The economic value of the R&D intangible asset

Abstract

This study utilizes firm-specific time-series data to estimate the economic value of the research and development (R&D) expenditures that investors consider an asset to the firm. The study uses a modification of the Ohlson (1995) model to estimate the persistence of abnormal earnings, the proportion of current R&D expenditures that represents a source of future benefits to the firm and the amortization rate of that asset. The parameters are estimated from time-series data of market and book values of equity, earnings and R&D expenditures. The study further compares the firm-specific estimates with those resulting from an application of a cross-sectional estimation procedure based on all available companies in the sample and industry-specific sub-samples. Results indicate the existence of significant differences in some two-digit SIC code industries between the time-series and the cross-sectional estimates of the parameters and the economic value of the R&D asset. Differences in the capitalization parameter are associated with the growth in R&D, the profitability of the firm, R&D intensity and the concentration of the industry. Differences in the persistence of earnings are related to the concentration ratio. Finally, differences in the estimated economic value of the R&D asset are associated with the profitability of the company as measured by its return on assets. We further compare the associations between the three different estimates of the R&D asset and subsequent stock returns, as well as the contemporaneous difference between the market and book value of companies. Results indicate that the time-series estimates of the R&D asset show stronger associations with both variables, followed by the intra-industry and the cross-industry cross-sectional estimates. Overall, our results provide evidence that market participants behave as if R&D expenditures have significant future economic benefits to the firm, and show that the cross-sectional and time-series approaches followed when assessing its economic value provide significantly different estimates.

ACKNOWLEDGEMENTS

The authors thank Factset Information Services, Inc., for data and retrieval programs used in this study. The authors also thank seminar participants at New York University and University of Lancaster for their comments. Manuel Garcia-Ayuso acknowledges the funding provided by AECA to the Carlos Cubillo Chair, as well as funds received from the Spanish Ministry of Economy (Project No. PB98-0415).

Notes

¹The only exception in the US is software development costs.

²An exception is the study of Megna and Mueller (1991), where the firm-specific R&D stocks are estimated by regressing sales on previous advertising and R&D expenditures. However, they also include in the model the aggregate advertising and R&D outlays of the firm's competitors in the industry.

³The assumption about the constant rates α and β is made for simplification of estimation. In reality, both are likely to vary depending on the specific stage in the life cycle of the firm. However, any non-constant series can be converted into a constant series as shown by certainty equivalent discount rates in finance.

⁴We thank an anonymous reviewer for drawing our attention to capital expenditures besides drilling expenses.

⁵The model in this paper assumes a world without taxes, just like the Ohlson (1995) model.

⁶In a prior version of this paper, we repeated the analysis with quarterly data. Parameter estimates and further analyses were very similar to those reported for the annual results.

⁷We also used market values three months after the fiscal year-end with very similar results to those reported in the text.

⁸One must bear in mind that the companies in Panel C are not representative of the entire Compustat population; they are selected to the sample if they disclose R&D expenditures for at least ten years between 1985 and 2001. Thus, R&D is likely to be an important concern for these firms which have also survived for a long time. Our sample selection criteria may have different implications for size and growth opportunities in these companies than in the rest of the population.

⁹A note of caution should be interjected here. The comparison above is necessarily based only on firms that have sufficient history data to estimate the time-series model. These firms may have been more successful at deploying their R&D expenditures, and more reliant on it. Thus, the impact of R&D on the difference between market and book value and future returns may be more closely estimated from the time-series model.