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 -- an artificial state-space model, the...

We estimate a reduced-form model of credit risk that incorporates stochastic volatility in default intensity via stochastic time-change. Our Bayesian MCMC estimation method overcomes nonlinearity in the measurement equation and state-dependent volatility in the state equation. We implement on...

The accuracy of particle filters for nonlinear state-space models crucially depends on the proposal distribution that mutates time t-1 particle values into time t values. In the widely-used bootstrap particle filter this distribution is generated by the state-transition equation. While...

We estimate asset pricing models with multiple risks: long-run growth, long-run volatility, habit, and a residual. The Bayesian estimation accounts for the entire likelihood of consumption, dividends, and the price-dividend ratio. We find that the residual represents at least 80% of the variance...

This paper develops new estimates of flows into and out of unemployment that allow for unobserved heterogeneity across workers as well as direct effects of unemployment duration on unemployment-exit probabilities. Unlike any previous paper in this literature, we develop a complete dynamic...

This paper explores the role that unobserved heterogeneity within an observed category plays in the dynamics of disaggregate unemployment and in the cross-sectional differences across individuals of the duration of unemployment spells. The distribution of unobserved heterogeneity is...

Primary care physicians (PCPs) provide more specialty procedures in less-urban areas, where specialists are fewer. Using a structural random-coefficient model and the demographic and time variation in the data, this paper shows that changes in policy-set reimbursements lead to a reallocation of...

It has been well documented that the share of the working-age population employed in "middle-skill" occupations has been falling for some time, while the share in lower- and higher-skill jobs has been rising -- i.e. "polarization" of the labor market (e.g. Autor 2010). However, the dynamics and...

We study how a bank credit crunch -- a dramatic worsening of firm and consumer access to bank credit, such as the one observed over the Great Recession -- translates into job losses in U.S. manufacturing industries. To identify the impact of the recent credit crunch, we rely on differences in...

Aggregate U.S. labor market dynamics are well approximated by a dual labor market supplemented with a third, predominantly, home-production segment. We uncover this structure by estimating a Hidden Markov Model, a machine-learning method. The different market segments are identified through...