Michele Fabi, a postdoctoral fellow at CREST-École polytechnique has recently received the Award for the best paper presented at the International Fintech Research Conference, held at Parthenope University of Naples on 2-3 November 2023.
Michele Fabi
Michele Fabi is currently a post-doctoral researcher at CREST-Ecole polytechnique, serving as a member of the Blockchain and Platform Chair—a research initiative dedicated to blockchains and associated technologies.
Broadly speaking, Michele’s research fields are Financial Economics and Microeconomics, with a focus on topics such as fintech, platforms, decentralized and startup finance, blockchain, and the digitalization of money and markets. He is actively involved into a promoting research on these subjects by taking part in the organization of academic activities such as the BlockSem seminar and the Blockchain@X-OMI Workshop on Blockchain and Decentralized Finance.
Finally, Michele obtained his PhD in 2021 from the doctoral program IDEA-UAB (Universitat Autonoma de Barcelona), working with Matthew Ellman as his advisor.
In 2023-2024, Michele is one of CREST’s International Job Market candidate.
2nd International Fintech Research Conference
The International Fintech Research Conference is set to be a vibrant hub for researchers, encouraging cross-disciplinary discussions and collaborations in the expansive field of Fintech. Covering diverse areas, the conference welcomes contributions in theoretical analysis, machine learning applications, cryptocurrencies, cybersecurity, neural networks, smart contracts, and more.
With a focus on cutting-edge topics such as blockchain technologies, big data analysis, and behavioral finance, the event promises to be a dynamic platform for researchers to share insights, engage in discussions, and shape the future of finance and technology.
During this conference, the Organizing Committee establishes a prize for the best paper presented which was awarded, this year, to Michele Fabi for his paper “Blockchain Design with Transmission Delays”.
More information on the Conference: https://www.disaq.uniparthenope.it/fintechlab/international-fintech-research-conference/
Blockchain Design with Transmission Delays
The article investigates the economics of blockchain design. Unlike previous studies, this research introduces a strategic variable for miners: the ability to choose the size of transaction blocks. This departure from the assumption of maximum block capacity provides insights applicable to modern blockchains like Ethereum.
The study makes two key contributions. Firstly, it establishes testable predictions on block size and justifies transaction fees from the perspective of consensus layer incentives. This differs from earlier approaches that focused on application layer incentives. Secondly, the research addresses the limitations of a partial-equilibrium approach found in previous market microstructure papers. By endogenizing token inflation, the model can provide insights into the optimal balance between transaction fees and token inflation.
The paper builds upon prior works in the economics literature on blockchain and cryptocurrencies, pioneered by Chiu and Koeppl (2019) and Pagnotta (2022) among others, incorporating elements of the new monetarist matching models like Choi and Rocheteau (2020). It is also deeply inspired by the computer science literature on blockchain consensus and distributed algorithms (e.g. Pass and Shi, 2017; Ren, 2019), which lays out the methodological and conceptual foundations for the study of miner incentives.
In conclusion, the article sheds light on the economic challenges of blockchain designs, providing valuable insights for both researchers and practitioners in the blockchain space.
To read the full paper: https://drive.google.com/file/d/1VWGl65Mbg5iCSVNWnW3IMZZ1IL4oJuEU/view
Lea Pessin Receives ERC Grant
Léa Pessin is an assistant professor of Sociology and Demography. She recently joined CREST in the sociology team.
Léa holds a PhD in Sociology and Demography from the Pompeu Fabra University obtained in 2016. She also completed an NICHD postdoctoral fellow at the Population Research Institute and spent the last year of her Ph.D. as a visiting pre-doctoral scholar at the Maryland Population Research Center. She was a 2018 Work and Family Researchers Network Early Career Fellow.
Léa previously worked in the department of Sociology and Criminology and was a faculty associate at the Population Research Institute at the Pennsylvania State University.
Her research agenda focuses on the unequal consequences of the gender revolution on women’s work and family outcomes across class, race, and contexts. She applies quantitative methods to cross-national and longitudinal data to explore variation across countries and time. Her work has been published in Demography, Social Forces, The Journal of Marriage and Family, Demographic Research, The European Sociological Review, and The Journal of Personal and Social Relationships.
As a recognition to her exceptional contributions to sociology, Lea Pessin has recently been awarded an ERC grant, reaffirming her dedication to advancing the boundaries of knowledge in her field.
Léa Pessin was awarded the ERC Starting Grant to work on Social Inequalities in Work-Family Strategies Within and Across 24 Industrialized Countries (WeEqualize).
