Long Run Stock Returns Following R&D Increases - A Test of R&D Spillover Effect

1. Long Run Stock Returns Following R&D Increases- A Test of R&D Spillover Effect By Sheng-Syan Chen, Wei-Ju Huang and Yanzhi Wang Yanzhi Wang Yuan Ze University Taiwan

2. R&D and Firm Valuation • What is research and development (R&D)? • The investments on innovations and patents. • In accounting treatment, R&D is expensed. • Related to intangible assets • R&D has the externality (spillover effect) • ASKEY (亞旭) obtained the technologies via patents from ATEONIX NETWORKS in 2004. • These patents are about • Method and system for providing remote storage for an internet appliance • Method and system for providing a modulized server on board • ASUS (華碩) obtained the technologies via patents from ASKEy via acquisition in 2008. Then, ASUS sued IBM.

3. R&D and Stock Return • R&D level is positively related to future stock return (Lev and Sougiannis, 1996; Chan, Lakonishok, and Sougiannis, 2001). • Given that R&D generates intangible assets which is difficult to be valued, the R&D is normally underreacted. R&D level affects future long term stock return. • R&D increase is also positively related to future stock return (Chan, Martin and Kensinger, 1990; Eberhart, Maxwell and Siddique; 2004) • R&D increase indicates the improvement on profitability that investors slowly react to. • R&D outlay reduces the current earnings while R&D is beneficial to future profitability. Investors extrapolate R&D increase firm’s future earnings too low, and this biased estimation causes positive return.

4. Ebarhart, Maxwell and Siddique (2004) • The firms with R&D intensity over 5% and R&D increase over 5% are investigated.The R&D information is obtained from the annual report. • The five-year long run abnormal return is about 0.74% and 0.53% per month based on equal- and value-weighted Carhart (1997) four-factor model, respectively. • The operating performance improves in consequent of the R&D increase.

5. Some Comparisons

6. The Issue • Why the R&D increase that is a non-timing event experiences abnormal return so high? • There could be other factor affecting the long run abnormal return of the R&D increase. • Economics literature has widely discussed the spillover effect of the R&D for past decades (Arrow, 1962; Griliches, 1979; Bernstein and Nadiri, 1988; Hanel and St-Pierre, 2002; Agarwal, Echambadi, Franco and Sarkar, 2004; Hunt, 2006), but few papers mention this in finance literature. This could be the factor.

7. R&D Spillover Effect • R&D spillover describes the fact that privately owned firm does not (or cannot) appropriate the outcome of its R&D investment. • Due to the industrial competition, the rival firms may follow to increase the R&D after the EMS sample firm increases R&D.

8. Hypothesis • Eberhart, Maxwell and Siddique (2004) find significantly high abnormal return for R&D increase firms. • We hypothesize that this result is related to the R&D spillover effect. • For the Eberhart, Maxwell and Siddique (2004) sample firm with more R&D followers, then the abnormal return of the sample firm should be higher.

9. Sample Collection • Our sample is collected from U.S companies listed on the NYSE/Amex/Nasdaq during January 1974 to December 2006. • We start our R&D sample collection from 1974 because the requirement of reporting R&D became effective from 1974. • We mainly follow EMS and set up five criterions for our sample that includes firm-year observations with significant increases in R&D: (i) the ratio of R&D expenditures divided by sales over 5%, (ii) the ratio of R&D expenditures divided by average total assets over 5%, (iii) the change of the ratio of R&D expenditures divided by sales over 5%, (iv) the ratio of change of R&D expenditures divided by average total assets over 5%, and (v) the ratio of change of R&D expenditure and than divided by R&D expenditures over 5%. • As a result, the sample with significant increase in R&D expenditures includes 10,280 U.S firm-year observations.

