Estimating persistence in Employee Business Expense correspondence examinations using Hidden Markov and Semi-Markov models 1

Abstract

We use Hidden Markov and Semi-Markov Models to study persistence of the compliance impact for tax examinations of Employee Business Expense (EBE). Using panels of yearly returns for taxpayers reporting EBE, we compare future filing behavior of those audited to those not audited, by fitting and comparing Hidden Markov and Semi-Markov Models for both groups. The Markov state space is EBE reporting compliance. The observation vectors are a function of reported line item amounts for a series of annual returns filed starting two years after the year of the tax audits, the baseline year. The functions used to create the observation vectors are proxies for compliance, and the unobserved Markov state space is true compliance. The observations have a probability distribution that is conditional upon unobserved compliance status. Our fitted models give some evidence that a no change audit may worsen compliance slightly.