This paper develops a novel approach for estimating latent state variables of Dynamic Stochastic General Equilibrium (DSGE) models that are solved using a second-order accurate approximation. I apply the Kalman filter to a state-space representation of the second-order solution based on the...

In this paper we investigate the effects of uncertainty shocks on economic activity using a Dynamic Stochastic General Equilibrium (DSGE) model with heterogenous agents and a stylized banking sector. We show that frictions in credit supply amplify the effects of uncertainty shocks on economic...

This paper presents an algorithm to solve up to the second order of approximation rational expectations models with informational subperiods, and provides simple examples to demonstrate how the algorithm works. Copyright Springer Science+Business Media New York 2013

The empirical Bayes (EB) estimator or empirical best linear unbiased predictor (EBLUP) in the linear mixed model (LMM) is useful for the small area estimation in the sense of increasing the precision of estimation of small area means. However, one potential difficulty of EB is that when...

In this paper we investigate the effects of uncertainty shocks on economic activity using a Dynamic Stochastic General Equilibrium (DSGE) model with heterogenous agents and a stylized banking sector. We show that frictions in credit supply amplify the effects of uncertainty shocks on economic...

This paper shows how to compute a second-order accurate solution of a non-linear rational expectation model using algorithms developed for the solution of linear rational expectation models. The result is a state-space representation for the realized values of the variables of the model. This...

This paper shows how to compute a second-order accurate solution of a non-linear rational expectation model using algorithms developed for the solution of linear rational expectation models. The result is a state-space representation for the realized values of the variables of the model. This...

This paper shows how to compute a second-order accurate solution of a non-linear rational expectation model using algorithms developed for the solution of linear rational expectation models. This result is a state-space representation for the realized values of the variables of the model. This...