Corporate governance characteristics and valuation: Inferences from quantile regression
Descripción del Articulo
Prior literature on corporate governance and performance provides mixed evidence on the impact of various corporate governance measures on performance indicators. However, most of literatures adopt the Ordinary Least Square (OLS). This method is based on the central tendency, which may not appropria...
| Autores: | , , , , |
|---|---|
| Formato: | artículo |
| Fecha de Publicación: | 2016 |
| Institución: | Universidad ESAN |
| Repositorio: | Revistas - Universidad ESAN |
| Lenguaje: | inglés |
| OAI Identifier: | oai:ojs.pkp.sfu.ca:article/141 |
| Enlace del recurso: | https://revistas.esan.edu.pe/index.php/jefas/article/view/141 |
| Nivel de acceso: | acceso abierto |
| Materia: | Desempeno Gobierno corporativo OLS Regresión de cuantiles |
| id |
REVESAN_123d62026c8c8953f68ab15dae58b209 |
|---|---|
| oai_identifier_str |
oai:ojs.pkp.sfu.ca:article/141 |
| network_acronym_str |
REVESAN |
| network_name_str |
Revistas - Universidad ESAN |
| repository_id_str |
. |
| spelling |
Corporate governance characteristics and valuation: Inferences from quantile regressionShawtari, Fekri Ali Abdelnabi Salem, MiladIqbal Hussain, Hafezali Alaeddin, Omar Bin Thabit, OmerDesempenoGobierno corporativoOLSRegresión de cuantilesPrior literature on corporate governance and performance provides mixed evidence on the impact of various corporate governance measures on performance indicators. However, most of literatures adopt the Ordinary Least Square (OLS). This method is based on the central tendency, which may not appropriately represent the reality in cases where the dependent variable ranges between upper and lower values and hence the relationship may not be homogenous across different percentiles of the dependent variables. A variable having a positive impact based on the central tendency for firms may not be the case for the firms in the upper or lower bounds. Thus, estimating the means using OLS may not reflect and represent the heterogeneity in the estimated relationship. Therefore, quantile regression estimates the relationship at any point conditional on the distribution of dependent variable. This would enable us to generate various estimated coefficient at certain quantile of dependent variable. Therefore, the objective of the study is twofold. First, this study aims to investigate the relationship between corporate governance and performance using OLS. Second,this work further explores the impact of corporate governance mechanisms on performance using quantile regression so as to compare and to shed light on whether there is heterogeneity in the influence of these variables on the performance of listed companies across quantiles. The results of the study provide evidence that quantile approach shows inconsistency in the result with OLS and hence indicating the impact depends on the scale size. This theoretically provides further support that OLS may represent a poor estimation approach for the reality of firms. Doi: https://doi.org/10.1016/j.jefas.2016.06.004Universidad ESAN2016-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPeer-reviewed Articleapplication/pdfhttps://revistas.esan.edu.pe/index.php/jefas/article/view/141Journal of Economics, Finance and Administrative Science; Vol. 21 No. 41 (2016): July - December; 81-88Journal of Economics, Finance and Administrative Science; Vol. 21 Núm. 41 (2016): July - December; 81-882218-06482077-1886reponame:Revistas - Universidad ESANinstname:Universidad ESANinstacron:ESANenghttps://revistas.esan.edu.pe/index.php/jefas/article/view/141/111Copyright (c) 2016 Journal of Economics, Finance and Administrative Sciencehttps://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:ojs.pkp.sfu.ca:article/1412021-08-17T23:25:53Z |
| dc.title.none.fl_str_mv |
Corporate governance characteristics and valuation: Inferences from quantile regression |
| title |
Corporate governance characteristics and valuation: Inferences from quantile regression |
| spellingShingle |
Corporate governance characteristics and valuation: Inferences from quantile regression Shawtari, Fekri Ali Desempeno Gobierno corporativo OLS Regresión de cuantiles |
| title_short |
Corporate governance characteristics and valuation: Inferences from quantile regression |
| title_full |
