We develop a sequential procedure to test the adequacy of jump-diffusion models for return distributions. We rely on intraday data and nonparametric volatility measures, along with a new jump detection technique and appropriate conditional moment tests, for assessing the import of jumps and...

A more powerful version of the ADF test and a test that has trend stationarity as the null are applied to U.S. GNP. Simulated critical values generated from plausible trend and difference stationary models are used in order to minimize possible finite sample biases. The discriminatory power of...

This paper shows that the asymptotic normal approximation is often insufficiently accurate for volatility estimators based on high frequency data. To remedy this, we compute Edgeworth expansions for such estimators. Unlike the usual expansions, we have found that in order to obtain meaningful...

We propose two new jump-robust estimators of integrated variance based on high-frequency return observations. These MinRV and MedRV estimators provide an attractive alternative to the prevailing bipower and multipower variation measures. Specifically, the MedRV estimator has better theoretical...

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 consisting of an artificial state-space...

We develop an empirical search-matching model which is suitable for analyzing the wage, employment and welfare impact of regulation in a labor market with heterogeneous workers and jobs. To achieve this we develop an equilibrium model of wage determination and employment which extends the...

This paper studies the pruned state-space system for higher-order approximations to the solutions of DSGE models. For second- and third-order approximations, we derive the statistical properties of this system and provide closed-form expressions for first and second unconditional moments and...

We compare the performance of maximum likelihood (ML) and simulated method of moments (SMM) estimation for dynamic discrete choice models. We construct and estimate a simplified dynamic structural model of education that captures some basic features of educational choices in the United States in...

Computable General Equilibrium models, widely used for the analysis of Free Trade Agreements (FTAs) are often criticized for having poor econometric foundations. This paper improves the linkage between econometric estimates of key parameters and their usage in CGE analysis in order to better...

This paper studies how stable over time are the so-called "structural parameters" of dynamic stochastic general equilibrium (DSGE) models. To answer this question, we estimate a medium-scale DSGE model with real and nominal rigidities using U.S. data. In our model, we allow for parameter...