I am an Assistant Professor at University College London, Computer Science department. Previously I was JSMF Fellow at the Complexity Science Hub Vienna and the Growth Lab at the Harvard Kennedy School. I did a PhD in Mathematics at the Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
My research draws from network science and agent-based modelling and focuses on labour economics, the future of work, net zero transition, and the economic impact of the Covid-19 pandemic.
I’m looking for PhD students! Please reach out if you are interested.
m [dot] delriochanona [at] ucl.ac.uk
Current Research
Net zero transition and employment
We analyze the employment dynamics of a fast transition scenario for the US electricity sector that reaches 95% decarbonization by 2035. We find three distinct labor market phases during the transition: scale-up, scale-down and a long-term steady state. During the scale-up phase, for every job lost in a given industry, twelve new jobs are created elsewhere. But only a few occupations experience a consistent increase in demand throughout the transition.
We study sustainable transition scenarios for Brazil and their implications for the labor force.
References
Large Language Models and Digital Public Goods
We study the impact of Large Language Models (LLMs) on digital public goods, focusing on Stack Overflow. We estimate a 16% decrease in weekly posts on Stack Overflow after the release of ChatGPT, escalating to 25% by June. This widespread LLM adoption might diminish public web exchanges, thereby constraining the open data available for future learning.
References
- del Rio-Chanona, R. Maria, et al. “Are Large Language Models a Threat to Digital Public Goods? Evidence from Activity on Stack Overflow” arXiv preprint arXiv:2307.07367 (2023) Read here
Labor Markets and Networks
We study the network structure of the division of labour by analysing discrete work activities. We find that our measure of occupational work-activity similarity is more predictive of job-to-job transitions than existing benchmark measures.
We develop a data-driven network model to study the impact of automation on employment. We find that the network structure plays an important role in determining unemployment levels, with occupations in particular areas of the network having very few job transition
References
- Mealy, Penny, R. Maria del Rio-Chanona, and J. Doyne Farmer. “What you do at work matters: New lenses on labour.” What You Do at Work Matters: New Lenses on Labour (March 18, 2018) (2018). Read here
- del Rio-Chanona, R. Maria, et al. “Automation and occupational mobility: A data-driven network model.” Journal of the Royal Society Interface (2021). Read here
Finished Research Projects
The Great Resignation
We use text analysis to investigate the changes in work- and quit-related posts between 2018 and 2021 on Reddit. We find that mental health and work-related distress topics disproportionally increased among quit-related posts since the onset of the pandemic, likely contributing to the Great Resignation.
References
- del Rio-Chanona, R. Maria, et al. “Mental health concerns precede quits: shifts in the work discourse during the Covid-19 pandemic and great resignation” EPJ Data Science (2023). Read here
COVID-19 Economic Impact
We integrated an economic and an epidemic agent-based models to assess the health-economy trade-off in New York City.
The economic model we developed predicted the economic impact of the pandemic on UK economy well at both the aggregate and sectoral level.
We provide quantitative predictions of first order COVID-19 supply and demand shocks for the US economy. Compared to the pre-COVID period, these shocks threaten around 20% of the US economy’s GDP and jeopardize 23% of jobs.
References
- Pangallo, Marco, et al. “The unequal effects of the health–economy trade-off during the COVID-19 pandemic.” Nature Human Behaviour (2023). Read here
- Pichler, Anton, et al. “Forecasting the propagation of pandemic shocks with a dynamic input-output model” Journal of Economic Dynamics and Control (2022). Read here
- del Rio-Chanona, R. Maria, et al. “Supply and demand shocks in the COVID-19 pandemic: An industry and occupation perspective.” Oxford Review of Economic Policy (2020). Read here
Multilayer Networks and Financial Contagion
We study interconnectedness of the global financial system and its susceptibility to shocks. We study multiple channels of financial contagion using a multilayer network approach.
References
Maria del Rio-Chanona 