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Effect of R&D expenditures and funding strategies on the market value of biotech firms
ELSEVIER
J. Eng. TechnoI.Manage. 12 (1996) 287-299
Journal of ENGINEERINGAND TECHNOLOGY MANAGEMENT JET-M
Effect of R & D expenditures and funding strategies on the market value of biotech firms William W. McCutchen Jr. a, Paul M. Swamidass b,, ,I a Department of Management, Baruch College, School of Business and Public Administration, Box F1831, 17 Lexington Avenue, New York, NY 10010, USA b Thomas Walter Center for Technology Management, Auburn University, Room 104, Tiger Drive, Auburn, AL 36849-5358, USA
Abstract Market value of biotech firms is important to investors and venture capitalists who keep this industry alive and dynamic. It is a particularly valuable index of investors' estimate of current and future success of the firms in this industry because other conventional indices of performance and success are inappropriate. Our hypothesis is that market value in this industry can be explained in terms of funding strategies and R&D expenditures. Using all sixty publicly-held biotech firms, that are included in a national directory for such firms engaged in the research of biotech products for human use, we estimate multiple regression models that explain most of the variance in market value using funding strategies and R&D expenditures (R-squared = 0.93). Our models also demonstrated that small biotech finns ( < $10 million in total revenue) are substantially different from larger ones. Keywords: Biotech firm market value; Biotech research funding; Biotech R&D costs
1. Introduction and background Estimates of the worldwide bio-pharmaceutical industry sales by the year 2000 place it between $40 billion and $60 billion; this amount is equal to the whole pharmaceutical industry sales today (Bylinsky, 1991). At the root of this rapid change in the pharmaceutical industry is the emerging biotech industry made of numerous small firms engaged primarily in R & D . Various researchers have investigated several different aspects of
* Corresponding author. Tel.: + 1 334 844-4333. Fax: + 1 334 844-1678. t Names listed in alphabetical order. 0923-4748/96/$15.00 © 1996 Elsevier Science B.V. All rights reserved SSDI 0923-4748(95)00014-3
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Table I Selected measures for small biotech firms ~
Small firms Large firms All firms
Total revenue (million $)
R&D costs Total revenue
Market value of equity (million $)
n
3.94 82.3 24.84
1.94 b 0.56 1.57
32.88 417.68 135.5M
44 16 60
Small biotech firms are defined as firms with total revenue less than $10 million in 1988 (i.e., beginning of 1989). One outlier (with R&D cost/total revenue = 255.8) dropped.
this n e w industry, but no o n e h a d d e v e l o p e d an e x p l a n a t i o n for the s t r o n g m a r k e t v a l u e o f p u b l i c l y - h e l d b i o t e c h firms, M a r k e t v a l u e o f b i o t e c h firms play at least two i m p o r t a n t roles. First, since equity a n d v e n t u r e capital are i m p o r t a n t s o u r c e s o f r e v e n u e , m a r k e t v a l u e s e r v e s as an i n d e x o f t h e s e potential s o u r c e s o f i n c o m e . S e c o n d , since c o n v e n t i o n a l p e r f o r m a n c e m e a s u r e s for the firms in this industry are i n a p p r o p r i a t e , m a r k e t v a l u e s e e m s to be the sole, v i s i b l e i n d e x o f the f i r m ' s c u r r e n t a n d future success. S m a l l b i o t e c h firms, as a rule, s p e n d far in e x c e s s o f total r e v e n u e on R & D e x p e n s e s y e a r after year. T h e a v e r a g e v a l u e o f the ratio ( R & D c o s t s ) / ( t o t a l r e v e n u e ) for the s m a l l firms ( < $ 1 0 m i l l i o n in a n n u a l r e v e n u e ) in this i n d u s t r y w a s a b n o r m a l l y h i g h at 1.94 in the y e a r 1989 ( T a b l e 1). T h a t is, in the y e a r 1989, the a v e r a g e s m a l l b i o t e c h firm s p e n t nearly twice its total r e v e n u e on R & D e x p e n s e s alone, thus, assets w e r e d e p l e t e d rapidly. C o n s e q u e n t l y , t r a d i t i o n a l p e r f o r m a n c e m e a s u r e s s u c h as R O I a n d R O E for m o s t firms in this i n d u s t r y w e r e m e a n i n g l e s s . F o r e x a m p l e , a c c o r d i n g to T a b l e 2, R O I a n d R O E were - 0 . 5 8 9 a n d - 1 . 3 4 , r e s p e c t i v e l y for s m a l l firms for the y e a r 1989, a n d - 0 . 4 5 a n d - 0 . 8 7 for all p u b l i c l y - h e l d b i o t e c h f i n n s c o v e r e d in this study. But, t h e s e firms are by no m e a n s c o n s i d e r e d failures. O n the contrary, t h e s e firms are h i g h l y r e g a r d e d by i n v e s t o r s b a s e d on the m a r k e t v a l u e o f t h e s e firms.
Table 2 Traditional financial ratios and averages for biotech firms (1989) Sample size (n) Return on investment (ROI) h Return on equity (ROE) Cash flow a Cash flow margin c
Small firms (TR < $10M)
Large firms (TR >_$10M)
All firms
44 - 0.589 - 1.34 d -$0.5 million - 1.203 °
16 - 0.06 -- 0.16 $1.9 million -0.23
60 - 0.45 -- 0.87 -$1.2 million -0.92
a Cash flow = net income + depreciation + deferred taxes. b Cash flow return on investment = cash flow/total assets. c Cash flow margin = cash flow/total sales. '~ One outlier not included in ROE computations; ROE = + 267.50 for the deleted firm because of very high loss coupled with very low negative equity. Four outliers excluded; outlier values, - 496.33, - 47.08, - 35.68, and infinity.
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In the late eighties, the new biotechnology industry was still in the early stages of development characterized by a number of small companies which emerged mostly during the decade with the intent of developing products based on biotechnology. Although the principles of biotechnology have been known for a number of years, recent developments have significantly enhanced the opportunity to develop commercial materials of enormous value. While biotechnology has useful applications across many industries, at this point in time, some of the most significant uses for biotechnology are in healthcare; this paper focuses on biotech firms utilizing biotechnology to develop products for therapeutic or pharmaceutical use. This was done to ensure the homogeneity of the sample. Several small firms in the biotech industry came into being in a big way during the early 1980s (Smith and Fleck, 1988). Pisano (1990) notes that "most of the early commercial biotechnology R & D was conducted by new ventures that were formed in the United States between 1976 and 1982 and not by established firms" (p. 155). Established, large pharmaceutical firms conducted less than half (47 percent) of their biotech related R&D in-house (Pisano, 1990, p. 156). The remaining proportion of the R&D was conducted by procuring R&D services from new, emerging biotech firms. It is generally accepted that it takes 8 to 10 years to find commercial success with biotechnology products and that the R&D related pre-market costs could be as high as $75-100 million per product (Fildes, 1990, p. 65). According to this estimate, a small firm with an annual research budget of $10 million will take seven to ten years to find a commercially viable product. Another estimate by Eli Lilly & Co. places the average cost of developing new pharmaceutical products at $231 million and average time at 10 to 12 years (Eli Lilly, 1990). Biotech firms have generally been formed by a group of scientists trained in biotechnology. Their objective is usually limited to developing one or more products in the hope of making them commercially successful. These firms depend on pre-commercialization funding, which comes from private sources or limited stock offerings. Further, biotech firms also secure funding during the initial years before product commercialization using rather unique methods such as, (1) the selling of research efforts to larger firms, (2) the selling of marketing rights to potential products to larger firms, (3) collaborative research alliances with larger firms, and (4) in rare cases, marketing the products themselves (e.g., Genentech). In contrast, large pharmaceutical firms such as Eli Lilly have pursued biotechnology within the confines of their many research projects using internal funds. In addition to in-house research, large firms also enter the biotech industry through the acquisition of smaller firms, through the purchase of marketing rights to the products of smaller firms, and through the acquisition of marketable products developed by smaller firms in return for royalties. Market value is perhaps the only tangible measure or index of present and expected success of these firms as well as an index of their potential to raise critical equity capital. Our goal here is to explain market value using revenue strategies and R & D expenditures. We studied the entire population of 60 publicly-held biotech firms operating in the U.S. during 1989, investigating products for human or animal healthcare use.
