Project Summary

Rapid technological change in AI and Robotics are likely to have significant impact on a range of economic variables – from GDP and productivity through to employment and inequality. The aim of this work is to develop theoretical and empirical models to understand this impact, identify and calibrate the mechanisms at work, determine how different forms of technological change have different impacts and what are the optimal policy responses.

The research will:

• Develop theoretical general equilibrium models with heterogenous agents to understand the impact of AI and robotics.
• Quantify the macroeconomic impact of technological change induced by AI and robotics and analyse the sectoral and distributional implications.
• Examine the interaction between techonological progress and demographic change
• Empirically estimate the impact of AI and robotics on productivity and employment
• Investigate optimal policy responses to rapid progress in AI and robotics.  

Why it Matters

AI and robotics will be one of the most transformational forces for the economy. Possible outcomes vary depending on assumptions about the breadth and speed of change and vary from utopian outcomes of abundance and increases in leisure to the dystopian scenario of no output gains but rising unemployment and inequality. In the past major technological revolutions have led to a mix of economic and social upheaval. Understanding the impact of AI and robotics and the policies needed to support optimal outcomes will be a key policy trend.  

Why EIT is the place

EIT provides access to cutting edge trends in AI and robotics through its AI and Robotics team, enabling a deep understanding of how this technology is evolving. In combination with a strong Economics group, the strength of Oxford University Economics Department and access to global experts in this area, EIT offers a first rate research environment linked to state of the art methods.  

Potential Supervisors

• Supervisors are to be confirmed

Skills Recommended

• Graduate micro and macro theory (dynamic optimisation, GE)
• Solid quantitative background in maths/stats (stochastic calculus, numerical methods)
• Programming experience (Python, Julia or MATLAB)
• Strong interest in macroeconomics and labour markets.  

Skills to be Developed

• Continuous-time and discrete-time heterogenous agent modelling
• Sparse matric and GPU accelerated solvers for HJB-KFE systems
• Welfare analysis and policy simulation
• Translation skills for decision makers

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University DPhil Courses

• DPhil in Economics