Knowledge flows across European regions

Knowledge flows across European regions

Raffaele Paci and Stefano Usai

CRENoS, University of Cagliari

EU FP7 SSH Project: Intangible Assets and Regional Economic Growth

forthcoming in Annals of Regional Science

Università di Palermo, 10 aprile 2008

Motivations /1• Many economists have attempted to find evidence

of the existence of knowledge spillovers or flows either embodied in R&D exchanges, in bilateral trade, in capital goods acquisition or in foreign direct investment….

• These indicators are mainly indirect since technological flows, at the interregional and international levels, are hard to be captured:Krugman (1991) “knowledge flows are invisible and cannot be measured and tracked”

Motivations /2

• Jaffe et al (1993): knowledge flows may leave a “paper trail”, in the form of patent citations, which can be measured and used to obtain information on the geographical component of the innovation spillover mechanism

• Citations made are a measure of previous knowledge extracted from the cited patent and embodied in the new invention.

• They allow us to represent this knowledge flow in the geographical space (by using the inventors’ residence) to have an idea of the knowledge links (network) among cited and citing regions

Aims• Contribute to the analysis of knowledge flows and

their determinants across European regions

• Examine whether geographical distance and spatial contiguity influence knowledge exchanges: i.e. are knowledge spillovers locally bounded ?

• Control for the role of other types of “distances”: production structure, economic conditions, technological efforts, national borders

• Investigate on the changes along time

Background literature

• Seminal contributions on the USPTO database:– Jaffe et al, 1993– Jaffe and Trajtemberg, 1996 and 1998

• Some more recent works on EPO– Maurseth and Verspagen, 1999 and 2002– Lukatch and Plasmans, 2003 – Breschi and Lissoni, 2004– Maggioni et al., 2005– LeSage et al., 2006

CRENOS dataset• Patents granted by EPO, 1978 – 2004• Each patent attributed to one of 175 regions of 17

countries in Europe, the 15 members of the EU15 plus Switzerland and Norway (based on inventors –single and multiple- and not firms HQs).

• Citations are linked to patents from both a geographical and an industrial point of view.

• Each patent is classified by industrial sector (3 digit) based either on the IPC - ISIC Yale Technology or on the Schmock-OECD concordance. Results on sectors are preliminary and are not reported here.

• Note: citation list (both at EPO, USPTO) is completed by the examiner during the granting procedure

Table 1. International flows of patent citations(only patents granted by EPO to inventors resident in the 17 European countries)

1990 1998

Patents granted 19.987 18.659

Citations 77.463 72.804

Citations to patents granted by: % shares % shares

EPO 24,2 24,3

17 countries 15,0 14,6 other countries 9,3 9,7

European national patent offices 45,7 33,7

USA 25,6 30,8

Japan 0,3 0,3

Rest of the world 4,1 11,0Total 100,0 100,0

Table 2. Geographical distribution of patent citations

1990 1998

Citations by EPO to EPO (17 countries) 11.589 10.606

Geographical flows % shares % shares

Intraregional 28,6 21,9

National interregional

- contiguous regions 9,3 9,7

- not contiguous regions 15,4 16,2

International interregional 46,7 52,1

Total 100,0 100,0

Table 3. Geographical distribution of patent citations in selected countries(% shares on total citations made)

Nation no of regionsintraregional

flowsinternational

flowsintraregional

flowsinternational

flows

Austria 9 18,3 72,1 21,0 70,1 Belgium 3 31,3 56,1 36,4 56,3 Switzerland 7 29,2 53,8 27,6 54,3 Germany 40 27,0 36,8 17,5 44,9 Spain 15 22,2 72,1 19,3 76,9 Finland 6 19,8 70,3 19,0 71,5 France 22 30,7 51,8 30,6 48,7 Italy 20 27,4 58,8 30,6 54,3 Netherlands 4 43,7 46,7 24,3 66,7 Sweden 8 17,9 76,6 14,9 77,9 United Kingdom 12 28,8 48,7 16,4 65,3

1990 1998

Map 1. Distribution of patents citations by region of origin

1990 1998

Gini = 0.72 Gini = 0.68

Table 5. Concentration indices across 175 regions

1990 1998 1990 1998

CR 5 0.26 0.24 0.26 0.25

CR 10 0.41 0.37 0.41 0.38

CR 20 0.60 0.53 0.61 0.56

Gini 0.72 0.68 0.73 0.70

Herfindhal 0.025 0.021 0.026 0.023

Citations madeConcentration indices

Citations received

Table 6. Sectoral composition of citations

Sectors Shares (%) Citations Shares (%) Citationsorigin within sector (%) origin within sector (%)

