UC Berkeley

This study examines the use of classification shifting from cost of sales to research and development (R&D) to myopically overstate gross profits and R&D in high technology industries. Moving beyond the conventional earnings management paradigm, I explore the incentives and motivations driving the usage of R&D classification shifting as an expense management tool. I find that R&D classification shifting increases the likelihood of meeting or beating gross margin benchmarks and is used to show steady growth in firm performance. I use case studies to supplement my empirical results and provide further insights into the motivation and practice of R&D classification shifting. Prior literature concentrates on the determinants but not the consequences of R&D classification shifting. My study investigates the impact of R&D classification shifting on future R&D productivity, stock returns, and operating performance. I find evidence that firms engaging in R&D classification shifting exhibit lower future R&D productivity because the shifted portion of R&D does not yield innovative outputs. The negative effects of R&D misclassification are further evidenced by lower future stock returns and operating performance. Taken together, my results indicate that the short-term benefits of meeting or beating gross margin benchmarks are offset by the long-term negative impact of R&D overstatement.