To measure income inequality with right censored (topcoded) data, we propose multiple imputation for censored observations using draws from Generalized Beta of the Second Kind distributions to provide partially synthetic datasets analyzed using complete data methods. Estimation and inference...

This paper considers the role of gender in the promotion process and the impact of promotion on wages and wage growth, using data from the National Longitudinal Survey of Youth (NLSY79). Its focus is upon mid-career promotion and wages, thereby complementing extant studies of the NLSY that...

Atypical work, or alternative work arrangements in U.S. parlance, has long been criticized for providing poorly-compensated employment. Although one group of atypical workers (contractors) seems to enjoy a wage premium, our cross-section results from the CPS and NLSY for the better-known...

The generalized entropy class of inequality indices is derived for Generalized Beta of the Second Kind (GB2) income distributions, thereby providing a full range of top-sensitive and bottom-sensitive measures. An examination of British income inequality in 1994/95 and 2004/05 illustrates the...

Cross-national differences in outcomes are often analysed using regression analysis of multilevel country datasets, examples of which include the ECHP, ESS, EU-SILC, EVS, ISSP, and SHARE. We review the regression methods applicable to this data structure, pointing out problems with the...

We examine the determinants of low income transitions using first-order Markov models that control for initial conditions effects (those found to be poor in the base year may be a nonrandom sample) and for attrition (panel retention may also be non-random). Our econometric model is a form of...

The paper constructs an asymmetric information model to investigate the efficiency and equity cases for government mandated benefits. A mandate can improve workers' insurance, and may also redistribute in favour of more "deserving" workers. The risk is that it may also reduce output. The more...