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Do Innovators Gain from Patenting and Training

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NES 20th Anniversary Conference, Dec 13-16, 2012
Do Innovators Gain from Patenting and Training (based on the article presented by Maksim Belitski at the NES 20th Anniversary Conference).
Authors: Maksim Belitski, Yulia Rodionova

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Do Innovators Gain from Patenting and Training

  1. 1. DO INNOVATORS GAIN FROMPATENTING AND TRAINING? Maksim Belitski1 Yulia Rodionova2 1 IndianaUniversity Bloomington 2 De Montfort University
  2. 2. Outline Motivation Study Objectives Literature Model Empirical Results Conclusions
  3. 3. Motivation Three kinds of potential revenue increases that firms can have from their innovative activities:- First, firms that innovate can earn larger revenues due to strategic and legal protection of their innovation;- Second, firm’s revenue increases due to investment in knowledge (innovative training, R&D).- Lastly, firms can license their technology if they are adequately backed by patents and other IP protection instruments. Data now available from the CIS, BERD and BSD released by IPO / ONS allow us to assess how these revenues vary according to the fact of holding a IP protection & knowledge investment.
  4. 4. Key objectives Estimating private returns to patenting and training in the UK; Estimate private incentive that IP protection offers for further investment in innovative training, as well as for innovation more broadly; Understanding the impact of crises on private returns to patenting and training in the UK.
  5. 5. Literature on returns on patenting• Schumpeter’s (1939) ideas on higher returns on innovation in less than perfect competitive markets which contradicts Arrow (1962) who argued that, the competitive market structure provides higher incentives to innovate.• Exploring various methods to protect inventions (e.g. Levin et al., 1987; Cohen and Klepper, 2006; Cohen et. al. 2011);• Scherer’s (1983) “Propensity to patent”. - relationship between R&D and invention patenting;• Quantifying the private value of patent protection (Pakes, 1986; Schankerman and Pakes, 1984; Pakes and Simpson, 1989);• Schankerman (1998) – first work on returns to patenting and the resulting incentives for innovation;• Leiponen and Byma (2009)- examines small firms’ strategies for capturing the returns to investment in innovation vs. large firm strategies;• Greenhalah and Rogers (2006) estimated the link between innovation, R&D and competition;• Artz et. al. (2010) estimated the link between a firms R&D and innovative outcomes. Result: knowledge spending is positively related to patents.• Arora et. al (2011). - estimates on returns on IP protection and the way it enhances R&D
  6. 6. Literature on returns on training• Bassi (1984) - women are found to benefit significantly from manpower training programs;• Ichiniowski et al. (1987) - positive effect of high and low incidence of training on productivity in manufacturing.• Acemoglu (1997) analyzed innovation and training decisions by employees to invest in general training, not training premia.• Marotta et al. (2007) – analyzing a link between training effectiveness (perception) and new product revenue;• Hansson (2007) - positive relationship between the number of employees receiving training and being in Top 10 of profitability among other firms in the same sector.• Van Reenen et al., 2005. BIS Report. Understanding the private and public returns on training in the UK.
  7. 7. Industry structure of knowledge expenditure per firm, UK External knowledge, Firms invest in SIC 2007 Training, 000£ R&D In-house, 000£ R&D external, 000£ 000£ No firms knowledgeManufacture of other transport equipment 1493 1945 1103 1401 116 45.7Extraction of crude petroleum and natural gas 611 3181 115 40 55 38.2 Manufacture of chemicals and chemical products 313 2619 682 272 166 57.8 Manufacture of radio, television and communication equipment 63 1493 493 505 128 61.7 Manufacture of office machinery and computers 50 1993 15 10 41 58.5Manufacture of other transport equipment 269 8904 5223 11 68 55.9Manufacture of motor vehicles, trailers and semi-trailers 59 2978 922 113 161 54.0 Manufacture of chemicals and chemical products 97 2804 680 430 170 53.5 Manufacture of radio, television and communication equipment 71 1973 227 96 79 59.5Manufacture of machinery and equipment not classified 41 1356 189 49 414 49.3 Research and development 33 6220 2003 54 176 49.4Manufacture of motor vehicles, trailers and semi-trailers 36 773 2578 38 227 33.9Manufacture of machinery and equipment not classified 18 1956 324 27 270 38.5 Manufacture of radio, television and communication equipment 24 1647 445 142 109 48.6 Manufacture of chemicals and chemical products 145 1610 202 99 130 33.1
  8. 8. Knowledge premium Knowledge Prop. ofRound CIS NPR, 000£ Profits, 000£ Wages, 000£ Sales, 000£ expenditure scientists No 643 8717 7562 34971 4 2002- 2004 Yes 3393 9977 11738 53873 8 No 1670 15477 9164 38252 5 2004- 2006 Yes 6591 21295 15413 56984 10 No 245 11487 21381 37131 4 2007- 2009 Yes 2637 13028 20785 58962 10 Note: Number of firms: CIS4 (13,215); CIS5 (14,219); CIS6 (12,671).
