THE BANKRUPTCY RISK IN INFRASTRUCTURE SECTORS: AN ANALYSIS FROM 2006 TO 2018

Detalhes bibliográficos
Autor(a) principal: DELAPEDRA-SILVA,VANDERSON A.
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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spelling 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
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