THE BANKRUPTCY RISK IN INFRASTRUCTURE SECTORS: AN ANALYSIS FROM 2006 TO 2018
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | RAM. Revista de Administração Mackenzie |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-69712021000400402 |
Resumo: | ABSTRACT Purpose: This research aims to identify the probability of default of infrastructure companies considering the sector specificities of their activities. In addition, the work seeks to identify the application of structural variables of probability of default in a model in a reduced way in order to identify the significance of its use. For this purpose, we investigated 1,520 North American companies from six different sectors linked to infrastructure. Originality/value: The analyzes carried out to identify the probability of a company going bankrupt hardly consider its sectorial particularity. Although most models bring important inputs for risk assessment, most of them do not consider this sectoral view. Then, this work has as value and originality the contribution to fill this gap and identify the existence of sectorial differences in the analysis of default risk in infrastructure companies in the North American market in the period between 2006 and 2018. Design/methodology/approach: The study performed a logistic regression (logit model) using 11 model variables established in calculating the probability of default. It also used the variable distance to default as an explanatory variable in order to identify its ability to explain the researched phenomenon. Findings: The study identified that, in addition to the size of the companies, the distance to default variable is the only variable that can be applied with significance in all the analyzed sectors. In addition, it was identified that companies in the oil and gas sector have less sensitivity to this variable than companies in the other sectors. |
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THE BANKRUPTCY RISK IN INFRASTRUCTURE SECTORS: AN ANALYSIS FROM 2006 TO 2018Sectoral riskDistance to defaultInfrastructureMerton modelCredit riskABSTRACT Purpose: This research aims to identify the probability of default of infrastructure companies considering the sector specificities of their activities. In addition, the work seeks to identify the application of structural variables of probability of default in a model in a reduced way in order to identify the significance of its use. For this purpose, we investigated 1,520 North American companies from six different sectors linked to infrastructure. Originality/value: The analyzes carried out to identify the probability of a company going bankrupt hardly consider its sectorial particularity. Although most models bring important inputs for risk assessment, most of them do not consider this sectoral view. Then, this work has as value and originality the contribution to fill this gap and identify the existence of sectorial differences in the analysis of default risk in infrastructure companies in the North American market in the period between 2006 and 2018. Design/methodology/approach: The study performed a logistic regression (logit model) using 11 model variables established in calculating the probability of default. It also used the variable distance to default as an explanatory variable in order to identify its ability to explain the researched phenomenon. Findings: The study identified that, in addition to the size of the companies, the distance to default variable is the only variable that can be applied with significance in all the analyzed sectors. In addition, it was identified that companies in the oil and gas sector have less sensitivity to this variable than companies in the other sectors.Editora MackenzieUniversidade Presbiteriana Mackenzie2021-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-69712021000400402RAM. Revista de Administração Mackenzie v.22 n.4 2021reponame:RAM. Revista de Administração Mackenzieinstname:Universidade Presbiteriana Mackenzie (UPM)instacron:MACKENZIE10.1590/1678-6971/eramf210104info:eu-repo/semantics/openAccessDELAPEDRA-SILVA,VANDERSON A.eng2021-06-23T00:00:00Zoai:scielo:S1678-69712021000400402Revistahttps://www.scielo.br/j/ram/https://old.scielo.br/oai/scielo-oai.phprevista.adm@mackenzie.br1678-69711518-6776opendoar:2021-06-23T00:00RAM. Revista de Administração Mackenzie - Universidade Presbiteriana Mackenzie (UPM)false |
dc.title.none.fl_str_mv |
THE BANKRUPTCY RISK IN INFRASTRUCTURE SECTORS: AN ANALYSIS FROM 2006 TO 2018 |
title |
THE BANKRUPTCY RISK IN INFRASTRUCTURE SECTORS: AN ANALYSIS FROM 2006 TO 2018 |
spellingShingle |
THE BANKRUPTCY RISK IN INFRASTRUCTURE SECTORS: AN ANALYSIS FROM 2006 TO 2018 DELAPEDRA-SILVA,VANDERSON A. Sectoral risk Distance to default Infrastructure Merton model Credit risk |
title_short |
THE BANKRUPTCY RISK IN INFRASTRUCTURE SECTORS: AN ANALYSIS FROM 2006 TO 2018 |
title_full |
THE BANKRUPTCY RISK IN INFRASTRUCTURE SECTORS: AN ANALYSIS FROM 2006 TO 2018 |
title_fullStr |
THE BANKRUPTCY RISK IN INFRASTRUCTURE SECTORS: AN ANALYSIS FROM 2006 TO 2018 |
title_full_unstemmed |
THE BANKRUPTCY RISK IN INFRASTRUCTURE SECTORS: AN ANALYSIS FROM 2006 TO 2018 |
title_sort |
THE BANKRUPTCY RISK IN INFRASTRUCTURE SECTORS: AN ANALYSIS FROM 2006 TO 2018 |
author |
DELAPEDRA-SILVA,VANDERSON A. |
author_facet |
DELAPEDRA-SILVA,VANDERSON A. |
author_role |
author |
dc.contributor.author.fl_str_mv |
DELAPEDRA-SILVA,VANDERSON A. |
dc.subject.por.fl_str_mv |
Sectoral risk Distance to default Infrastructure Merton model Credit risk |
topic |
Sectoral risk Distance to default Infrastructure Merton model Credit risk |
description |
ABSTRACT Purpose: This research aims to identify the probability of default of infrastructure companies considering the sector specificities of their activities. In addition, the work seeks to identify the application of structural variables of probability of default in a model in a reduced way in order to identify the significance of its use. For this purpose, we investigated 1,520 North American companies from six different sectors linked to infrastructure. Originality/value: The analyzes carried out to identify the probability of a company going bankrupt hardly consider its sectorial particularity. Although most models bring important inputs for risk assessment, most of them do not consider this sectoral view. Then, this work has as value and originality the contribution to fill this gap and identify the existence of sectorial differences in the analysis of default risk in infrastructure companies in the North American market in the period between 2006 and 2018. Design/methodology/approach: The study performed a logistic regression (logit model) using 11 model variables established in calculating the probability of default. It also used the variable distance to default as an explanatory variable in order to identify its ability to explain the researched phenomenon. Findings: The study identified that, in addition to the size of the companies, the distance to default variable is the only variable that can be applied with significance in all the analyzed sectors. In addition, it was identified that companies in the oil and gas sector have less sensitivity to this variable than companies in the other sectors. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-69712021000400402 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1678-69712021000400402 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1678-6971/eramf210104 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Editora Mackenzie Universidade Presbiteriana Mackenzie |
publisher.none.fl_str_mv |
Editora Mackenzie Universidade Presbiteriana Mackenzie |
dc.source.none.fl_str_mv |
RAM. Revista de Administração Mackenzie v.22 n.4 2021 reponame:RAM. Revista de Administração Mackenzie instname:Universidade Presbiteriana Mackenzie (UPM) instacron:MACKENZIE |
instname_str |
Universidade Presbiteriana Mackenzie (UPM) |
instacron_str |
MACKENZIE |
institution |
MACKENZIE |
reponame_str |
RAM. Revista de Administração Mackenzie |
collection |
RAM. Revista de Administração Mackenzie |
repository.name.fl_str_mv |
RAM. Revista de Administração Mackenzie - Universidade Presbiteriana Mackenzie (UPM) |
repository.mail.fl_str_mv |
revista.adm@mackenzie.br |
_version_ |
1752128650577182720 |