Instagram Linkedin

Gross profit manipulation in emerging economies: evidence from India

Title: Gross profit manipulation in emerging economies: evidence from India

Author (s):: Bansal M.; Kumar A.; Kumar V.

Journal: Pacific Accounting Review

Month and Year: November 2021

Abstract: Purpose: This study aims to explore peer performance as the motivation behind gross profit manipulation through two different channels, namely, cost of goods sold (COGS) misclassification and revenue misclassification. Design/methodology/approach: Gross profit expectation model (Poonawala and Nagar, 2019) and operating revenue expectation model (Malikov et al., 2018) are used to measure COGS and revenue misclassification, respectively. The panel data regression models are used to analyze the data for this study. Findings: The study results show that firms engage in gross profit manipulation to meet the industry’s average gross margin, implying that peer performance is an important benchmark that firms strive to achieve through misclassification strategies. Further results exhibit that firms prefer COGS misclassification over revenue misclassification for manipulating gross profit, implying that firms choose the shifting strategy based on the relative advantage of each shifting tool. Practical implications: The findings suggest that firms that just meet or slightly beat industry-average profitability levels are highly likely to engage in classification shifting (CS). Thus, investors and analysts should be careful when evaluating such firms by comparing them with other firms in the same industry. Originality/value: First, this study is among earlier attempts to investigate CS motivated by peer performance. Second, this study investigates both tools of gross profit manipulation by taking a uniform sample of firms over the same period and provides compelling evidence that firms prefer one shifting tool over another depending on the relative advantage of each shifting tool. © 2021, Emerald Publishing Limited.

Document Type: Article

DOI: https://doi.org/10.1108/PAR-06-2020-0083