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Novas evidências de causalidade entre sistema financeiro e crescimento econômico no Brasil usando séries de tempo no domínio da frequência [New evidence on the causality between financial system and economic growth in Brazil using time series in the frequency domain]

Author

Listed:
  • Bruno de Paula Rocha

    (UFABC)

  • Igor Viveiro de Souza

    (UFMG)

Abstract

Este trabalho tem como objetivo apresentar testes de causalidade entre sistema financeiro e crescimento econômico no domínio da frequência, para séries temporais brasileiras. Esta abordagem permite não-linearidades associadas a mudanças de direção na causalidade do curto para o longo prazo. Para avaliar esta relação no Brasil, o artigo emprega séries temporais para o PIB per capita e de crédito bancário entre 1960 e 2010. Os resultados mostram variação nos testes de causalidade dependendo da frequência dos ciclos considerados, havendo evidências de que o sistema financeiro seja um fator causal para o crescimento econômico no Brasil, mas apenas no longo prazo.

Suggested Citation

  • Bruno de Paula Rocha & Igor Viveiro de Souza, 2018. "Novas evidências de causalidade entre sistema financeiro e crescimento econômico no Brasil usando séries de tempo no domínio da frequência [New evidence on the causality between financial system and e," Nova Economia, Economics Department, Universidade Federal de Minas Gerais (Brazil), vol. 28(1), pages 273-295, January-A.
  • Handle: RePEc:nov:artigo:v:28:y:2018:i:1:p:273-295
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    More about this item

    Keywords

    crescimento econômico; sistema financeiro; séries de tempo no domínio da frequência;
    All these keywords.

    JEL classification:

    • O16 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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