Zobrazeno 1 - 10
of 73
pro vyhledávání: '"Antonio F. Galvao"'
Publikováno v:
Econometrics, Vol 9, Iss 2, p 16 (2021)
This paper studies estimation and inference for linear quantile regression models with generated regressors. We suggest a practical two-step estimation procedure, where the generated regressors are computed in the first step. The asymptotic propertie
Externí odkaz:
https://doaj.org/article/982d9b68e0bd448ab95a699de15a2136
Publikováno v:
Econometrics, Vol 3, Iss 3, Pp 654-666 (2015)
This paper evaluates bootstrap inference methods for quantile regression panel data models. We propose to construct confidence intervals for the parameters of interest using percentile bootstrap with pairwise resampling. We study three different boot
Externí odkaz:
https://doaj.org/article/eba2c622e7284c759c4404ad9dade304
Autor:
Sergio Firpo, Alexandre Poirier, Cristine Campos de Xavier Pinto, Antonio F. Galvao, Graciela Sanroman
Publikováno v:
Journal of Econometrics. 230:432-452
This paper develops generalized method of moments (GMM) estimation and inference procedures for quantile regression models. We propose a GMM estimator for simultaneous estimation across multiple quantiles. This estimator allows us to model quantile r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7fe5e7294c65bb0e47c2db8fb102e4d3
https://doi.org/10.1016/j.jeconom.2020.11.014
https://doi.org/10.1016/j.jeconom.2020.11.014
Publikováno v:
Bernoulli. 29
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::36b5ea73f89b0426cbd9d239f4637f55
https://doi.org/10.3150/22-bej1546
https://doi.org/10.3150/22-bej1546
Publikováno v:
Annals of Finance. 18:133-181
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::00d902d0cd09facfd9ad012c348fbe12
https://doi.org/10.1007/s10436-021-00405-4
https://doi.org/10.1007/s10436-021-00405-4
Publikováno v:
Economic Theory. 73:747-779
This paper axiomatizes static and dynamic quantile preferences. Static quantile preferences specify that a prospect should be preferred if it has a higher $$\tau $$ -quantile, for some $$\tau \in (0,1)$$ , while its dynamic counterpart extends this t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::96034fae68954696210f9bc72da61fe1
https://doi.org/10.1007/s00199-021-01355-8
https://doi.org/10.1007/s00199-021-01355-8
Publikováno v:
Journal of Econometrics. 218:178-215
Nonlinear panel data models with fixed individual effects provide an important set of tools for describing microeconometric data. In a large class of such models (including probit, proportional hazard and quantile regression to name just a few) it is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d5853917a0c57b0b352cc5e32532e68c
https://doi.org/10.1016/j.jeconom.2019.12.017
https://doi.org/10.1016/j.jeconom.2019.12.017
Publikováno v:
The Stata Journal: Promoting communications on statistics and Stata. 20:276-296
In this article, we present a new command, qcte, that implements several methods for estimation and inference for quantile treatment-effects models with a continuous treatment. We propose a semiparametric two-step estimator, where the first step is b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a64cf6897d626dfd5b6ea73915d6dd82
https://doi.org/10.1177/1536867x20930997
https://doi.org/10.1177/1536867x20930997
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ac301154c32049587360d413b3a010b1
https://doi.org/10.2139/ssrn.4108230
https://doi.org/10.2139/ssrn.4108230
This paper develops bootstrap methods for practical statistical inference in panel data quantile regression models with fixed effects. We consider random-weighted bootstrap resampling and formally establish its validity for asymptotic inference. The
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11bb80f82d761a22ecf716d94a79d1d3
http://arxiv.org/abs/2111.03626
http://arxiv.org/abs/2111.03626
