Research Interests

Trained as a labor economist, my research is at the frontier between theory and applied microeconometrics. Driven by a genuine interest in understanding outcome/performance inequality, I draw my attention to matching and hedonic models. These models study markets where heterogenous agents aim at matching with each other and answer two important questions: who matches with whom and why? They therefore can be applied to numerous decision-making processes: whom to marry with and how to share the surplus, whom to work for and at what wage, whom to hire and at what salary, what product to purchase/sell and at what price, whom to team up with and how to share the surplus, where to live, with whom and how to share the surplus, etc.

On the methodological side, my research contributes to developing estimation strategies for matching models when agents' attributes are possibly continuous, multivariate and some are unobserved to the analyst. I use tools from discrete choice models, convex analysis, linear programming and optimal transport.

On the empirical side, I apply these methods to various datasets: households surveys, labor force surveys, data on performance and pay in sports.

My empirical applications of these methods to the marriage market have shown that e.g.:

  • although education explains a quarter of a couple's marital surplus, personality traits explain another 20% and different personality traits matter differently for men and for women,

  • structural estimates of marital surplus are informative about subjective well-being and separation: the larger the (estimated) marital surplus, the lower the probability of divorce and the lower the difference in spouses' subjective satisfaction, and

  • for floating migrant women in China the migration surplus is equally due to better marital prospects in the city and better labor market opportunities,

whereas my applications to the labor market show that e.g.:

  • the hierarchical organization of work within teams can lead to significantly higher within and between team performance inequality, explaining up to 46% of the rise in performance inequality in the Tour de France,

  • taxation can lead to large allocative inefficiency by altering who is matched to whom, as indeed, as taxes increase, workers put more weight on job amenities than productivity leading to mismatches, and,

  • The Value of a Statistical Life (VSL) is $6.3 million in 2017 in the US.

Keywords: Inequality, Matching, Marriage, Organization, Taxation, Value of a Statistical Life.