We propose an empirical likelihood-based method of inference for comparing inequality between two populations. A series of Monte Carlo experiments are used to assess our method’s finite sample performance. We illustrate our approach using some Canadian household income data.

We propose an empirical likelihood method for application to a partially linear panel data model with fixed effects. The empirical log-likelihood ratio statistic is proved to be asymptotically chi-squared distributed, and the asymptotic properties of estimators for both the parametric and...

Using an empirical likelihood approach, we show that generalized linear models can still be consistently estimated even if dependent variables are not missing at random, and derive a Hausman test by comparing this estimator to the standard one.