2026
The Evolution of Discrimination in Online Markets: How the Rise in Anti-Asian Bias Affected Airbnb During the Pandemic
Marketing Science, 45(1), 108–122
Researcher · Practitioner · Educator
ElizavetaPronkina
Economist at Amazon.
Adjunct Professor at ENSAE Paris.
I am a Ph.D. economist at Amazon and an adjunct professor at ENSAE Paris. At Amazon, I build and deploy models combining causal inference with generative AI to evaluate market-facing policies and deliver evidence-based recommendations to Vice Presidents and Directors. My research examines discrimination and reputation in digital markets, with work published in Marketing Science and Harvard Business Review. At ENSAE Paris, I designed and teach Artificial Intelligence for Business Decisions, bridging LLM foundations with real-world applications.
Research interestsQuantitative MarketingDigital EconomicsArtificial Intelligence and Economic Decision-MakingLabour and Personnel EconomicsHealth Economics
01 / RESEARCH
Papers & publications
Academic and practitioner publications on online markets, reputation, discrimination, labour, and health.
Read paper
2026
Five Stars on the Way Out: Reputation and Seller Effort Near Exit
CESifo Working Paper No. 11253
2023
The COVID-19 Curtain: Can Past Communist Regimes Explain the Vaccination Divide in Europe?
Social Science & Medicine, 321, 115759
2023
Robinson Crusoe: Less or More Depressed? With Whom and Where to Live in a Pandemic if You Are Above 50
Review of Economics of the Household, 21(2), 435–459
2023
Family Size and Vaccination among Older Individuals: The Case of COVID-19 Vaccine
Economics & Human Biology, 50, 101256
2023
Behind the Curtain: How Did Women’s Work History Vary across Central and Eastern Europe?
Economics of Transition and Institutional Change, 31(2), 465–489
2023
Housing, Living Arrangements, and Contagion among Europeans Aged 50+
Book chapter · Social, Health, and Economic Impacts of the COVID-19 Pandemic and the Epidemiological Control Measures: First Results from SHARE Corona Waves 1 and 2
2023
Housing Conditions, Living Arrangements, and Mental Well-Being of Europeans Aged 50+: How the COVID-19 Pandemic Made a Difference
Book chapter · Social, Health, and Economic Impacts of the COVID-19 Pandemic and the Epidemiological Control Measures: First Results from SHARE Corona Waves 1 and 2
2022
Ensuring Your Products Aren’t Used for Discrimination
Harvard Business Review · October 10, 2022
2022
The Heterogeneous Effects of the Great Recession on Informal Care to the Elderly
International Journal of Health Economics and Management, 22(4), 355–367
2022
Predicting COVID-19 Vaccine Uptake
IZA Discussion Paper No. 15625
11 research outputsView Google Scholar
02 / TEACHING
Ideas into practice
Graduate teaching that connects economic foundations with real-world decisions.
ENSAE Paris · Graduate course · Since 2025
Artificial Intelligence
for Business Decisions
I designed and teach a course on how AI reshapes business strategy and decision-making. Students connect economic reasoning with hands-on model evaluation and examine how AI transforms business decisions, and how organisations adopt, deploy and govern it.
LLM applicationsModel evaluationEnterprise deploymentAI governance
3 ECTS · 18 hours · Taught in English
A foundation in economics
Previously, I taught graduate and undergraduate economics at Universidad Carlos III de Madrid, where I ranked in the top 5% for teaching excellence.
I also organised the Mathematics Preparatory Course for Ph.D. and M.A. students.
Microeconometrics · Game Theory
Microeconomics · Economics of Education
Advanced Mathematics
Student evaluations · ENSAE Paris95% overall satisfaction · 100% pedagogical quality · 95% course interest
03 / ABOUT
Across research & practice
I am a Ph.D. economist with around four years of industry experience at Amazon. I use causal inference to evaluate organisational policies and translate findings into recommendations for Vice Presidents and Directors. My work also puts generative AI into practice: I designed and deployed a scalable workflow combining it with econometric evaluation.
Alongside my industry role, I study discrimination and reputation in digital markets. This research has appeared in Marketing Science and Harvard Business Review. My interests include quantitative marketing and the role of AI in economic decision-making, with additional work in labour and health economics.
At ENSAE Paris, I designed and teach Artificial Intelligence for Business Decisions. The course connects economic reasoning with practical applications, helping students assess how AI changes business strategy. I also mentor early-career scientists. Within Amazon, I supervise economist interns and deliver training on causal inference and AI.
View full curriculum vitae2023–PRESENT
Economist II · Amazon
People Experience & Technology · France
2025–PRESENT
Adjunct Professor · ENSAE Paris
Artificial Intelligence for Business Decisions · France
2022–2023
Economist · Amazon
Employee Experience & Relations · France
2021–2022
Postdoctoral Researcher
Université Paris-Dauphine – PSL · France
2021
Ph.D. in Economics
Universidad Carlos III de Madrid · Spain
2017 / 2015
Master’s degrees
Economic Analysis · Universidad Carlos III de Madrid · Spain
Economics · New Economic School · Russia
2012
B.A. in Economics
Lomonosov Moscow State University · Russia
Methods & business applications
Causal inference; field experiments; econometrics; machine learning and generative AI applied to platform markets and consumer data.
Generative AI, large language model applications, and deployed AI-assisted workflows that connect empirical evidence with business decisions.
Python · Stata · SQL · Generative AI · AWS
Industry and Academic Engagement
National Association for Business Economics (NABE Europe), London (2024); NABE Europe, Berlin (2023); NABE, Seattle (2022).
Amazon Economist Summit, Seattle (2023–2025); HR Policy Global Latin America Summit, Miami (2024).
Invited talks at Toulouse Business School, Swansea University and Université Paris-Dauphine – PSL.
04 / CONTACT