Leonardo Melosi

Modeling the Evolution of Expectations and Uncertainty in General Equilibrium

We develop methods to solve general equilibrium models in which forward-looking agents are subject to waves of pessimism, optimism, and uncertainty that turn out to critically affect macroeconomic outcomes. Agents in the model are fully rational, conduct Bayesian learning, and they know that they do not know. Therefore, agents take into account that their beliefs will evolve according to what they will observe. This framework accommodates both gradual and abrupt changes in beliefs and allows for an analytical characterization of uncertainty. Shocks to beliefs affect economic dynamics and uncertainty. We use a prototypical Real Business Cycle to illustrate the methods.

MODELING THE EVOLUTION OF EXPECTATIONS AND UNCERTAINTY IN GENERAL EQUILIBRIUM

We develop methods to solve general equilibrium models in which forward-looking agents are subject to waves of pessimism, optimism, and uncertainty that turn out to critically affect macroeconomic outcomes. Agents in the model are fully rational, conduct Bayesian learning, and they know that they do not know. Therefore, agents take into account that their beliefs will evolve according to what they will observe. This framework accommodates both gradual and abrupt changes in beliefs and allows for an analytical characterization of uncertainty. Shocks to beliefs affect economic dynamics and uncertainty. We use a prototypical Real Business Cycle to illustrate the methods.

Methods for Computing Marginal Data Densities from the Gibbs Output

We introduce two estimators for estimating the Marginal Data Density (MDD) from the Gibbs output. Our methods are based on exploiting the analytical tractability condition, which requires that some parameter blocks can be analytically integrated out from the conditional posterior densities. This condition is satisfied by several widely used time series models. An empirical application to six-variate VAR models shows that the bias of a fully computational estimator is sufficiently large to distort the implied model rankings. One of the estimators is fast enough to make multiple computations of MDDs in densely parameterized models feasible.

A Likelihood Analysis of Models with Information Frictions

This paper develops a dynamic stochastic general equilibrium model where firms are imperfectly informed. We estimate the model through likelihood-based methods and find that it can explain the highly persistent real effects of monetary disturbances that are documented by a benchmark VAR. The model of imperfect information nests a model of rational inattention where firms optimally choose the variances of signal noise, subject to an information-processing constraint. We present an econometric procedure to evaluate the predictions of this rational inattention model. Implementing this procedure delivers insights on how to improve the fit of rational inattention models.

Forward Guidance and Macroeconomic Outcomes Since the Financial Crisis

This chapter studies the effects of FOMC forward guidance. We begin by using high-frequency identification and direct measures of FOMC private information to show that puzzling responses of private-sector forecasts to movements in federal funds futures rates on FOMC announcement days can be attributed entirely to Delphic forward guidance. However, a large fraction of futures rates’ variability on announcement days remains unexplained, leaving open the possibility that the FOMC has successfully communicated Odyssean guidance. We then examine whether the FOMC used Odyssean guidance to improve macroeconomic outcomes since the financial crisis. To this end we usean estimated medium-scale New Keynesian model to perform a counterfactual experiment for the period 2009:Q1–2014:Q4, in which we assume the FOMC did not employ any Odyssean guidance and instead followed its reaction function from before the crisis as closely as possible while respecting the effective lower bound. We find that a purely rule-based policy would have delivered a shallower recession and kept inflation closer to target in the years immediately following the crisis than FOMC forward guidance did in practice. However, starting toward the end of 2011, after the Fed’s introduction of “calendar-based” communications, the FOMC’s Odyssean guidance appears to have boosted real activity and moved inflation closer to target. We show that our results do not reflect Del Negro, Giannoni, and Patterson’s (2015) forward-guidance puzzle.