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Why develop a model to explain market value of biotech firms? Market value is increased when share price increases. Increasing share price is vital to the success of these firms, which derive a substantial portion of their financial needs from capital raised from investors and venture capitalists. Equity capital is particularly important to this industry because, given the extremely high risk associated with this industry, debt financing is rarely an option for funding research in biotech firms.
2. Theoretical framework
The underlying hypothesis guiding this investigation of the market value of biotech firms is described by the following proposition: The market value of the firms in the biotech industry is not a random phenomenon. Market value in this industry can be explained by a rational model that ties market value to research funding and R &D costs. In this industry, research is funded by collaborative research revenue, interest income, and product sales. Biotechnology literature demonstrates that the success of R & D intensive biotech firms is tied to a combination of: (1) R&D funding, (2) R&D aggressiveness, and (3) the choice of biotech products for R & D (Arora and Gambardella, 1990; Fildes, 1990; Hamilton et al., 1990; Patterson, 1988). In this study, we investigate the ability of the first two variables to explain the market value of biotech firms. The two variables of interest are described in the following paragraphs. 2.1. R & D funding The importance of R & D funding to biotech firms is stressed in this statement, "Biotechnology is a very capital-intensive business. This fact of life means that most managers in the field have had to spend a great deal of their time raising capital" (Fildes, 1990, p. 68). He also notes that, in the early years, before a marketable product was ready, the primary objective of emerging biotech firms was "research and development funding" (p. 68). Chris Lowell, national coordinator of biotechnology services in Peat Marwick, Co. notes that a majority of biotech firms "have excellent research and development capabilities. So, what will make the difference between success and failure? Capitalization as well as management" (Patterson, 1988, pp. 42-43). Consequently, he argues that a key strategy of these firms is the "matter of making the right choice among many available funding mechanisms" (p. 42). For this industry, there are a number of funding options which further complicates this difficult decision for the executives in this industry. Funding decisions must balance the short-term as well as the long-term welfare of the firm and its investors. For example, in the short-term, these firms need a continuous supply of funds to stay alive; but in the long-run, they should judiciously trade away long-term interests in their expected products for the sake of short-term cash flow. The decision to sell part or all of the interest in yet undiscovered products of the firm is a major strategic decision.
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Biotech firms, which raise venture capital to finance their operations, generally invest the proceeds of their capital offerings in interest bearing securities. The interest income from the investment is usually recognized as "revenue" by these firms. For some firms, this item may be the only source of revenue for several years. Thus, equity funding is a key strategic variable in emerging firms in this industry. It is often done through a private placement of equity with specialized investors such as venture capitalists. After some years of operations, these firms usually proceed to issue an "initial public offering" known as an IPO. If marketable products are slow in coming, and if initial equity is used up in R&D expenses, firms may proceed with additional "secondary" public offerings. 2. I. 1. Product sales Product sales is not a very important source of funds for small biotech firms but it gets more and more important as the firms get larger. Since many biotech firms license their products to other firms, royalty income is included in product sales. 2.1.2. Collaborative research revenue Funding of R & D in biotech firms through external agreements is an important form of funding in this industry. The most important external agreements are collaborative research agreements with larger and more established pharmaceutical firms (Arora and Gambardella, 1990). A collaborative research agreement represents a long-term strategic alliance between a financially and commercially weaker biotech firm and a financially and commercially established larger pharmaceutical firm (Pisano, 1990). Specific commercialization capabilities that larger pharmaceutical firms may offer are know-how to do broad-scale testing of new pharmaceutical products, the know-how to deal with various regulatory agencies around the world such as the FDA, and the ability to launch a substantial marketing campaign for a new pharmaceutical product. Because of this, "only in rare instances has a single enterprise financed the complete development of a new biotech entity from research through volume production and marketing" (Quinn, 1992, pp. 54, 55). The strategic alliance represented by collaborative research revenue offers more than funds for conducting research for biotech firms. A collaborative research relationship with larger firms brings external legitimacy to emerging biotech firms in many ways: (1) it adds expensive and valuable commercialization capabilities of the larger firms; (2) the long-term nature of collaborative research contracts for one or more projects with larger firms lends a long-term income stream to emerging firms; and (3) the association with larger firms signals to investors that something of value is going on in the emerging small firm. The relationship between small biotech firms, which focus on research, and large firms in the pharmaceutical industry, which are capable of bringing new drugs to the market successfully, benefits both parties. Consider this, "the potential new protein drugs made possible by biotechnology must go through the same clinical tests and regulatory approval process and are sold through the same distribution channels as traditional drugs. With years of commercial experience and existing organizational capabilities in these 'downstream' functions, established pharmaceutical companies had an advantage over new entrants in bringing new drugs from the laboratory to the
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market" (Pisano, 1990, p. 155). Above all, for the small biotech firm, collaborative research agreements provide vital cash inflow for conducting research.
2.2. R & D aggressiveness R & D expenses or ratios based on R & D expenses are indices of R & D aggressiveness. What is the conceptual basis for linking R & D expenses and market value in this study? Some researchers see a direct link between R & D expense and firm value. For example, Gartrell (1990, p. 89) notes that " R & D is widely accepted as a positive net present value activity. It contributes to economic profits because it is a means of creating growth options..." The importance of R & D aggressiveness is even greater in biotech firms. Venture capitalists use the term "burn rate" to describe the high rate of R & D spending per month in biotech firms. The "burn rate" is often compared to cash and cash equivalents in the finn to assess the firm's survival index. This index gives an indication of how long the firm may last given its current R & D spending rate (Burrill, 1990). In the literature, R & D expenses divided by product sales is often referred to as research intensity. As indicated earlier, pharmaceutical firms have used this research intensity ratio as a device for budgetary control and strategic planning. This measure is well recognized as an important index of a firm's strategic use of R & D (Caglarcan, 1977; Grabowski and Vernon, 1981; Cool and Schendel, 1987; Cool and Schendel, 1988; Sudharshan et al., 1985; Sudharshan et al., 1986; Franko, 1989; McCutchen, 1993a and McCutchen, 1993b). This ratio for some of the most aggressive non-biotech firms in the U.S., Japan, and Europe in selected industries is given below for comparative purposes (Franko, 1989): Electrical equipment and electronics: Chemicals: Pharmaceutical:
0.022 to 0.094 (range). 0.010 to 0.048 (range). 0.030 to 0.130 (range).
Clearly, the ratio for biotech firms is many times larger than the comparable ratio for firms in mature industries (see Table 1). Thus, we hypothesize that the strategic importance of R & D expenses, or ratios based on R & D expenses to biotech firms is so great that they are reflected in the firm's market value.
3. Research design Our hypothesis investigated here is that market value of biotech firms is a function of funding strategies and R & D aggressiveness.
