Essays in Tax Policy Evaluation

Abstract

This dissertation contains a collection of new theories, empirical methodologies, and data analyses for the evaluation of tax policy.

In the first chapter, I investigate the degree to which tax deductions respond to the tax rate, and the implications this has for tax policy. I define a new tax instrument, the 'deductibility rate', which specifies the proportion of eligible expenses a taxpayer may deduct when preparing her taxes. If the utilities of gross income and deductions are separable, then the deduction elasticity reflects the revenue leakage caused by greater deductibility. To identify this elasticity, I develop the first method to decompose bunching in taxable income into its constituent parts, exploiting the removal of a notch in the tax schedule. This setting also generates an observed counterfactual density, obviating the parametric assumptions routinely made in bunching studies. Applying this method to new administrative tax data from Australia, I find that while deductions account for just 5% of taxable income, they account for 35% of the response of taxable income to the tax rate. Based on an elasticity of taxable income of 0.06, the deduction elasticity is -0.45, and the gross-income elasticity is 0.04. Consistent with standard optimal-tax logic, the sensitivity of deductions to the tax rate suggests that restricting deductions could raise welfare.

In the second chapter, I develop a new empirical method for addressing a common problem afflicting regression discontinuity (RD) designs. This design has gained wide popularity for its perceived credibility in identifying treatment effects. But there are common settings in which the necessary assumptions of the method are not satisfied. When units manipulate their value of the running variable across the treatment threshold, this can distort the average outcome near the threshold, invalidating the RD design. Some settings in which the design would otherwise be appropriate offer a comparison group for which the treatment status does not change at the threshold. In such settings, it's common to observe variables, such as lags of the outcome, that predict the outcome in the absence of manipulation. I devise a nonparametric propensity-score reweighting method that exploits these variables to correct for manipulation bias. The method relies on 'manipulation-on-observed-variables' and common-support assumptions akin to those used in standard matching and weighting exercises.

In the third chapter, I develop a new theory of tax evasion under third-party reporting. When a tax authority requires reports from third parties about a taxable transaction, tax evasion is feasible only if the reporters underreport collusively. I develop a model of third-party reporting to investigate its limits as an enforcement tool. Under what conditions is a third-party reporting regime robust to collusion between reporters? The deterrence effect of third-party reporting increases with the number of reporters per transaction and with uncertainty about the other reports. Under certain conditions, third-party reporting can ensure full compliance when a common report is required across transactions. Compliance also improves with the number of related transactions in which there is underreporting, such that there is a maximum number of related transactions beyond which evasion is infeasible. These findings offer insights into the settings in which third-party reporting obligations are most effective in increasing compliance.