Factor modeling is a popular strategy to induce sparsity in multivariate models as they scale to higher dimensions. We develop Bayesian inference for a recently proposed latent factor copula model, which utilizes a pair copula construction to couple the variables with the latent factor. We use...

I develop methods that produce consistent estimates of the Vasicek-Basel IRB (VAIRB) credit risk model parameters. I apply these methods to Moody's data on corporate defaults over the period 1920–2008 and assess the model fit and construct hypothesis tests using bootstrap methods. The results...

Comparing groups with respect to hypothetical constructs requires that the measurement models are equal across groups. Otherwise conclusions drawn from the observed indicators regarding differences at the latent level (mean differences, differences in the structural relations) might be severly...

This paper develops a generalized hedonic model in which an exogenous shock to a single product attribute can affect other attributes, the markets for the product's complements and substitutes, and aggregate quantity produced. These factors are shown to be empirically relevant and to cause bias...

We propose an approach for Bayesian inference in time-varying structural vector autoregressions (SVARs) identified with sign restrictions. The linchpin of our approach is a class of rotation-invariant time-varying SVARs in which the prior and posterior densities of any sequence of structural...