3.1. Dependent variable What does market value represent? First, the efficient markets hypothesis offers some guidance here. "In an efficient market you can trust prices. They impound all available
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information about the value of each security" (Brealey and Myers, 1991, p. 300). A finn's market value can reflect, "either (1) present value of the stream of expected future dividends, or (2) the present value of free cash flow, or (3) the present value of average future earnings under a no-growth policy plus the present value of growth opportunities", or a combination of the above (Brealey and Myers, p. 60). Some of these claims are questioned by those who think that the efficient market hypothesis cannot fully explain stock prices. Further, sceptics of the hypothesis think that the ability of the hypothesis to explain stock price changes with time. Yet, the hypothesis is not entirely without merit. Market value (MKTVAL) was calculated by multiplying the price per share of the firm's stock at the end of the fiscal year by the number of shares outstanding at the end of the fiscal year. We found that market value of the firm at the end of the fiscal year was highly correlated with the market value at the end of the calendar year (correlation = 0.993 for the year 1989). Thus, one could use the market value at the end of either the fiscal or the calendar year.
3.2. hldependent variables Market value was modeled using the following four independent/predictor variables representing funding options and R & D aggressiveness. In addition to the literature discussed above, discussions with industry experts and insiders confirmed the appropriateness and the validity of the independent variables chosen. Funding options were measured by four different variables, one each for measuring income from interest, income from product sales, income from collaborative research revenue and stockholders' equity. We included stockholders' equity as an independent variable in the model because common wisdom expects market value to reflect stockholders' equity. Our primary intent was to study the effect of various income streams on market value, therefore, if stockholders' equity was highly correlated with one of the funding variables, our research design called for dropping stockholders' equity from the model altogether. The measures for the variables were:
Funding : Predictor Predictor Predictor Predictor
variable variable variable variable
1. Annual interest income (INTINC). 2. Annual product sales (PRODSAL). 3. Annual collaborative research revenue (COLLRR). 4. Stockholders' equity (STEQ).
Research Aggressiveness: Predictor variable 5. Annual cost of research and development (RDCOST).
3.3. Sample and data We investigated only publicly held, emerging biotech firms because of the need to access company financial reports to get data on independent variables. Additionally, the
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dependent variable of this study required outstanding company shares and share price information in order to compute the market value of these shares. By investigating small publicly held, emerging biotechnology firms, we obtained all essential data from published annual and quarterly reports and historical stock market records. The firms included in this study are listed in the Biotechnology Guide USA (Dibner, 1988), which is a reference book of companies active in the biotechnology industry prepared by the North Carolina Biotechnology Information Division. The guide includes information on the type of work that individual biotech firms pursue; therapeutic, diagnostic, agricultural, etc. including an assessment of the emphasis placed in these areas as "primary" or "secondary." To ensure the homogeneity of the industry investigated, this study investigated biotech firms which were identified in the guide as having a primary or secondary interest in therapeutics or vaccines for human, veterinary or animal health care products; it excluded firms developing products for diagnostics, agricultural and industrial use. To summarize, the criteria for a firm to be included in this study were: (1) publicly owned firm, and (2) engaged in therapeutic or vaccines research. In the year 1988, according to the Biotechnology Guide USA (Dibner, 1988), there were a total of 66 firms that met both criteria. The data for this study came from diverse sources. First, stock prices were taken from "asked" prices in the Daily Stock Price Record/Over-the-counter published by Standard and Poors Co. Fiscal years used in the study covered the period June 1 to May 31 of the following year. Since some of the shares were traded infrequently, if there were no trades on the last day of the fiscal year, the price for the nearest transaction date was used. If there were no record of price in Daily Stock Price Record/Over-thecounter, the average price for the last quarter in the annual report or 10K report was substituted. Secondly, all 66 firms identified to be part of the population were sent a letter requesting their annual reports and 10Ks for the years since the beginning of their public existence. Firms that sent us incomplete data were contacted again for the missing data. In some occasions, financial officers of individual firms were contacted by phone to fill-in missing data. Where possible, the Securities Exchange Commission and Docutronics, a private firm, provided information to complete the data that were missing. Although, these firms are publicly held, the access to data on some of the small firms in this industry is difficult to obtain; because they are not all traded in the larger and more visible exchanges and their equities have very limited, specialized markets. We were able to obtain data for 1988 and 1989. Out of the entire population of 66 firms in operation at the end of 1988, five firms were the subject of mergers or takeovers during 1989 and one firm apparently went out of business in 1989 because it could not be reached by mail or phone, and it filed no reports to the SEC after 1988. Thus, the population shrank to 60 firms during 1989. We successfully collected data on this population of 60 firms for 1989, which were used in subsequent analyses. 4. Results
Several OLS regression models were estimated using the five independent variables Stockholders' Equity, Product Sales, Collaborative Research Revenue, Interest Income,
MKTVAL
4
- 0.951 ( - 0.064)
3.14 * * * (0.58)
6.69 * * * (0.616)
4.17 (0.17)
4.27 (0.51)
8.63 " (0.244)
35.88 + + (0.35)
36.18 (0.35)
(0.35)
0.244 (0.027)
dropped
-0.101 (-0.01)
b
RDCOST
43
16
16
60
0.63
0.89
0.88
0.93
0.000' * *
0.000 * * *
0.0001 * * *
0.000 * * *
Significance (F)
case 44 with C o o k ' s D = 18.46 dropped
none
none
none
Outliers (Cook's D)
none
none
RDCOST (22.63)
none
Multicollinearity (VIF) ~
Small firms
Larger firms
Larger firms
All firms
Comments
b,,
7n
* p_<0.06;
**
p_<0.05;
***
p_<0.01.
,..¢1
,~ t~
MKTVAL
3
3.15 * * * (0.59)
(0.17)
(0.55)
INTINC 25.99 * * *
Adj. R 2
I N T I N C = Interest Income. R D C O S T = Total R&D Cost.
MKTVAL
2
2.63 ° * *
COLLRR
3.03 * * '
PRODSAL
n
"
MKTVAL
1
Unstandardized coefficients (Beta coefficients in parentheses)
.~
VIF = Variance Inflation Factor. Multicollinearity exists if VIF > 10. VIF for RDCOST is 18.75, so it was dropped from the model. If R D C O S T is included but C O L L R R , with which it is highly correlated, is dropped, R-squared drops to 0.849 from 0.930. M K T V A L = Market Value. P R O D S A L = Product Sales. C O L L R R = Collaborative Research Revenue.
Dependent variable
Model #
Table 3 Multiple regression models (1989 data)
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and R & D costs, and the dependent variable Market Value. At the outset, we found that the correlation between Stockholders' Equity and R & D costs to be very high (0.92). Therefore, as planned, we dropped Stockholders' Equity from the list of independent variables in the regression. The result of the regression models, their coefficients, R-squared values, and other data concerning the models are reported in Table 3. In Table 3, Model 1 includes all 60 cases. As we developed our models, we used Cook's D to identify outliers and employed Variance Inflation Factor (VIF) to detect multicollinearity. For the computation of these indices, see Berenson and Levine (1986, pp. 698, 699) a n d / o r the manual for SPSS/PC +, version 2.0. We dropped a variable from the model if its VIF exceeded 10 (see Snee, 1973). Model 1 for all 60 cases has a very strong adjusted R-squared value of 0.93 that is significant. Model 1 does not include R & D Costs because the VIF for this variable at 18.75 exceeded our limit. Thus, the three independent variables in the linear Model 1 can explain Market Value extremely well. Further, in Model 1, all three independent variables are significant at less than 0.01. Model 1 strongly confirms our hypothesis that the market value of biotech firms is a reflection of funding sources and R & D expenses. In the next step, we estimate Models 2 and 3 for the larger firms, and Model 4 for the small finns. Model 2 is discarded in favor of Model 3 because the former is flawed by multicollinearity as indicated by a VIF value of 22.63 for R & D Costs (this is consistent with Model 1 for all finns). Model 3, which drops R & D Costs, is an excellent predictor of market value with an R-squared value of 0.84 for the 16 larger finns in the sample with a significance < 0.01. Similarly, Model 4 turns out to be a very good predictor of market value with a R-squared value of 0.63 for the 43 small finns in the sample excluding one outlier. We can infer from Models 3 and 4 that small biotech firms are different from large firms. The differences and implications are discussed in the next section.
