The Gini coefficient is a downward-biased measure of inequality in small populations when income is generated by one of three common distributions. The paper discusses the sources of bias and argues that this property is far more general. This has implications for (i) the comparison of inequality among subsamples, some of which may be small, and (ii) the use of the Gini in measuring firm size inequality in markets with a small number of firms. The small-sample bias has often led to misperceptions about trends in industry concentration. A small-sample adjustment results in a reduced bias, which can no longer be signed. This remaining bias rises with the dispersion and falls with increasing skewness of the distribution. Finally, an empirical example illustrates the importance of using the adjusted Gini. In this example it is shown that, controlling for market characteristics, larger shipping cartels include a set of firms that is stochastically identical (in terms of relative size) to those of smaller shipping cartels.

We investigate the impact of passenger shipping cartels on trans-Atlantic migration during the early twentieth century. We assemble from primary sources a detailed database of passenger flows and cartel operations and show that cartel operation reduced migratory flows by approximately 20% to 25%. Further, we show that there was no strong intertemporal substitution in migration to North America (at least in the short run) and, therefore, that the effects of cartel operation were not “undone” by later migration. Lastly, we find that cartel operation had no appreciable effect on the variability of migration flows, providing evidence against the notion that unfettered competition was destabilizing to turn-of-the-century transportation markets.

In elections with three or more candidates, coordination among like-minded voters is an important problem. We analyse the trade-off between coordination and learning about candidate quality under different temporal election systems in the context of the U.S. presidential primary system. In our model, candidates with different policy positions and qualities compete for the nomination, and voters are uncertain about the candidates' valence. This setup generates two effects: vote splitting ( i.e . several candidates in the same policy position compete for the same voter pool) and voter learning (as the results in earlier elections help voters to update their beliefs on candidate quality). Sequential voting minimizes vote splitting in late districts, but voters may coordinate on a low-quality candidate. Using the parameter estimates obtained from all the Democratic and Republican presidential primaries during 2000–12, we conduct policy experiments such as replacing the current system with a simultaneous system, adopting the reform proposal of the National Association of Secretaries of State, or imposing party rules that lead to candidate withdrawal when prespecified conditions are met.