“WeEqualize” is a research project that aims to understand the complex dynamics of the gender revolution’s impact on work-family patterns in different-sex couples across 24 countries from the 1960s to the present. It acknowledges that despite predictions of linear progress toward gender equality in work and home responsabilities, various structural and cultural factors have stalled this convergence in industrialized countries. The project seeks to characterize and quantify social inequalities in work-family strategies, identify typologies of these strategies, and examine their prevalence across education levels and countries. It also explores the role of contextual factors, changing demographics, and the influence of gender beliefs and labor market constraints on couples’ choices. WeEqualize combines computational methods and survey-based experimental data to challenge and reshape our understanding of gender equality within families.
2023 France-Berkeley Fund: 2 recipients from the CREST
The France-Berkeley Fund
Established in 1993 as a partnership with the French Ministry of Foreign Affairs, the France-Berkeley Fund (FBF) promotes and supports scholarly exchange in all disciplines between faculty and research scientists at the University of California and their counterparts in France.
Through its annual grant competition, the FBF provides seed money for innovative, bi-national collaborations. The Fund’s core mission is to advance research of the highest caliber, to foster interdisciplinary inquiry, to encourage new partnerships, and to promote lasting institutional and intellectual cooperation between France and the United States.
2023-2024 Call: 2 CREST recipients
For the 2023-2024 call, 2 projects have been submitted and are getting funded:
• Decentralizing divorces
A project developed by Matias Nunez (CREST, CNRS Research fellow) and his counterpart Federico Echenique, Professor of Economics and Social Sciences at UC Berkeley.
Abstract:
This project focuses on the development of practical applications of mechanism design, a branch of economics concerned with developing well-functioning institutions that ensure efficient and fair outcomes. In particular, we will focus on legal settings where two persons need to reach an agreement while their preferences are misaligned. Examples are dissolution of partnerships, allocation of rights and duties among conflicting agents, and divorces. While a judge, legal experts and lengthy bargaining procedures are often needed in practice, we plan to develop economic tools to appraise reasonable compromises, reducing both cost and time.
• Towards Local, Distribution-Free and Efficient Guarantees in Aggregation and Statistical Learning
A project developed by Jaouad Mourtada (CREST, ENSAE Paris) and his counterpart Nikita Zhivotovskiy, Assistant Professor in Statistics at UC Berkeley.
Description:
Statistical learning theory is dedicated to the analysis of procedures for learning based on data. The general aim is to understand what guarantees on the prediction accuracy can be obtained, under which conditions and by which procedures. It can inform the design of sound and robust methods, that can withstand corruption in the data or departure from an idealized posited model, without sacrificing accuracy or efficiency in more favorable situations. In particular, the problem of aggregation can be formulated as follows: given a class of predictors and a sample, form a new predictor that is guaranteed to have an accuracy approaching that of the best predictor within the class, up to an error that should be as small as possible.
This problem can be cast in several settings and has been investigated through various angles in Statistics and Computer Science. While the topic is classical, it has seen a renewed interest through (for instance) the recent direction of robust statistical learning, which raises the question of the most general conditions under which a good accuracy can be achieved. Despite important progress, several important and basic questions have remained unanswered in the literature, which we aim to study.
2023 France-Berkeley Fund: 2 CREST recipients
The France-Berkeley Fund
Established in 1993 as a partnership with the French Ministry of Foreign Affairs, the France-Berkeley Fund (FBF) promotes and supports scholarly exchange in all disciplines between faculty and research scientists at the University of California and their counterparts in France.
Through its annual grant competition, the FBF provides seed money for innovative, bi-national collaborations. The Fund’s core mission is to advance research of the highest caliber, to foster interdisciplinary inquiry, to encourage new partnerships, and to promote lasting institutional and intellectual cooperation between France and the United States.
2023-2024 Call: 2 CREST recipients
For the 2023-2024 call, 2 projects have been submitted and are getting funded:
• Decentralizing divorces
A project developed by Matias Nunez (CREST, CNRS Research fellow) and his counterpart Federico Echenique, Professor of Economics and Social Sciences at UC Berkeley.
Abstract:
This project focuses on the development of practical applications of mechanism design, a branch of economics concerned with developing well-functioning institutions that ensure efficient and fair outcomes. In particular, we will focus on legal settings where two persons need to reach an agreement while their preferences are misaligned. Examples are dissolution of partnerships, allocation of rights and duties among conflicting agents, and divorces. While a judge, legal experts and lengthy bargaining procedures are often needed in practice, we plan to develop economic tools to appraise reasonable compromises, reducing both cost and time.