5. Discussion In this study, we have been able to explain up to 93% of the variance in the market value of biotech finns in terms of funding variables; 84% for larger finns and 63% for small finns. True to the proposition stated at the outset of the paper, market value in this industry is not a random phenomenon. The R 2 value for Model 1 (93%) in Table 3 lends support to the efficient market hypothesis. This finding should be reassuring to investors who finance this industry and executives who run it. Some may criticize the independent variables employed here because they do not directly measure the quality of the research facility or the quality of research scientists in biotech finns. But, this is not necessarily a weakness of the models in Table 3. Larger pharmaceutical collaborators, who enter into agreements with smaller biotech finns are knowledgeable enough to evaluate the quality of the research facilities and the quality of scientists in small biotech finns; they can do a better job of this evaluation than most investors. Therefore, collaborative research revenue for biotech finns may be viewed as an index of the quality of the facilities and personnel in small biotech finns as evaluated
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by larger pharmaceutical firms that enter into collaborative research agreements with the smaller firms. Since collaborative research revenue is a statistically significant variable in Models 1 and 4, the model does have an indirect way of accounting for the quality of facilities and personnel in the small firms.
5.1. Small versus large biotech firms Models 3 and 4 reveal why and how small (total annual revenue < $10 million) and larger biotech firms are different from each other. The following are some of the inferences from the two models: (1) Product Sales, Collaborative Research Revenue, and Interest Income are able to explain the Market Value of larger firms (R-squared = 0.93) better than the Market Value of small firms (R-squared = 0.63). This finding may suggest that small biotech firms face more uncertainty than larger firms about funding prospects, and therefore their Market Value is less predictable by income streams than the Market Value of larger firms. (2) Based on significant independent variables in the models, Market Value of larger firms is a function of Product Sales and Interest Income whereas the Market Value of small firms is a function of Collaborative Research Revenue and Interest Income. That is, both small and larger firms are similar in the sense that Interest Income is a good predictor of Market Value. But, Product Sales is a good predictor of Market Value only in the case of larger firms. (3) Based on Model 4, the Market Value of small biotech firms depends upon Collaborative Research Revenue more than larger biotech firms with marketable products. Collaborative research revenue is a form of income stream flowing from large pharmaceutical firms interested in contracting with small biotech firms to conduct research in an area in which the larger firms may not have the capacity or capability for research. Investors consider this income stream to be important in the case of small biotech firms. (4) In summary, based on Models 3 and 4, while small as well as larger biotech firms depend on interest income, larger firms are more product sales-driven, while small biotech firms are collaborative research-driven. Therefore, it appears that, in the evolution from small to larger biotech firms, collaborative research revenues are an important early source of income that is progressively reduced in importance by product sales and licensing.
6. Implications and research directions The strong relationship between R & D funding and market value evident in the magnitude of the R 2 for the models in Table 3 must act as a stimulant for further research of related issues of the phenomenon. Particularly, the strong evidence from this cross-sectional study should stimulate interest in longitudinal investigations of market value in this industry.
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Although strong relations have been detected by this study, this cross-sectional study cannot be a substitute for longitudinal investigation of the market value in this industry. This study does not answer the question, what happens to market value over time? How do the relationships detected here stand up to volatility in market value? Only longitudinal investigations of the market value in this industry can answer these important questions. As a follow-up on this study, researchers may also dig deeper into the phenomenon investigated here. For example, researchers may explore how the quality of the research facility, the quality of the scientists in the firm, the nature of the research conducted by the firm, etc. influence the market value of biotech firms. These variables are important to biotech firms' success because they have direct or indirect effect on the ability of these firms to raise capital and attract collaborative research revenue. The most important implication for practitioners stems from the important role played by collaborative research revenue in the market value of biotech firms, particularly in the case of small firms. Executives interested in increasing the market value of these firms must seek to understand and strengthen the factors that lead to collaborative research agreements. A notable finding of this study is that R & D Costs are not associated with Market Value in this industry (Table 3) as predicted. It appears that income streams are more important to investors than R & D expenses because investors seem to read more into income streams than R & D expenses in valuing biotech firms. The logic may be that Collaborative Research Revenue may be a good indication of the small firm's ability to convince knowledgeable large collaborators of their capabilities. Further, in the opinion of investors, income from product sales and royalties is perhaps a strong indication of the successful outcome of past research efforts of the biotech firm. In summary, biotech firms that can convince large pharmaceutical firms to enter into collaborative research agreements with them, and biotech firms with marketable products will succeed in increasing their market value. The reward for increasing the market value is the increased ability to raise equity capital, which can increase the interest income for the firms in this industry. As shown in Table 3, increased interest income has its own reward; it contributes to increased market value of biotech firms. The positive feedback nature of these relationships may partially explain the market value of the firms in this industry.
Acknowledgements This paper has benefitted from the valuable comments of JET-M reviewers and the editor. The authors are grateful to Professors T.K. Das, Granger Macy and Prakash Sethi for helpful suggestions based on an earlier version of this paper. The authors thank graduate students Sally Bashker, Sanjiv Khosla, Rajeev Kurkigowdara and Bing-Sheng Teng, who provided valuable assistance with data analysis. This project was partially funded by a grant from Baruch College; the support is gratefully acknowledged.
