The Oxford Summer School in Economic Networks will bring together students from a range of disciplines for a week to learn about the techniques, applications and impact of network theory in economics and development. We will have globally leading experts guide lectures and interactive workshops on topics such as social networks, games and learning, financial networks, economic complexity and urban systems.
We look forward to welcoming a large number of world renowned experts in economic networks and complexity science. Confirmed guest speakers and panellists for the 2018 edition include Prof Fernando Vega-Redondo (keynote), Prof Peter Grindrod, Dr Mariano Beguerisse, Prof Renaud Lambiotte, Dr Taha Yasseri, Prof Mihaela van der Schaar, Dr Bassel Tarbush, Dr Elsa Arcaute, Prof David Cox, Prof Robert Northcott, Dr Jurgen Doornik, Prof Rama Cont, Prof Doyne Farmer and Dr Adrian Carro.
Dates: June 25-29, 2018
Location: Mathematical Institute, Oxford Martin School and Department of Statistics, University of Oxford
- This school is targeted towards graduate students (Masters/PhD) from Mathematics, Statistics, Economics, Social Sciences, Geography, Development, and Public Policy. Other disciplines and young professionals welcome.
- Admission is closed.
- We will admit a small number of outstanding undergraduates.
- You will need some mathematical/computational background (in particular, familiarity with university level linear algebra and dynamical systems, and some coding experience). Experience with networks is an advantage but not compulsory.
- Practical tutorials will be held in Matlab. We will cater for Matlab beginners, but students are expected work on their own laptop and have a Matlab installation from their home institution.
- The registration fee including all tuition and social events will be 200 pounds sterling. Note: this does not include meals or accommodation. It does include social events.
- If accepted, you will need to pay the fee within 2 weeks of acceptance. This payment deadline can occasionally be extended by special request.
- Summer accommodation in Oxford fills up fast! Affordable university college rooms may be available here.
- We will have a small number of accommodation bursaries (full or part payment of accommodation in a college room for 5 nights, June 24th-28th). To be considered for a bursary, please select that option when you apply for a place.
Organising team (Mathematical Institute, Institute for New Economic Thinking and Oxford Martin School): Neave O'Clery (Chair, MI), Francois Lafond (INET, OMS), Nils Rochowicz (MI, INET), Marco Pangallo (INET), Maria Chanona (INET, MI), Penny Mealy (INET), Hattie Moody (MI) and all the helpers!
Contact: For more information, contact us at email@example.com
Public Lecture organised by the Oxford Summer School in Economic Networks
Title: Contagious disruptions and complexity traps in economic development
Speaker: Prof. Fernando Vega-Redondo from Bocconi University
Date: Thursday, 28th June 2018 at 5pm
Venue: Lecture Theatre 1, Mathematical Institute, University of Oxford
Poor economies not only produce less; they typically produce things that involve fewer inputs and fewer intermediate steps. Yet the supply chains of poor countries face more frequent disruptions---delivery failures, faulty parts, delays, power outages, theft, government failures---that systematically thwart the production process. To understand how these disruptions affect economic development, we model an evolving input--output network in which disruptions spread contagiously among optimizing agents. The key finding is that a poverty trap can emerge: agents adapt to frequent disruptions by producing simpler, less valuable goods, yet disruptions persist. Growing out of poverty requires that agents invest in buffers to disruptions. These buffers rise and then fall as the economy produces more complex goods, a prediction consistent with global patterns of input inventories. Large jumps in economic complexity can backfire. This result suggests why "big push" policies can fail, and it underscores the importance of reliability and of gradual increases in technological complexity.