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...

This paper studies the econometrics of computed dynamic models. Since these models generally lack a closed-form solution, their policy functions are approximated by numerical methods. Hence, the researcher can only evaluate an approximated likelihood associated with the approximated policy...

The dynamics of a linear (or linearized) dynamic stochastic economic model can be expressed in terms of matrices (A,B,C,D) that define a state space system. An associated state space system (A,K,C,Sigma) determines a vector autoregression for observables available to an econometrician. We review...

This paper uses a seminonparametric model and Consumer Expenditure Survey data to estimate life cycle profiles of consumption, controlling for demographics, cohort and time e.ects. In addition to documenting profiles for total and nondurable consumption, we devote special attention to the age...

We study the mechanisms through which the adoption of the Euro delayed, rather than advanced, economic reforms in the Euro zone periphery and led to the deterioration of important institutions in these countries. We show that the abandonment of the reform process and the institutional...

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...