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References Arora, A. and Gambardella A., 1990. Complementarity and external linkages: The strategies of the large firms in biotechnology. The Journal t~flndustrial Economics, 38(4), June: 361-379. Berenson, M.L. and Levine D.H., 1986. Basic Business Statistics, 3rd ed. Prentice-Hall, Englewood, NJ. Brealey, R.A. and Myers S.C., 1988. Principles t~f Corporate Finance. McGraw-Hill Co, New York. Burrill, G.S., 1990. Biotech 90: Into the Next Decade. Mary Ann Liebert, New York. Bylinsky, G., 1991. Biotech firms tackle the giants. Fortune, Aug. 12: 78-82. Caglarcan, E., 1977. Economics of innovation in the pharmaceutical industry. Unpublished Ph.D. dissertation. George Washington University. Cool, K. and Schendel D., 1987. Strategic group formation and performance: The case of the U.S. pharmaceutical industry, 1963-1982. Management Science, 33(9): 1102-1124. Cool, K. and Schendel D., 1988. Performance differences among strategic group members. Strategic Management Journal, 9: 207-223. Dibner, M.D., 1988. Bioteehnology Guide - USA. Stockton Press, New York, NY. Eli Lilly and Company, 1990. Third Quarter Report, p. 12. Fildes, R.A., 1990. Strategic challenges in commercializing biotechnology. California Management Review, 32(3): 63-72. Franko, L.G., 1989. Global corporate competition: who's winning, who's losing, and the R&D factor as one reason why. Strategic Management Journal, 10: 449-474. Gartrell, K.D., 1990. Innovation, industry specialization and stockholder wealth. California Management Review, Spring: 87-101. Grabowski, H.G. and Vernon, J., 1981. The determinants or research and development expenditures in the pharmaceutical industry, in: R. Helms (Ed.), Drugs and Health. American Enterprise Institute, Washington, DC, pp. 3-21. Hamilton, W.F., Vila J. and Dibner, M., 1990. Patterns of strategic choice in emerging finns: Positioning for innovation in biotechnology. California Management Review, Spring: 73-86. McCutchen, W.W., 1993a. Strategy changes as response to alteration in tax policy. Journal of Management. McCutchen, W.W., 1993b. Estimating the impact of the R&D tax credit on strategic groups in the pharmaceutical industry. Research Polio', 22:337-351. Patterson, T.D., 1988. The business of biotech. World, Winter: 40-45. Pisano, G.P., 1990. The R&D boundaries of the firm: An empirical analysis. Administrative Science Quarterly, 35: 153-176. Quinn, J.B., 1992. The intelligent enterprise: A new paradigm. Academy ~fManagement Executive, Vol VI, No. 4, November: 48-63. Smith, J.G. and Fleck V., 1988. Strategies of new biotechnology firms. Long Range Planning, 21(3): 51-58. Snee, R.D., 1973. Some aspects of nonorthogonal data analysis, Part I: Developing prediction equations. Journal of Quality Technology, 5: 67-79. Sudharshan, D., Thomas H. and Fiegenbaum A., 1985. Strategic time periods and strategic groups research: Concepts and an empirical example. Research paper, University of illinois at Urbana-Champaign. Sudharshan, D., Thomas H. and Fiegenbaum A., 1986. Mobius - a procedure for identifying mobility barriers based on dynamic strategic grouping analysis. Working Paper No. 1226, University of Illinois at Urbana-Champaign.
J. Eng. TechnoI.Manage. 12 (1996) 287-299
Journal of ENGINEERINGAND TECHNOLOGY MANAGEMENT JET-M
Effect of R & D expenditures and funding strategies on the market value of biotech firms William W. McCutchen Jr. a, Paul M. Swamidass b,, ,I a Department of Management, Baruch College, School of Business and Public Administration, Box F1831, 17 Lexington Avenue, New York, NY 10010, USA b Thomas Walter Center for Technology Management, Auburn University, Room 104, Tiger Drive, Auburn, AL 36849-5358, USA
Abstract Market value of biotech firms is important to investors and venture capitalists who keep this industry alive and dynamic. It is a particularly valuable index of investors' estimate of current and future success of the firms in this industry because other conventional indices of performance and success are inappropriate. Our hypothesis is that market value in this industry can be explained in terms of funding strategies and R&D expenditures. Using all sixty publicly-held biotech firms, that are included in a national directory for such firms engaged in the research of biotech products for human use, we estimate multiple regression models that explain most of the variance in market value using funding strategies and R&D expenditures (R-squared = 0.93). Our models also demonstrated that small biotech finns ( < $10 million in total revenue) are substantially different from larger ones. Keywords: Biotech firm market value; Biotech research funding; Biotech R&D costs
1. Introduction and background Estimates of the worldwide bio-pharmaceutical industry sales by the year 2000 place it between $40 billion and $60 billion; this amount is equal to the whole pharmaceutical industry sales today (Bylinsky, 1991). At the root of this rapid change in the pharmaceutical industry is the emerging biotech industry made of numerous small firms engaged primarily in R & D . Various researchers have investigated several different aspects of
* Corresponding author. Tel.: + 1 334 844-4333. Fax: + 1 334 844-1678. t Names listed in alphabetical order. 0923-4748/96/$15.00 © 1996 Elsevier Science B.V. All rights reserved SSDI 0923-4748(95)00014-3
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Table I Selected measures for small biotech firms ~
Small firms Large firms All firms
Total revenue (million $)
R&D costs Total revenue
Market value of equity (million $)
n
3.94 82.3 24.84
1.94 b 0.56 1.57
32.88 417.68 135.5M
44 16 60
Small biotech firms are defined as firms with total revenue less than $10 million in 1988 (i.e., beginning of 1989). One outlier (with R&D cost/total revenue = 255.8) dropped.
this n e w industry, but no o n e h a d d e v e l o p e d an e x p l a n a t i o n for the s t r o n g m a r k e t v a l u e o f p u b l i c l y - h e l d b i o t e c h firms, M a r k e t v a l u e o f b i o t e c h firms play at least two i m p o r t a n t roles. First, since equity a n d v e n t u r e capital are i m p o r t a n t s o u r c e s o f r e v e n u e , m a r k e t v a l u e s e r v e s as an i n d e x o f t h e s e potential s o u r c e s o f i n c o m e . S e c o n d , since c o n v e n t i o n a l p e r f o r m a n c e m e a s u r e s for the firms in this industry are i n a p p r o p r i a t e , m a r k e t v a l u e s e e m s to be the sole, v i s i b l e i n d e x o f the f i r m ' s c u r r e n t a n d future success. S m a l l b i o t e c h firms, as a rule, s p e n d far in e x c e s s o f total r e v e n u e on R & D e x p e n s e s y e a r after year. T h e a v e r a g e v a l u e o f the ratio ( R & D c o s t s ) / ( t o t a l r e v e n u e ) for the s m a l l firms ( < $ 1 0 m i l l i o n in a n n u a l r e v e n u e ) in this i n d u s t r y w a s a b n o r m a l l y h i g h at 1.94 in the y e a r 1989 ( T a b l e 1). T h a t is, in the y e a r 1989, the a v e r a g e s m a l l b i o t e c h firm s p e n t nearly twice its total r e v e n u e on R & D e x p e n s e s alone, thus, assets w e r e d e p l e t e d rapidly. C o n s e q u e n t l y , t r a d i t i o n a l p e r f o r m a n c e m e a s u r e s s u c h as R O I a n d R O E for m o s t firms in this i n d u s t r y w e r e m e a n i n g l e s s . F o r e x a m p l e , a c c o r d i n g to T a b l e 2, R O I a n d R O E were - 0 . 5 8 9 a n d - 1 . 3 4 , r e s p e c t i v e l y for s m a l l firms for the y e a r 1989, a n d - 0 . 4 5 a n d - 0 . 8 7 for all p u b l i c l y - h e l d b i o t e c h f i n n s c o v e r e d in this study. But, t h e s e firms are by no m e a n s c o n s i d e r e d failures. O n the contrary, t h e s e firms are h i g h l y r e g a r d e d by i n v e s t o r s b a s e d on the m a r k e t v a l u e o f t h e s e firms.
Table 2 Traditional financial ratios and averages for biotech firms (1989) Sample size (n) Return on investment (ROI) h Return on equity (ROE) Cash flow a Cash flow margin c
Small firms (TR < $10M)
Large firms (TR >_$10M)
All firms
44 - 0.589 - 1.34 d -$0.5 million - 1.203 °
16 - 0.06 -- 0.16 $1.9 million -0.23
60 - 0.45 -- 0.87 -$1.2 million -0.92
a Cash flow = net income + depreciation + deferred taxes. b Cash flow return on investment = cash flow/total assets. c Cash flow margin = cash flow/total sales. '~ One outlier not included in ROE computations; ROE = + 267.50 for the deleted firm because of very high loss coupled with very low negative equity. Four outliers excluded; outlier values, - 496.33, - 47.08, - 35.68, and infinity.
