Overview

For most of the twentieth century the methodological toolkit of economics was centred on equilibrium models, analytical proofs, and traditional econometric methods. But the advent of inexpensive high-speed computing, the explosion of data made available by the web, and methodological advances in other fields have opened up economics to an array of new tools and methods. INET Oxford's Economic Modelling group (EMoD) has pioneered a new approach to econometrics using computerised automatic model selection that can detect and model multiple structural breaks in time series, model non-linearities, and provide significantly better forecasts than traditional methods. The Complexity Economics Programme has developed novel methods of modelling nested, multiple level networks which are a common feature of many economic systems (e.g. supply chains, interbank networks). The group are also leaders in the use of agent-based modelling and are developing the world's first large-scale agent-based macroeconomic-financial model. INET Oxford researchers are also experimenting with evolutionary models of economic growth, machine learning on 'Big Data' sets and collaborating with experimental economists to incorporate behavioural heuristics derived from laboratory experiments into economic models.

Members of the Institute are also exploring the philosophical, moral, and behavioural foundations of the economy. Examples of this include research on new approaches to normative (i.e., welfare) economics, participation in an initiative on “new moral political economy”, and work on understanding the role of prosocial behaviours, cooperation, institutions, and culture in the economy.

Related Projects


Recent Publications

Mar 2025
INET Working Paper
No. 2025-06 - Systems thinking in UK environmental policy making
Pete Barbrook-Johnson ,  Domenica Cox ,  Alexandra S. Penn
Mar 2025
INET Working Paper
2025-08 - Skill and spatial mismatches for sustainable development in Brazil
Anna Berryman ,  Joris Bucker ,  Fernanda Senra de Moura ,  Pete Barbrook-Johnson ,  Marek Hanusch ,  Penny Mealy ,  J. Doyne Farmer ,  R. Maria del Rio-Chanona
Mar 2025
Journal
Improving empirical models and forecasts with saturation-based machine learning
in Annals of Operations Research
Andrew Martinez ,  Neil Ericsson
Mar 2025
Journal
Agent-Based Modeling in Economics and Finance: Past, Present, and Future
in Journal of Economic Literature
Robert Axtell ,  J. Doyne Farmer
Feb 2025
Paper
Robust Policy Design in Agent-Based Simulators using Adversarial Reinforcement Learning
Akash Agrawal ,  Joel Dyer ,  Aldo Glielmo ,  Michael Wooldridge
Jan 2025
INET Working Paper
Dec 2024
Journal
The impact of prudential regulation on the UK housing market and economy: Insights from an agent-based model
in Journal of Economic Behavior & Organization
Marco Bardoscia ,  Adrián Carro ,  Marc Hinterschweiger ,  Mauro Napoletano ,  Lilit Popoyan ,  Andrea Roventini ,  Arzu Uluc
Nov 2024
Chapter
Econometric forecasting of climate change
Jennifer L. Castle ,  David F. Hendry ,  J. Isaac Miller
Nov 2024
Journal
Supply network stress-testing of food security on the establishment-level
in International Journal of Production Research
Christian Diem ,  William Schueller ,  Melanie Gerschberger ,  Johannes Stangl ,  Beate Conrady ,  Markus Gerschberger ,  Stefan Thurner
Oct 2024
Video
David Hendry: Forecasting UK Inflation during 2021-24
David Hendry ,  Jennifer Castle ,  Jurgen Doornik
Sept 2024
Journal
Approximate Bayesian Computation with Path Signatures
in Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence
Joel Dyer ,  Patrick Cannon ,  Sebastian M Schmon
View All Related Publications

Who's Involved