Food, beverages 1.0 47.4 0.8 32.3Tobacco 0.0 39.1 0.2 51.2Textiles 1.0 9.7 1.2 9.3Wearing apparel 0.2 2.8 0.3 3.7Leather and footwear 0.3 51.3 0.3 48.1Wood products, except furniture 0.9 4.0 0.8 3.9Paper 0.8 12.4 1.0 14.7Printing and publishing 0.3 6.8 0.3 7.0Coke and refined petroleum products 2.1 12.3 1.3 10.6Chemicals and chemical products 27.3 72.6 18.4 66.5Rubber and plastic 2.2 12.4 2.6 14.8Non metallic mineral products 2.1 14.1 2.2 13.5Basic metals 0.6 12.8 0.9 15.0Fabricated metal products 6.3 21.0 8.0 20.9Machinery 20.0 37.4 25.7 40.4Office, computing 1.5 7.7 1.7 7.4Electrical machinery 8.6 27.2 8.8 28.2Radio, tv, communication equipment 6.2 30.8 4.9 26.5Medical, precision instruments 7.7 22.4 6.8 18.4Motor vehicles, trailers 3.9 19.0 5.3 17.3Other transport equipment 3.1 6.6 3.4 6.9Furniture and other 3.6 11.4 4.7 14.2Recycling 0.3 2.6 0.4 2.5

Total / average 100.0 37.9 100.0 33.1

19981990

Table 7. Geographical distribution of patent citations in selected sectors

Nation Within the region

Towards contiguous

regions

Within the nation

Towards other

countriesTotal

Average distance of

citations, Km

1990Footwear 32.7 9.5 3.4 54.4 100.0 339Machinery 28.3 8.8 15.3 47.7 100.0 542Computing, office 31.7 7.0 15.2 46.1 100.0 549Total citations 28.6 9.3 15.4 46.7 100.0 516

1998Footwear 47.5 9.2 10.8 32.5 100.0 290Machinery 23.8 9.1 16.6 50.5 100.0 573Computing, office 22.2 8.1 16.7 52.9 100.0 625Total citations 21.9 9.7 16.2 52.1 100.0 570

The main hypothesis to test is if knowledge linkages are localized in space and therefore if geographical distance and spatial contiguity influence knowledge flows across regions.

Moreover, the use of a set of national and regional dummies allows to control for other potential influences coming from institutional and cultural differences specific either to the country or to the local area.

The basic model

Dependent variable: patent citations (C) Knowledge flows are proxied by the number of citations between each couple of the 175 European regions considered.

175x175 matrix where the generic element Cij is the number of

citations originated from patents granted by EPO to inventors resident in the citing region i and directed to patents granted by EPO to inventors resident in the cited region j.

Geographical distance (GD)

175x175 matrix, the generic element GDij represents the

distance in hundreds of kilometers between the centroids of the citing region i and the cited region j.

Hypothesis:a higher distance has a negative impact on the strength of knowledge spillovers.

Explanatory variables

Dummy Contiguity (DC)

175x175 dummy matrix, the generic element takes value one where citing and receiving regions share a border (even in different countries) and 0 otherwise

Hypothesis:

knowledge flows are facilitated by physical proximity between regions which share a common border, irrespective of distance in kilometers (already included in GD). Positive impact

Dummy Nation (DN)175x175 dummy matrix, the generic element is equal to 1 if the citing region i and the cited one j belong to the same nation, or equal to 0 elsewhere

Hypothesis: knowledge flows take place more frequently among regions located in the same nation: exchanges are facilitated by language, cultural, institutional homogeneity. Positive impact.

Dummy Region (DR) A set of 175 fixed effects for each region i is included to allow for idiosyncratic aspects not appropriately measured by the other explanatory variables, it implies that the model is estimated with the Least Squares Dummy Variable (LSDV) method

The estimated basic model

Cij = 1 GDij + 2 DCij + 3 DNij + iDRi + ij

Estimation method: LSDV

Two periods: 1990 and 1998

To reduce the problem of firms self-citations, we exclude the observations within the same region (exclude i = j )(Maurseth and Verspagen, 2002)

Total number of observations: 30450

Table 8. Determinants of knowledge flows at the aggregate level

1990 1998

Geographical Distance (GDij) -1.252 -1.349(0.105)*** (0.089)***

Dummy Contiguity (DCij) 0.835 0.735(0.048)*** (0.040)***

Dummy Nation (DNij) 0.290 0.269(0.026)*** (0.022)***

Dummies 175 Regions (DRi) yes yes

Adj. R2 0.14 0.16

Extensions to the basic model: robustness checks

• Estimation methods: Poisson • Intra regional citations (include i = j )• Structural distance (SD)• Economic distance (ED) • Technological effort (TE)• General specification

Robustness /1 Estimation methods: Poisson

Poisson estimation may be helpful to ensure a control for the presence of zeros in the knowledge exchange matrix, i.e. pair of regions without citation flows.