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In the late eighties, the new biotechnology industry was still in the early stages of development characterized by a number of small companies which emerged mostly during the decade with the intent of developing products based on biotechnology. Although the principles of biotechnology have been known for a number of years, recent developments have significantly enhanced the opportunity to develop commercial materials of enormous value. While biotechnology has useful applications across many industries, at this point in time, some of the most significant uses for biotechnology are in healthcare; this paper focuses on biotech firms utilizing biotechnology to develop products for therapeutic or pharmaceutical use. This was done to ensure the homogeneity of the sample. Several small firms in the biotech industry came into being in a big way during the early 1980s (Smith and Fleck, 1988). Pisano (1990) notes that "most of the early commercial biotechnology R & D was conducted by new ventures that were formed in the United States between 1976 and 1982 and not by established firms" (p. 155). Established, large pharmaceutical firms conducted less than half (47 percent) of their biotech related R&D in-house (Pisano, 1990, p. 156). The remaining proportion of the R&D was conducted by procuring R&D services from new, emerging biotech firms. It is generally accepted that it takes 8 to 10 years to find commercial success with biotechnology products and that the R&D related pre-market costs could be as high as $75-100 million per product (Fildes, 1990, p. 65). According to this estimate, a small firm with an annual research budget of $10 million will take seven to ten years to find a commercially viable product. Another estimate by Eli Lilly & Co. places the average cost of developing new pharmaceutical products at $231 million and average time at 10 to 12 years (Eli Lilly, 1990). Biotech firms have generally been formed by a group of scientists trained in biotechnology. Their objective is usually limited to developing one or more products in the hope of making them commercially successful. These firms depend on pre-commercialization funding, which comes from private sources or limited stock offerings. Further, biotech firms also secure funding during the initial years before product commercialization using rather unique methods such as, (1) the selling of research efforts to larger firms, (2) the selling of marketing rights to potential products to larger firms, (3) collaborative research alliances with larger firms, and (4) in rare cases, marketing the products themselves (e.g., Genentech). In contrast, large pharmaceutical firms such as Eli Lilly have pursued biotechnology within the confines of their many research projects using internal funds. In addition to in-house research, large firms also enter the biotech industry through the acquisition of smaller firms, through the purchase of marketing rights to the products of smaller firms, and through the acquisition of marketable products developed by smaller firms in return for royalties. Market value is perhaps the only tangible measure or index of present and expected success of these firms as well as an index of their potential to raise critical equity capital. Our goal here is to explain market value using revenue strategies and R & D expenditures. We studied the entire population of 60 publicly-held biotech firms operating in the U.S. during 1989, investigating products for human or animal healthcare use.
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Why develop a model to explain market value of biotech firms? Market value is increased when share price increases. Increasing share price is vital to the success of these firms, which derive a substantial portion of their financial needs from capital raised from investors and venture capitalists. Equity capital is particularly important to this industry because, given the extremely high risk associated with this industry, debt financing is rarely an option for funding research in biotech firms.
2. Theoretical framework
The underlying hypothesis guiding this investigation of the market value of biotech firms is described by the following proposition: The market value of the firms in the biotech industry is not a random phenomenon. Market value in this industry can be explained by a rational model that ties market value to research funding and R &D costs. In this industry, research is funded by collaborative research revenue, interest income, and product sales. Biotechnology literature demonstrates that the success of R & D intensive biotech firms is tied to a combination of: (1) R&D funding, (2) R&D aggressiveness, and (3) the choice of biotech products for R & D (Arora and Gambardella, 1990; Fildes, 1990; Hamilton et al., 1990; Patterson, 1988). In this study, we investigate the ability of the first two variables to explain the market value of biotech firms. The two variables of interest are described in the following paragraphs. 2.1. R & D funding The importance of R & D funding to biotech firms is stressed in this statement, "Biotechnology is a very capital-intensive business. This fact of life means that most managers in the field have had to spend a great deal of their time raising capital" (Fildes, 1990, p. 68). He also notes that, in the early years, before a marketable product was ready, the primary objective of emerging biotech firms was "research and development funding" (p. 68). Chris Lowell, national coordinator of biotechnology services in Peat Marwick, Co. notes that a majority of biotech firms "have excellent research and development capabilities. So, what will make the difference between success and failure? Capitalization as well as management" (Patterson, 1988, pp. 42-43). Consequently, he argues that a key strategy of these firms is the "matter of making the right choice among many available funding mechanisms" (p. 42). For this industry, there are a number of funding options which further complicates this difficult decision for the executives in this industry. Funding decisions must balance the short-term as well as the long-term welfare of the firm and its investors. For example, in the short-term, these firms need a continuous supply of funds to stay alive; but in the long-run, they should judiciously trade away long-term interests in their expected products for the sake of short-term cash flow. The decision to sell part or all of the interest in yet undiscovered products of the firm is a major strategic decision.
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Biotech firms, which raise venture capital to finance their operations, generally invest the proceeds of their capital offerings in interest bearing securities. The interest income from the investment is usually recognized as "revenue" by these firms. For some firms, this item may be the only source of revenue for several years. Thus, equity funding is a key strategic variable in emerging firms in this industry. It is often done through a private placement of equity with specialized investors such as venture capitalists. After some years of operations, these firms usually proceed to issue an "initial public offering" known as an IPO. If marketable products are slow in coming, and if initial equity is used up in R&D expenses, firms may proceed with additional "secondary" public offerings. 2. I. 1. Product sales Product sales is not a very important source of funds for small biotech firms but it gets more and more important as the firms get larger. Since many biotech firms license their products to other firms, royalty income is included in product sales. 2.1.2. Collaborative research revenue Funding of R & D in biotech firms through external agreements is an important form of funding in this industry. The most important external agreements are collaborative research agreements with larger and more established pharmaceutical firms (Arora and Gambardella, 1990). A collaborative research agreement represents a long-term strategic alliance between a financially and commercially weaker biotech firm and a financially and commercially established larger pharmaceutical firm (Pisano, 1990). Specific commercialization capabilities that larger pharmaceutical firms may offer are know-how to do broad-scale testing of new pharmaceutical products, the know-how to deal with various regulatory agencies around the world such as the FDA, and the ability to launch a substantial marketing campaign for a new pharmaceutical product. Because of this, "only in rare instances has a single enterprise financed the complete development of a new biotech entity from research through volume production and marketing" (Quinn, 1992, pp. 54, 55). The strategic alliance represented by collaborative research revenue offers more than funds for conducting research for biotech firms. A collaborative research relationship with larger firms brings external legitimacy to emerging biotech firms in many ways: (1) it adds expensive and valuable commercialization capabilities of the larger firms; (2) the long-term nature of collaborative research contracts for one or more projects with larger firms lends a long-term income stream to emerging firms; and (3) the association with larger firms signals to investors that something of value is going on in the emerging small firm. The relationship between small biotech firms, which focus on research, and large firms in the pharmaceutical industry, which are capable of bringing new drugs to the market successfully, benefits both parties. Consider this, "the potential new protein drugs made possible by biotechnology must go through the same clinical tests and regulatory approval process and are sold through the same distribution channels as traditional drugs. With years of commercial experience and existing organizational capabilities in these 'downstream' functions, established pharmaceutical companies had an advantage over new entrants in bringing new drugs from the laboratory to the
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market" (Pisano, 1990, p. 155). Above all, for the small biotech firm, collaborative research agreements provide vital cash inflow for conducting research.
