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Michèle Belot

Researcher at Cornell University

Publications -  109
Citations -  4199

Michèle Belot is an academic researcher from Cornell University. The author has contributed to research in topics: Unemployment & Incentive. The author has an hindex of 30, co-authored 103 publications receiving 3643 citations. Previous affiliations of Michèle Belot include Tilburg University & Institute for the Study of Labor.

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Does the Recent Success of Some OECD Countries in Lowering their Unemployment Rates Lie in the Clever Design of their Labour Market Reforms

TL;DR: In this paper, the authors present a theoretical and empirical framework to investigate how unemployment is affected by different labour market institutions (LMI) such as labour taxes, unemployment benefits, employment protection, union bargaining power and centralisation of bargaining.
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Immigrant Selection in the OECD

TL;DR: This paper examined the determinants of educational selectivity in immigration using immigrant stock data for 70 source countries and 21 destination countries, as observed in the year 2000/2001, and found that cultural similarities, colonial legacies, and physical distance are often more important determinants than wage incentives or selective immigration policy.
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Does the recent success of some OECD countries in lowering their unemployment rates lie in the clever design of their labor market reforms

TL;DR: In this article, the authors present a theoretical and empirical framework to investigate how unemployment is affected by different labour market institutions (LMI) such as labour taxes, unemployment benefits, employment protection, union bargaining power and centralisation of bargaining.
Journal ArticleDOI

Socio-demographic factors associated with self-protecting behavior during the Covid-19 pandemic.

TL;DR: This article examined factors associated with the adoption of self-protective health behaviors, such as social distancing and mask wearing, at the start of the Covid-19 pandemic in the USA.
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The determinants of food choice

TL;DR: To develop the evidence base necessary for effective policies, the authors need to build bridges across different levels of knowledge and understanding, which requires experimental models that can fill in the gaps in understanding that are needed to inform policy, translational models that connect mechanistic understanding from laboratory studies to the real life human condition, and formal models that embed understanding in a way that enables policy-relevant predictions to be made.