This article develops a Bayesian approach for estimating panel quantile regression with binary outcomes in the presence of correlated random effects. We construct a working likelihood using an asymmetric Laplace (AL) error distribution and combine it with suitable prior distributions to obtain...

This paper suggests that the weak empirical effect of human capital on growth in existing cross-country studies is partly the result of an inappropriate specification that does not account for the different channels through which human capital affects growth. A systematic replication of earlier...

Standard income inequality indices can be interpreted as a measure of welfare loss entailed in departures from equality of outcomes, for egalitarian social welfare functions defined on the distribution of outcomes. But such a welfare interpretation has been criticized for a long time on the...

Using detailed data on a cohort of young Americans who were in their late twenties and early thirties in 2008, we investigate the importance of forces different from economic incentives in nest-leaving decisions. We apply recent methods from social network econometrics to identify the importance...

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...

Prior empirical research on the theoretically proposed interaction between the quantity and the quality of children builds on exogenous variation in family size due to twin births and focuses on human capital outcomes. The typical finding can be described as a statistically nonsignificant...

In recent years there has been increasing concern about the identification of parameters in dynamic stochastic general equilibrium (DSGE) models. Given the structure of DSGE models it may be difficult to determine whether a parameter is identified. For the researcher using Bayesian methods, a...

Probabilistic risk beliefs are key drivers of economic and health decisions, but people are not always certain about their beliefs. We study these "imprecise probabilities", also known as ambiguous beliefs. We show that imprecision is measurable separately from the levels of risk beliefs. People...