Outline. Patents as indicators. Economic research on patents. What are patent citations? Two types of data. Measuring the returns to innovation (2)

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1 Measuring the returns to innovation (2) Prof. Bronwyn H. Hall Globelics Academy May 26/27 25 Outline This morning 1. Overview measuring the returns to innovation 2. Measuring the returns to R&D using productivity regressions 3. Measuring the private returns to R&D using market value equations This afternoon 1. Patent data overview 2. Measuring innovation using patent data 3. Innovation survey data March 24 Globelics Academy - Lisbon 2 Economic research on patents Normative how should we design IP systems; how should a firm use them Positive patents as a measure of inventive activity knowledge value knowledge flows March 24 Globelics Academy - Lisbon 3 Patents as indicators A patent is a property right to a knowledge asset => patents can be used to measure innovative output Counts at the firm, industry, country level over time Counts weighted by the number of subsequent citations that they receive Citations from one patent to another a map of the links between these bits of output or knowledge Requires understanding of patents: how and why they are taken out, administered, and enforced how this changes over time March 24 Globelics Academy - Lisbon 4 Two types of data Patent information Date of application and grant Name and geographic location of inventor Name and type of entity to which assigned Detailed classification by technology Title, abstract, description, and claims Citation information Of other patents (in the same or different patent systems) Of the scientific literature type of citation (examiner added, importance) March 24 Globelics Academy - Lisbon 5 What are patent citations? Somewhat like citations in a research paper: References to prior technology, either patents or other scientific literature on which the current patent builds or which it uses Some added by the USPTO examiner (the referee ) Some added after the fact (not used by inventor) Some added to avoid infringement (limit scope, defense against suits) Some added for teaching (like survey articles) USPTO differs from EPO in citation practice Jaffe, Trajtenberg, Fogarty inventor survey (NBER) About half correspond to some kind of knowledge flow About one quarter to a very substantial flow Remainder are primarily those added by others (not the inventor) March 24 Globelics Academy - Lisbon 6 1

2 March 24 Globelics Academy - Lisbon 7 March 24 Globelics Academy - Lisbon 8 Some facts - U. S. citations More valuable patents are cited more One quarter of patents receive no citations.1% receive more than one hundred citations Lag distribution is skew to the left with a mode at about 3.5 years. Most cites happen by 1 years, but there can be long lags (3 years) Number per patent has increased recently with the advent of computerized search March 24 Globelics Academy - Lisbon 9 March 24 Globelics Academy - Lisbon 1 Number of Patents Figure 3 Citation Distribution Citation Distribution - More than 1 Citations > Citation Count through 1995 March 24 Globelics Academy - Lisbon 11 Number of Patents Citation Count through 1995 EPO Citations Fewer in number (median around 3 instead of 6) Three types: X has potential to defeat novelty or inventive step when the reference is considered alone Y potential to defeat or refute inventive step when combined with one or more other such references - combination being obvious to a person skilled in the art A - reference showing the general state of the art but would not be considered to be of particular relevance Michel, J. and B. Bettels (21). "Patent Citation Analysis - A closer look at the basic input data from patent search reports," Scientometrics, 51 (1), March 24 Globelics Academy - Lisbon 12 2

3 NBER Patent Citations Data File Available at ~3 million U.S. patents granted between January 1963 and December 1999 (now updated to 22) Patent number, application and grant dates Country and state of first inventor Main US patent class; number of claims Number of citations, forward and backward; generality and originality measures based on citations All citations made to these patents between 1975 and 1999 (over 16 million). Match of patenting organizations to Compustat (the data set of all firms traded in the U.S. stock market). enables ownership assignment for part of the dataset March 24 Globelics Academy - Lisbon 13 Other patent data For EPO patent searching For EPO data purchase (CD-Roms) Contains triad (USPTO, EPO, JPTO) patents CD-Rom available from Colin Webb Complete statistical data from EPO New project under Dominique Guellec (Chief Economist, EPO) to provide this on the web March 24 Globelics Academy - Lisbon 14 Citations as indicators of knowledge flow Idea: if one patent cites an earlier patent, that implies that the knowledge or invention builds on or uses knowledge in the earlier patent Jaffe, Trajtenberg, Fogarty inventor survey (NBER) About half correspond to some kind of knowledge flow About one quarter to a very substantial flow Remainder are primarily those added by others (not the inventor) March 24 Globelics Academy - Lisbon 15 Applications of this idea Self measure in HJT Jaffe, Trajtenberg and Henderson (1993) Measured geographic localization of knowledge spillovers Compared citing patents to control patents with same technology and temporal distribution Citing patents more likely to come from same locality as patent being cited Macgarvie (23) Citations used to measure knowledge flow induced by exporting or importing Example: French firms begin exporting to Germany Do they cite German patents more after than before? yes March 24 Globelics Academy - Lisbon 16 Patents as value indicators Review earlier work on measuring innovation with patents briefly Hall, Jaffe, and Trajtenberg (RJE 25) March 24 Globelics Academy - Lisbon 17 Measuring innovation using patents Schmookler (196 book) pioneer in the use of patent statistics Scherer s (196s) work in oil, chemicals, steel Griliches et al ~198 (incl. Hall) first large sample work using computerized USPTO data. Conclusions: Patents strongly related to R&D across firms, elasticity close to one Controlling for unobserved differences across firms, elasticity lower (about.3) Difficult to determine lag structure R&D very smooth over time within firm Poisson-type models patents exhibit overdispersion In the presence of R&D, patents add little explanatory power for sales, profits, market value, etc. Why? March 24 Globelics Academy - Lisbon 18 3

