PhD Position F/M [Campagne DOC BMI-NF-GRA-2024] Measure of extreme inequality in wealth distribution

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Type de contrat : CDD

Niveau de diplôme exigé : Bac + 5 ou équivalent

Fonction : Doctorant

A propos du centre ou de la direction fonctionnelle

The Centre Inria de l’Université de Grenoble groups together almost 600 people in 22 research teams and 7 research support departments.

Staff is present on three campuses in Grenoble, in close collaboration with other research and higher education institutions (Université Grenoble Alpes, CNRS, CEA, INRAE, …), but also with key economic players in the area.

The Centre Inria de l’Université Grenoble Alpe is active in the fields of high-performance computing, verification and embedded systems, modeling of the environment at multiple levels, and data science and artificial intelligence. The center is a top-level scientific institute with an extensive network of international collaborations in Europe and the rest of the world.

Mission confiée

The richest 1% on the planet own almost half of the world's wealth, according to a study by Oxfam International published in 2021. This marked inequality in the distribution of wealth is of major interest for the global economy. In 1912, Italian economist Corrado Gini introduced the first measure of inequality, the Gini coefficient. This statistical index is used to account for the variability of a variable within a population. It thus makes it possible to quantify the level of inequality in the distribution of wealth in a population. The Gini coefficient is a number ranging from 0 to 1, where 0 means perfect equality (everyone has the same share of wealth) and 1 represents perfect inequality (one person has all the wealth). However, it turns out that if the focus is on the distribution of wealth among the highest income earners, the Gini coefficient underestimates inequality. Indeed, if the variable of interest follows a heavy-tailed distribution (with possibly infinite variance), then it has the same Gini index as a light-tailed distribution. The Gini coefficient is therefore robust to extreme observations and fails to discriminate between two different distributions of wealth for extreme values.

 

Principales activités

The objectives are as follows:
- To define and theoretically study a new coefficient for measuring inequalities in the distribution of wealth, dedicated to extreme values. This will enable to take better account of the behavior of the tail of the distribution and to better discriminate the distribution of great wealth by no longer underestimating inequalities.
- Implement the estimation of this new index, apply it to economic data, where it will be compared with other existing measures of inequality.

Compétences

We look for candidates strongly motivated by challenging statistical research with application to real world data. The applicant should have a solid background in probability and statistics. He/she will also ideally have experience in extreme value analysis. The applicant will have significant experience in programming with either C/C++, Matlab, Python or R.

Avantages

  • Subsidized meals
  • Partial reimbursement of public transport costs
  • Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
  • Possibility of teleworking (90 days / year) and flexible organization of working hours (except for intership)
  • Social, cultural and sports events and activities
  • Access to vocational training
  • Social security coverage under conditions

 

Rémunération

1st and 2nd year: 2 100 euros gross salary /month
 
 3rd year: 2 190 euros gross salary / month