CCE Theses and Dissertations

Date of Award

2019

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

College of Computing and Engineering

Advisor

Amon B. Seagull

Committee Member

Michael Laszlo

Committee Member

Steven R. Terrell

Keywords

cross-references, information science, Internal Revenue Code, law, readability

Abstract

Scholars and practitioners have long argued that U.S. income tax law (“the Tax Code”) is excessively complex and difficult to understand, and hence imposes non-trivial adjudication, administration, planning, and compliance costs across the spectrum of income tax stakeholders: the courts, the Internal Revenue Service, tax practitioners, business managers, and individual taxpayers. Hence, there is considerable interest in reducing the effort needed to accurately understand and apply the provisions of income tax law. Prior scholarly work has strongly argued that exceptions to Tax Code provisions as expressed by cross-references embedded in the Tax Code text constitute a major source of reading complexity.

The goal of the study was to gain a first empirical understanding about the readability impacts on users who encounter cross-references while reading Tax Code provisions. The study included a human subjects task performance experiment with 75 undergraduate and graduate accounting student participants who were completing or had completed an introductory level course in federal income taxation. Participants were presented with integrated tax scenarios and accompanying sets of scenario questions. Copies of several Tax Code sections were the only reference materials available to the study participants. The study was based on a within-subjects experimental design.

To investigate the prior work argument, cross-references embedded in the Tax Code reference materials provided to study participants that expressed exceptions were all assigned to one cross-reference category, and all other cross-references that served different purposes were assigned to a second category. As responses to scenario questions were binary (correct/incorrect), logistic regression was used to test study hypotheses.

The study’s major finding was that reading cross-references assigned to the exceptions category had a very strong negative effect on task performance, while reading cross-references assigned to the second category had a modest positive effect on task performance. The finding thus supports decades of analysis and argument that cross-references related to expressing exceptions are a major source of Tax Code reading complexity. This outcome warrants further research into statutory exception language, that subset of statutory language used to express exceptions. Such a subset will include cross-references as one of many language elements that are available for the purpose of expressing exceptions.

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