The finance inequality nexus in Portugal: An empirical study
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/23838 |
Resumo: | This paper conducts a time-series econometric analysis in order to assess the effect of finance on the distribution of income in Portugal between 1977 to 2016 using annual data. A battery of bank and market-based proxies are used to measure financial indicators (private credit, foreign direct investment, money supply, stock market capitalisation, financial value added and financial openness) to provide a holistic representation of the financial system in terms of depth, access, and efficiency (Svirydzenka, 2016). To ensure robustness, two different measures of the Gini coefficient are employed to proxy income inequality (gross and net). School enrolment (as a proxy for human capital), inflation, real GDP, government spending and trade openness were used as control variables. Additionally, the estimations were conducted using the Generalised Method of Moments (GMM) estimator to control for endogeneity. Linear and non-linear estimations were performed to test the different hypotheses available in literature concerning the relationship between finance and income inequality. Our results suggest that bank-based financial indicators have reduced income inequality while market-based financial indicators have worsened income distribution in Portugal. Additionally, financial liberalisation has increased income inequality in Portugal. The majority of our models support a concave relationship between finance and inequality in Portugal. |
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The finance inequality nexus in Portugal: An empirical studyIncome inequalitySistema financeiro -- Financial systemFinancial liberalisationPortugalGMM estimatorDesigualdade de rendimentosDesenvolvimento financeiroLiberalização financeiraGreenwood-JovanovicGMMThis paper conducts a time-series econometric analysis in order to assess the effect of finance on the distribution of income in Portugal between 1977 to 2016 using annual data. A battery of bank and market-based proxies are used to measure financial indicators (private credit, foreign direct investment, money supply, stock market capitalisation, financial value added and financial openness) to provide a holistic representation of the financial system in terms of depth, access, and efficiency (Svirydzenka, 2016). To ensure robustness, two different measures of the Gini coefficient are employed to proxy income inequality (gross and net). School enrolment (as a proxy for human capital), inflation, real GDP, government spending and trade openness were used as control variables. Additionally, the estimations were conducted using the Generalised Method of Moments (GMM) estimator to control for endogeneity. Linear and non-linear estimations were performed to test the different hypotheses available in literature concerning the relationship between finance and income inequality. Our results suggest that bank-based financial indicators have reduced income inequality while market-based financial indicators have worsened income distribution in Portugal. Additionally, financial liberalisation has increased income inequality in Portugal. The majority of our models support a concave relationship between finance and inequality in Portugal.Este estudo pretende avaliar o efeito da financeirização na desigualdade de rendimentos em Portugal utilizando uma série temporal de dados anuais entre 1977 e 2016. Um conjunto de proxies financeiros foram utilizados para o efeito, nomeadamente, o crédito privado, o investimento directo estrangeiro, a oferta de Moeda, a capitalização bolsista, o valor acrescentado financeiro e o grau de abertura financeira, de modo a garantir uma representatividade adequada do Setor Financeiro em termos de profundidade, acesso e eficiência (Svirydzenka, 2016). Para efeitos de robustez, foram empregues duas medidas do coeficiente de Gini, mais especificamente, o coeficiente de Gini líquido e bruto. A taxa de escolarização (como proxy para o capital humano), a inflação, a taxa de crescimento real do PIB, a despesa pública e o grau de abertura comercial foram empregues como variáveis de controlo. As regressões foram estimadas utilizando o Método dos Momentos Generalizado (GMM) para controlar a endogeneidade. Foram estimados modelos lineares e não lineares de modo a testar as diferentes hipóteses disponíveis na literatura sobre a relação entre desigualdade de rendimentos e o desenvolvimento financeiro, nomeadamente, a hipótese linear (Positiva ou Negativa) e a hipótese não-linear (côncava ou convexa). Os resultados obtidos sugerem que o desenvolvimento financeiro bancário reduziu a desigualdade de rendimentos enquanto o desenvolvimento financeiro baseado nos mercados produziu o efeito oposto. Adicionalmente, a liberalização financeira gerou um efeito nefasto na distribuição de rendimentos em Portugal. A maioria dos modelos estimados apoiam a hipótese côncava.2022-12-07T00:00:00Z2021-12-07T00:00:00Z2021-12-072021-10info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10071/23838TID:202814564engLakhani, Rishi Ajitkumarinfo: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:RCAAP2023-11-09T17:30:02Zoai:repositorio.iscte-iul.pt:10071/23838Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:13:29.088752Repositório 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 |
The finance inequality nexus in Portugal: An empirical study |
title |
The finance inequality nexus in Portugal: An empirical study |
spellingShingle |
The finance inequality nexus in Portugal: An empirical study Lakhani, Rishi Ajitkumar Income inequality Sistema financeiro -- Financial system Financial liberalisation Portugal GMM estimator Desigualdade de rendimentos Desenvolvimento financeiro Liberalização financeira Greenwood-Jovanovic GMM |
title_short |
The finance inequality nexus in Portugal: An empirical study |
title_full |
The finance inequality nexus in Portugal: An empirical study |
title_fullStr |
The finance inequality nexus in Portugal: An empirical study |
title_full_unstemmed |
The finance inequality nexus in Portugal: An empirical study |
title_sort |
The finance inequality nexus in Portugal: An empirical study |
author |
Lakhani, Rishi Ajitkumar |
author_facet |
Lakhani, Rishi Ajitkumar |
author_role |
author |
dc.contributor.author.fl_str_mv |
Lakhani, Rishi Ajitkumar |
dc.subject.por.fl_str_mv |
Income inequality Sistema financeiro -- Financial system Financial liberalisation Portugal GMM estimator Desigualdade de rendimentos Desenvolvimento financeiro Liberalização financeira Greenwood-Jovanovic GMM |
topic |
Income inequality Sistema financeiro -- Financial system Financial liberalisation Portugal GMM estimator Desigualdade de rendimentos Desenvolvimento financeiro Liberalização financeira Greenwood-Jovanovic GMM |
description |
This paper conducts a time-series econometric analysis in order to assess the effect of finance on the distribution of income in Portugal between 1977 to 2016 using annual data. A battery of bank and market-based proxies are used to measure financial indicators (private credit, foreign direct investment, money supply, stock market capitalisation, financial value added and financial openness) to provide a holistic representation of the financial system in terms of depth, access, and efficiency (Svirydzenka, 2016). To ensure robustness, two different measures of the Gini coefficient are employed to proxy income inequality (gross and net). School enrolment (as a proxy for human capital), inflation, real GDP, government spending and trade openness were used as control variables. Additionally, the estimations were conducted using the Generalised Method of Moments (GMM) estimator to control for endogeneity. Linear and non-linear estimations were performed to test the different hypotheses available in literature concerning the relationship between finance and income inequality. Our results suggest that bank-based financial indicators have reduced income inequality while market-based financial indicators have worsened income distribution in Portugal. Additionally, financial liberalisation has increased income inequality in Portugal. The majority of our models support a concave relationship between finance and inequality in Portugal. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-12-07T00:00:00Z 2021-12-07 2021-10 2022-12-07T00:00:00Z |
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/10071/23838 TID:202814564 |
url |
http://hdl.handle.net/10071/23838 |
identifier_str_mv |
TID:202814564 |
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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1799134691273474048 |