論文

We estimate a New Keynesian model incorporating two notable features: bounded rationality and the zero lower bound on the nominal interest rate. Our Bayesian estimation of a nonlinear model shows that the model with bounded rationality better fits the U.S. data than its rational expectations counterpart, and that both households and firms exhibit a substantial degree of bounded rationality. Moreover, we demonstrate that bounded rationality expands a parameter region in which the model can be estimated and weakens the power of forward guidance.

Empirical literature has documented that the persistence of the gap between inflation and its trend declined after the Volcker disinflation. Previous studies into the source of the decline in inflation gap persistence have offered competing views while sidestepping the possibility of equilibrium indeterminacy. We examine the source of the decline by estimating a medium-scale dynamic stochastic general equilibrium model using Bayesian methods that allow for indeterminacy. We show that the Fed's change from a passive to an active policy response to the inflation gap or a decrease in firms' probability of price change can fully account for the decline in inflation gap persistence by ruling out indeterminacy that induces persistent economic dynamics.

We review solution and estimation methods for nonlinear dynamic stochastic general equilibrium models and their application, with a special focus on the zero lower bound on the nominal interest rate. In a fully nonlinear setting, both the solution and estimation methods involve iterative procedures, and their computational expense grows rapidly with an increase in the dimensionality of state variables and parameters. We describe how the procedures deal with the dimensionality problem.

Benhabib et al. [(2001) Journal of Economic Theory 96, 40–69] argue that there exists a deflation steady state when the zero lower bound on the nominal interest rate is considered in a Taylor-type monetary policy rule. This paper estimates a medium-scale DSGE model with a deflation steady state for the Japanese economy during the period from 1999 to 2013, when the Bank of Japan conducted a zero interest rate policy and the inflation rate was almost always negative. Although the model exhibits equilibrium indeterminacy around the deflation steady state, a set of specific equilibria is selected by Bayesian methods. According to the estimated model, positive shocks to households’ preferences and wage markup, and a negative shock to monetary policy do not necessarily have an inflationary effect, in contrast to a standard model with a targeted-inflation steady state. An economy in the deflation equilibrium could experience unexpected volatility because of sunspot fluctuations, but it turns out that sunspot shocks have a limited effect on Japan’s output fluctuations and rather contribute to stabilizing the economy after the global financial crisis.

A large literature has established the view that the Fed's change from a passive to an active policy response to inflation led to U.S. macroeconomic stability after the Great Inflation of the 1970s. We revisit this view by estimating a generalized New Keynesian model using a full-information Bayesian method that allows for indeterminacy of equilibrium and adopts a sequential Monte Carlo algorithm. The estimated model empirically outperforms canonical New Keynesian models that confirm the literature's view. It also points to substantial uncertainty about whether the policy response to inflation was active or passive during the Great Inflation. More importantly, a more active policy response to inflation alone does not suffice for explaining the U.S. macroeconomic stability, unless it is accompanied by a change in either trend inflation or policy responses to the output gap and output growth. This extends the literature by emphasizing the importance of the changes in other aspects of monetary policy in addition to its response to inflation.

The empirical importance of news shocks - anticipated future shocks - in business cycle fluctuations has been explored by using only actual data when estimating models augmented with news shocks. This paper additionally exploits forecast data to identify news shocks in a canonical dynamic stochastic general equilibrium model. The estimated model shows new empirical evidence that technology news shocks are a major source of fluctuations in US output growth. Exploiting the forecast data not only generates more precise estimates of news shocks and other parameters in the model, but also increases the contribution of technology news shocks to the fluctuations.