4 Citations and market value Hall, Jaffe, Trajtenberg (21/24) do patents weighted by forward citations provide a better measure of patent value than patent counts themselves? Broad firm-level analysis previous studies invention- or narrow industry-specific: Trajtenberg (RJE 199) - consumer welfare for CAT scanners and citations Klock and Shane (AER 1995) - market value of citation weighted patents in semiconductors Austin (1993) - event studies on citation-weighted biotech patents Hirschey et al (1998); Lev et al (1998) - accounting-based work similar to ours. March 24 Globelics Academy - Lisbon 19 Market value equation K it logqit = logqt + log 1 + γ1 + αtd( K it = ) + εit Ait where Q it =V it /A it (market to book or Tobin s Q) Interpretation: q t = overall market level (approximately one). γ t = Relative shadow value of K assets (=1 if depreciation correct, investment strategy optimal, and no adjustment costs). α t = Premium or discount for the absence of K assets Modified to accommodate patents and citations/patent: R & D logq = logq + log 1 + γ + γ PAT CITES + γ + ε it it it it t it Ait R & Dit PATit March 24 Globelics Academy - Lisbon 2 Some measurement issues Explanatory power of knowledge stock measures Patenting Firms Only - R-Squared from Tobin's Q Equation.25 R-squared R&D Pat Patent stocks: P = no. of patents applied for at t K P (85) = (1-δ) K P (84) + P(85) Citation stocks: C = citations to patents applied for at t K C (85) = (1-δ) K C (84) + C(85) Past cite stocks: use only citations received by date of market value measurement March 24 Globelics Academy - Lisbon 21 Cite-wtd Pat.5 Past Cite-wtd Year March 24 Globelics Academy - Lisbon 22 Exploration of the functional form Include stock of R&D, patents per R&D, and cites per patent. Cites per patent are more important than patent yield itself Increase of one cite per patent is associated with an increase of 3-4% in market value Break up cites per patent into five ranges: to 4, 4 to 6, 6 to 1, 1 to 2, over 2 Only the latter three categories are positive; the other two are zero 5-75% boost to market value if citations per patent average above 2! Timing do citations received before value is measured matter more or less than those received after? Less, although they are useful for forecasting. Predictable and unpredictable citations receive approximately equal weight. March 24 Globelics Academy - Lisbon 23 Self citations Self-cites = citations to patents owned by the same firm. More valuable => owning a technology trajectory, cumulativeness is valuable Less valuable => cite whatever is at hand, does not necessarily signify any value Results High self-citation share is valuable (worth about twice as much) if firm is small or medium-sized, neutral if firm is large. Not having self cites is negative if firm is large, positive if firm is small. March 24 Globelics Academy - Lisbon 24 4

5 Innovation surveys Widely used since mid-199s Based on Yale/CM surveys in US, but. Now in EU countries; Chile, China,. Surveys at the firm or plant level Both quantitative and qualitative questions Cover a larger range of innovative activities than traditional measures Intermediate output measures New product introduction (to firm or market) New process introduction (to firm or industry) Share of new products in sales Organizational innovation March 24 Globelics Academy - Lisbon 25 March 24 Globelics Academy - Lisbon 26 Input measures Source of innovation (firm, cooperation, joint) Amount of cooperation Use of public support Innovation expenditure Internal and external R&D; continuous? Purchase of machinery & equipment Related marketing/design expenditure K purchase Training related to innovation March 24 Globelics Academy - Lisbon 27 Qualitative measures Impetus/discouragement of innovation Market factors (demand pull) Cost factors and tech push Sources of knowledge Suppliers, customers, regulation (standards) Trade press, competitors, conferences Public sector Methods for protection of returns Informal: lead time, secrecy, confidentiality, complexity Formal: trademarks, patents, copyrights, design registration March 24 Globelics Academy - Lisbon 28 How to use these new data Most useful when combined with hard accounting data Allows concrete performance measurement A number of studies of this kind Crepon, Duguet, Mairesse (EINT 1997) Special issue of EINT forthcoming (now on my website) China, Chile, Scandinavia, Netherlands March 24 Globelics Academy - Lisbon 29 5

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