We explore the implications of heterogeneity in the elasticity of taxable income (ETI) for tax-reform based estimation methods. We theoretically show that existing methods yield elasticities that are biased and lack policy relevance. We illustrate the empirical importance of our theoretical...

Given the key role of the taxable income elasticity in designing an optimal tax system there are many studies attempting to estimate this elasticity. To account for nonlinear taxes these studies either use instrumental variables approaches that are not fully consistent, or impose strong...

Many studies have estimated the effect of taxes on taxable income. To account for nonlinear taxes these studies either use instrumental variables approaches that are not fully consistent, or impose strong functional form assumptions. None allow for general heterogeneity in preferences. In this...

Many studies have estimated the effect of taxes on taxable income. To account for nonlinear taxes these studies either use instrumental variables approaches that are not fully consistent or impose strong functional form assumptions. None allow for general heterogeneity in preferences. In this...

We explore the implications of heterogeneity in the elasticity of taxable income (ETI) for tax-reform based estimation methods. We theoretically show that existing methods yield elasticities that are biased and lack policy relevance. We illustrate the empirical importance of our theoretical...

We exploit the 1998 and 2003 constitutional amendment in Texas—allowing home equity loans and lines of credit for non-housing purposes—as natural experiments to estimate the effect of easier credit access on the labor market. Using state-level as well as county-level data and the...

We extend a standard taxable income model with its typical functional-form assumptions to account for nonlinear budget sets. We propose a new method to estimate taxable income elasticity that is more policy relevant than the typically estimated elasticity based on linearized budget sets. Using...