We investigate the relationship between social interaction and household finances using data from the British Household Panel Survey. We contribute to the existing literature by exploring the relationship between a wide range of aspects of household finances and social interaction, rather than...

In this paper, we contribute to the empirical literature on household finances by introducing a Bayesian bivariate two-part model. With correlated random effects, the proposed approach allows for the potential interdependence between the holding of assets and debt at the household level and also...

Joint modeling of multiple health related random variables is essential to develop an understanding for the public health consequences of an aging population. This is particularly true for patients suffering from multiple chronic diseases. The contribution is to introduce a novel model for...

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,...

We estimate the cost of cultural biases in high-stake economic decisions by comparing agents' peer-to-peer lending choices with those the same agents make under the assistance of an automated robo-advisor. We first confirm substantial in-group vs. out-group and stereotypical discrimination,...

Measurement error models often arise in epidemiological and clinical research. Usually, in this set up it is assumed that the latent variable has a normal distribution. However, the normality assumption may not be always correct. Skew-normal/independent distribution is a class of asymmetric...

In many biomedical applications, researchers encounter semicontinuous data where data are either continuous or zero. When the data are collected over time the observations may be correlated. Analysis of this kind of longitudinal semicontinuous data is challenging due to the presence of strong...