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Author:Schorfheide, Frank 

Working Paper
Macroeconomic Dynamics Near the ZLB : A Tale of Two Countries

We compute a sunspot equilibrium in an estimated small-scale New Keynesian model with a zero lower bound (ZLB) constraint on nominal interest rates and a full set of stochastic fundamental shocks. In this equilibrium a sunspot shock can move the economy from a regime in which inflation is close to the central bank's target to a regime in which the central bank misses its target, inflation rates are negative, and interest rates are close to zero with high probability. A nonlinear filter is used to examine whether the U.S. in the aftermath of the Great Recession and Japan in the late 1990s ...
International Finance Discussion Papers , Paper 1163

Working Paper
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 ...
Working Papers , Paper 14-4

Working Paper
Inference for VARs identified with sign restrictions

There is a fast growing literature that partially identifies structural vector autoregressions (SVARs) by imposing sign restrictions on the responses of a subset of the endogenous variables to a particular structural shock (sign-restricted SVARs). To date, the methods that have been used are only justified from a Bayesian perspective. This paper develops methods of constructing error bands for impulse response functions of sign-restricted SVARs that are valid from a frequentist perspective. The authors also provide a comparison of frequentist and Bayesian error bands in the context of an ...
Working Papers , Paper 11-20

Working Paper
Priors from general equilibrium models for VARs

This paper uses a simple New Keynesian monetary DSGE model as a prior for a vector autoregression and shows that the resulting model is competitive with standard benchmarks in terms of forecasting and can be used for policy analysis.
FRB Atlanta Working Paper , Paper 2002-14

Working Paper
DSGE model-based forecasting of non-modelled variables

This paper develops and illustrates a simple method to generate a DSGE model-based forecast for variables that do not explicitly appear in the model (non-core variables). The authors use auxiliary regressions that resemble measurement equations in a dynamic factor model to link the non-core variables to the state variables of the DSGE model. Predictions for the non-core variables are obtained by applying their measurement equations to DSGE model- generated forecasts of the state variables. Using a medium-scale New Keynesian DSGE model, the authors apply their approach to generate and evaluate ...
Working Papers , Paper 08-17

Working Paper
Evaluating DSGE model forecasts of comovements

This paper develops and applies tools to assess multivariate aspects of Bayesian Dynamic Stochastic General Equilibrium (DSGE) model forecasts and their ability to predict comovements among key macroeconomic variables. The authors construct posterior predictive checks to evaluate the calibration of conditional and unconditional density forecasts, in addition to checks for root-mean-squared errors and event probabilities associated with these forecasts. The checks are implemented on a three-equation DSGE model as well as the Smets and Wouters (2007) model using real-time data. They find that ...
Working Papers , Paper 11-5

Working Paper
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.
Working Papers , Paper 13-16

Working Paper
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 ...
Working Papers , Paper 13-29

Working Paper
Sequential Monte Carlo sampling for DSGE models

We develop a sequential Monte Carlo (SMC) algorithm for estimating Bayesian dynamic stochastic general equilibrium (DSGE) models, wherein a particle approximation to the posterior is built iteratively through tempering the likelihood. Using three examples--an artificial state-space model, the Smets and Wouters (2007) model, and Schmitt-Grohe and Uribe's (2012) news shock model--we show that the SMC algorithm is better suited for multimodal and irregular posterior distributions than the widely-used random-walk Metropolis-Hastings algorithm. We find that a more diffuse prior for the Smets and ...
Finance and Economics Discussion Series , Paper 2013-43

Working Paper
Tempered Particle Filtering

The accuracy of particle filters for nonlinear state-space models crucially depends on the proposal distribution that mutates time t-1 particle values into time t values. In the widely-used bootstrap particle filter this distribution is generated by the state-transition equation. While straightforward to implement, the practical performance is often poor. We develop a self-tuning particle filter in which the proposal distribution is constructed adaptively through a sequence of Monte Carlo steps. Intuitively, we start from a measurement error distribution with an inflated variance, and then ...
Finance and Economics Discussion Series , Paper 2016-072

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