A Portfolio-Balance Approach to the Nominal Term Structure
Explanations of why changes in the relative quantities of safe debt seem to affect asset prices often appeal informally to a ?portfolio balance? mechanism. I show how this type of effect can be incorporated in a general class of structural, arbitrage-free asset-pricing models using a numerical solution method that allows for a wide range of nonlinearities. I consider some applications in which the Treasury market is isolated, investors have mean-variance preferences, and the short-rate process is truncated at zero. Despite its simplicity, a version of this model incorporating inflation can ...
Adverse Selection, Risk Sharing and Business Cycles
I consider a real business cycle model in which agents have private information about an idiosyncratic shock to their value of leisure. I consider the mechanism design problem for this economy and describe a computational method to solve it. This is an important contribution of the paper since the method could be used to solve a wide class of models with heterogeneous agents and aggregate uncertainty. Calibrating the model to U.S. data I find a striking result: That the information frictions that plague the economy have no effects on business cycle fluctuations.
Optimal monetary policy regime switches
Given regime switches in the economy?s growth rate, optimal monetary policy rules may respond by switching policy parameters. These optimized parameters differ across regimes and from the optimal choice under fixed regimes, particularly in the inflation target and interest rate inertia. Optimal switching rules produce welfare gains relative to constant rules, with switches in the implicit real interest rate used for policy and the degree of interest rate inertia producing the largest gains. However, gains from switching rules decrease if the monetary authority trades-off the probability of ...
Computing Equilibria of Stochastic Heterogeneous Agent Models Using Decision Rule Histories
This paper introduces a general method for computing equilibria with heterogeneous agents and aggregate shocks that is particularly suitable for economies with private information. Instead of the cross-sectional distribution of agents across individual states, the method uses as a state variable a vector of spline coefficients describing a long history of past individual decision rules. Applying the computational method to a Mirrlees RBC economy with known analytical solution recovers the solution perfectly well. This test provides considerable confidence on the accuracy of the method.
Model Averaging and Persistent Disagreement
The authors consider the following scenario: Two agents construct models of an endogenous price process. One agent thinks the data are stationary, the other thinks the data are nonstationary. A policymaker combines forecasts from the two models using a recursive Bayesian model averaging procedure. The actual (but unknown) price process depends on the policymaker?s forecasts. The authors find that if the policymaker has complete faith in the stationary model, then beliefs and outcomes converge to the stationary rational expectations equilibrium. However, even a grain of doubt about ...
Learning about Regime Change
Total factor productivity (TFP) and investment specific technology (IST) growth both exhibit regime-switching behavior, but the regime at any given time is difficult to infer. We build a rational expectations real business cycle model where the underlying TFP and IST regimes are unobserved. We then develop a general perturbation solution algorithm for a wide class of models with unobserved regime-switching. Using our method, we show that learning about regime-switching alters the responses to regime shifts and intra-regime shocks, increases asymmetries in the responses, generates forecast ...
Optimal Monetary Policy Regime Switches
An economy that switches between high and low growth regimes creates incentives for the monetary authority to change its rule. As lower growth tends to produce lower real interest rates, the monetary authority has an incentive to increase the inflation target and increase the degree of inertia in setting rates in an attempt to keep the nominal rate positive. An optimizing monetary authority therefore responds to permanently lower growth by slightly increasing both the inflation target and inertia; focusing solely on the inflation target ignores a key margin of adjustment. With repeated growth ...
A Generalized Approach to Indeterminacy in Linear Rational Expectations Models
We propose a novel approach to deal with the problem of indeterminacy in Linear Rational Expectations models. The method consists of augmenting the original state space with a set of auxiliary exogenous equations to provide the adequate number of explosive roots in presence of indeterminacy. The solution in this expanded state space, if it exists, is always determinate, and is identical to the indeterminate solution of the original model. The proposed approach accommodates determinacy and any degree of indeterminacy, and it can be implemented even when the boundaries of the determinacy region ...
Some Implications of Uncertainty and Misperception for Monetary Policy
When choosing a strategy for monetary policy, policymakers must grapple with mismeasurement of labor market slack, and of the responsiveness of price inflation to that slack. Using stochastic simulations of a small-scale version of the Federal Reserve Board?s principal New Keynesian macroeconomic model, we evaluate representative rule-based policy strategies, paying particular attention to how those strategies interact with initial conditions in the U.S. as they are seen today and with the current outlook. To do this, we construct a current relevant baseline forecast, one that is loosely ...
Likelihood Evaluation of Models with Occasionally Binding Constraints
Applied researchers interested in estimating key parameters of DSGE models face an array of choices regarding numerical solution and estimation methods. We focus on the likelihood evaluation of models with occasionally binding constraints. We document how solution approximation errors and likelihood misspecification, related to the treatment of measurement errors, can interact and compound each other.