A subjective poverty line for Portugal
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.14/26314 |
Resumo: | The aim of this thesis is to estimate a subjective poverty line for Portugal, using data collected by the PEO – Painel de Estudos Online of the Catolica Lisbon School of Business and Economics in March and November 2016. The analysis is based on a log-log regression for stated income needs (answer to a minimum income question) using as explanatory variables net monthly income, number of adults, number of children, and including a vector of other demographic characteristics of the household. After several attempts to include other variables concerning demographic characteristics in the model, it was possible to conclude that the only significant variables to add to the model would be a set of geographic dummies depending on the area of location of the household: North, Centre, South and Islands. Finally, two regressions were run, one without any demographic characteristics and one including the location dummies. In both regressions the answer to the Minimum Income Question depends positively on Net Monthly Income, the number of adults and the number of children living in the household. Using the second model it is also possible to conclude that the answer to Minimum Income Question also depends on the location of the household, and that the answers are higher in the South than in any other region. |
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A subjective poverty line for PortugalPovertySubjectiveMinimum income questionGeographic differentiationPobrezaSubjetivaQuestão de rendimento mínimoDiferenciação geográficaDomínio/Área Científica::Ciências Sociais::Economia e GestãoThe aim of this thesis is to estimate a subjective poverty line for Portugal, using data collected by the PEO – Painel de Estudos Online of the Catolica Lisbon School of Business and Economics in March and November 2016. The analysis is based on a log-log regression for stated income needs (answer to a minimum income question) using as explanatory variables net monthly income, number of adults, number of children, and including a vector of other demographic characteristics of the household. After several attempts to include other variables concerning demographic characteristics in the model, it was possible to conclude that the only significant variables to add to the model would be a set of geographic dummies depending on the area of location of the household: North, Centre, South and Islands. Finally, two regressions were run, one without any demographic characteristics and one including the location dummies. In both regressions the answer to the Minimum Income Question depends positively on Net Monthly Income, the number of adults and the number of children living in the household. Using the second model it is also possible to conclude that the answer to Minimum Income Question also depends on the location of the household, and that the answers are higher in the South than in any other region.O objetivo desta tese é estimar uma Linha de Pobreza Subjetiva em Portugal, usando dados recolhidos pelo PEO – Painel de Estudos Online da Catolica Lisbon School of Business and Economics em Março e Novembro de 2016. Para que tal fosse possível foi usado um modelo log-log com as seguintes variáveis: rendimento mensal líquido, número de adultos e número de crianças no agregado familiar e um vetor de características demográficas do agregado familiar. Após várias tentativas de um incluir um vetor de variáveis especificas, foi possível concluir que o único conjunto de variáveis relevantes era relativamente ao local de habitação do agregado familiar, nomeadamente: Norte, Centro, Sul e Ilhas. Finalmente, foram efetuadas duas regressões, uma sem incluir nenhuma característica demográfica e outra incluindo a localização de habitação referida anteriormente. Foi possível concluir que em ambas as regressões a resposta à Questão de Rendimento Mínimo depende positivamente do rendimento mensal liquido, do número de adultos e do número de crianças que vivem no agregado familiar. Adicionalmente, usando o segundo modelo podemos concluir que estas mesmas respostas variam consoante a região de habitação do agregado familiar, nomeadamente as respostas são em média mais altas na região Sul do país do que em outra qualquer região.Gouveia, Miguel Rebordão de AlmeidaVeritati - Repositório Institucional da Universidade Católica PortuguesaLourenço, Sara Gonçalves2018-12-10T16:04:33Z2018-03-082018-03-08T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10400.14/26314TID:201888483enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-12T17:31:47Zoai:repositorio.ucp.pt:10400.14/26314Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T18:20:59.918216Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
A subjective poverty line for Portugal |
title |
A subjective poverty line for Portugal |
spellingShingle |
A subjective poverty line for Portugal Lourenço, Sara Gonçalves Poverty Subjective Minimum income question Geographic differentiation Pobreza Subjetiva Questão de rendimento mínimo Diferenciação geográfica Domínio/Área Científica::Ciências Sociais::Economia e Gestão |
title_short |
A subjective poverty line for Portugal |
title_full |
A subjective poverty line for Portugal |
title_fullStr |
A subjective poverty line for Portugal |
title_full_unstemmed |
A subjective poverty line for Portugal |
title_sort |
A subjective poverty line for Portugal |
author |
Lourenço, Sara Gonçalves |
author_facet |
Lourenço, Sara Gonçalves |
author_role |
author |
dc.contributor.none.fl_str_mv |
Gouveia, Miguel Rebordão de Almeida Veritati - Repositório Institucional da Universidade Católica Portuguesa |
dc.contributor.author.fl_str_mv |
Lourenço, Sara Gonçalves |
dc.subject.por.fl_str_mv |
Poverty Subjective Minimum income question Geographic differentiation Pobreza Subjetiva Questão de rendimento mínimo Diferenciação geográfica Domínio/Área Científica::Ciências Sociais::Economia e Gestão |
topic |
Poverty Subjective Minimum income question Geographic differentiation Pobreza Subjetiva Questão de rendimento mínimo Diferenciação geográfica Domínio/Área Científica::Ciências Sociais::Economia e Gestão |
description |
The aim of this thesis is to estimate a subjective poverty line for Portugal, using data collected by the PEO – Painel de Estudos Online of the Catolica Lisbon School of Business and Economics in March and November 2016. The analysis is based on a log-log regression for stated income needs (answer to a minimum income question) using as explanatory variables net monthly income, number of adults, number of children, and including a vector of other demographic characteristics of the household. After several attempts to include other variables concerning demographic characteristics in the model, it was possible to conclude that the only significant variables to add to the model would be a set of geographic dummies depending on the area of location of the household: North, Centre, South and Islands. Finally, two regressions were run, one without any demographic characteristics and one including the location dummies. In both regressions the answer to the Minimum Income Question depends positively on Net Monthly Income, the number of adults and the number of children living in the household. Using the second model it is also possible to conclude that the answer to Minimum Income Question also depends on the location of the household, and that the answers are higher in the South than in any other region. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-12-10T16:04:33Z 2018-03-08 2018-03-08T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.14/26314 TID:201888483 |
url |
http://hdl.handle.net/10400.14/26314 |
identifier_str_mv |
TID:201888483 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799131909356257280 |