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Working Paper
Bayesian semiparametric stochastic volatility modeling
This paper extends the existing fully parametric Bayesian literature on stochastic volatility to allow for more general return distributions. Instead of specifying a particular distribution for the return innovation, we use nonparametric Bayesian methods to flexibly model the skewness and kurtosis of the distribution while continuing to model the dynamics of volatility with a parametric structure. Our semiparametric Bayesian approach provides a full characterization of parametric and distributional uncertainty. We present a Markov chain Monte Carlo sampling approach to estimation with ...
Journal Article
Policy analysis using DSGE models: an introduction
Many central banks have come to rely on dynamic stochastic general equilibrium, or DSGE, models to inform their economic outlook and to help formulate their policy strategies. But while their use is familiar to policymakers and academics, these models are typically not well known outside these circles. This article introduces the basic structure, logic, and application of the DSGE framework to a broader public by providing an example of its use in monetary policy analysis. The authors present and estimate a simple New Keynesian DSGE model, highlighting the core features that this basic ...
Working Paper
Reputation, career concerns, and job assignments
Does a worker who had a successful career have stronger or weaker incentives to manipulate his reputation than a worker who performed poorly? This paper presents a tractable model that allows us to study career concerns when the strength of a worker?s incentives depends on his employment history (the history of his past actions, jobs, and performances). More specifically, the paper incorporates standard job assignments into the main model in Holmstrom?s (1999) seminal paper on career concerns. Equilibrium wages, equilibrium job assignments, and the strength of career-concern incentives are ...
Working Paper
Stochastic volatility
Given the importance of return volatility on a number of practical financial management decisions, the efforts to provide good real- time estimates and forecasts of current and future volatility have been extensive. The main framework used in this context involves stochastic volatility models. In a broad sense, this model class includes GARCH, but we focus on a narrower set of specifications in which volatility follows its own random process, as is common in models originating within financial economics. The distinguishing feature of these specifications is that volatility, being inherently ...
Working Paper
Solving stochastic money-in-the-utility-function models
This paper analyzes the necessary and sufficient conditions for solving money-in-the-utility-function models when contemporaneous asset returns are uncertain. A unique solution to such models is shown to exist under certain measurability conditions. Stochastic Euler equations, whose existence is normally assumed in these models, are then formally derived. The regularity conditions are weak, and economically innocuous. The results apply to the broad range of discrete-time monetary and financial models that are special cases of the model used in this paper. The method is also applicable to ...
Working Paper
Input and output inventories in general equilibrium
We build and estimate a two-sector (goods and services) dynamic stochastic general equilibrium model with two types of inventories: materials (input) inventories facilitate the production of finished goods, while finished goods (output) inventories yield utility services. The model is estimated using Bayesian methods. The estimated model replicates the volatility and cyclicality of inventory investment and inventory-to-target ratios. Although inventories are an important element of the model?s propagation mechanism, shocks to inventory efficiency or management are not an important source of ...
Report
Monetary policy analysis with potentially misspecified models
Policy analysis with potentially misspecified dynamic stochastic general equilibrium (DSGE) models faces two challenges: estimation of parameters that are relevant for policy trade-offs and treatment of estimated deviations from the cross-equation restrictions. This paper develops and explores policy analysis approaches that are based on either the generalized shock structure for the DSGE model or the explicit modeling of deviations from cross-equation restrictions. Using post-1982 U.S. data, we first quantify the degree of misspecification in a state-of-the art DSGE model and then document ...
Journal Article
How good is what you've got? DSGE-VAR as a toolkit for evaluating DSGE models
In the constant search for better models to help guide policy decisions, central banks have begun to use and develop dynamic stochastic general equilibrium (DSGE) models. Although such models were until recently considered theoretically sound but overly restrictive, newly developed methods have proved successful in specifying DSGE models that fit the macroeconomic data well. ; Policy institutions that use DSGE models in policymaking need a reliable method for evaluating the models? effectiveness. This article reviews a procedure recently proposed by the authors and their colleagues. The ...
Report
The term structure of inflation expectations
We present estimates of the term structure of inflation expectations, derived from an affine model of real and nominal yield curves. The model features stochastic covariation of inflation with the real pricing kernel, enabling us to extract a time-varying inflation risk premium. We fit the model not only to yields, but also to the yields' variance-covariance matrix, thus increasing identification power. We find that model-implied inflation expectations can differ substantially from break-even inflation rates when market volatility is high. Our model's ability to be updated weekly makes it ...
Working Paper
Frequentist inference in weakly identified DSGE models
The authors show that in weakly identified models (1) the posterior mode will not be a consistent estimator of the true parameter vector, (2) the posterior distribution will not be Gaussian even asymptotically, and (3) Bayesian credible sets and frequentist confidence sets will not coincide asymptotically. This means that Bayesian DSGE estimation should not be interpreted merely as a convenient device for obtaining asymptotically valid point estimates and confidence sets from the posterior distribution. As an alternative, the authors develop a new class of frequentist confidence sets for ...