Tagging and income taxation: Theory and an application

We derive a set of analytical results for optimal income taxation with tags using quasilinear preferences and a Rawlsian social welfare function. Secondly, assuming a constant elasticity of labor supply and log-normality of the skills distribution, we analytically identify the winners and losers of tagging. Third, we prove that if the skills distribution in one group first-order stochastically dominates the other, tagging calls for redistribution from the former to the latter group. Finally, we calibrate our model to the US workers using gender as tag. Welfare implications are dramatic. Only male high-wage earners lose. Everyone else gains, some substantially.