Methodological Issues with Common Accounting Variables in the Context of Measuring Income Shifting Consequences

51 Pages Posted: 25 Jun 2020

See all articles by Paul Demere

Paul Demere

University of Georgia - J.M. Tull School of Accounting

Jeffrey Gramlich

Carson College of Business

Date Written: June 2, 2020

Abstract

We document the empirical limitations of two common types of measures used in accounting research: additive linear scores and first-stage coefficients. While they have valid applications, using these measures in hypothesis testing can lead to misleading inferences. We describe these measures and their limitations, uses, and misuses in the context of recent literature that examines the consequences of income shifting. After illustrating why these measures are not ideal for empirical hypothesis testing, including examining income shifting consequences, we develop and validate a new measure of income shifting that can move the income shifting literature forward. This measure can be parsed to separately identify exogenous and endogenous variation in income shifting, and to separately analyze the U.S.–foreign and foreign–foreign components of income shifting.

Keywords: Income shifting, accounting measurement, correlated omitted variables

JEL Classification: C18, C81, F38, H26, H32, M40

Suggested Citation

Demere, Paul and Gramlich, Jeffrey, Methodological Issues with Common Accounting Variables in the Context of Measuring Income Shifting Consequences (June 2, 2020). Available at SSRN: https://ssrn.com/abstract=3617177 or http://dx.doi.org/10.2139/ssrn.3617177

Paul Demere (Contact Author)

University of Georgia - J.M. Tull School of Accounting ( email )

Athens, GA 30602
United States

Jeffrey Gramlich

Carson College of Business ( email )

Wilson Rd.
College of Business
Pullman, WA 99164
United States

HOME PAGE: http://https://business.wsu.edu/research-faculty/institutes/hoops-institute/

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
48
Abstract Views
221
PlumX Metrics