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Master's Dissertation
DOI
https://doi.org/10.11606/D.12.2016.tde-21092016-104808
Document
Author
Full name
Fernando Kuwer dos Santos
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2016
Supervisor
Committee
Madeira, Gabriel de Abreu (President)
Nakane, Márcio Issao
Bonomo, Marco Antonio Cesar
Koyama, Sérgio Mikio
Title in English
Earmarked credit and misallocation: evidence from Brazil
Keywords in English
Borrowing constraints
Earmarked credit
Misallocation
Abstract in English
Essa dissertação estuda os efeitos de políticas de direcionamento de crédito sobre alocação de recursos na economia brasileira. Esse é um tópico particularmente importante para o Brasil, dado que a proporção do crédito que é direcionada no Brasil é próxima a 40%. As regras de direcionamento provavelmente geram distorções no preço de empréstimos, afetando assim o retorno marginal de fatores entre firmas e entre setores, consequentemente gerando misallocation de recursos. Fazendo uso de um modelo de agentes heterogêneos em tempo contínuo, se é capaz de estudar efeitos distributivos de tais políticas e explorar vantagens computacionais na solução do modelo. Calibra-se o modelo usando dados da economia brasileira e estatísticas de microdados de crédito que conectam informações sobre crédito e tamanho de firmas. Adicionalmente, verifica-se como tais políticas de direcionamento de crédito interagem com restrições ao crédito.
Title in Portuguese
Crédito direcionado e misallocation: evidência do Brasil
Keywords in Portuguese
Crédito
Direcionamento
Misallocation
Restrições ao crédito
Abstract in Portuguese
This paper looks at misallocation effects of earmarked credit in the Brazilian Economy. This is a very important topic in Brazil, where the proportion of credit earmarked for specific types of loans reach about 40% of total credit. The earmarking rules are likely to generate distortions in loan's prices, producing differences in marginal returns to inputs across firms and sectors, and therefore misallocation of resources. Using a heterogeneous agents in continuous time model, we are able to study distributional effects of such policies and explore some computational advantages to solve the model. Furthermore, we calibrate such model using Brazilian credit microdata statistics linking firm size and loans. Additionally, we will verify how these earmarked resources interact with credit constraints that are probably present in the Brazilian economy
 
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CorrigidaFernando.pdf (1.52 Mbytes)
Publishing Date
2016-09-27
 
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