R Maria Del Rio-Chanona
Biographic Data
| ID | 1933016 |
|---|---|
| NAME | R Maria Del Rio-Chanona |
| GIVEN NAMES | R Maria |
| FAMILY NAME | Del Rio-Chanona |
| SIGNATURE | DEL RIO-CHANONA R M |
| AFFILIATIONS | Institute for New Economic Thinking at the Oxford Martin School and Mathematical Institute, University of Oxford |
| ORCID | 0000-0002-0189-7919 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 5 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 2 |
Winners and losers of generative AI
The unequal effects of the health-economy trade-off during the Covid-19 pandemic
Despite the global impact of the coronavirus disease 2019 pandemic, the question of whether mandated interventions have similar economic and public health effects as spontaneous behavioural change remains unresolved. Addressing this question, and understanding differential effects across socioeconomic groups, requires building quantitative and fine-grained mechanistic models. Here we introduce a data-driven, granular, agent-based model that simul…
Supply and demand shocks in the Covid-19 pandemic
We provide quantitative predictions of first-order supply and demand shocks for the US economy associated with the COVID-19 pandemic at the level of individual occupations and industries. To analyse the supply shock, we classify industries as essential or non-essential and construct a Remote Labour Index, which measures the ability of different occupations to work from home. Demand shocks are based on a study of the likely effect of a severe infl…
The unequal effects of the health-economy trade-off during the Covid-19 pandemic
Despite the global impact of the coronavirus disease 2019 pandemic, the question of whether mandated interventions have similar economic and public health effects as spontaneous behavioural change remains unresolved. Addressing this question, and understanding differential effects across socioeconomic groups, requires building quantitative and fine-grained mechanistic models. Here we introduce a data-driven, granular, agent-based model that simul…
Winners and losers of generative AI
Supply and demand shocks in the Covid-19 pandemic
We provide quantitative predictions of first-order supply and demand shocks for the US economy associated with the COVID-19 pandemic at the level of individual occupations and industries. To analyse the supply shock, we classify industries as essential or non-essential and construct a Remote Labour Index, which measures the ability of different occupations to work from home. Demand shocks are based on a study of the likely effect of a severe infl…
The unequal effects of the health-economy trade-off during the Covid-19 pandemic
Despite the global impact of the coronavirus disease 2019 pandemic, the question of whether mandated interventions have similar economic and public health effects as spontaneous behavioural change remains unresolved. Addressing this question, and understanding differential effects across socioeconomic groups, requires building quantitative and fine-grained mechanistic models. Here we introduce a data-driven, granular, agent-based model that simul…
Winners and losers of generative AI
COVID-19 epidemiological studies (2 works) · COVID-19 Pandemic Impacts (2 works) · Economics (2 works) · 2019-20 coronavirus outbreak (1 work) · Artificial Intelligence (1 work) · Computer Science (1 work) · Construct (python library) (1 work) · Coronavirus disease 2019 (COVID-19) (1 work) · Demand shock (1 work) · Digital Economy and Work Transformation (1 work)