Analysis and simulation


Risk-based auditing and taxpayers’ responses

The research will model the equilibrium consequences of risk-based audits and investigate improved designs for risk-based auditing. The objective of the research is to improve the hit-rate on audits and to raise the tax yield. The project will model the consequences of taxpayers learning about the audit strategy, the optimal updating of a risk-based strategy, and the potential benefits of random sampling.

Estimating Risk-Based Audit Rules

The simulation analysis of risk-based auditing will be of greater value if it is informed by the audit outcome data held in Datalab. The use of such data will permit the calibration of the simulation models. Moreover, the data and simulation can be used in tandem to estimate risk-based auditing rules on the basis of actual audit outcomes and to test for the consequence by implementing within the simulation model. The IRS has an ongoing project to implement a simulation analysis that uses real data to represent individual taxpayers. The project will build on the lessons learned from the IRS work but will focus on the modelling choice behaviour and upon greater sophistication in the estimation of risk-based auditing rules.

Understanding the intertemporal aspects of tax evasion and lifecycle choices

The aim of this project is to construct and calibrate a comprehensive lifecycle model of tax compliance using data on individual tax returns linked to data on audit outcomes in the Datalab. The project will extend this framework to incorporate lifecycle choice of labour supply, savings and investment, where all potential sources of income are subject to tax. This project will also assess whether a quasi-hyperbolic model of preferences has better explanatory power than the exponential model. The predictions of the calibrated model will be used to analyse the optimal dynamic structure of audit and penalty strategy of the tax administrator.