Optimal Spatial Taxation: Are Big Cities too Small?

We analyze the role of optimal income taxation across different local labor markets. Should labor in large cities be taxed differently from labor in small cities? We find that a planner who needs to raise a given level of revenue and is constrained by the free mobility of labor across cities and by endogenous housing prices does not choose equal taxes across cities of different sizes. The optimal tax schedule is place-based, and tax differences between large and small cities depend on the level of government spending, how resulting land rents are distributed, and the strength of agglomeration economies. Our estimates for the U.S. imply higher optimal tax rates in bigger cities. Under the current Federal Income tax code with redistributive taxes, marginal rates are already higher in big cities, which have higher wages, but the optimal difference we estimate is lower than what is currently observed. Simulating the U.S. economy under the optimal spatial tax schedule, there are large effects on population mobility: the fraction of the population in the 5 largest cities grows by 7.65%, with 3.31% of the country-wide population moving to bigger cities. The welfare gains are smaller due to the fact that much of the output gains are spent on the increased costs of housing in bigger cities. Aggregate goods consumption goes up by 0.95% while aggregate housing consumption goes down by 1.90\%.