Zobrazeno 1 - 10
of 59
pro vyhledávání: '"Fernando Rios Avila"'
Autor:
Kusum Mundra, Fernando Rios-Avila
Publikováno v:
Education Economics. :1-25
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0d9911159cea8a1b8db1c8de746d3fa6
https://doi.org/10.1080/09645292.2023.2200911
https://doi.org/10.1080/09645292.2023.2200911
Publikováno v:
The Stata Journal: Promoting communications on statistics and Stata. 23:53-85
Researchers use finite mixture models to analyze linked survey and administrative data on labor earnings, while also accounting for various types of measurement error in each data source. Different combinations of error-ridden and error-free observat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5154d59174c74b5752440ebe9a61a910
https://doi.org/10.1177/1536867x231161976
https://doi.org/10.1177/1536867x231161976
Publikováno v:
Ecos de Economía, Vol 21, Iss 44, Pp 4-36 (2017)
Este artículo analiza el impacto económico de los sindicatos sobre la productividad en el sector manufacturero en seis países de América Latina: Argentina, Bolivia, Chile, México, Uruguay y Panamá. Utilizando una función de producción aumenta
Externí odkaz:
https://doaj.org/article/a4fd93f24a0f49ecb979c57efbf0ff0f
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::898f292b90a94e15dca09c8520f978f1
https://doi.org/10.2139/ssrn.4354397
https://doi.org/10.2139/ssrn.4354397
Publikováno v:
Journal of Applied Econometrics. 36:474-483
Meijer, Rohwedder, and Wansbeek (MRW, Journal of Business & Economic Statistics, 2012) developed methods for prediction of a single earnings figure per worker from mixture factor models fitted using earnings data from multiple linked data sources. MR
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::976c204ff111a31f49e3f019abd86065
https://doi.org/10.1002/jae.2811
https://doi.org/10.1002/jae.2811
Autor:
Fernando Rios-Avila
Publikováno v:
The Stata Journal: Promoting communications on statistics and Stata. 21:81-96
margins is a powerful postestimation command that allows the estimation of marginal effects for official and community-contributed commands, with well-defined predicted outcomes (see predict). While the use of factor-variable notation allows one to e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3a1dad73c3573bf3c01f184d8011fd52
https://doi.org/10.1177/1536867x211000005
https://doi.org/10.1177/1536867x211000005
Autor:
Fernando Rios-Avila
Publikováno v:
Econometrics, Vol 7, Iss 2, p 28 (2019)
This paper presents an extension to the Oaxaca−Blinder decomposition with continuous groups using a semiparametric approach known as varying coefficients model. To account for potential self-selection into the continuum of groups, the use of invers
Externí odkaz:
https://doaj.org/article/530ceca121a04bfa8beceb4944deca61
Autor:
Fernando Rios-Avila
Publikováno v:
The Stata Journal: Promoting communications on statistics and Stata. 20:647-679
Nonparametric regressions are powerful statistical tools that can be used to model relationships between dependent and independent variables with minimal assumptions on the underlying functional forms. Despite their potential benefits, these models h
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::03962a011da3d841863f168259e0911b
https://doi.org/10.1177/1536867x20953574
https://doi.org/10.1177/1536867x20953574
The Effect of Immigration on Labor Market Transitions of Native-Born Unemployed in the United States
Publikováno v:
Journal of Labor Research. 41:295-331
Unemployed workers are the group most likely to be affected by the presence of immigrants in their local labor markets since they are actively competing for job opportunities. Yet, little is known about the effect of immigration on labor market oppor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9ae40849880e51761735e026e0508510
https://doi.org/10.1007/s12122-020-09304-5
https://doi.org/10.1007/s12122-020-09304-5