2.2. R & D aggressiveness R & D expenses or ratios based on R & D expenses are indices of R & D aggressiveness. What is the conceptual basis for linking R & D expenses and market value in this study? Some researchers see a direct link between R & D expense and firm value. For example, Gartrell (1990, p. 89) notes that " R & D is widely accepted as a positive net present value activity. It contributes to economic profits because it is a means of creating growth options..." The importance of R & D aggressiveness is even greater in biotech firms. Venture capitalists use the term "burn rate" to describe the high rate of R & D spending per month in biotech firms. The "burn rate" is often compared to cash and cash equivalents in the finn to assess the firm's survival index. This index gives an indication of how long the firm may last given its current R & D spending rate (Burrill, 1990). In the literature, R & D expenses divided by product sales is often referred to as research intensity. As indicated earlier, pharmaceutical firms have used this research intensity ratio as a device for budgetary control and strategic planning. This measure is well recognized as an important index of a firm's strategic use of R & D (Caglarcan, 1977; Grabowski and Vernon, 1981; Cool and Schendel, 1987; Cool and Schendel, 1988; Sudharshan et al., 1985; Sudharshan et al., 1986; Franko, 1989; McCutchen, 1993a and McCutchen, 1993b). This ratio for some of the most aggressive non-biotech firms in the U.S., Japan, and Europe in selected industries is given below for comparative purposes (Franko, 1989): Electrical equipment and electronics: Chemicals: Pharmaceutical:
0.022 to 0.094 (range). 0.010 to 0.048 (range). 0.030 to 0.130 (range).
Clearly, the ratio for biotech firms is many times larger than the comparable ratio for firms in mature industries (see Table 1). Thus, we hypothesize that the strategic importance of R & D expenses, or ratios based on R & D expenses to biotech firms is so great that they are reflected in the firm's market value.
3. Research design Our hypothesis investigated here is that market value of biotech firms is a function of funding strategies and R & D aggressiveness.
3.1. Dependent variable What does market value represent? First, the efficient markets hypothesis offers some guidance here. "In an efficient market you can trust prices. They impound all available
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information about the value of each security" (Brealey and Myers, 1991, p. 300). A finn's market value can reflect, "either (1) present value of the stream of expected future dividends, or (2) the present value of free cash flow, or (3) the present value of average future earnings under a no-growth policy plus the present value of growth opportunities", or a combination of the above (Brealey and Myers, p. 60). Some of these claims are questioned by those who think that the efficient market hypothesis cannot fully explain stock prices. Further, sceptics of the hypothesis think that the ability of the hypothesis to explain stock price changes with time. Yet, the hypothesis is not entirely without merit. Market value (MKTVAL) was calculated by multiplying the price per share of the firm's stock at the end of the fiscal year by the number of shares outstanding at the end of the fiscal year. We found that market value of the firm at the end of the fiscal year was highly correlated with the market value at the end of the calendar year (correlation = 0.993 for the year 1989). Thus, one could use the market value at the end of either the fiscal or the calendar year.
3.2. hldependent variables Market value was modeled using the following four independent/predictor variables representing funding options and R & D aggressiveness. In addition to the literature discussed above, discussions with industry experts and insiders confirmed the appropriateness and the validity of the independent variables chosen. Funding options were measured by four different variables, one each for measuring income from interest, income from product sales, income from collaborative research revenue and stockholders' equity. We included stockholders' equity as an independent variable in the model because common wisdom expects market value to reflect stockholders' equity. Our primary intent was to study the effect of various income streams on market value, therefore, if stockholders' equity was highly correlated with one of the funding variables, our research design called for dropping stockholders' equity from the model altogether. The measures for the variables were:
Funding : Predictor Predictor Predictor Predictor
variable variable variable variable
1. Annual interest income (INTINC). 2. Annual product sales (PRODSAL). 3. Annual collaborative research revenue (COLLRR). 4. Stockholders' equity (STEQ).
Research Aggressiveness: Predictor variable 5. Annual cost of research and development (RDCOST).
3.3. Sample and data We investigated only publicly held, emerging biotech firms because of the need to access company financial reports to get data on independent variables. Additionally, the
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dependent variable of this study required outstanding company shares and share price information in order to compute the market value of these shares. By investigating small publicly held, emerging biotechnology firms, we obtained all essential data from published annual and quarterly reports and historical stock market records. The firms included in this study are listed in the Biotechnology Guide USA (Dibner, 1988), which is a reference book of companies active in the biotechnology industry prepared by the North Carolina Biotechnology Information Division. The guide includes information on the type of work that individual biotech firms pursue; therapeutic, diagnostic, agricultural, etc. including an assessment of the emphasis placed in these areas as "primary" or "secondary." To ensure the homogeneity of the industry investigated, this study investigated biotech firms which were identified in the guide as having a primary or secondary interest in therapeutics or vaccines for human, veterinary or animal health care products; it excluded firms developing products for diagnostics, agricultural and industrial use. To summarize, the criteria for a firm to be included in this study were: (1) publicly owned firm, and (2) engaged in therapeutic or vaccines research. In the year 1988, according to the Biotechnology Guide USA (Dibner, 1988), there were a total of 66 firms that met both criteria. The data for this study came from diverse sources. First, stock prices were taken from "asked" prices in the Daily Stock Price Record/Over-the-counter published by Standard and Poors Co. Fiscal years used in the study covered the period June 1 to May 31 of the following year. Since some of the shares were traded infrequently, if there were no trades on the last day of the fiscal year, the price for the nearest transaction date was used. If there were no record of price in Daily Stock Price Record/Over-thecounter, the average price for the last quarter in the annual report or 10K report was substituted. Secondly, all 66 firms identified to be part of the population were sent a letter requesting their annual reports and 10Ks for the years since the beginning of their public existence. Firms that sent us incomplete data were contacted again for the missing data. In some occasions, financial officers of individual firms were contacted by phone to fill-in missing data. Where possible, the Securities Exchange Commission and Docutronics, a private firm, provided information to complete the data that were missing. Although, these firms are publicly held, the access to data on some of the small firms in this industry is difficult to obtain; because they are not all traded in the larger and more visible exchanges and their equities have very limited, specialized markets. We were able to obtain data for 1988 and 1989. Out of the entire population of 66 firms in operation at the end of 1988, five firms were the subject of mergers or takeovers during 1989 and one firm apparently went out of business in 1989 because it could not be reached by mail or phone, and it filed no reports to the SEC after 1988. Thus, the population shrank to 60 firms during 1989. We successfully collected data on this population of 60 firms for 1989, which were used in subsequent analyses. 4. Results
Several OLS regression models were estimated using the five independent variables Stockholders' Equity, Product Sales, Collaborative Research Revenue, Interest Income,
MKTVAL
4
- 0.951 ( - 0.064)
3.14 * * * (0.58)
6.69 * * * (0.616)
4.17 (0.17)
4.27 (0.51)
8.63 " (0.244)
35.88 + + (0.35)
36.18 (0.35)
(0.35)
0.244 (0.027)
dropped
-0.101 (-0.01)
b
RDCOST
43
16
16
60
0.63
0.89
0.88
0.93
0.000' * *
0.000 * * *
0.0001 * * *
0.000 * * *
Significance (F)
case 44 with C o o k ' s D = 18.46 dropped
none
none
none
Outliers (Cook's D)
none
none
RDCOST (22.63)
none
Multicollinearity (VIF) ~
Small firms
Larger firms
Larger firms
All firms
Comments
b,,
7n
* p_<0.06;
**
p_<0.05;
***
p_<0.01.
,..¢1
,~ t~
MKTVAL
3
3.15 * * * (0.59)
(0.17)
(0.55)
INTINC 25.99 * * *
Adj. R 2
I N T I N C = Interest Income. R D C O S T = Total R&D Cost.
