Online Estimation of DSGE Models
The estimation of dynamic stochastic general equilibrium (DSGE) models is a computationally demanding task. As these models change to address new challenges (such as household and firm heterogeneity, the lower bound on nominal interest rates, and occasionally binding financial constraints), they become even more complex and difficult to estimate?so much so that current estimation procedures are no longer up to the task. This post discusses a new technique for estimating these models which belongs to the class of sequential Monte Carlo (SMC) algorithms, an approach we employ to estimate the ...
Online Estimation of DSGE Models
This paper illustrates the usefulness of sequential Monte Carlo (SMC) methods in approximating DSGE model posterior distributions. We show how the tempering schedule can be chosen adaptively, explore the benefits of an SMC variant we call generalized tempering for ?online? estimation, and provide examples of multimodal posteriors that are well captured by SMC methods. We then use the online estimation of the DSGE model to compute pseudo-out-of-sample density forecasts of DSGE models with and without financial frictions and document the benefits of conditioning DSGE model forecasts on nowcasts ...
Inflation dynamics in a small open-economy model under inflation targeting: some evidence from Chile
This paper estimates a small open-economy dynamic stochastic general equilibrium (DSGE) model, specified along the lines of Gal and Monacelli (2005) and Lubik and Schorfheide (2007), using Chilean data for the full inflation-targeting period of 1999 to 2007. We study the specification of the policy rule followed by the Central Bank of Chile, the dynamic response of inflation to domestic and external shocks, and the change in these dynamics under different policy parameters. We use the DSGE-VAR methodology from our earlier work (2007) to assess the robustness of the conclusion to the presence ...
Improving GDP measurement: a measurement-error perspective
We provide a new and superior measure of U.S. GDP, obtained by applying optimal signal-extraction techniques to the (noisy) expenditure-side and income-side estimates. Its properties -- particularly as regards serial correlation -- differ markedly from those of the standard expenditure-side measure and lead to substantially-revised views regarding the properties of GDP.
Shrinkage estimation of high-dimensional factor models with structural instabilities
In high-dimensional factor models, both the factor loadings and the number of factors may change over time. This paper proposes a shrinkage estimator that detects and disentangles these instabilities. The new method simultaneously and consistently estimates the number of pre- and post-break factors, which liberates researchers from sequential testing and achieves uniform control of the family-wise model selection errors over an increasing number of variables. The shrinkage estimator only requires the calculation of principal components and the solution of a convex optimization problem, which ...
Macroeconomic dynamics near the ZLB: a tale of two equilibria
This paper studies the dynamics of a New Keynesian dynamic stochastic general equilibrium (DSGE) model near the zero lower bound (ZLB) on nominal interest rates. In addition to the standard targeted-inflation equilibrium, we consider a deflation equilibrium as well as a Markov sunspot equilibrium that switches between a targeted-inflation and a deflation regime. We use the particle filter to estimate the state of the U.S. economy during and after the 2008-09 recession under the assumptions that the U.S. economy has been in either the targeted-inflation or the sunspot equilibrium. We consider ...
Piecewise-Linear Approximations and Filtering for DSGE Models with Occasionally Binding Constraints
We develop an algorithm to construct approximate decision rules that are piecewise-linear and continuous for DSGE models with an occasionally binding constraint. The functional form of the decision rules allows us to derive a conditionally optimal particle ﬁlter (COPF) for the evaluation of the likelihood function that exploits the structure of the solution. We document the accuracy of the likelihood approximation and embed it into a particle Markov chain Monte Carlo algorithm to conduct Bayesian estimation. Compared with a standard bootstrap particle ﬁlter, the COPF signiﬁcantly ...
DSGE model-based estimation of the New Keynesian Phillips curve
This paper surveys estimates of New Keynesian Phillips curve (NKPC) parameters that have been obtained by fitting fully specified dynamic stochastic general equilibrium (DSGE) models to U.S. data. We examine various sources of identification in the context of a simple analytical model. DSGE model-based NKPC estimates tend to be fragile and sensitive to the model specification, in particular if marginal costs are treated as an unobserved variable. Estimates of the NKPC slope lie between 0 and 4. If the observations span the labor share, which is in most instances the model-implied measure of ...
Non-stationary hours in a DSGE model
The time series fit of dynamic stochastic general equilibrium (DSGE) models often suffers from restrictions on the long-run dynamics that are at odds with the data. Relaxing these restrictions can close the gap between DSGE models and vector autoregressions. This paper modifies a simple stochastic growth model by incorporating permanent labor supply shocks that can generate a unit root in hours worked. Using Bayesian methods we estimate two versions of the DSGE model: the standard specification in which hours worked are stationary and the modified version with permanent labor supply shocks. ...
Assessing DSGE model nonlinearities
We develop a new class of nonlinear time-series models to identify nonlinearities in the data and to evaluate nonlinear DSGE models. U.S. output growth and the federal funds rate display nonlinear conditional mean dynamics, while inflation and nominal wage growth feature conditional heteroskedasticity. We estimate a DSGE model with asymmetric wage/price adjustment costs and use predictive checks to assess its ability to account for nonlinearities. While it is able to match the nonlinear inflation and wage dynamics, thanks to the estimated downward wage/price rigidities, these do not spill ...