the AI & Robotics Insitute at EIT, Professor of Genomics of Endocrinology and Metabolism at the University of Oxford, Director of the Oxford Big Data Institute.

Executive Director & Principal Scientist - AI & Robotics Institute

Professor Chris Holmes

Co-Director of AI & Robotics Institute at EIT. Professor of Biostatistics at the University of Oxford. Researching theory, methods and applications of statistics and statistical modelling.