This paper describes a semiparametric Bayesian method for analyzing duration data. The proposed estimator specifies a complete functional form for duration spells, but allows flexibility by introducing an individual heterogeneity term, which follows a Dirichlet mixture distribution. I show how...

Empirical Bayes methods for Gaussian compound decision problems involving longitudinal data are considered. The new convex optimization formulation of the nonparametric (Kiefer-Wolfowitz) maximum likelihood estimator for mixture models is employed to construct nonparametric Bayes rules for...

We study job durations using a multivariate hazard model allowing for workerspecific and firm-specific unobserved determinants. The latter are captured by unobserved heterogeneity terms or random effects, one at the firm level and another at the worker level. This enables us to decompose the...

We study job durations using a multivariate hazard model allowing for worker-specific and firm-specific unobserved determinants. The latter are captured by unobserved heterogeneity terms or random effects, one at the firm level and another at the worker level. This enables us to decompose the...

This paper uses the Bayesian approach to solve and estimate a New Keynesian model augmented by a generalized Phillips curve, in which the shape of the price reset hazards can be identified using aggregate data. My empirical result shows that a constant hazard function is easily rejected by the...

This paper presents an approach to identify aggregate price reset hazards from the joint dynamic behavior of inflation and macroeconomic aggregates. The identification is possible due to the fact that inflation is composed of current and past reset prices and that the composition depends on the...