The market value of patents and R&D: evidence from European firms BRONWYN H. HALL University of California, Berkeley and NBER GRID THOMA University of Camerino and CESPRI-Bocconi, Italy SALVATORE TORRISI University of Bologna and CESPRI-Bocconi, Italy JRC IPTS, Seville May 2009

hall thoma torrisi 2 outline  Goals  Motivations/background  Contribution of the paper  Methods  Data  Results  Conclusions

May 2009 hall thoma torrisi 3 1. goals  What is the private value of EP patent rights for European firms?  What is the additional value of patent ‘quality’?  are there any differences between EP and US patents?

May 2009 hall thoma torrisi 4 2. Motivations  Rising % of intangibles as a determinant of firm’s value  N patents , but often patents are not effective to protect innovation (Cohen et al, 2000)  the distribution of patent value is very skewed (Shankerman& Pakes, 1986; Harhoff et al 1999; Scherer and Harhoff, 2000)

May 2009 hall thoma torrisi 5 Motivations (iii)  many low ‘quality’ patents taken out for strategic reasons (Bessen, Hall&Ziedonis)  Need for patent quality indicators to identify valuable patents, successful R&D output (Pakes and Schankerman, 1986; Hall et al, 2005)

May 2009 hall thoma torrisi 6 3. Contribution of this paper  novel empirical evidence on the market value of R&D and patents in European firms (a proxy for the value of patent protection)  different measures of patent ‘quality’ (a proxy for the reward for invention) (only 1 study before on UK firms – US pats)

May 2009 hall thoma torrisi 7 3. contribution of this paper (ii)  comparison between US and EP patents  EP system is different from US: no Community-wide patent; no European Patent Court,  enforcement costs  Protection of the same inventions at both US and EPO as an indicator of quality beyond family size

May 2009 hall thoma torrisi 8 main argument  the market places a positive value on R&D and high ‘quality’ patents  why? –a source of intangible benefits, not reported in the balance sheet –strategic flexibility –superior knowledge, higher quality products –future long-term growth, higher profitability and lower risk

May 2009 hall thoma torrisi 9 4. Method measuring the value of R&D and patents  Ex-post evaluation – productivity –(e.g., Mansfield 1968; Griliches 1979; Hall and Mairesse 1995)  Benefits: data availability  Problems: –uses accounting data, often incomplete –R&D-TFP lag is difficult to predict and difficult to identify

May 2009 hall thoma torrisi 10 Measuring the value of R&D and patents  Survey-based direct measures of patent value –Harhoff et al. 1999; Gambardella et al  Benefits: direct inventors estimation  Problems: –high cost of data collection, especially over time –possible respondent bias (inventors)  Patent renewal data –Schankerman and Pakes, etc  Benefits: owner’s expectations  Problems: –not informative about shape of upper tail, the important part of the value distribution –US data available only recently

May 2009 hall thoma torrisi 11 Measuring the value of R&D and patents  Ex-ante evaluation - market value –Griliches 1981; Griliches et al 1991; Hall 1993 and 1999; Hall et al. 2005) –Profit-maximizing firms as bundles of N assets (A, K, brand names etc.) (see Wildasin, 1984) –Calculation of the shadow price of assets estimating their marginal return in a market value equation  Problems: –efficient capital market assumption –only publicly-traded firms can be analyzed

May 2009 hall thoma torrisi 12 Empirical studies in Europe

May 2009 hall thoma torrisi 13 the market value model A it = physical assets K it = knowledge assets  t = marginal or shadow value of K/A under CRS ( t =1) equation becomes or

May 2009 hall thoma torrisi 14 estimation of the market value model V it = Market value: market cap (equity) plus current and non current liabilities less current assets plus inventories A it = Tangible assets: gross fixed assets and inventories less [depreciation, depletion, and amortization (accumulated), and other deductions] K it = knowledge assets: R&D stock, US and EP stocks  t = marginal (shadow) value of K/A

May 2009 hall thoma torrisi Data  1,061 publicly-traded firms, (5,312 obs) from 21 West and East Euro countries  Data sources: –EPO PATSTAT, Delphion –Bureau van Djik’s Amadeus, Hoovers, D&B’s WOW, Thomson Financial’s Datastream

May 2009 hall thoma torrisi 16 Country-size distribution

May 2009 hall thoma torrisi 17 construction of key variables: EPO and/or USPTO patents (1)

