This paper, intended for researchers, introduces a stochastic method for calculating the optimal tax schedule based on taxpayer utility, population skill distribution, and wages. It implements and extends the classic approach to optimal income tax calculation introduced by J.A. Mirrlees. A...

We use a behavioural microsimulation model embedded in a numerical optimization procedure in order to identify optimal (social welfare maximizing) tax-transfer rules. We consider the class of tax-transfer rules consisting of a universal basic income and a tax defined by a 4th degree polynomial....

When should you harvest a tax loss? Tax-loss harvesting is a strategy used to improve the net of tax returns of a portfolio, where an investor deliberately sells assets that have incurred a loss in order to use these losses to offset current or future capital gains. However, an important...

Should automation be regulated? This paper studies optimal tax of robot and regulation of automation. A job assignment model is embedded into a Mirrleesian tax problem. A task may either be assigned to the robot or one type of labors, which naturally determines the automation rate. The robot can...

In this chapter we study dynamic incentive models in which risk sharing is endogenously limited by the presence of informational or enforcement frictions. We comprehensively overview one of the most important tools for the analysis such problems—the theory of recursive contracts. Recursive...

In a less widely known contribution, Béla Martos (1966, Hungarian Academy of Sciences) introduced a generalized notion of concavity that is closely related to what is nowadays known as r-concavity in the operations research literature, and that is identical to what is nowadays known as...

We look at the theory of arbitrage with taxation under certainty. The tax scale in our model is not linear. Under the premise that tax scale is convex, we analyze prices that do not exhibit arbitrage opportunities. It turns out that there are two kinds of arbitrage: unbounded as well as bounded...