February 28, 11.00 Jérôme Adda (Bocconi University)
"TBA"

March 7,11.00 Antonio Cabrales (Universidad Carlos III de
Madrid)
"TBA"

March 14,11.00 David Craininch (IESEG School of Management)
"TBA"

March 28,11.00 David de la Croix (Université Catholique de Louvain)
"TBA"

April 11,11.00 Michael Burda (Humboldt Universität zu Berlin)
"TBA"

Past seminars 2021-2022

November 15,11.00 Etienne Billette de Villemeur (Université de Lille)
"Assessing Inequality Assessments:A General Representation of Inequality Indices"

We propose a unifying representation of all normalized inequality indices, regardless of their properties. The key concept behind our results is that of negative extreme transfers (NETs), which are transfers from the poorest individuals to the richest individuals. This concept alone is rich enough to describe the entire space of income distributions. Indeed, our first result (Lemma 1) is that any income distribution can be obtained as an expansion from the equal distribution by applying a sequence of NETs. In other words, NETs constitute a mathematical basis of the space of income distributions. Our main representation theorem (Theorem 1) builds upon the NET decomposition of income distributions to describe any given inequality index based on the weight it attaches to all possible NETs. Accordingly, desirable properties (axioms) of inequality indices translate into properties of the weight function that are easy to check. We express well-known inequality indices according to this decomposition. We define the λ -NET Criterion, the requirement that the weighting function is greater than some parameter λ >0 . The stringency of the λ -NET Criterion filters out inequality indices as λ increases, so that one can therefore rank inequality measures on the basis of the λ -NET Criterion they satisfy. According to this ranking, we find that the Pietra index is the unique measure to satisfy the maximal λ.

October 11,11.00 Pierre Dubois (Toulouse School of Economics)
"Bargaining and International Reference Pricing in the Pharmaceutical Industry"

The United States spends twice as much per person on pharmaceuticals as European countries, in large part because prices are much higher in the US. This fact has led policymakers to consider legislation for price controls. This paper assesses the effects of a US reference pricing policy that would cap prices in US markets by those offered in reference countries as proposed in the H.R.3 Lower Drug Costs Now Act of 2019. We estimate a structural model of demand and supply for pharmaceuticals in the US and reference countries like Canada where prices are set through a negotiation process between pharmaceutical companies and the government. We then simulate the counterfactual international reference pricing equilibrium, allowing firms to internalize the cross-country externalities introduced by this policy. We find that such a policy results in a slight decrease in US prices and a substantial increase in reference countries prices. The magnitude of these effects depends on the number, size and market structure of references countries. Overall, we find modest consumer welfare gains in the US but substantial losses in reference countries suggesting that this policy may not be the best way to introduce price controls in the US.

September 14, 11.00 Friederike Mengel (University of Essex)
"Non-Bayesian Statistical Discrimination"

Models of statistical discrimination typically assume that employers make rational inference from (education) signals. However, there is a large amount of evidence showing that most people do not update their beliefs rationally. We use a model and two experiments to show that employers who are conservative, in the sense of signal neglect, discriminate more against disadvantaged groups than Bayesian employers. We find that such irrational statistical discrimination deters high-ability workers from disadvantaged groups from pursuing education, further exacerbating initial group inequalities. Excess discrimination caused by employer conservatism is especially important when signals are very informative. Out of the overall hiring gap in our data, around 40% can be attributed to rational statistical discrimination, a further 40% is due to irrational statistical discrimination, and the remaining 20% is unexplained or potentially taste-based.

Lundi 19 novembre 2018 11:30-13:00 -
Yann Bramoullé - AMSE

[External Seminar] Yann Bramoullé

Lieu : Seminar room, Ecully

Lundi 3 décembre 2018 11:30-13:00 -
Mathieu Parenti - (Université Libre de Bruxelles)

[External Seminar] Mathieu Parenti

Lieu : Seminar room, Ecully

Lundi 10 décembre 2018 11:30-13:00 -
Nicolas Sirven - LIRAES, Université Paris Descartes

[External Seminar] Nicolas Sirven

Lieu : Seminar room, Ecully

Lundi 14 janvier 2019 11:30-13:00 -
Etienne Lehmann - CRED, Université Paris II

[External Seminar] Etienne Lehmann

Résumé : "Comprehensive or Separate Income Tax ? A sufficient Statistics Approach"

In this paper, I investigate how to tax the different sources of income of taxpayers. I consider on optimal nonlinear income tax model with many sources of income. I first exhibit a specification where the optimal tax system consists in a nonlinear schedule that applies to the sum of all income - a comprehensive income tax system - and another specification where the optimal tax system consists in a nonlinear schedule specific to each income - a separate income tax system. In the more general environment I specialize the tax schedule to be combination of these two polar systems : the tax system is restricted to be the sum of a comprehensive personal income tax schedule and of income specific tax schedules, I derive an optimal ABC formula for each of these schedules. I also derive a condition expressed in terms of empirically meaningful sufficient statistics under which decreasing the indexation of the personal income tax base on one income and compensating the revenue loss with a lumpsum or a proportional increase in the taxation of that income is socially desirable.

Résumé : "Mass Refugee Inflow and Long-run Prosperity : Lessons from the Greek Population Resettlement", joint with Seyhun Orcan Sakalli.

This paper investigates the long-term consequences of mass refugee inflow on eonomic development by examining the effect of the first large-scale population resettlement in modern history. After the Greco-Turkish war of 1919-1922, 1.2 million Greek Orthodox were forcibly resettled from Turkey to Greece, increasing the Greek population by more than 20% within a few months. We build a novel geocoded dataset locating settlements of refugees across the universe of more than four thousand Greek municipalities that existed in Greece in 1920. Exploiting the spatial variation in the resettlement location, we find that localities with a greater share of refugees in 1923 have today higher earnings, higher levels of household wealth, greater educational attainment, as well as larger financial and manufacturing sectors. These results hold when comparing spatially contiguous municipalities with identical geographical features and are not driven by pre-settlement differences in initial level of development across localities. The long-run beneficial effects appear to arise from agglomeration economies generated by the large increase in the workforce, occupational specialization, as well as by new industrial know-hows brought by refugees, which fostered early industrialization and economic growth.

Lieu : ENS, Site Descartes, D8-001

Lundi 4 février 2019 11:30-13:00 -
Nagore Iriberri - University of the Basque Country

[External Seminar] Nagore Iriberri

Résumé : "Brave Boys and Play-it-Safe Girls : Gender Differences in Willingness to Guess in a Large Scale Natural Experiment".

We study gender differences in a sample with over 9,000 multiple-choice math tests, where in half of the questions both wrong answers and omitted questions score 0, and in the other half wrong answers score 0 but omitted questions score +1. Using a within-participant regression analysis, we find that female participants leave more omitted questions than males under both types of scoring rules, but furthermore, the gender difference gets larger when there is a reward for omitted questions. This gender difference, which is stronger among high ability and older participants, has negative consequences for females in the final score and ranking. In a subsequent survey, female participants show lower levels of confidence and higher risk aversion, which could potentially explain this differential behavior. When both are considered, risk aversion seems to be the main factor in explaining the gender differential in the willingness to guess. A scoring rule that is gender neutral begs for non-differential scoring between wrong answers and omitted questions.

Lieu : (!) AMPHI, Ecully

Lundi 11 février 2019 11:30-13:00 -

[External Seminar] Antonio Russo

Lieu : Seminar Room, Ecully

Lundi 4 mars 2019 11:30-13:00 -
Jérôme Adda - Bocconi University