Estimating the effects of fiscal consolidations: A synthetic control approach
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/10071/23842 |
Resumo: | This thesis applies the synthetic control method to estimate the effects of fiscal consolidations on GDP. The framework developed requires the identification of suitable multi-year treatment episodes as well as periods that can serve as controls (where fiscal policy was relatively neutral). The identification of treatment and control episodes is done through the two most used measures of fiscal policy in the recent literature. Since the two measures are very different and have little overlap in terms of countries and period covered, the estimation is done in two different datasets and only the main results are compared. The rationale behind the implementation of the synthetic control method was to explore the possibility that it could provide robust estimations for the effects of individual fiscal consolidations. However, through the evaluation of the estimation method on placebos, it seems that this methodology generates too much variance, making individual estimations unreliable. Nevertheless, the average estimated effects are unbiased and can provide some useful insights: fiscal consolidations tend to generate significant losses in GDP, consolidations based on expenditure reduction are less contractionary than those based on tax increases and consolidations implemented following a recession generate higher costs. These conclusions are robust to both identification methods (when it could be tested with both) and are also in line with recent studies that use more common estimation methods. |
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Estimating the effects of fiscal consolidations: A synthetic control approachFiscal consolidationPolítica fiscal -- Fiscal policySynthetic control methodConsolidação orçamentalMétodo de controlo sintéticoThis thesis applies the synthetic control method to estimate the effects of fiscal consolidations on GDP. The framework developed requires the identification of suitable multi-year treatment episodes as well as periods that can serve as controls (where fiscal policy was relatively neutral). The identification of treatment and control episodes is done through the two most used measures of fiscal policy in the recent literature. Since the two measures are very different and have little overlap in terms of countries and period covered, the estimation is done in two different datasets and only the main results are compared. The rationale behind the implementation of the synthetic control method was to explore the possibility that it could provide robust estimations for the effects of individual fiscal consolidations. However, through the evaluation of the estimation method on placebos, it seems that this methodology generates too much variance, making individual estimations unreliable. Nevertheless, the average estimated effects are unbiased and can provide some useful insights: fiscal consolidations tend to generate significant losses in GDP, consolidations based on expenditure reduction are less contractionary than those based on tax increases and consolidations implemented following a recession generate higher costs. These conclusions are robust to both identification methods (when it could be tested with both) and are also in line with recent studies that use more common estimation methods.A presente tese aplica o método de controlo sintético como processo de estimação dos efeitos de consolidações orçamentais no PIB. A metodologia desenvolvida requer a identificação de episódios de tratamento (períodos em que se verifiquem consolidações orçamentais) e a identificação de episódios de controlo (quando a política orçamental foi relativamente neutra). A identificação destes episódios é feita usando as duas variáveis mais comuns na literatura recente. Como estas variáveis são muito diferentes e cobrem períodos e países distintos, a estimação é feita separadamente em duas bases de dados e apenas os resultados são comparados. A justificação para a implementação do método de controlo sintético foi a possibilidade de este conseguir fornecer estimações robustas para um único tratamento, com a intenção de estudar a heterogeneidade dos efeitos de consolidações orçamentais. Através da avaliação do método de estimação em placebos, foi possível concluir que esta metodologia gera demasiada variância, fazendo com que estimações individuais sejam inadequadas. No entanto, as estimações dos efeitos médios não são enviesadas e fornecem algumas conclusões úteis: consolidações orçamentais geram perdas significativas de PIB, consolidações baseadas em redução de despesa são menos contracionárias e consolidações implementadas a seguir a uma recessão geram maiores perdas. Estas conclusões são robustas aos dois métodos de identificação (quando podem ser testadas com ambos) e estão em linha com as conclusões obtidas na literatura recente.2021-12-29T13:08:06Z2021-11-04T00:00:00Z2021-11-042021-09info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10071/23842TID:202814513engMartins, Tomás Manuel Lançainfo: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:RCAAP2023-11-09T17:53:44Zoai:repositorio.iscte-iul.pt:10071/23842Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:26:59.358028Repositório 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 |
Estimating the effects of fiscal consolidations: A synthetic control approach |
title |
Estimating the effects of fiscal consolidations: A synthetic control approach |
spellingShingle |
Estimating the effects of fiscal consolidations: A synthetic control approach Martins, Tomás Manuel Lança Fiscal consolidation Política fiscal -- Fiscal policy Synthetic control method Consolidação orçamental Método de controlo sintético |
title_short |
Estimating the effects of fiscal consolidations: A synthetic control approach |
title_full |
Estimating the effects of fiscal consolidations: A synthetic control approach |
title_fullStr |
Estimating the effects of fiscal consolidations: A synthetic control approach |
title_full_unstemmed |
Estimating the effects of fiscal consolidations: A synthetic control approach |
title_sort |
Estimating the effects of fiscal consolidations: A synthetic control approach |
author |
Martins, Tomás Manuel Lança |
author_facet |
Martins, Tomás Manuel Lança |
author_role |
author |
dc.contributor.author.fl_str_mv |
Martins, Tomás Manuel Lança |
dc.subject.por.fl_str_mv |
Fiscal consolidation Política fiscal -- Fiscal policy Synthetic control method Consolidação orçamental Método de controlo sintético |
topic |
Fiscal consolidation Política fiscal -- Fiscal policy Synthetic control method Consolidação orçamental Método de controlo sintético |
description |
This thesis applies the synthetic control method to estimate the effects of fiscal consolidations on GDP. The framework developed requires the identification of suitable multi-year treatment episodes as well as periods that can serve as controls (where fiscal policy was relatively neutral). The identification of treatment and control episodes is done through the two most used measures of fiscal policy in the recent literature. Since the two measures are very different and have little overlap in terms of countries and period covered, the estimation is done in two different datasets and only the main results are compared. The rationale behind the implementation of the synthetic control method was to explore the possibility that it could provide robust estimations for the effects of individual fiscal consolidations. However, through the evaluation of the estimation method on placebos, it seems that this methodology generates too much variance, making individual estimations unreliable. Nevertheless, the average estimated effects are unbiased and can provide some useful insights: fiscal consolidations tend to generate significant losses in GDP, consolidations based on expenditure reduction are less contractionary than those based on tax increases and consolidations implemented following a recession generate higher costs. These conclusions are robust to both identification methods (when it could be tested with both) and are also in line with recent studies that use more common estimation methods. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-12-29T13:08:06Z 2021-11-04T00:00:00Z 2021-11-04 2021-09 |
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/10071/23842 TID:202814513 |
url |
http://hdl.handle.net/10071/23842 |
identifier_str_mv |
TID:202814513 |
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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1799134832900440064 |