Improving accuracy of inflation forecasts using macroeconomic information

Detalhes bibliográficos
Autor(a) principal: Kocsis, Arpad
Data de Publicação: 2016
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/16852
Resumo: This thesis examines the effects of macroeconomic factors on inflation level and volatility in the Euro Area to improve the accuracy of inflation forecasts with econometric modelling. Inflation aggregates for the EU as well as inflation levels of selected countries are analysed, and the difference between these inflation estimates and forecasts are documented. The research proposes alternative models depending on the focus and the scope of inflation forecasts. I find that models with a Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) in mean process have better explanatory power for inflation variance compared to the regular GARCH models. The significant coefficients are different in EU countries in comparison to the aggregate EU-wide forecast of inflation. The presence of more pronounced GARCH components in certain countries with more stressed economies indicates that inflation volatility in these countries are likely to occur as a result of the stressed economy. In addition, other economies in the Euro Area are found to exhibit a relatively stable variance of inflation over time. Therefore, when analysing EU inflation one have to take into consideration the large differences on country level and focus on those one by one.
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spelling Improving accuracy of inflation forecasts using macroeconomic informationDomínio/Área Científica::Ciências Sociais::Economia e GestãoThis thesis examines the effects of macroeconomic factors on inflation level and volatility in the Euro Area to improve the accuracy of inflation forecasts with econometric modelling. Inflation aggregates for the EU as well as inflation levels of selected countries are analysed, and the difference between these inflation estimates and forecasts are documented. The research proposes alternative models depending on the focus and the scope of inflation forecasts. I find that models with a Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) in mean process have better explanatory power for inflation variance compared to the regular GARCH models. The significant coefficients are different in EU countries in comparison to the aggregate EU-wide forecast of inflation. The presence of more pronounced GARCH components in certain countries with more stressed economies indicates that inflation volatility in these countries are likely to occur as a result of the stressed economy. In addition, other economies in the Euro Area are found to exhibit a relatively stable variance of inflation over time. Therefore, when analysing EU inflation one have to take into consideration the large differences on country level and focus on those one by one.Franco, FrancescoBasturk, NalanRUNKocsis, Arpad2016-03-21T15:01:45Z2016-012016-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/16852TID:201525860enginfo: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:RCAAP2024-03-11T03:54:08Zoai:run.unl.pt:10362/16852Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:23:33.728383Repositório 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 Improving accuracy of inflation forecasts using macroeconomic information
title Improving accuracy of inflation forecasts using macroeconomic information
spellingShingle Improving accuracy of inflation forecasts using macroeconomic information
Kocsis, Arpad
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
title_short Improving accuracy of inflation forecasts using macroeconomic information
title_full Improving accuracy of inflation forecasts using macroeconomic information
title_fullStr Improving accuracy of inflation forecasts using macroeconomic information
title_full_unstemmed Improving accuracy of inflation forecasts using macroeconomic information
title_sort Improving accuracy of inflation forecasts using macroeconomic information
author Kocsis, Arpad
author_facet Kocsis, Arpad
author_role author
dc.contributor.none.fl_str_mv Franco, Francesco
Basturk, Nalan
RUN
dc.contributor.author.fl_str_mv Kocsis, Arpad
dc.subject.por.fl_str_mv Domínio/Área Científica::Ciências Sociais::Economia e Gestão
topic Domínio/Área Científica::Ciências Sociais::Economia e Gestão
description This thesis examines the effects of macroeconomic factors on inflation level and volatility in the Euro Area to improve the accuracy of inflation forecasts with econometric modelling. Inflation aggregates for the EU as well as inflation levels of selected countries are analysed, and the difference between these inflation estimates and forecasts are documented. The research proposes alternative models depending on the focus and the scope of inflation forecasts. I find that models with a Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) in mean process have better explanatory power for inflation variance compared to the regular GARCH models. The significant coefficients are different in EU countries in comparison to the aggregate EU-wide forecast of inflation. The presence of more pronounced GARCH components in certain countries with more stressed economies indicates that inflation volatility in these countries are likely to occur as a result of the stressed economy. In addition, other economies in the Euro Area are found to exhibit a relatively stable variance of inflation over time. Therefore, when analysing EU inflation one have to take into consideration the large differences on country level and focus on those one by one.
publishDate 2016
dc.date.none.fl_str_mv 2016-03-21T15:01:45Z
2016-01
2016-01-01T00:00:00Z
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/16852
TID:201525860
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