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...

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...

This paper examines the determinants of unemployment duration in a competing risks framework with two destination states, namely, inactivity and employment. The major innovation is our recognition of defective risks. We first use a polynomial hazard function to test for the presence of...

This paper proposes a new approach for analyzing the relationship between macroeconomic factors and the income distribution. The conventional method of analysis is regression of summary inequality indices on variables such as the unemployment and inflation rates. Building on the lessons from...

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...