This paper develops a particle …ltering algorithm to estimate dynamic equilibrium models with stochastic volatility using a likelihood-based approach. The algorithm, which exploits the structure and profusion of shocks in stochastic volatility models, is versatile and computationally...

This paper shows how changes in the volatility of the real interest rate at which small open emerging economies borrow have a quantitatively important effect on real variables like output, consumption, investment, and hours worked. To motivate our investigation, we document the strong evidence...

The authors study the effects of changes in uncertainty about future fiscal policy on aggregate economic activity. Fiscal deficits and public debt have risen sharply in the wake of the financial crisis. While these developments make fiscal consolidation inevitable, there is considerable...

We study the effects of changes in uncertainty about future fiscal policy on aggregate economic activity. Fiscal deficits and public debt have risen sharply in the wake of the financial crisis. While these developments make fisscal consolidation inevitable, there is considerable uncertainty...

This paper examines how supply-side policies may play a role in fighting a low aggregate demand that traps an economy at the zero lower bound (ZLB) of nominal interest rates. Future increases in productivity or reductions in mark-ups triggered by supply-side policies generate a wealth effect...

This paper shows how particle filtering allows us to undertake likelihood-based inference in dynamic macroeconomic models. The models can be nonlinear and/or non-normal. We describe how to use the output from the particle filter to estimate the structural parameters of the model, those...

Jesus Fernandez-Villaverde and Juan F. Rubio-Ramirez are both Associate Professors of Economics at Duke University. They have written several papers about how to take dynamic general equilibrium models to the data.

This paper presents a framework to undertake likelihood-based inference in nonlinear dynamic equilibrium economies. We develop a Sequential Monte Carlo algorithm that delivers an estimate of the likelihood function of the model using simulation methods. This likelihood can be used for parameter...

This paper compares two methods for undertaking likelihood-based inference in dynamic equilibrium economies: a Sequential Monte Carlo filter proposed by Fernández-Villaverde and Rubio-Ramírez (2004) and the Kalman filter. The Sequential Monte Carlo filter exploits the nonlinear structure of...