10. Methodology- Return • From July 1976 to December 2006, each R&D increase portfolio p is formed by including sample firms which were increase firm within past 60 months. For example, the R&D increase calendar-time portfolio is composed of firms classified as the R&D increase firm in any of the past 5 years. As a result, the R&D increase portfolio monthly returns are regressed on Carhart (1997) four-factors as follows: • Coefficient tests are adjusted with Newey-West autocorrelation-heteroskedasicity estimation. Holding period Compute ΔR&D ΔR&D is publicly available Year t-1/Dec Year t /Dec Year t+1/July Year t+6/June end

11. Methodology- Operating Performance • Using EBITDA/Assets as ROA and as well as the measure of operating performance (Barber, Lyon, 1996) • We look at the median of changes of ROAs. • We compute abnormal operating performance by matching firm approach. • Minimize |OPt-OPt| around 80%~120% of OPt with the same 2-digit SIC code. • Minimize |OPt-OPt| around 80%~120% of OPt with the same 1-digit SIC code if it’s not found at step 1. • Minimize |OPt-OPt| around 80%~120% of OPt without industry requirement if it’s still not found at step 2. • Minimize |OPt-OPt| without industry and filter requirement for all remaining sample.

12. Summary Statistics • R&D increase firms are small growth firms • R&D increase firms are high R&D firms • About 30% of R&D increasing firms are followed by their industry peers. • R&D increasing firms cluster in two industries: manufacturing and pharmaceutical. Table 1

13. Abnormal Return of R&D Increase • RD followed ratio is the percentage of rival firms that follow the EMS sample firms to increase R&D over at least 1% • High RD followed ratio implies higher R&D spillover effects. Get a closed look at result

14. Some Robust Checks • Fama and French (1993) three-factor model • Control the time-varying risk betas in factor model • Control the delisting return in factor model • Remove the repeating R&D increase events • Change the definitions of the R&D increase follower • All these approaches appear consistent result.

15. β1 and β2 are coefficients for RD followed rank and RD followed ratio, respectively Operating Performance • We use Fama and French (2000) earnings regression Abnormal ROAt+5－Abnormal ROAt=β0+β1RD followed rankt+β2RD followed ratiot +(γ1+γ2NDFEDt+γ3NDFEDt×DFEt+γ4PDFEDt×DFEt)×DFEt +(λ1+λ2NCEDt+λ3NCEDt×CEt+λ4PCEDt×CEt)×CEt+εt

16. R&D Mimicking • Rival firms engage in R&D mimicking to undo the negative effect of the sample firm’s R&D investment. • In a concentrated industry, the strategic reactions are more active, thus the R&D increasing benefit could be offset by rivals’ following R&D increases. • The R&D increasing firms earn lower return in a more concentrated industry.

17. Stock Return and Industry Concentration • Firms in high-concentration industry earn lower return • This confirms the mimicking hypothesis.

18. Fama and MacBeth Regression • For monthly stock returns during July at year t+1 to June year t+2, we include the monthly stocks with significant R&D increases in any of past five years (t to t–4) in the regression model. We regress the monthly returns on independent variables including the RD-followed ratio. • The Fama-MacBeth estimates are obtained by the time-series average and tested by time-series volatility.

19. Fama-Macbeth (1973) Regression

20. Industry R&D Growth as Spillover Proxy • The R&D spillover describes the impact of rivals’ R&D inputs on sample firms’ outputs. • So the aggregative industrial R&D inputs (excluding sample firm) could be an alternative. • We use the industry-wide R&D growth. • Link to Table 9

21. Conclusion • The long-term positive abnormal stock return following a firm’s R&D increase is argued by Eberhart, Maxwell and Siddique (2004). • In this paper, we turn to propose an economical hypothesis, the R&D spillover effect, to account for the long-term stock return post to the R&D increase. • As a firm increases the R&D investment, its industry peers may follow and increase their R&D investments under a competitive industry. Given that R&D investment has spillover effect, the follower’s R&D investment is beneficial to the firm that has significantly invested in R&D projects. • Hence we argue and find that the firm with significant R&D increases and with sufficient R&D investment followers tends to outperform that with few R&D followers. • This economic explanation also helps to answer the puzzle why the R&D increase, which is a non-timing event, is followed by significant abnormal stock return.