This paper derives optimal income tax formulas using compensated and uncompensated elasticities of earnings with respect to tax rates. A simple formula for the high income optimal tax rate is obtained as a function of these elasticities and the thickness of the top tail of the income...

This paper derives optimal income tax formulas using compensated and uncompensated elasticities of earnings with respect to tax rates. A simple formula for the high income optimal tax rate is obtained as a function of these elasticities and the thickness of the top tail of the income...

This paper discusses the response of the US federal income tax to financial innovation. Income taxation in the US and elsewhere has traditionally relied on distinction, such as the difference between fixed and contingent returns, that can be undermined by new financial products. The principal...

The principal purpose of this paper is to derive an expected value measure of the tax underreporting rate given only tax authority enforcement data. The main result is that the expected value measure of the underreporting rate is a modified geometric mean function of the audit rate and the...

On January 24, 2013, Congressman Dave Camp (R-MI), the Chairman of the House Ways and Means Committee, released the discussion draft of a bill that would tax derivatives under a mark-to-market system of taxation. This truly Copernican proposal would replace our entire federal system of taxing...

We study forwards and European call options, which are written on a non-storable renewable resource. Examples of such derivatives in form of futures on fresh catch of wild salmon for the US and the recently created Fish Pool market in Norway, where futures on a composite of wild catch and farmed...

In this paper we introduce the reader to the basic tools for the computation of Counterparty Credit Risk such as Credit Value Adjustment and Debt Value Adjustment. We also present the effect of mitigating clauses, like netting and collateral, in reducing the credit exposure. Detailed numerical...

This paper uses deep learning to value derivatives. The approach is broadly applicable, and we use a call option on a basket of stocks as an example. We show that the deep learning model is accurate and very fast, capable of producing valuations a million times faster than traditional models. We...