Modelling an Evolving Economy

A workshop on using new methods to measure structural economic change & inform policy

New sources of data and ways to analyse them with machine learning, Artificial Intelligence (AI) and complexity science can help to capture the emergence of new scientific fields, technologies, industries and occupations, improving our ability to measure and model economic change and inform policy, funding and investment decisions. This includes how to identify and support emerging technologies and industries, level up local economies, make innovation more inclusive and accelerate the transition to a green economy.

This workshop will bring leading scholars, policymakers and statistical agencies at the forefront of this agenda together to discuss the state of the art and what’s needed to maximise the impact of these new data sources and methods on our understanding of the economy and the effectiveness of economic and research and innovation policy.

The in-person attendance places at this event has now sold out and a waiting list is in place. To register for a place on the waiting list please click here.

Due to popular demand we will also be live streaming the event. To register for an online place please click here. Please note only registered online attendees will be able to access the live stream.

9:15 am – 9:45 am Registration

9:50 am – 10:00 am Welcome

10:00 am – 10:45 am Keynote address 1

Regional Resilience in Today’s Evolving Economy

Mercedes Delgado, Copenhagen Business School, MIT Innovation Initiative and Institute for Strategy and Competitiveness at Harvard Business School

10:45 am – 11:25 am Session 1 – Measurement

Economic Growth Goes Fractal: The Changing Structure of UK Venture Capital

Anna Valero, London School of Economics

A Bottom-up Industrial Taxonomy Using Web-data

Juan Mateos-Garcia, Nesta and ESCoE

11:25 am – 11:45 am Tea and coffee break

11:45 am – 12:30 pm Keynote address 2 

J. Doyne Farmer, The Institute for New Economic Thinking at the Oxford Martin School

12:30 pm – 12:50 pm Session 1 continued – Measurement

Work2Vec: Learning a Latent Representation of Labor Demand

Daniel Rock, Wharton (virtual presentation)

12:50 pm – 2:00 pm Lunch break

2:00 pm – 3:00 pm Session 2 – Modelling

Is Innovation a Process of Combination? A Roundup of Recent Evidence

Matt Clancy, Institute for Progress

Pathway of Innovation: Micro to Macro

Hyejin Youn, Northwestern University / Santa Fe Institute

Measuring Exploration and Exploitation Patterns in Technological Innovation

Mirko Draca, University of Warwick-CAGE

3:00 pm – 4:00 pm Session 3 – Informing

Using Data Science to Better Understand Economic Activity

Arthur Turrell, Office for National Statistics

Data Science for STI Policy: On Realistic Opportunities and Major Hurdles

Caroline Paunov, OECD

The Policy Implications of Economic Complexity

Viktor Stojkosi, Macedonian Academy of Sciences and Arts

4:00 pm – 4:30 pm Tea and coffee break

4:30 pm – 5:30 pm Panel discussion

Panel Chair: Rebecca Riley, ESCoE and King’s College London

Panel Members including:

• Grant Fitzner, Office for National Statistics
• Laura Gilbert, No 10 Data Science Unit
• Stian Westlake, Royal Statistical Society

5:30 pm – 6:30 pm Drinks reception