May 2009 hall thoma torrisi 18 Key variables: Patent “quality”  Three “quality” measures: –Family size: number of equivalent patents (same priority date) –forward citations (pub. date of cited pat – appl. date of citing patents, max length 3 yrs) [family cites: direct cits + cits to equivalents] –technological fields (8-digit IPC classes

May 2009 hall thoma torrisi 19 Linear combination of these measures  Linear combination of these measures: the Lanjouw & Schankerman ‘composite’ index of patent quality  Two steps: 1.3SLS of indicator variables on time and macro-tech fields to control for overall trends 2.Factor analysis (ML) with the 3SLS residuals

May 2009 hall thoma torrisi 20 Correcting for truncation  Problem: unobserved citations for newer patents  Use “structural” method developed by Caballero & Jaffe (1993) and Hall et al. (2005) –corrects observed citation rates for citation lag effects in six technology classes –Restriction on number of classes is imposed by the small number of cites

May 2009 hall thoma torrisi 21 Sample selection bias  sample selection model – 3,773 R&D-reporting publicly-listed firms and 3,194 matching sample (no R&D data reported) (Amadeus) – Heckman 2 steps method – Probit equation for selection into the sample: leverage, ownership shares, capital and labor intensity, industry and year dummies – Include inverse Mills’ ratio in market value equation – little evidence of sample selection bias

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May 2009 hall thoma torrisi 26 Magnitudes of coefficients: R&D  R&D stock/A: the magnitude of the coefficient is consistent with most of those reported in earlier works on single or multiple countries  impact of R&D: one standard deviation increase in R&D-assets ratio yields a 30% increase in market value

May 2009 hall thoma torrisi 27 Magnitude of coefficients: patents  patents taken out in only one jurisdiction have little if any association with firm market value  one SD increase in EPUS patent stock per €1 million of R&D yields about 12% increase of V  The corresponding value for USEP is 10%  one EP only pat per €1mil R&D is worthless

May 2009 hall thoma torrisi 28 Magnitude of coefficients: patent quality  Patent “quality” –Both cites and the composite index yield additional significant value, albeit effects are relatively small –cits to EPUS: Forward citations have a stronger effect as the index (the opposite for USEP) –a standard deviation increase in EPUS cites- patents ratio yields a 8.8% increase in V (vs. a 4.6% increase due to USEP pats) –The corresponding increase in V induced by the composite index is 5% for EPUS and 7% for USEP

May 2009 hall thoma torrisi Conclusions  EPO patents are valued only if they have an US equivalent (premium for targeting US mkt?)  Although investors distinguish patents with a consistent set of characteristics (family size, forward cites and tech fields)  citations alone capture most of the effect of patent quality indicators for EPUS patents (additional value of the composite index is limited)  Why? by including equivalents (and their cits) we already capture much of the information associated with family size

May 2009 hall thoma torrisi Conclusions (ii)  Compared to US patents held by US firms, EPO patent stock held by EU firms is valued more whereas citations are valued less

May 2009 hall thoma torrisi 31 implications  New regulations and international agreements (Basel II, Sarbanes-Oxley Act,)  accounting for IP value and risk  IAS/International Accounting Standard Committee (IAS 38): revision of international accounting standards helps reducing the gap B-to-M value of assets  a proposal for EU firms: compulsory R&D disclosure for publicly-listed firms

May 2009 hall thoma torrisi 32 Limitations and future research  assumed that citation lag distribution does not vary between EPO and non-EPO citing patents  self-citations not treated separately –but previous work has not found big differences in results for citations as a whole –HJT found self-cites worth more  results based on the corporate structure as of  quality index excludes number of claims, type of references (XY cits …)

May 2009 hall thoma torrisi 33 Limitations and future research  panel data analysis  R&D and patent stock changes only slowly then differentiating the model  other sources of bias  previous studies have found that IV estimates are problematic (e.g., Greenhalgh and Rogers, 2006)  possible instruments for firm’s R&D and patent choices: firm-specific pre-determined characteristics (geographical diversification, presence in the US stock mkt …), industry- characteristics (capital intensity, competitors’ R&D and patenting)  non-European firms

May 2009 hall thoma torrisi 34 further information

May 2009 hall thoma torrisi Motivations (i)

May 2009 hall thoma torrisi 36 June 2008ZEW Conference36 Background on Measuring the Economic value of R&D and Patents APPROACHES MAIN CONTRIBUTIONS LIMITATIONS Productivity accounting - Ex-post evaluation Mansfield 1968; Griliches 1979; Hall and Mairesse 1995 uses accounting data, often incomplete; R&D-TFP lag is difficult to predict and identify Survey-based direct measures of patent value Harhoff et al. 1999; Gambardella et al High cost of data collection; possible respondent bias Patent renewal data Schankerman and Pakes 1986; Pakes 1986; Schankerman 1998 not informative about shape of upper tail; US data available only recently Market value - Ex-ante evaluation Griliches 1981; Griliches et al 1991; Hall 1993 and 1999; Hall et al requires efficient capital market assumption; only publicly-traded firms can be analyzed

