A decomposition algorithm for computing income taxes with pass-through entities and its application to the Chilean case

TL;DR

This paper introduces a mathematical model and a decomposition algorithm based on Markov chains to accurately compute taxable incomes in complex pass-through entity networks, exemplified by the Chilean tax system reform.

Contribution

It presents a novel decomposition algorithm utilizing Markov chain theory to efficiently solve the income distribution problem in pass-through entity networks.

Findings

Unique income distribution solution established

Algorithm efficiently computes taxable incomes

Application to Chilean taxpayers' network demonstrated

Abstract

Income tax systems with pass-through entities transfer a firm's incomes to the shareholders, which are taxed individually. In 2014, a Chilean tax reform introduced this type of entity and changed to an accrual basis that distributes incomes (but not losses) to shareholders. A crucial step for the Chilean taxation authority is to compute the final income of each individual, given the complex network of corporations and companies, usually including cycles between them. In this paper, we show the mathematical conceptualization and the solution to the problem, proving that there is only one way to distribute incomes to taxpayers. Using the theory of absorbing Markov chains, we define a mathematical model for computing the taxable incomes of each taxpayer, and we propose a decomposition algorithm for this problem. This allows us to compute the solution accurately and with the efficient use of computational resources. Finally, we present some characteristics of the Chilean taxpayers' network and computational results of the algorithm using this network.