Search Results
Working Paper
Predictive density construction and accuracy testing with multiple possibly misspecified diffusion models
This paper develops tests for comparing the accuracy of predictive densities derived from (possibly misspecified) diffusion models. In particular, the authors first outline a simple simulation-based framework for constructing predictive densities for one-factor and stochastic volatility models. Then, they construct accuracy assessment tests that are in the spirit of Diebold and Mariano (1995) and White (2000). In order to establish the asymptotic properties of their tests, the authors also develop a recursive variant of the nonparametric simulated maximum likelihood estimator of Fermanian and ...
Report
Sectoral price facts in a sticky-price model
We develop a multi-sector sticky-price DSGE (dynamic stochastic general equilibrium) model that can endogenously deliver differential responses of prices to aggregate and sectoral shocks. Input-output production linkages induce across-sector pricing complementarities that contribute to a slow response of prices to aggregate shocks. In turn, input-market segmentation at the sectoral level induces within-sector pricing substitutability, which helps the model deliver a fast response of prices to sector-specific shocks. Estimating the factor-augmented vector autoregression specification of ...
Working Paper
The Chicago Fed DSGE model
The Chicago Fed dynamic stochastic general equilibrium (DSGE) model is used for policy analysis and forecasting at the Federal Reserve Bank of Chicago. This article describes its specification and estimation, its dynamic characteristics and how it is used to forecast the US economy. In many respects the model resembles other medium scale New Keynesian frameworks, but there are several features which distinguish it: the monetary policy rule includes forward guidance, productivity is driven by neutral and investment specific technical change, multiple price indices identify inflation and there ...
Working Paper
Documentation of the Research and Statistics Division’s estimated DSGE model of the U.S. economy: 2006 version
This paper provides documentation for the large-scale estimated DSGE model of the U.S. economy used in Edge, Kiley, and Laforte (2007). The model represents part of an ongoing research project (the Federal Reserve Board's Estimated, Dynamic, Optimization-based--FRB/EDO--model project) in the Macroeconomic and Quantitative Studies section of the Federal Reserve Board aimed at developing a DSGE model that can be used to address practical policy questions and the model documented here is the version that was current at the end of 2006. The paper discusses the model's specification, estimated ...
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
Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and realized volatilities
This paper proposes a method for constructing a volatility risk premium, or investor risk aversion, index. The method is intuitive and simple to implement, relying on the sample moments of the recently popularized model-free realized and option-implied volatility measures. A small-scale Monte Carlo experiment suggests that the procedure works well in practice. Implementing the procedure with actual S&P 500 option-implied volatilities and high-frequency five-minute-based realized volatilities results in significant temporal dependencies in the estimated stochastic volatility risk premium, ...
Working Paper
Estimating dynamic equilibrium models with stochastic volatility
We propose a novel method to estimate dynamic equilibrium models with stochastic volatility. First, we characterize the properties of the solution to this class of models. Second, we take advantage of the results about the structure of the solution to build a sequential Monte Carlo algorithm to evaluate the likelihood function of the model. The approach, which exploits the profusion of shocks in stochastic volatility models, is versatile and computationally tractable even in large-scale models, such as those often employed by policy-making institutions. As an application, we use our algorithm ...
Report
Evaluating interest rate rules in an estimated DSGE model
The empirical DSGE (dynamic stochastic general equilibrium) literature pays surprisingly little attention to the behavior of the monetary authority. Alternative policy rule specifications abound, but their relative merit is rarely discussed. We contribute to filling this gap by comparing the fit of a large set of interest rate rules (fifty-five in total), which we estimate within a simple New Keynesian model. We find that specifications in which monetary policy responds to inflation and to deviations of output from its efficient level?the one that would prevail in the absence of ...
Working Paper
Estimation and evaluation of DSGE models: progress and challenges
Estimated dynamic stochastic equilibrium (DSGE) models are now widely used for empirical research in macroeconomics as well as for quantitative policy analysis and forecasting at central banks around the world. This paper reviews recent advances in the estimation and evaluation of DSGE models, discusses current challenges, and provides avenues for future research.
Working Paper
A Bayesian multi-factor model of instability in prices and quantities of risk in U.S. financial markets
This paper analyzes the empirical performance of two alternative ways in which multi-factor models with time-varying risk exposures and premia may be estimated. The first method echoes the seminal two-pass approach advocated by Fama and MacBeth (1973). The second approach extends previous work by Ouysse and Kohn (2010) and is based on a Bayesian approach to modelling the latent process followed by risk exposures and idiosynchratic volatility. Our application to monthly, 1979-2008 U.S. data for stock, bond, and publicly traded real estate returns shows that the classical, two-stage approach ...