MKTVAL
2
2.63 ° * *
COLLRR
3.03 * * '
PRODSAL
n
"
MKTVAL
1
Unstandardized coefficients (Beta coefficients in parentheses)
.~
VIF = Variance Inflation Factor. Multicollinearity exists if VIF > 10. VIF for RDCOST is 18.75, so it was dropped from the model. If R D C O S T is included but C O L L R R , with which it is highly correlated, is dropped, R-squared drops to 0.849 from 0.930. M K T V A L = Market Value. P R O D S A L = Product Sales. C O L L R R = Collaborative Research Revenue.
Dependent variable
Model #
Table 3 Multiple regression models (1989 data)
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and R & D costs, and the dependent variable Market Value. At the outset, we found that the correlation between Stockholders' Equity and R & D costs to be very high (0.92). Therefore, as planned, we dropped Stockholders' Equity from the list of independent variables in the regression. The result of the regression models, their coefficients, R-squared values, and other data concerning the models are reported in Table 3. In Table 3, Model 1 includes all 60 cases. As we developed our models, we used Cook's D to identify outliers and employed Variance Inflation Factor (VIF) to detect multicollinearity. For the computation of these indices, see Berenson and Levine (1986, pp. 698, 699) a n d / o r the manual for SPSS/PC +, version 2.0. We dropped a variable from the model if its VIF exceeded 10 (see Snee, 1973). Model 1 for all 60 cases has a very strong adjusted R-squared value of 0.93 that is significant. Model 1 does not include R & D Costs because the VIF for this variable at 18.75 exceeded our limit. Thus, the three independent variables in the linear Model 1 can explain Market Value extremely well. Further, in Model 1, all three independent variables are significant at less than 0.01. Model 1 strongly confirms our hypothesis that the market value of biotech firms is a reflection of funding sources and R & D expenses. In the next step, we estimate Models 2 and 3 for the larger firms, and Model 4 for the small finns. Model 2 is discarded in favor of Model 3 because the former is flawed by multicollinearity as indicated by a VIF value of 22.63 for R & D Costs (this is consistent with Model 1 for all finns). Model 3, which drops R & D Costs, is an excellent predictor of market value with an R-squared value of 0.84 for the 16 larger finns in the sample with a significance < 0.01. Similarly, Model 4 turns out to be a very good predictor of market value with a R-squared value of 0.63 for the 43 small finns in the sample excluding one outlier. We can infer from Models 3 and 4 that small biotech firms are different from large firms. The differences and implications are discussed in the next section.
5. Discussion In this study, we have been able to explain up to 93% of the variance in the market value of biotech finns in terms of funding variables; 84% for larger finns and 63% for small finns. True to the proposition stated at the outset of the paper, market value in this industry is not a random phenomenon. The R 2 value for Model 1 (93%) in Table 3 lends support to the efficient market hypothesis. This finding should be reassuring to investors who finance this industry and executives who run it. Some may criticize the independent variables employed here because they do not directly measure the quality of the research facility or the quality of research scientists in biotech finns. But, this is not necessarily a weakness of the models in Table 3. Larger pharmaceutical collaborators, who enter into agreements with smaller biotech finns are knowledgeable enough to evaluate the quality of the research facilities and the quality of scientists in small biotech finns; they can do a better job of this evaluation than most investors. Therefore, collaborative research revenue for biotech finns may be viewed as an index of the quality of the facilities and personnel in small biotech finns as evaluated
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by larger pharmaceutical firms that enter into collaborative research agreements with the smaller firms. Since collaborative research revenue is a statistically significant variable in Models 1 and 4, the model does have an indirect way of accounting for the quality of facilities and personnel in the small firms.
5.1. Small versus large biotech firms Models 3 and 4 reveal why and how small (total annual revenue < $10 million) and larger biotech firms are different from each other. The following are some of the inferences from the two models: (1) Product Sales, Collaborative Research Revenue, and Interest Income are able to explain the Market Value of larger firms (R-squared = 0.93) better than the Market Value of small firms (R-squared = 0.63). This finding may suggest that small biotech firms face more uncertainty than larger firms about funding prospects, and therefore their Market Value is less predictable by income streams than the Market Value of larger firms. (2) Based on significant independent variables in the models, Market Value of larger firms is a function of Product Sales and Interest Income whereas the Market Value of small firms is a function of Collaborative Research Revenue and Interest Income. That is, both small and larger firms are similar in the sense that Interest Income is a good predictor of Market Value. But, Product Sales is a good predictor of Market Value only in the case of larger firms. (3) Based on Model 4, the Market Value of small biotech firms depends upon Collaborative Research Revenue more than larger biotech firms with marketable products. Collaborative research revenue is a form of income stream flowing from large pharmaceutical firms interested in contracting with small biotech firms to conduct research in an area in which the larger firms may not have the capacity or capability for research. Investors consider this income stream to be important in the case of small biotech firms. (4) In summary, based on Models 3 and 4, while small as well as larger biotech firms depend on interest income, larger firms are more product sales-driven, while small biotech firms are collaborative research-driven. Therefore, it appears that, in the evolution from small to larger biotech firms, collaborative research revenues are an important early source of income that is progressively reduced in importance by product sales and licensing.
6. Implications and research directions The strong relationship between R & D funding and market value evident in the magnitude of the R 2 for the models in Table 3 must act as a stimulant for further research of related issues of the phenomenon. Particularly, the strong evidence from this cross-sectional study should stimulate interest in longitudinal investigations of market value in this industry.
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Although strong relations have been detected by this study, this cross-sectional study cannot be a substitute for longitudinal investigation of the market value in this industry. This study does not answer the question, what happens to market value over time? How do the relationships detected here stand up to volatility in market value? Only longitudinal investigations of the market value in this industry can answer these important questions. As a follow-up on this study, researchers may also dig deeper into the phenomenon investigated here. For example, researchers may explore how the quality of the research facility, the quality of the scientists in the firm, the nature of the research conducted by the firm, etc. influence the market value of biotech firms. These variables are important to biotech firms' success because they have direct or indirect effect on the ability of these firms to raise capital and attract collaborative research revenue. The most important implication for practitioners stems from the important role played by collaborative research revenue in the market value of biotech firms, particularly in the case of small firms. Executives interested in increasing the market value of these firms must seek to understand and strengthen the factors that lead to collaborative research agreements. A notable finding of this study is that R & D Costs are not associated with Market Value in this industry (Table 3) as predicted. It appears that income streams are more important to investors than R & D expenses because investors seem to read more into income streams than R & D expenses in valuing biotech firms. The logic may be that Collaborative Research Revenue may be a good indication of the small firm's ability to convince knowledgeable large collaborators of their capabilities. Further, in the opinion of investors, income from product sales and royalties is perhaps a strong indication of the successful outcome of past research efforts of the biotech firm. In summary, biotech firms that can convince large pharmaceutical firms to enter into collaborative research agreements with them, and biotech firms with marketable products will succeed in increasing their market value. The reward for increasing the market value is the increased ability to raise equity capital, which can increase the interest income for the firms in this industry. As shown in Table 3, increased interest income has its own reward; it contributes to increased market value of biotech firms. The positive feedback nature of these relationships may partially explain the market value of the firms in this industry.
Acknowledgements This paper has benefitted from the valuable comments of JET-M reviewers and the editor. The authors are grateful to Professors T.K. Das, Granger Macy and Prakash Sethi for helpful suggestions based on an earlier version of this paper. The authors thank graduate students Sally Bashker, Sanjiv Khosla, Rajeev Kurkigowdara and Bing-Sheng Teng, who provided valuable assistance with data analysis. This project was partially funded by a grant from Baruch College; the support is gratefully acknowledged.
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