Capitalizing Research & Development: Signaling or Earnings Management?

Abstract

This paper analyzes the capitalization of Research & Development (R&D) expenditures under International Financial Reporting Standards (IFRS). Discretionary R&D capitalization can be exercised by managers to signal private information on future economic benefits to the market. It can, however, also serve as opportunistic earnings management. We analyze a unique, hand-collected sample of highly R&D intensive German IFRS firms during 1998–2012. We find that market values are not associated with capitalized R&D for the overall sample, indicating that earnings management may be a concern. We identify firm-years for which R&D capitalization is possibly used for pushing their earnings above a specific threshold (e.g. analysts' forecasted earnings, prior year's earnings). Our results show that both the decision to capitalize and how much to capitalize are strongly associated with benchmark beating. Consistently, we find that market values are negatively associated with capitalized R&D for firms who are likely to use capitalization for benchmark beating (about one third of the overall sample). On the other hand, the market values R&D capitalization positively for well-performing firms, for which capitalizing does not matter to beat an earnings benchmark (about half of the overall sample). This finding is robust to controls for endogeneity, various deflators, and different measures for earnings management.

Acknowledgements

This paper has benefited greatly from valuable comments by Philip Brown, Martin Glaum, Andrew Jackson, Alan Kilgore, Richard Morris, Kevin Rich, Thorsten Sellhorn, Baljit Sidhu, Brian Singleton-Green, Frank Verbeeten, Peter Wells, Christine Wiedman, Anne Wyatt, and workshop participants at the University of Augsburg, the University of New South Wales, the Workshop on Visualising, Measuring and Managing Intangibles & Intellectual Capital 2008, the AS-GAABR & IAAER Annual Conference 2009, the Annual Mid-Year Conference of the IAS of the AAA 2009, the AFAANZ Conference 2009, the EAA Annual Congress 2010, and the AAA Annual Meeting 2010. We are particularly thankful for the many helpful suggestions provided by Steve Young (Associate Editor) and an anonymous reviewer.

Notes

¹IAS 38 prescribes a general expensing rule for research expenditures. Development expenditures need to be capitalized if the entity can demonstrate all of the following (IAS 38.57):

(a) the technical feasibility of completing the intangible asset so that it will be available for use or sale.

(b) its intention to complete the intangible asset and use or sell it.

(c) its ability to use or sell the intangible asset.

(d) how the intangible asset will generate probable future economic benefits. Among other things, the entity can demonstrate the existence of a market for the output of the intangible asset or the intangible asset itself or, if it is to be used internally, the usefulness of the intangible asset.

(e) the availability of adequate technical, financial and other resources to complete the development and to use or sell the intangible asset.

(f) its ability to measure reliably the expenditure attributable to the intangible asset during its development.

²Note that only development expenditures can be capitalized under IAS 38. Research expenditures generally have to be expensed. Development expenditures are only capitalized from the point in time when the criteria are met. Development expenditures which occurred before that date are expensed. For brevity, we refer to ‘R&D capitalization’ as the fact that some portion of the overall R&D expenditures is capitalized. Hence, ‘capitalized R&D’ in this context includes development expenditures only.

³Note that while earnings management may also occur for tax purposes, R&D capitalization for accounting versus tax purposes is not relevant in our study. Under German tax regulations, R&D generally has to be expensed as incurred and, hence, provides no incentives for earnings management for tax purposes.

⁴In Germany, companies report under German GAAP for tax purposes where R&D is immediately expensed. Hence there is no need to make adjustments for tax effects.

⁵Due to the small number of firm-years with BEAT_ZERO_it = 1, we do not run model (3) separately for the firm-years that may try to beat the zero line through R&D capitalization.

⁶Since 1998, listed firms in Germany were allowed to voluntarily adopt IFRS or US GAAP, before IFRS became mandatory in 2005. Our sample period therefore starts in 1998 and includes all existing firm-years under IFRS.

⁷A firm-year is defined as ‘capitalizer’ if R&D capitalization is larger than 0 for a specific year and ‘expenser’ otherwise.

⁸The standard IAS 38 requires companies to disclose the aggregate amount of R&D expenditures, including the amount recognized as an expense during the period. For some firms, this information is missing and we therefore set the amount of R&D expense equal to 0.

⁹Note that for each proxy of accounting earnings management, the suspect firm-years and non-suspect firm-years (below and above the benchmark) add up to 100%.

¹⁰The only exception is the Pearson correlation coefficient for RDCAP_it and MV_it+3months.

¹¹The number of observations drops to 776 because we lose 111 observations in the probit regression due to perfect failure prediction.

¹²The displayed elasticities ey/ex are based on average marginal effects; of the three alternative marginal effects for Tobit regressions that exist, we select the marginal effect on the censored observed variable since we are interested in the effect that the regressors have on the observable amount of capitalized R&D, which is censored at 0, that is, E(RDCAP* RDCAP > 0) as opposed to the marginal effect on the latent variable or the marginal effect on the probability of being uncensored (Greene, 2003, p. 764).

¹³We restrict our Tobit regression in Table 3 Panel C to the number of observations from our probit regression in Table 3 Panel B for a more consistent comparison. Our results remain unchanged when running the Tobit regression for all 887 firm-years.

¹⁴For the economic interpretation of the results, we compute elasticities at mean. All calculations are based on mean values for the respective subsamples used in the regression.