  9. 9. Model P1 Q1= PQ (1-) + PQ (1)where P is the price of products created without the patent protection andQ is the average quantity of products without the patent protection sold. is the share of products for which patent protection was sought, calledpatent propensity, and  is the patent premium. N1 = f(T) (2)where N1 is a share of new products/ innovations as a function ofinvestment in knowledge; T is the amount of money spent on training forproduct innovation. Equivalent of endogenous growth parameter H(t) NPR = N1 P1 Q1 = PQ (1 -  + ) f(T) (3)
  10. 10. Model: Patent and training revenue premiumTaking logs, and transforming the model into econo-metric form, we getnpr = p + q + ln(1-  + ) + ln(f(T)) + εi (4)The modified model can be written in the following form:npri = A+ b1ln(Ti) + ln(1- i *(1-)) (5)Assuming that ln(1- i *(1-)) ~ (1-)i, (5) can bere-written :npri = A + b1ln(Ti) + i (-1)+ εi (6)
  11. 11. Model: Patent and training revenue premiumNow we can rewrite (6) as the reducedformnpri = A + B1ln(Ti) + B2xi + ei (7)Therefore, xi= i and 0<i<1 and B2= (-1)  = B2+1 (8)Success!
  12. 12. Model: Patent and training revenue premiumAssuming firms choose their training investments to maximizereturns, so that actual NPR and T are jointly determined by underlying firm and industry characteristics (denoted by X), the estimating equation becomesln(Ti) = C1 + Xi i + Bixi+ e2 (9)npri = C2 + Xi i + B1ln(Ti) + Bixi+ e2 (10)where C1 , C2 are vectors of intercept terms in equations (9) and(10) respectively, i is a vector of unknown coefficients of theexogenous variables in equation (9), i is a vector of unknowncoefficients of the exogenous variables in equation (10), Xi is avector of exogenous variables (controls) in both equations; T isinnovative training expenditure.
  13. 13. Hypotheses testingHypothesis 1: Investment in knowledge and skills (training) ismore likely to impact innovation rather than profits.Hypothesis 2: Returns to patenting is positive in both innovationand profits.Hypothesis 3: External economic shocks (crises) is likely to makeIP protection a substitute of training (knowledge investment).Controls: Sectoral controls (2 digit SIC), time, regional dummies,firm size; global nature; ownership type, age, degree of competition(rivals), cooperation with government, managerial andorganizational strategy changes, External & in-house R&D, humancapital.
  14. 14. CIS4 CIS5 CIS6 Variables Obs. Mean St.dev. Obs. Mean St.dev. Obs. Mean St.dev. NPR, log 13215 1.06 2.54 14219 0.71 2.12 12671 0.71 2.12GVA per employee 13215 4.16 1.22 14219 3.85 1.68 12671 3.64 1.88 GOS 6703 6.59 2.07 5968 7.02 2.14 3432 7.83 2.15 Training, log 13215 0.98 1.55 14219 0.71 1.32 12671 0.41 1.04 Rivals, log 13215 6.42 0.97 14219 6.34 0.98 12671 6.29 0.99 Global 13215 0.36 0.48 14219 0.33 0.47 12671 0.31 0.46 Public 13215 0.86 0.35 14219 0.86 0.35 12671 0.88 0.32 Age, log 13215 2.68 0.77 14219 2.72 0.80 12671 2.62 0.84 Foreign 13215 0.43 0.49 14219 0.40 0.49 12671 0.12 0.33 Patent 13215 0.22 0.42 14219 0.22 0.41 12671 0.04 0.21 R&D internal, log 13215 1.03 1.94 14219 0.79 1.73 12671 0.85 1.81 R&D external, log 13215 0.34 1.18 14219 0.27 1.02 12671 0.27 1.05 Size 13215 4.06 1.51 14219 4.05 1.47 12671 4.26 1.54Management strategy 13215 0.19 0.39 14219 0.16 0.36 12671 0.13 0.34Organization strategy 13215 0.24 0.43 14219 0.24 0.43 12671 0.20 0.40 Cooperation 13215 0.05 0.22 14219 0.03 0.17 12671 0.06 0.23 UK regulation 13215 0.90 1.06 14219 0.59 0.94 12671 0.67 0.92 Scientists 13215 6.10 15.48 14219 5.33 14.67 12671 5.06 14.21 Market capacity 13215 1.21 1.12 14219 0.44 0.94 12671 0.62 1.03
  15. 15. MethodologyThe econometric model is based oni)cross-sectional data (Tobit);ii)panel data – IMLE, IV-RE / 2SLS; nprit = C + Xit  + B1ln(Tit) + B2xit+ eit (11) eit =vi + uit•where i denotes a reporting unit (i=1, …,n) and t - the timeperiod (t=1,..,T); C is a vector of intercept terms, it is a vectorof unknown coefficients of the exogenous variables, Xit is avector of exogenous variables (controls); Tit and xit are thevariables of interest: training expenditure and patent protectionof a firm i in period t. The error term eit consists of theunobserved individual-specific effects, vi and the observation-specific errors, uit.
