In today"s rapidly evolving business landscape, where unicorns and knowledge-based giants dominate, it"s no secret that a firm"s intangible investments play a pivotal role in shaping its future success.
Intangible investments vary depending on the industry and the company"s specific strategy. However, some of the most common types of intangible assets that companies invest in include:
My colleagues, Shivaram Rajgopal, Anup Srivastava, and Rong Zhao, and I recently co-authored a research paper that explores the challenges posed by the accounting treatment of in-house intangible investments and propose a more flexible approach to estimate their value, shedding light on the true worth of these assets.
Various financial metrics, such as return on invested capital, debt-to-equity ratios, and Tobin"s Q – a ratio frequently used to measure whether a company is being overvalued or undervalued in the stock market – depend on accurate asset and equity values, making it crucial to address this disparity.
Recent research endeavors aim to address the absence of in-house intangible assets from reported balance sheets by incorporating the expenses classified as selling, general, and administrative (SG&A) expenditures into capital calculations. However, these studies often employ simplified, one-size-fits-all approaches, such as uniformly considering 30%, 50%, or even 100% of SG&A as investments, without regard for a firm"s industry, operational model, or the economic context of the measurement period.
Adding to this uniform capitalization assumption for R&D and SG&A is another assumption: that the useful lifespan of these investments remains constant across all industries and periods. Thus, critical parameters used in estimating the values of capitalized intangible assets in a perpetual inventory model are assumed to be consistent for all companies and throughout time.
Disregarding this reality also conflicts with the principles outlined in International Accounting Standard (IAS) 38, part of the International Financial Reporting Standards (IFRS). IAS 38 necessitates stringent criteria be met before permitting the capitalization of R&D outlays, including the requirement to distinguish between investment and maintenance R&D.
We depart from prior studies by using future revenues instead of operating income as the dependent variable. This modification aligns with the principle of matching, as expenditures are typically matched to revenues in accounting conventions rather than to profits. Furthermore, operating profits are computed after deducting investments within R&D and SG&A.
We alter the approach by making outlays the dependent variable (in contrast to previous studies where they served as independent variables). In this adjustment, we employ current revenues alongside a series of future revenues as independent variables. This approach allows us to precisely identify the portion of expenditures linked to current or forthcoming revenues while simultaneously controlling for the potential influence of these expenditures on revenues in subsequent periods.
As an illustration, the SG&A category encompasses both investments with anticipated future benefits and maintenance expenditures essential for sustaining ongoing operations. In industries such as wholesale establishments and restaurants, where these outlays are vital for supporting current business operations, the proportion of maintenance expenses within SG&A (e.g., rents, sales discounts, commissions, and promotions) is expected to be relatively higher. Conversely, in sectors focused on establishing long-term assets, such as distribution networks, trademarks, brands, or organizational capabilities required to leverage the value of patents or mining rights, the proportion of investments within SG&A is likely to be more pronounced.
Comparable reasoning applies to R&D. Entities operating in industries characterized by rapidly evolving technologies typically experience shorter-term benefits from their R&D efforts, in contrast to those involved in sectors with stable and enduring technologies. This new approach provides a more accurate estimate of useful lives by incorporating these differences.
In extractive industries such as metal mining and oil, the investment component within operational SG&A exceeds 80%, mainly due to the inclusion of exploration and dry-hole expenses. Similarly, industries requiring continuous product adjustments to meet evolving customer preferences, such as medical equipment, computers, and pharmaceuticals, also highly invest in operational SG&A, hovering around 80%. Additionally, the investment component of R&D ranges from 40% to 90% across most industries, dispelling the notion that it"s consistently 100%.
Furthermore, the study reveals variations in the useful life of R&D and operational SG&A across industries. By not considering 100% of R&D as investments and accounting for the shorter lifespan of operational SG&A, the study"s estimates of capitalized intangible assets are lower than those in earlier research. Additionally, the study notes that the investment portions and useful lives of R&D and Operational SG&A vary across decades, indicating that they are not constant over time, even within the same industries.
Additionally, we analyze the data by decades, uncovering enhanced performance periods spanning 2001"’2010 and 2011"’2022. These specific decades coincide with the emergence of intangibles as a crucial production factor and the growing significance of knowledge-intensive enterprises in the economy, marking a notable shift from earlier decades. Moreover, our results exhibit greater strength within industries heavily reliant on intangible assets, including business equipment, chemicals, and healthcare, aligning with our initial expectations. Second, we demonstrate that our recalculated Tobin"s Q predicts future investments more accurately.
First Published: Apr 12, 2024, 14:17
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