Reg 1 Reg 2Estimation year 1990 1998Number of observations 30450 30450Estimation method Poisson with f.e. Poisson with f.e.

Geographical Distance (GDij) -0,953 -1,008

(0.021)*** (0.021)***

Dummy Contiguity (DCij) 0,536 0,449(0.034)*** (0.034)***

Dummy Nation (DNij) 0,304 0,197(0.027)*** (0.026)***

Robustness /2 Intra regional citations

Consider citations originated and received by the same regions.Problem: it may also include some intra firm citations. Include also a dummy “within region” (DW) which controls for i = j

Reg 3 Reg 4Estimation year 1990 1998Number of observations 30625 30625Estimation method random eff. random eff.

Geographical Distance (GDij) -0,852 -1,013(0.313)*** (0.221)***



Dummy Within region (DWij) 20,4 14,0(0.287)*** (0.201)***

Adj. R2 0,18 0,19

Robustness /3 Structural distance (SD)

Hypothesis: knowledge flows occur with greater intensity between regions with comparable production structure since exchanges are easier within similar sectors.

175x175 matrix: the generic element SDij is :

Pij measures the similarity between i and j (correlation index) fik represents region i share in sector k with respect to the total (measured in terms of patents)

The index ranges between: 0 (identical sectoral structure between the two regions) 1 (the production structures are orthogonal)

K

kjk

K

kik

K

kjkik

ijij

ff

ffPSD

1

2

1

2

1

(11

Robustness /3 Structural distance (SD)

Reg 5 Reg 6Estimation year 1990 1998Number of observations 30450 30450Estimation method fixed eff. fixed eff.




Structural Distance (SDij) -0,445 -0,389(0.046)*** (0.039)***

Adj. R2 0,14 0,17

Robustness /4 Economic distance (ED)

Hypothesis: more knowledge exchanges happen among regions which are closer in terms of economic conditions.

175x175 matrix: the generic element EDij is computed as the absolute difference in GDP over population between the origin and the destination region:

EDij = (GDP / POP)i – (GDP / POP)j

Robustness /4 Economic distance (ED)Reg 7 Reg 8

Estimation year 1990 1998Number of observations 30450 30450Estimation method fixed eff. fixed eff.




Economic Distance (EDij) -0,006 -0,005(0.001)*** (0.000)***

Adj. R2 0,14 0,16

Robustness /5 Technological effort (TE)

Hypothesis: more knowledge exchanges happen among regions which are characterised by a larger amount of resources allocated to technological activity

Include two vectors calculated as the shares of R&D expenditure over GDP both in the origin region i and in the destination region j:

TDi = (R&D / GDP)i TDj = (R&D / GDP)j

Robustness /5 Technological effort (TE)Reg 9 Reg 10

Estimation year 1990 1998Number of observations 30450 30450Estimation method random eff. random eff.




Technological effort origin (TEi) 0,153 0,214

(0.018)*** (0.025)***

Technological effort destination (TEj) 0,160 0,222(0.004)*** (0.006)***

Adj. R2 0,17 0,20

The general specificationCij = 1 GDij + 2 DCij + 3 DNij + 4 SDij + 5 EDij + 6 TEi + 7 TEj + i DRi + ij

Reg 11 Reg 12Estimation year 1990 1998Number of observations 30450 30450Estimation method random eff. random eff.




Structural Distance (SDij) -0,218 -0,205(0.045)*** (0.038)***

Economic Distance (EDij) -0,009 -0,005(0.001)*** (0.000)***

Technological effort origin (TEi) 0,153 0,211(0.018)*** (0.025)***

Technological effort destination (TEj) 0,161 0,219(0.004)*** (0.006)***

Adj. R2 0,17 0,20

• Knowledge flows are bounded in space and characterized by a spatial declining effect (due to spatial transaction costs in knowledge exchange).

• Flows between neighboring regions are higher.

• Flows are more likely when the two regions belong to the same country; national borders constitute an obstacle to knowledge leakages, the national systems of innovation still play a role with respect to a unified European system.

• The diffusion of technological spillovers is improved when the origin and destination regions are similar in terms of production/technological structure and economic conditions and allocate more resources to innovative activities.

• The importance of such effects is changing along time

Summary results

Future work

• Integrate the sample of citations with data provided by OECD

• Analysis of spatial dependence with spatial econometric techniques

• Focus on the industrial dimension (traditional vs high- tech)

• Deeper analysis of technological networks among firms and inventors in specific industries

Documents

Knowledge flows across European regions