Two essays on the relevance of interest rates on capital flows and credit

• Ano de defesa: 2020
• Autor(a) principal: Alan Marques Miranda Leal
• Orientador(a): Rafael Saulo Marques Ribeiro
• Banca de defesa: Pedro Vasconcelos Maia do Amaral, Maurício Andrade Weiss
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Federal de Minas Gerais
• Programa de Pós-Graduação: Programa de Pós-Graduação em Economia
• Departamento: FACE - FACULDADE DE CIENCIAS ECONOMICAS
• País: Brasil
• Palavras-chave em Português: Capital flows; Interest rates; Credit; GDP
• Link de acesso: http://hdl.handle.net/1843/35012; https://orcid.org/0000-0002-1141-7747

The role played by internal factors such as interest rates and GDP at determining capital flows is of long-time interest for researchers. At the same time, many studies postulate how foreign variables, in general, interest rates and GDP of an economically advanced country, contribute to determine the volume and direction of the capital flows. The first research question of this dissertation consists of exactly verifying the relevance through time of internal factors (pull) and foreign factors (push), that determine both capital inflows and outflows. We accomplish this task using a dynamic panel on our database, built from the Balance of Payments from the International Monetary Fund (IMF), among other data. The results confirm a larger relevance of internal factors as determinants of capital flows in the long run than in the short run, such as GDP and monetary policy interest rates. Further research might be interested in considering more disaggregated capital flows that are aligned with the methodology of the IMF’s Balance of Payments. Besides, this dissertation attempts to answer another research question, regarding the regional impact of monetary policy on credit. Studies in this area consider largely time series methods (such as Vector Auto-regressive - VAR) and spatial econometrics methods. In this matter, the present study innovates by constructing an annual database spanning 2000 and 2016 and by evaluating the impact of monetary and macroprudential policies on local credit supplied at the municipality-bank level. Results point to the existence of relevant impacts of these variables on credit, with institutional and regional aspects affecting this causal relation. In terms of the methods, Bayesian crossed models are the main toolset used in this research question, with spatial panels used secondarily as a robustness check in the results found. Future venues of research may study these results for a larger period and work with unbalanced data (balancing necessary due to the spatial panel).