In February 2015, the editors of eight health economics journals sent out an editorial statement which aims to reduce the extent of specification searching and reminds referees to accept studies that: "have potential scientific and publication merit regardless of whether such studies' empirical...

We develop a parametrization of the multinomial probit model that yields greater insight into the underlying decision-making process, by decomposing the error terms of the utilities into latent factors and noise. The latent factors are identified without a measurement system, and they can be...

We explore whether a protective role for savings against future financial hardship exists using household level panel data. We jointly model the incidence and extent of financial problems, as well as the likelihood of having secured debt and the amount of monthly secured debt repayments,...

This paper estimates the impact of training incidence and duration on employment transitions accounting for the endogeneity of program participation and duration. We specify a very flexible bivariate random effects probit model for employment and training participation and we use Bayesian Markov...

We measure labor market frictions using a strategy that bridges design-based and structural approaches: estimating an equilibrium search model using reduced-form minimum wage elasticities identified from border discontinuities and fitted with Bayesian and LIML methods. We begin by providing the...

Dynamic discrete choice models usually require a general specification of unobserved heterogeneity. In this paper, we apply Bayesian procedures as a numerical tool for the estimation of a female labor supply model based on a sample size which is typical for common household panels. We provide...

We use panel data from NLSY79 to analyze the effects of the timing and spacing of births on the labor supply of married women in a framework that accounts for the endogeneity of labor market and fertility decisions, the heterogeneity of the effects of children and their correlation with the...

We propose a Bayesian factor analysis model to rank the health of localities. Mortality and morbidity variables empirically contribute to the resulting rank, and population and spatial correlation are incorporated into a measure of uncertainty. We use county-level data from Texas and Wisconsin...

This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the...

Empirical studies have found that cannabis commonly precedes consumption of drugs like amphetamine, ecstasy, cocaine and heroin. As a result a causal linkage between cannabis and subsequent hard drug use has been hypothesized. Despite mixed empirical evidence and a limited understanding of...