Corporate governance characteristics and valuation: Inferences from quantile regression |
| title_fullStr |
Corporate governance characteristics and valuation: Inferences from quantile regression |
| title_full_unstemmed |
Corporate governance characteristics and valuation: Inferences from quantile regression |
| title_sort |
Corporate governance characteristics and valuation: Inferences from quantile regression |
| dc.creator.none.fl_str_mv |
Shawtari, Fekri Ali Abdelnabi Salem, Milad Iqbal Hussain, Hafezali Alaeddin, Omar Bin Thabit, Omer |
| author |
Shawtari, Fekri Ali |
| author_facet |
Shawtari, Fekri Ali Abdelnabi Salem, Milad Iqbal Hussain, Hafezali Alaeddin, Omar Bin Thabit, Omer |
| author_role |
author |
| author2 |
Abdelnabi Salem, Milad Iqbal Hussain, Hafezali Alaeddin, Omar Bin Thabit, Omer |
| author2_role |
author author author author |
| dc.subject.none.fl_str_mv |
Desempeno Gobierno corporativo OLS Regresión de cuantiles |
| topic |
Desempeno Gobierno corporativo OLS Regresión de cuantiles |
| description |
Prior literature on corporate governance and performance provides mixed evidence on the impact of various corporate governance measures on performance indicators. However, most of literatures adopt the Ordinary Least Square (OLS). This method is based on the central tendency, which may not appropriately represent the reality in cases where the dependent variable ranges between upper and lower values and hence the relationship may not be homogenous across different percentiles of the dependent variables. A variable having a positive impact based on the central tendency for firms may not be the case for the firms in the upper or lower bounds. Thus, estimating the means using OLS may not reflect and represent the heterogeneity in the estimated relationship. Therefore, quantile regression estimates the relationship at any point conditional on the distribution of dependent variable. This would enable us to generate various estimated coefficient at certain quantile of dependent variable. Therefore, the objective of the study is twofold. First, this study aims to investigate the relationship between corporate governance and performance using OLS. Second,this work further explores the impact of corporate governance mechanisms on performance using quantile regression so as to compare and to shed light on whether there is heterogeneity in the influence of these variables on the performance of listed companies across quantiles. The results of the study provide evidence that quantile approach shows inconsistency in the result with OLS and hence indicating the impact depends on the scale size. This theoretically provides further support that OLS may represent a poor estimation approach for the reality of firms. Doi: https://doi.org/10.1016/j.jefas.2016.06.004 |
| publishDate |
2016 |
| dc.date.none.fl_str_mv |
2016-12-01 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
https://revistas.esan.edu.pe/index.php/jefas/article/view/141 |
| url |
https://revistas.esan.edu.pe/index.php/jefas/article/view/141 |
| dc.language.none.fl_str_mv |
eng |
| language |
eng |
| dc.relation.none.fl_str_mv |
https://revistas.esan.edu.pe/index.php/jefas/article/view/141/111 |
| dc.rights.none.fl_str_mv |
Copyright (c) 2016 Journal of Economics, Finance and Administrative Science https://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
| rights_invalid_str_mv |
Copyright (c) 2016 Journal of Economics, Finance and Administrative Science https://creativecommons.org/licenses/by/4.0/ |
| eu_rights_str_mv |
openAccess |
| dc.format.none.fl_str_mv |
application/pdf |
| dc.publisher.none.fl_str_mv |
Universidad ESAN |
| publisher.none.fl_str_mv |
Universidad ESAN |
| dc.source.none.fl_str_mv |
Journal of Economics, Finance and Administrative Science; Vol. 21 No. 41 (2016): July - December; 81-88 Journal of Economics, Finance and Administrative Science; Vol. 21 Núm. 41 (2016): July - December; 81-88 2218-0648 2077-1886 reponame:Revistas - Universidad ESAN instname:Universidad ESAN instacron:ESAN |
| instname_str |
Universidad ESAN |
| instacron_str |
ESAN |
| institution |
ESAN |
| reponame_str |
Revistas - Universidad ESAN |
| collection |
Revistas - Universidad ESAN |
| repository.name.fl_str_mv |
|
| repository.mail.fl_str_mv |
|
| _version_ |
1847512519676002304 |
| score |
12.63363 |
Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).