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pro vyhledávání: '"Gaillac, Christophe"'
We study partially linear models when the outcome of interest and some of the covariates are observed in two different datasets that cannot be linked. This type of data combination problem arises very frequently in empirical microeconomics. Using rec
Externí odkaz:
http://arxiv.org/abs/2204.05175
Autor:
Gaillac, Christophe, Gautier, Eric
This paper studies point identification of the distribution of the coefficients in some random coefficients models with exogenous regressors when their support is a proper subset, possibly discrete but countable. We exhibit trade-offs between restric
Externí odkaz:
http://arxiv.org/abs/2105.11720
Publikováno v:
Quantitative Economics 2021 (12)
In this paper, we build a new test of rational expectations based on the marginal distributions of realizations and subjective beliefs. This test is widely applicable, including in the common situation where realizations and beliefs are observed in t
Externí odkaz:
http://arxiv.org/abs/2003.11537
Autor:
Gaillac, Christophe, Gautier, Eric
The Fourier transform truncated on [-c,c] is usually analyzed when acting on L^2(-1/b,1/b) and its right-singular vectors are the prolate spheroidal wave functions. This paper considers the operator acting on the larger space L^2(exp(b|.|)) on which
Externí odkaz:
http://arxiv.org/abs/1905.11338
Autor:
Gaillac, Christophe, Gautier, Eric
We consider a linear model where the coefficients - intercept and slopes - are random with a law in a nonparametric class and independent from the regressors. Identification often requires the regressors to have a support which is the whole space. Th
Externí odkaz:
http://arxiv.org/abs/1905.06584
Autor:
Bied, Guillaume, Nathan, Solal, Perennes, Elia, Gaillac, Christophe, Caillou, Philippe, Crépon, Bruno, Sebag, Michèle
Publikováno v:
AI for HR and Public Employment Services
AI for HR and Public Employment Services, Feb 2023, Ghent (BE), Belgium
AI for HR and Public Employment Services, Feb 2023, Ghent (BE), Belgium
International audience; The Vador Project started in 2018 between the French Public Employment Service Pole Emploi, computer scientists from Paris Saclay and economist from CREST. The project aims to learn a new recommender system from past hirings a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______165::ba5aa8d9e5db03b91880aa32542a08bc
https://inria.hal.science/hal-04025000
https://inria.hal.science/hal-04025000
Autor:
Bied, Guillaume, Gaillac, Christophe, Hoffmann, Morgane, Nathan, Solal, Caillou, Philippe, Crépon, Bruno, Sebag, Michèle
Publikováno v:
AI for HR and Public Employment Services
AI for HR and Public Employment Services, Feb 2023, Ghent (BE), Belgium
AI for HR and Public Employment Services, Feb 2023, Ghent (BE), Belgium
International audience; Algorithmic recommendations of job ads to job seekers promise to alleviate frictional unemployment, but raise fairness considerations due to biases in training data. This paper strives to discuss the issue of algorithmic fairn
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______165::9e5b656c14af230d50888e9e8ef6518f
https://inria.hal.science/hal-04025006
https://inria.hal.science/hal-04025006
Autor:
D'Haultfoeuille, Xavier1 (AUTHOR) xavier.dhaultfoeuille@ensae.fr, Gaillac, Christophe1,2 (AUTHOR) christophe.gaillac@tse-fr.eu, Maurel, Arnaud3,4,5 (AUTHOR) arnaud.maurel@duke.edu
Publikováno v:
Quantitative Economics. Jul2021, Vol. 12 Issue 3, p817-842. 26p.
Akademický článek
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We consider the identification of and inference on a partially linear model, when the outcome of interest and some of the covariates are observed in two different datasets that cannot be linked. This type of data combination problem arises very frequ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1687::d62b77c2c2ed1e700a266f4f7ead0cc3
https://hdl.handle.net/10419/263446
https://hdl.handle.net/10419/263446