Adaptive Learning and Monetary Policy: Lessons from Japan

Motivated by Japan's economic experiences and policy debates over the past two decades, this paper uses a dynamic general equilibrium open economy model to examine the volatility and welfare impact of alternative monetary policies. To capture the dynamic effects of likely structural breaks in the Japanese economy, we model agents’ expectation formation process with an adaptive learning framework, and compare four Taylor-styled policy rules that reflect concerns commonly raised in Japan's actual monetary policy debate. We first show that imperfect knowledge and the associated learning process induce higher volatility in the economy, while still retaining some of the policy conclusions from rational-expectations setups. In particular, explicit exchange rate stabilization is unwarranted; moreover, under volatile foreign disturbances, policymakers should consider targeting domestic price inflation rather than consumer price inflation. However, contrary to results based on rational expectations, we show that even though highly inflation-sensitive rules do raise output volatility, they may nevertheless improve overall welfare in an adaptive learning setting by smoothing inflation fluctuations. Our findings suggest that previous policy conclusions that are based on partial equilibrium analyses, or that ignore likely deviations from rational expectations, may not be robust.