運用時變參數向量自我迴歸模型探討貨幣政策之有效性

MEASURING THE EFFECTS OF MONETARY POLICY: A TIME-VARYING PARAMETER VECTOR AUTOREGRESSIVE APPROACH

陳俊廷(Jiun-Ting Chen) ； 張勝凱(Sheng-Kai Chang)

《經濟論文》 47卷1期 (2019/03) Pp. 31-73

摘要

傳統上，央行藉操作短期名目利率調控國內物價及產出。然而於利率已降至極低水平期間，此道貨幣政策傳遞機制功效令人存疑。本文試圖回答：日本貨幣政策在利率管道上之效果是否隨時間而有所變化？另外，在近年低利率環境下，大規模寬鬆貨幣政策透過該管道對於實質變數影響為何？本文運用貝氏（Bayesian）統計理論與馬可夫鏈蒙地卡羅法（Markov Chain Monte Carlo, MCMC）估計時變參數向量自我迴歸模型（time-varying parameter vector autoregression）得到以下結論：（1）1975－2015年間，日本利率管道效果及外生衝擊影響於不同期間呈異質性。（2）日本利率政策衝擊在1990年後對產出及失業率無顯著正面影響，支持近年其貨幣政策難以透過利率管道提振景氣的論點。

關鍵字

利率 ； 貨幣政策傳遞機制 ； 貝氏向量自我迴歸模型 ； 時變參數 ； 馬可夫鏈蒙地卡羅

並列摘要

Monetary authorities typically manipulated short-term nominal interest rate in order to smooth domestic price and production. However, the effectiveness of such policy becomes doubtful when the nominal interest rate is close to the zero lower bound. This paper applies Markov Chain Monte Carlo (MCMC) methods to estimate a Bayesian time-varying parameter vector autoregression model and attempts to evaluate the effectiveness of Japanese monetary policies through the interest rate channel in recent years. The main empirical findings of the paper are as follows. First, the effects of monetary policy through the interest rate channel show time-varying effects between 1975 and 2015 in Japan. Second, the shock of a decreasing interest rate has little positive effect on production and the unemployment rate. These findings are supported by the view that it is difficult for the quantitative easing policy in recent years to stimulate the economy through the interest rate channel.

並列關鍵字

Interest rate ； Transmission mechanism of monetary policy ； Bayesian vector autoregression ； Time varying coefficient ； Markov Chain Monte Carlo

參考文獻

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