Computational Science of Taxation
Full course description
The aim of Computational Science of Taxation is that students learn to think interdisciplinary between tax and technology. Computational science is a multidisciplinary field and it aims to understand complex systems by developing computational models and simulations. Computational taxation is to tax law what bioinformatics is to medicine and econometrics and business analytics are to economics. The focus question of this course is how computational models and methods may help to understand and improve the tax domain and complexity in taxation?
Students who successfully complete this course will be able to build bridges between the tax domain and the technology domain. They will have the conceptual knowledge and personal competences to be able to co-create innovative computational tax solutions and work in multi-disciplinary teams of tax lawyers, business & public policy advisors, and computer and data scientists.
Course objectives
Upon successful completion of this course, a student is able to:
- Describe and explain major historical, current and future developments in computer science and their impact in the past or potential to reinvent the tax domain of the future.
- Explain taxation as a computational model:
- Translate taxation problems as computational models
- Describe, explain and apply the data science process;
- Describe and explain how computational models can assist in reasoning about taxation problems.
- Explain how computational tax models can be valorised in practice and/or have social impact.
This course is part of the national Tax and Technology series of courses organized by Maastricht University, Vrije Universiteit Amsterdam and Tilburg University. For more information, visit www.taxandtechnology.com.
This course has been made possible with a grant from the Fonds Tax & Technology.
Prerequisites
None
Recommended reading
Will be announced in Student Portal.