• Towards Local, Distribution-Free and Efficient Guarantees in Aggregation and Statistical Learning
A project developed by Jaouad Mourtada (CREST, ENSAE Paris) and his counterpart Nikita Zhivotovskiy, Assistant Professor in Statistics at UC Berkeley.
Description:
Statistical learning theory is dedicated to the analysis of procedures for learning based on data. The general aim is to understand what guarantees on the prediction accuracy can be obtained, under which conditions and by which procedures. It can inform the design of sound and robust methods, that can withstand corruption in the data or departure from an idealized posited model, without sacrificing accuracy or efficiency in more favorable situations. In particular, the problem of aggregation can be formulated as follows: given a class of predictors and a sample, form a new predictor that is guaranteed to have an accuracy approaching that of the best predictor within the class, up to an error that should be as small as possible.
This problem can be cast in several settings and has been investigated through various angles in Statistics and Computer Science. While the topic is classical, it has seen a renewed interest through (for instance) the recent direction of robust statistical learning, which raises the question of the most general conditions under which a good accuracy can be achieved. Despite important progress, several important and basic questions have remained unanswered in the literature, which we aim to study.
Michelangelo Rossi is nominated for his paper for the Antitrust Writing Award 2024
Paper: Competition and Reputation in an Online Marketplace: Evidence from Airbnb
Management Science, INFORMS, Michelangelo Rossi, April 2023
This paper studies how competition affects the role of reputation in encouraging sellers to exert effort. More competition disciplines sellers, but at the same time, it erodes reputational premia. This paper identifies whether one effect dominates the other using data from Airbnb. I exploit the introduction of a short-term rental regulation effective in San Francisco in 2017 that halved the number of short-term listings on the platform. I focus on hosts who are present on the platform before and after the regulation, and I identify a negative causal effect of the number of competitors on ratings about hosts’ effort. I extend this result with two other measures of effort: hosts’ response rate and response time. I confirm that hosts exert less effort when the number of competitors increases. The rate of responses within 24 hours decreases, and response time increases.
https://awards.concurrences.com/en/awards/2024/academic-articles/competition-and-reputation-in-an-online-marketplace-evidence-from-airbnb
Roland Rathelot, professor at ENSAE Paris and researcher at CREST, winner of an ERC-Consolidator 2022 grant
Roland Rathelot, professor at ENSAE Paris and at the Institut Polytechnique de Paris, researcher at the Centre de Recherche en Économie et STatistique (CREST) and Hi! PARIS joins the list of the already 3 scientific talents of CREST to obtain an ERC grant. His research focuses on the job search process, discrimination by ethnic origin and gender differences in the labor market.
Thanks to his ERC Consolidator grant, Roland Rathelot will work on the INASHI project in which he will study the nature of informational frictions that employers encounter during the recruitment process.
Many countries have both high unemployment rates and unfilled vacancies. Informational frictions are one possible source of this dual problem. On the one hand, job seekers may lack information about how the labor market works or how their skills are assessed. On the other hand, employers may find it difficult to assess the profile of applicants. The INASHI project focuses on this second hypothesis and aims to quantify and qualify the information deficits that employers encounter when they decide to post a job offer, or when they evaluate the applications received.
INASHI also aims to measure the macroeconomic consequences of these informam frictions and to propose solutions. Roland Rathelot and his co-authors will combine the use of administrative date sources and randomized experiments in three European countries: Austria, France and Sweden.
ICML 2021: Congratulations to our Researchers
Crest papers accepted at the international Conference on Machine Learning (ICML)
The Crest is pleased to present the work of its researchers and professors at the 38th International Conference on Machine Learning (ICML) being held this week (July 18-24, 2021).
The ICML conference is world-renowned for presenting and publishing cutting-edge research on all aspects of machine learning, and is one of the fastest growing AI conferences in the world.
Congratulations to our Researchers Marco Cuturi, Anna Korba, Vianney Perchet, Flore Sentenac, Meyer Scetbon (ENSAE Paris, Institut Polytechnique de Paris) an Romaric Gaudel (ENSAI Rennes).
https://www.hi-paris.fr/2021/07/10/hi-paris-at-icml-2021/
Congratulations to Anna Simoni and Arnak Dalalyan for their Hi!Paris Fellowships 2021
Frédérique Bec nommée membre du Haut Conseil des Finances Publiques
Anasuya Raj wins PhD Award
Congratulations to Anasuya Raj for her 2021 PSL SHS Dissertation Prize in « Law, Economics, Management »