  16. 16. Returns to patenting and training model 1 - NPR: (cross-section) basic Instrumented basic Instrumented basic Instrumented Variables 2002-2004 2004-2006 2007-2009 Training 0.61*** 5.42*** 0.76*** 10.6*** 1.23*** 22.4*** Rivals 0.24 -0.25 -0.30 -0.67 -0.97** -1.48* Global 2.05*** 2.45*** 2.34*** 1.74*** 2.44*** 2.21*** Public 0.54 0.94** 0.81* 1.28** 0.80 0.71 Age -0.62*** -0.50*** -0.31* -0.46** -0.41** -0.28 Foreign -0.23 -0.38 -0.74** -0.36 -0.89* -0.83 Patent 2.90*** 2.46*** 3.76*** 2.10*** 2.76*** 5.86*** R&D internal 1.01*** 0.08 1.15*** -0.90*** 1.21*** -2.71*** R&D external 0.27*** -0.36*** 0.13 -1.19*** 0.049 -2.61*** Size 0.027 -0.97*** -0.71*** -1.85*** -0.48*** -1.66*** Management 1.05*** -1.59*** 1.84*** -2.13*** 2.16*** -4.51*** Org strategy 1.88*** 0.66** 2.88*** -0.77 3.63*** -0.23 Cooperation 2.63*** 1.63*** 2.97*** 0.85 3.48*** -3.19*** Scientists 0.018** 0.015* 0.015* -0.013 0.022** -0.081*** Constant -14.3*** -10.8*** -12.6*** -8.61* -7.98** -3.27 No.obs 13215 13215 14219 14219 12671 12671 Uncensored obs. 2145 2145 1605 1605 1394 1394F-test for instruments 160.0 148.5 84.5 Wald test chi2(1) 2657 1458 2405 1020 2205 1105
  17. 17. Returns to patenting and training model 2 - GOS: (cross-section) basic Instrumented basic Instrumented basic Instrumented Variables 2002-2004 2004-2006 2007-2009 Training 0.05*** 0.02 0.04*** 0.17** 0.01 -0.21 Rivals -0.62*** 0.09 -0.08 -0.20 -0.17 -0.25* Global 0.26*** 0.26*** 0.31*** 0.30*** 0.25*** 0.26*** Public -0.20*** -0.20*** -0.22*** -0.21*** -0.16 -0.17 Age 0.08*** 0.08*** 0.09*** 0.10*** 0.15*** 0.15*** Foreign 0.39*** 0.39*** 0.42*** 0.42*** 0.57*** 0.57*** Patent 0.18*** 0.18*** 0.14*** 0.12** 0.15 0.12 R&D internal 0.016 0.02 0.03** 0.001 0.01 0.05 R&D external 0.05*** 0.05*** 0.06*** 0.04** 0.06** 0.09** Size 0.79*** 0.79*** 0.84*** 0.82*** 0.85*** 0.87*** Management 0.02 0.04 -0.05 -0.11* -0.01 0.05 Org strategy 0.06 0.07 0.02 -0.02 -0.13* -0.07 Cooperation 0.12 0.13* 0.21** 0.17 0.09 0.19 Scientists 0.006*** 0.006*** 0.008*** 0.008*** 0.008*** 0.010*** Constant 5.02*** 1.12* 3.55*** 3.17*** 3.23** 3.89*** No.obs 6703 6703 5968 5968 3432 3432 R2 0.61 0.61 0.60 0.59 0.52 0.51F-test for instruments 154 97 48
  18. 18. Discussion1. Hypothesis 1 – mixed evidence: The elasticity of theNPR with respect to training expenditure is within therange of 0.6-1.2 % (Tobit estimates), and 5.4-22.4 % (IV-Tobit). Mixed evidence for the impact on profits.2. Hypothesis 2 – supported: Returns to patentingmeasure = B2+1 means that, as a firm gets a patent,NPR (profits) increase by 1+2.46=3.46 (1.18) for CIS4and by 1+2.10=3.10 (1.12) for CIS5 & not significant forCIS6.3. Hypothesis 3 – supported: There is no furtherinvestment in training during the crises should firm usepatents as a form of IP protection.4. Patent propensity is estimated to fall from approx. 19%in CIS6 when compared to CIS5.

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