Unequal opportunity, limited information and meritocracy

A prominent fairness ideal is that of meritocratic fairness, which regards inequality in earnings as fair if they reflect differences in performance, but not otherwise. A complementary fairness view, consistent with meritocratic fairness, is luck egalitarianism, which would equalize earnings for those components of earnings that arise from pure luck, but not necessarily those parts that are determined by actions of individuals. A growing literature (e.g. Konow (2000), Cappelen et al. (2007), Mollerstrom et al. (2015), Almas et al. (2019)) has found support for both meritocratic fairness and luck egalitarianism for significant shares of decision makers in redistribution experiments and surveys. The existing experimental work however typically only considers one source of inequality of earnings, and provides full performance information. The current study is a lab experiment to test fairness preferences when there are multiple sources of inequality of opportunity that may accumulate, and there is limited performance information. We test in particular how accumulation of different sources of inequality of opportunity is taken into account in redistribution decisions, and whether different forms of performance information may lead to a neglect of inequality of opportunity information.