We develop novel methods for estimation and filtering of continuous-time models with stochastic volatility and jumps using so-called Approximate Bayesian Computation which build likelihoods based on limited information. The proposed estimators and filters are computationally attractive relative...

Given a sample from a fully specified parametric model, let Z_<em>n</em> be a given finite-dimensional statistic - for example, an initial estimator or a set of sample moments. We propose to (re-)estimate the parameters of the model by maximizing the likelihood of Z_<em>n</em>. We call this the maximum indirect...

Given a sample from a fully specified parametric model, let Zn be a given finite-dimensional statistic - for example, an initial estimator or a set of sample moments. We propose to (re-)estimate the parameters of the model by maximizing the likelihood of Zn. We call this the maximum indirect...

Given a sample from a fully specified parametric model, let $Z_n$ be a given finite-dimensional statistic - for example, an initial estimator or a set of sample moments. We propose to (re-)estimate the parameters of the model by maximizing the likelihood of $Z_n$. We call this the maximum...

Economists often use matched samples, especially when dealing with earnings data where a number of missing observations need to be imputed. In this paper, we demonstrate that the ordinary least squares estimator of the linear regression model using matched samples is inconsistent and has a...

Economists often use matched samples, especially when dealing with earnings data where a number of missing observations need to be imputed. In this paper, we demonstrate that the ordinary least squares estimator of the linear regression model using matched samples is inconsistent and has a...

We estimate by means of indirect inference a structural economic model where firms' exit and investment decisions are the solution to a discrete-continuous dynamic programming problem. In the model the exit probability depends on the current capital stock and a measure of short-run...

We estimate by means of indirect inference a structural economic model where firms’ exit and investment decisions are the solution to a discrete-continuous dynamic programming problem. In the model the exit probability depends on the current capital stock and a measure of short-run...

We estimate by means of indirect inference a structural economic model where firms’ exit and investment decisions are the solution to a discrete-continuous dynamic programming problem. In the model the exit probability depends on the current capital stock and a measure of short-run...

We propose a numerical method, based on indirect inference, for checking the identification of a DSGE model. Monte Carlo samples are generated from the model's true structural parameters and a VAR approximation to the reduced form estimated for each sample. We then search for a different set of...