Heterogeneity and Government Revenues: Higher Taxes at the Top?
By Nezih Guner, Martin Lopez-Daneri and Gustavo Ventura
We evaluate the effectiveness of a more progressive tax scheme in raising government revenues. We develop a life-cycle economy with heterogeneity and endogenous labor supply. Households face a progressive income tax schedule, mimicking the Federal Income tax, and flat-rate taxes that capture payroll, state and local taxes and the corporate income tax. We parameterize this model to reproduce aggregate and cross-sectional observations for the U.S. economy, including the shares of labor income for top earners. We find that a tilt of the Federal income tax schedule towards high earners leads to small increases in revenues which are maximized at an effective marginal tax rate of about 36.9% for the richest 5% of households – in contrast to a 21.7% marginal rate in the benchmark economy. Maximized revenue from Federal income taxes is only 8.4% higher than it is in the benchmark economy, while revenues from all sources increase only by about 1.6%. The room for higher revenues from more progressive taxes is even lower when average taxes are higher to start with. We conclude that these policy recommendations are misguided if the aim is to exclusively raise government revenue.
Taxing top earners: a human capital perspective
By Alejandro Badel and Mark Huggett
We assess the consequences of substantially increasing the marginal tax rate on U.S. top earners using a human capital model. The top of the model Laffer curve occurs at a 53 percent top tax rate. Tax revenues and the tax rate at the top of the Laffer curve are smaller compared to an otherwise similar model that ignores the possibility of skill change in response to a tax reform. We also show that if one applies the methods used by Diamond and Saez (2011) to provide quantitative guidance for setting the tax rate on top earners to model data then the resulting tax rate exceeds the tax rate at the top of the model Laffer curve
By coincidence, two papers on a very similar topic were listed in the same NEP-DGE report. And they have rather different results: Top tax rates of 37% versus 53%. How come? The models are quite different in fact. While the first one experiments with a tilting of the tax schedule, the second only increases the tax rate only of the top earners. This can justify part of the difference. Then the second one includes a human capital accumulation effect, which should actually lead to a lower top taxation rate. But as it considers the top 1% earners, while the first paper takes the top 5%, the results are not really comparable. Still both papers demonstrate that the top rates are lower than what simpler models show, and the additional complexity matters.
This all reminds us that quantitative results can sometimes be sensitive to 1) what your are measuring, and 2) what effects to include in the model. Hence the importance of either comparing results with previous literature as long as the models are nested or providing simplified models within the paper to gauge the impact of additional features.