Mathematical Institute, University of Oxford
Anton Pichler is a DPhil student in Mathematics at the University of Oxford under the supervision of Professor Doyne Farmer and Professor Cameron Hepburn. His research interest encompass technological evolution, innovation and complex economic networks. In his thesis, Anton develops methods for technology forecasting which incorporate economic network data with a special focus on green energy technologies.
Anton holds a BA in Political Science and a BSc in Economics, both awarded by the University of Vienna. He completed the MSc degree in Quantitative Finance at the Vienna University of Economics and Business. Anton is also an junior external faculty member of the Complexity Science Hub Vienna.
The rise of science in low-carbon energy technologies
21 Jan 21
Designing efficient allocation of R&D budgets requires a better understanding of how Low-Carbon Ener...
No. 2021-05 - Modeling simultaneous supply and demand shocks in input-output networks
19 Jan 21
We show that existing input-output models which allow for binding demand and supply constraints yiel...
Supply and demand shocks in the COVID-19 pandemic: an industry and occupation perspective
04 Sep 20
Production networks and epidemic spreading: Re-opening the UK economy
07 Jun 20
This column reports several re-opening scenarios for the UK economy, documenting their projected imp...
No. 2020-12 - Production networks and epidemic spreading: How to restart the UK economy?
21 May 20
We analyse the economics and epidemiology of different scenarios for a phased restart of the UK econ...
Supply and demand shocks in the COVID-19 pandemic: An industry and occupation perspective
17 Apr 20
We provide quantitative predictions of first order supply and demand shocks for the U.S. economy ass...
No.2020-04 - Technological interdependencies predict innovation dynamics
02 Mar 20
We propose a simple model where the innovation rate of a technological domain depends on the innovat...
No. 2019-03 - What is the Minimal Systemic Risk in Financial Exposure Networks?
16 May 19
It has been shown that systemic risk is to a large extent related to the underlying network topology...