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 I 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