An egocentric model of the relations among the opportunity to underreport, social norms, ethical beliefs, and underreporting behavior

A model of the relations among taxpayers\u27 opportunity, social norms, ethical beliefs, and tax compliance is proposed and tested using structural equation modeling. High opportunity taxpayers, who may personally benefit from evasion, judged evasion as less unethical than low opportunity taxpayers. High and low opportunity taxpayers judged social norms similarly. Further, ethical beliefs partially (fully) mediate the relation between opportunity (social norms) and underreporting. Implications from our study to tax compliance researchers and policy makers are discussed. © 2008 Elsevier Ltd. All rights reserved

An egocentric model of the relations among the opportunity to underreport, social norms, ethical beliefs, and underreporting behavior

A model of the relations among taxpayers' opportunity, social norms, ethical beliefs, and tax compliance is proposed and tested using structural equation modeling. High opportunity taxpayers, who may personally benefit from evasion, judged evasion as less unethical than low opportunity taxpayers. High and low opportunity taxpayers judged social norms similarly. Further, ethical beliefs partially (fully) mediate the relation between opportunity (social norms) and underreporting. Implications from our study to tax compliance researchers and policy makers are discussed.accounting, organizations, society

Why you should consider SEM: A guide to getting started

Structural Equation Modeling (SEM) offers researchers additional flexibility and enhanced research conclusions, yet it is still underutilized in accounting. This may be in part because many researchers are not sufficiently familiar with SEM. SEM can be difficult to apply, especially if the research study was not appropriately planned to accommodate the necessary assumptions and data requirements. This article helps researchers overcome some barriers to using SEM by providing a simple guide to effectively planning a study suitable for an SEM analysis while also suggesting references and additional reading on the topic. To further encourage the use of SEM, the practical benefits of using SEM over the traditional regression approach for some research situations are also explained. Finally, a comparison of a regression and an SEM analysis of the same data testing the same theoretical model is included in the Appendices A and B in order to compare the differences in the research conclusions obtained by the two methods of analysis. © 2006 Elsevier Ltd. All rights reserved