1. A RE ICT S PEEDING U P THE G EOGRAPHIC D IFFUSION OF K NOWLEDGE ? A N A NALYSIS OF P ATENT C ITATIONS Vincenzo Spiezia OECD vincenzo.spiezia@oecd.org

2. O UTLINE Review: why do we care? Patents and citations The OECD Regional Patent Database Analysis and results

3. R EVIEW (1/4) The diffusion of new ideas is at the heart of economic growth Innovation is a cumulative process that builds up on previous innovations Fast access to new discoveries are key to the capability of firms and countries to innovate Understanding how knowledge diffuse is crucial for the design and evaluation of innovation policies

4. R EVIEW (2/4) Our aim: to analyse the geographic diffusion of knowledge flows based on patent citations In particular, we want to test if: 1. Citation lags decrease with distance; 2. The effect of distance is weaker for ICT technologies, i.e. : ICT-related knowledge diffuses faster; 3. The effect of distance has decreased in recent time, i.e. : due to diffusion of ICTs.

5. R EVIEW (3/4) Home bias : inventors are more likely to cite other inventors living in the same country/states National/state data can only provide a very partial account of knowledge diffusion. Our first contribution : To analyse patents applications and citations from OECD Regional Patent Database (REGPAT) - over 5000 sub national regions in 29 OECD countries.

6. R EVIEW (4/4) The world is flat (Friedman 2005) ICT have reduced the importance of distance The world is spiky (Florida 2005) Distance matters for trade and innovation Our second contribution : Has the effect of distance on the speed of knowledge diffusion decreased in the ICT years, after 1995?

7. P ATENTS A patent is an intellectual property right in the commercial use of a devise For a patent to be granted, the invention must be novel, involve a (non-obvious) inventive step and be capable of industrial application Patents as a proxy for innovation output is well-established in economic analysis. Strong correlation between firm’s R&D and its patenting output (Griliches, 1990). Strong correlation patents and productivity/trade (survey in OECD 1994).

8. C ITATIONS Patent documents also contain citations to previous patents > (Jaffe et al., 1993). Patent citations are largely the contribution of patent examiners: social return to patents (Griliches, 1990) Limitations: different values, law & regulation, strategic A non-random sample of relevant knowledge

9. T HE OECD R EGIONAL P ATENT D ATABASE (1/2) Patent have been linked to regions according to the addresses of the applicants and inventors REGPAT includes patent applications to the EPO, to the PCT and to the USPTO We have focused on patents applications to the European Patent Office (EPO) All patents granted by all patent offices worldwide and that are cited in the patents applications to the EPO All patents application filed over the period 1978- 2004.

10. T HE OECD R EGIONAL P ATENT D ATABASE (2/2) An aggregation of the IPC codes developed by the French “Observatory of Sciences and Technology” (OST) to 30 technological groups Kept top 5% of patents with the largest number of citing regions. 2 advantages: First, focus on patents with a potential value for a large number of regions Second, less noise due to patents with few citations In all we selected over 17000 patents

11. D ISTANCE DOES NOT MATTER

12. D ISTANCE DOES MATTER

13. T HE ECONOMETRIC MODEL (1/2) Speed of knowledge flows across regions based on patent citations: duration model (Cox) The probability that region i would cite for the first time a patent k filed in region j at a given point in time t Self-citation is excluded If we observe a citation, we know that the region knows that patent. The opposite is not true! Unobserved differences in the propensity to cite (variance-corrected across citing regions)

14. T HE ECONOMETRIC MODEL (2/2) What determines the probability to cite? Technological complementarities : total patents in the citing region by OST groups; Quality of patents in the innovating region : ratio between total number of citations to and patents from the innovating region by OST groups; Concentration of innovation : total patents in the inventing regions by OST groups (search effect); Geographic distance between the inventing and the (potential) citing region.

15. R ESULTS (1/5)

16. R ESULTS (2/5) Geographic distance has a significant and negative effects on the probability to cite a patent. Strongest effect for “Civil engineering, building, mining” and “Agricultural and Food Processing Machinery” : for a region 500 miles away from the patenting region the probability to cite the patent is 10% lower ; Weakest effect for “Semiconductors” and “Information technology”: for a region 500 miles away from the patenting region the probability to cite the patent is only 1-2% lower ; Weak effects also in “Pharmaceuticals & Cosmetics”, “Treatments/Surface”, “Optics”, “Organic Chemistry” and “Medical Technology”: a region 500 miles away from the patenting region the decrease in the probability to cite the patent is lower than 3%.

17. R ESULTS (3/5) Another way to look at the differences among technological groups: Decrease in probability to cite a patent due to an increase in distance from 500 to 2000 miles The differences are striking: For “Information technology” the probability decreases from -2% to -8% ; For “Civil engineering, building, mining” the probability decreases from -12% to -40%.

18. R ESULTS (4/5)

19. R ESULTS (5/5) The effect of distance: Decreased in 4 technological groups: Medical Technology Technical Processes Electrical devices-Electrical engineering Transports Increased in 6 technological groups: Analysis, measurement, control Audiovisual technology Civil engineering building, mining Mechanical elements Thermal Processes Chemical Engineering Stayed the same in the remaining 19 groups

20. P RELIMINARY RESULTS 1. Distance slows down knowledge diffusion; 2. Diffusion is the fastest for semiconductors and ICT; 3. No evidence of a general increase in knowledge diffusion driven by ICT. Further checks on the econometric specification: unobserved differences; count data; citation types; multiregional firms; add an indicator of ICT diffusion.

21. E CONOMETRIC SPECIFICATION The probability that region i cites patent k at time t ik (t ik |x ik ;  )= k (t ik )*exp(x’ ik *  OST(k) +u i ) k (t ik ) = baseline hazard function for patent k x ik = attributes of region i and patent k  OST(k) = vector of parameters to be estimated u i = unobserved characteristics of the citing region V = U -1 BU