May 2009 hall thoma torrisi Summary of results variable Effect on M/A comment R&D stock/A ++ + Similar to other studies Pat stock/RDstk + + > Studies on US firms Cites/Pat stock +  from US LS composite index ++ similar to LS(2004) on US data

May 2009 hall thoma torrisi Contribution of this paper (iii)  focus on “software-related” patents  Why software? A highly controversial policy issue in Europe  EPC (art. 52): computer programs “as such” not patentable but … EPO and EC has been considering standards for “computer implemented inventions” (CIIs)

May 2009 hall thoma torrisi Contribution of this paper (iv)  focus on “software-related” patents  Why software? A highly controversial policy issue in Europe  EPC (art. 52): computer programs “as such” not patentable but … EPO and EC has been considering standards for “computer implemented inventions” (CIIs)  sw ‘as such’ is patentable in US

May 2009 hall thoma torrisi 40 Simple vs. complex q estimators  DaDalt, Donaldson and Garner (JFR, 2003)  Complex estimator (Qc) more precise than simple estimator (Qs)  But: sample selection bias (more than 20% loss in sample size (Compustat)  Qs and Qc are highly correlated  ∆(Qs, Qc)=f(S; liquidity; ; D…)  ∆0 in 90% of cases outside the range 0.8<q<1.2  less of 20% firms in our sample fall in this range  In general, Q>1 in sectors with unique inputs and outputs … (Lindenberg and Ross, 1981)

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May 2009 hall thoma torrisi 43 construction of key variables: software patents 1. Keywords method (Bessen-Hunt 2004) – Search for ((software) OR (computer AND program)) AND NOT (chip OR semiconductor OR bus OR circuit OR circuitry TI) AND NOT (antigen OR antigenic OR chromatography) in the patent document (title and full text) 2. Patent class method (Graham-Mowery, Hall- MacGarvie) – IPC classes in the patent portfolios of the world’s 15 largest specialized software firms –  3,518 classes-subclasses (117 if only the main IPC codes in each patent are considered). 3. This work – intersection of these two methods

May 2009 hall thoma torrisi 44 construction of key variables: software patents  Inspecting a random sample of EPO ‘software’ Bergstra and Klint found several Type-II error in when the union of the keyword and the IPC method is adopted  Using the intersection of the two methods we find that only 3.8% of EPO patents are software patents in our sample (N= 271)  1/3 are held by Siemens and 75 % by the top 5 firms (Siemens, BT, Philips, Oce, and Alcatel)  SAP, the largest software holds only 5.

May 2009 hall thoma torrisi 45 construction of key variables: software patents  Instead, 6.7 % of US patents owned by the sample firms are ‘software’ patents (N=9,213)  This makes sense: pure software patents do not qualify for patentable subject matter because (no technical effect, not capable of industrial application according to the EPC).

May 2009 hall thoma torrisi 46 Cumulative number of “software” patents granted by the EPO by year of application

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May 2009 hall thoma torrisi 49 results: software patents  Software patents of either kind are valued slightly more than ordinary patents  an additional software patent/€million of R&D yields less than 0.5% increase in V  explanations? –small numbers. most software firms in Europe are not using patents to protect their inventions –the EPO has been successful in excluding such patenting

May 2009 hall thoma torrisi 50 results: software patent quality  the quality of software patents is not evaluated more than the average patent  then, software pats evaluated as a signal of protection  but the market does not believe in the value of the underlying software inventions

May 2009 hall thoma torrisi 51 conclusions on sw  software patents are valued above ordinary patents … the market believes in the enforceability of software patents … despite EPC  … not in their quality… are these ‘strategic’ patents – e.g., to avoid litigation with IBM, Canon, Sony?  Hall and McGarvie (2006) found that citations are positively valued by the market only when cited patents are owned by software firms –And, software firms altogether own only 1% of software patents in our sample

May 2009 hall thoma torrisi 52 conclusions on sw  other reasons why software patent quality is not valued by the market? –too few observations and high concentration of EPO software pats in a few non-software firms – Siemens (44%), Alcatel, Thomson? –results do not change when Siemens is dropped