Racism and judicial corruption in the US
Is racial hate reflected in the degree of judicial corruption? Using US state-level data, we find racial hate to be a positive and statistically powerful predictor of judicial corruption. This relationship prevails after the inclusion of the conventional control variables and regional fixed effects....
- Autores:
-
Jetter, Michael
Mesa-Osorio, Alejandro
- Tipo de recurso:
- Fecha de publicación:
- 2016
- Institución:
- Universidad EAFIT
- Repositorio:
- Repositorio EAFIT
- Idioma:
- eng
- OAI Identifier:
- oai:repository.eafit.edu.co:10784/8262
- Acceso en línea:
- http://hdl.handle.net/10784/8262
- Palabra clave:
- corruption
racism
corrupción
racismo
- Rights
- License
- Acceso abierto
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repository_id_str |
|
dc.title.eng.fl_str_mv |
Racism and judicial corruption in the US |
title |
Racism and judicial corruption in the US |
spellingShingle |
Racism and judicial corruption in the US corruption racism corrupción racismo |
title_short |
Racism and judicial corruption in the US |
title_full |
Racism and judicial corruption in the US |
title_fullStr |
Racism and judicial corruption in the US |
title_full_unstemmed |
Racism and judicial corruption in the US |
title_sort |
Racism and judicial corruption in the US |
dc.creator.fl_str_mv |
Jetter, Michael Mesa-Osorio, Alejandro |
dc.contributor.eafitauthor.none.fl_str_mv |
amesaos@eafit.edu.co |
dc.contributor.author.none.fl_str_mv |
Jetter, Michael Mesa-Osorio, Alejandro |
dc.subject.keyword.eng.fl_str_mv |
corruption racism |
topic |
corruption racism corrupción racismo |
dc.subject.keyword.spa.fl_str_mv |
corrupción racismo |
description |
Is racial hate reflected in the degree of judicial corruption? Using US state-level data, we find racial hate to be a positive and statistically powerful predictor of judicial corruption. This relationship prevails after the inclusion of the conventional control variables and regional fixed effects. In terms of magnitude, one standard deviation increase of racial hate relates to an increase of 70 percent of one standard deviation in corruption. Interestingly, no such relationship can be found for corruption in the executive or legislative branch. |
publishDate |
2016 |
dc.date.available.none.fl_str_mv |
2016-04-13T01:48:59Z |
dc.date.issued.none.fl_str_mv |
2016-02-01 |
dc.date.accessioned.none.fl_str_mv |
2016-04-13T01:48:59Z |
dc.type.eng.fl_str_mv |
workingPaper info:eu-repo/semantics/workingPaper |
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http://purl.org/coar/version/c_b1a7d7d4d402bcce |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_8042 |
dc.type.local.spa.fl_str_mv |
Documento de trabajo de investigación |
dc.type.hasVersion.eng.fl_str_mv |
draft |
dc.identifier.uri.none.fl_str_mv |
http://hdl.handle.net/10784/8262 |
dc.identifier.jel.none.fl_str_mv |
D63 D73 H73 J15 J78 |
url |
http://hdl.handle.net/10784/8262 |
identifier_str_mv |
D63 D73 H73 J15 J78 |
dc.language.iso.eng.fl_str_mv |
eng |
language |
eng |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.local.spa.fl_str_mv |
Acceso abierto |
rights_invalid_str_mv |
Acceso abierto http://purl.org/coar/access_right/c_abf2 |
dc.coverage.spatial.eng.fl_str_mv |
Medellín de: Lat: 06 15 00 N degrees minutes Lat: 6.2500 decimal degrees Long: 075 36 00 W degrees minutes Long: -75.6000 decimal degrees |
dc.publisher.spa.fl_str_mv |
Universidad EAFIT |
dc.publisher.department.spa.fl_str_mv |
Escuela de Economía y Finanzas |
institution |
Universidad EAFIT |
bitstream.url.fl_str_mv |
https://repository.eafit.edu.co/bitstreams/c5b194c5-dcd5-4efa-8e50-c17bc6200936/download https://repository.eafit.edu.co/bitstreams/bbed1b66-557c-407e-940d-36d4fe375057/download |
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repository.name.fl_str_mv |
Repositorio Institucional Universidad EAFIT |
repository.mail.fl_str_mv |
repositorio@eafit.edu.co |
_version_ |
1814110438700351488 |
spelling |
Medellín de: Lat: 06 15 00 N degrees minutes Lat: 6.2500 decimal degrees Long: 075 36 00 W degrees minutes Long: -75.6000 decimal degrees2016-04-13T01:48:59Z2016-02-012016-04-13T01:48:59Zhttp://hdl.handle.net/10784/8262D63D73H73J15J78Is racial hate reflected in the degree of judicial corruption? Using US state-level data, we find racial hate to be a positive and statistically powerful predictor of judicial corruption. This relationship prevails after the inclusion of the conventional control variables and regional fixed effects. In terms of magnitude, one standard deviation increase of racial hate relates to an increase of 70 percent of one standard deviation in corruption. Interestingly, no such relationship can be found for corruption in the executive or legislative branch.engUniversidad EAFITEscuela de Economía y FinanzasRacism and judicial corruption in the USworkingPaperinfo:eu-repo/semantics/workingPaperDocumento de trabajo de investigacióndrafthttp://purl.org/coar/version/c_b1a7d7d4d402bccehttp://purl.org/coar/resource_type/c_8042Acceso abiertohttp://purl.org/coar/access_right/c_abf2corruptionracismcorrupciónracismoamesaos@eafit.edu.coJetter, MichaelMesa-Osorio, AlejandroLICENSElicense.txtlicense.txttext/plain; charset=utf-82556https://repository.eafit.edu.co/bitstreams/c5b194c5-dcd5-4efa-8e50-c17bc6200936/download76025f86b095439b7ac65b367055d40cMD51ORIGINAL2016_08_Michael_Jetter_Alejandro_Mesa.pdf2016_08_Michael_Jetter_Alejandro_Mesa.pdfDocumento de trabajo de investigaciónapplication/pdf516476https://repository.eafit.edu.co/bitstreams/bbed1b66-557c-407e-940d-36d4fe375057/download4f3bd7df2e08328b43234421cc509c95MD5210784/8262oai:repository.eafit.edu.co:10784/82622024-03-05 14:06:24.694open.accesshttps://repository.eafit.edu.coRepositorio Institucional Universidad EAFITrepositorio@eafit.edu.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 |