The Effects of. on the Patenting Activities of Biotechnology Firms

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1 The More You Spend, the More You Get? The Effects of R&D and Capital Expenditures on the Patenting Activities of Biotechnology Firms Roberta Piergiovanni Istat - Istituto Nazionale di Statistica Ufficio Regionale per l Emilia-Romagna Enrico Santarelli University of Bologna, Department of Economics & European Commission JRC, Institute for Prospective Technological Studies 1

2 Outline 1. This paper explores for a sample of biotechnology firms the impact exerted on the production of new (patented) knowledge by: 1.1 In-house R&D spending (as a proxy of the direct knowledge inputs in the innovation process); 1.2 Capital expenditures (as a proxy of the most crucial indirect knowledge input in the innovation process, namely technological change embodied in new machinery and capital equipment). 2. The analysis is carried out in relation to firms included in subsequent releases of the EU Industrial R&D Investment Scoreboard, over the period between2002 and

3 Why biotechnology as a whole? 1. Biotechnology o ogy is multidisciplinary from both a scientific c and a technological perspective; 2. Biotechnology is highly versatile: it can be used in a number of industrial applications and for the development of a variety of products; 3. Biotechnology comprises both (large) diversified firms performing R&D in a variety of subfields, and specialized (small) Dedicated Biotechnology Firms; 4. In certain fields (e. g. medical biotechnology) it has been seen as a typical case in which the relationship between R&D expenditures and patenting is subject to decreasing returns. 3

4 Why R&D and capital expenditures? 1. Analysis of the impact of current and past R&D expenditures on knowledge output in science-based industries standard exercise in the innovation literature; 2. Less attention paid to the impact pc of capital cp expenditures epedues (an exception being Hall and Ziedonis (2001) on semiconductors); 3. In the overall innovation process characterizing science-based industries, it is likely that capital expenditures become more crucial: 3.1 when the knowledge created by means of R&D expenditures is about to be used for new product development. 4

5 Why R&D and capital expenditures? 4. Findings might corroborate hypothesis in the case of biotechnology, supporting the view that it is in the phase of transition from an entrepreneurial technological l regime to a routinized i technological l regime (Malerba and Orsenigo, 1993; Audretsch, 1995): 4.1 Former dominated dbynewlyestablished tblihdscience-based dfirms, 4.2 Latter characterized by firms focused on the production of new products based on exploitation of the new knowledgethat they have already developed by performing R&D. 5. Thus, capital expenditures might be complementary to R&D expenditures. 6. Likely that an era of rapid investment-specificspecific technological progress has come, making embodied technological change crucial for turning new knowledge into viable productinnovations. 5

6 Data EU INDUSTRIAL R&D INVESTMENT SCOREBOARD - R&D investment (Scoreboard): cash investment directly funded by the companies; -Capital expenditures (Scoreboard): expenditures used by acompany to acquire or upgrade physical assets such as equipment, property, industrial buildings. PATENT APPLICATIONS with - European Patent Office (EPO) - U.S. Patents and Trademark Office (USPTO) - WIPO/PCT Patents Fulltext database. 6

7 Data Combining the various sources to arrive at a new and unique dataset we have an unbalanced panel with a minimum of 97 (in 2002) and a maximum of 123 (in 2007) firms in each of the 6 years. 7

8 8

9 Summary statistics for firm-specific characteristics Variable: employees Year Obs Mean Std. Dev. Min Max , , , , , , , , , , , , , , ,500 Variable: capital expenditures Year Obs Mean Std. Dev. Min Max , Variable: R&D expenditures Year Obs Mean Std. Dev. Min Max , , , , , ,234 9

10 Summary statistics for patent applications ( ) 10

11 Baseline model Pati, t = αi, t + zi, t + D ni, t = 0) + β1 ln RDi, t + β2 ln RDi, t 1 + β3 ln RDi, t 2 ( β4(ln RDi, t ) + χ1 lncapexpi, t + χ2 lncapexpi, t 1t + χ3 lncapexpi, t 2t 2 + χ4 (ln CapExp i, t ) + δ ln Empi, t + u, Pat i t + 11

12 12

13 Number of patent applications on R&D and Capital Expenditure Patents/R&D Patents/R& &D Patents/R&D EPO/R&D EPO/CapExp USPTO/CapExp USPTO/R&D WIPO/CapExp WIPO/R&D Pate tents/capitalexp xpenditur 13 Pate tents/capitalexp xpenditur Paten ents/capitalexpen enditur

14 Model specification 1.With count variables the regression cannot be linear. Nonlinearity is handled through nonlinear ( link ) functions that transform the expected value of the count variable into a linear function of the explanatory variables; 2.We therefore used various procedures alternative to OLS, based on a generalized linear model (GLM), including the Poisson model and the negative binomial model; 3.Performing goodness-of-fitof fit tests of the Poisson model, we found that it is inappropriate due to high over-dispersion; 4.Our patent counts fit well with the negative binomial model (Figure ). 14

15 Actual, Poisson, and negative binomial distribution of patents counts: EPO, USPTO, WIPO 15

16 16

17 Main results 1. In general, for both R&D and capital expenditure variables higher estimates found when USPTO patents used as dependent variable; 2. Coefficient of R&D variable never significant; 3. Coefficient of R&D variable lagged by 1 period positive significant (5% confidence level) only in relation to USPTO patents; 4. Coefficient of R&D variable lagged by 2 periods positive and significant for both EPO and USPTO (5% confidence level); 5. Coefficient of squared value of R&D expenditures negative and significant for USPTO patents: decreasing returns to scale in R&D?; 17

18 Main results 6. Coefficients of the current capital expenditures variable are positive and significant ifi for patent applications i with ihboth EPO and USPTO; 7. Coefficients of the 1-period lagged capital expenditures variable never significant; 8. Coefficients of the 2-period lagged capital expenditures variable either non-significant (USPTO and WIPO) or negative and significant (EPO): rapid exhaustion of the role played by physical assets?; 9. Number of patent applications always increasing along with firm employment size; 10. European firms tend to patent more with EPO: coefficient of the dummy variable for European firm positive and (slightly) significant also in relation to WIPO patents and never significant in relation to USPTO patents. 18

19 Conclusions 1. R&D and capital expenditures complementary determinants of the overall innovation process, which requires the creation of both new knowledge and a viable manufacturing platform. 2. Biotechnology shifting from an entrepreneurial to a routinized technological regime?; 3. Biotech firms with strong market orientation worth spending the money they devote to the creation of new knowledge on a mix of direct (R&D) and indirect (embodied t. c.) sources of innovation, rather than simply spending more and more on R&D; 4. Policy aimed at promoting the emergence of science-based industries should pay more attention to activities that make new products manufacturable and more easily marketable; 5. The better you spend, the more (patentable inventions and discoveries) you get? 19

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