In this paper, we use Bayesian nonparametric learning to estimate the skill of actively managed mutual funds and also to estimate the population distribution for this skill. A nonparametric hierarchical prior, where the hyperprior distribution is unknown and modeled with a Dirichlet process...

We consider nonparametric estimation of a mixed discrete-continuous distribution under anisotropic smoothness conditions and possibly increasing number of support points for the discrete part of the distribution. For these settings, we derive lower bounds on the estimation rates in the total...

Change point models using hierarchical priors share in the information of each regime when estimating the parameter values of a regime. Because of this sharing, hierarchical priors have been very successful when estimating the parameter values of short-lived regimes and predicting the...

We model the log-cumulative baseline hazard for the Cox model via Bayesian, monotonic P-splines. This approach permits fast computation, accounting for arbitrary censorship and the inclusion of nonparametric effects. We leverage the computational efficiency to simplify effect interpretation for...

Change point models using hierarchical priors share in the information of each regime when estimating the parameter values of a regime. Because of this sharing, hierarchical priors have been very successful when estimating the parameter values of short-lived regimes and predicting the...

In this paper we develop procedures for performing inference in regression models about how potential policy interventions affect the entire marginal distribution of an outcome of interest. These policy interventions consist of either changes in the distribution of covariates related to the...

Ridder and Woutersen (2003) have shown that under a weak condition on the baseline hazard there exist root-N consistent estimators of the parameters in a semiparametric Mixed Proportional Hazard model with a parametric baseline hazard and unspecified distribution of the unobserved heterogeneity....

We reanalyze the effects of a Danish active labour market program social experiment, that included a range of sub-treatments, including monitoring, job search assistance and training. Previous studies have shown that the overall effect of the experiment is positive. We apply newly developed...

This paper considers the definition and identification of treatment effects on conditional transition probabilities. We show that even under sequential random assignment only the instantaneous average treatment effect is point identified. Because treated and control units drop out at different...

Public programs often use statistical profiling to assess the risk that applicants will become long-term dependent on the program. The literature uses linear probability models and (Cox) proportional hazard models to predict duration outcomes. These either focus on one threshold duration or...