A meta-analysis on the Bank of Japan quantitative easing policy: the Bank of Japan's effectiveness to promote economic growth

• Autor(a) principal: Linhares, Pedro André Simões Roque
• Data de Publicação: 2018
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10071/18630
• topic: Quantitative easing; Bank of Japan; Effects of monetary policy on economic growth; Economia monetária; Banco Central; Política monetária; Instrumentos financeiros; Crescimento económico; Meta-análise; Japão

As the Qualitative and Quantitative Easing programmes are still in place there have been signs that the Japanese economy will maintain a path of moderate economic growth, still, without glancing the desired 2% inflation. The question over whether and how the Bank of Japan successive quantitative easing programmes, which were based on an unprecedented increase on the central bank’s asset sheet, have been successful in promoting a steady growth of the Japanese Economy, has been debated by the literature that is focused on the transmission channels of monetary policy. We present a comprehensive meta-analysis that focus on the literature that have been studying the effectiveness of the Bank of Japan’s policies during the 2001 to 2016 period, that resorts to the Vector Auto-regressive methodology to analyze, through impulse response functions, how monetary policy shocks impact output. An analysis based on funnel plots - Funnel Asymmetry Test - and linear regressions - Precision Effect Test - does not provide evidence of publication bias, neither the consensus over the output growth during the quantitative years. A meta-probit analysis suggests that a study with the characteristics mentioned above, which uses certain variables to build the model – industrial output, price level, bond yield and either the money base or the money supply - as well as different specifications in the data used - increasing the number of observations used or choosing quarterly data - will affect the probability of reporting statistically significant output growth; notwithstanding, the evidence found in this last analysis varies in terms of statistical robustness.