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- Work in Progress - Inventor mobility and regions' innovation potential Riccardo Cappelli, U Insubria Dirk Czarnitzki, K.U.Leuven and ZEW Mannheim Thorsten Doherr, ZEW Mannheim Fabio Montobbio, U Insubria and Bocconi. Introduction.

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- Work in Progress -Inventor mobility and regions' innovation potential Riccardo Cappelli, U InsubriaDirk Czarnitzki, K.U.Leuven and ZEW MannheimThorsten Doherr, ZEW MannheimFabio Montobbio, U Insubria and Bocconi

  • In knowledge-based economies, human capital and innovation are usually seen as key driver of wealth and growth
    • „new growth theory“, see e.g. Aghion and co-authors
  • How to measure „knowledge“ that is present in an economy or region?
  • To what extent does knowledge contribute to growth?
technology gap models
„Technology gap models“

Technology gapmodelsattempttoexplaingrowth (or „catching-up) in income per capita in economiesorregionsby

  • changes in knowledgestocksorinnovation(see e.g. Fagerberg, 1994 in JEL for an overview)
  • and othercommoncontrols, e.g.
    • Laggedincome per capita
    • investmentintophysicalassets (change in stock ofphysicalassets)
    • Size oftheregionoreconomy (usuallymeasuredbypopulation)
technology gap models1
Technology gap models


  • Scholarshaveused R&D expendituretoproxythechange in knowledgestocksofregions
    • e.g. Verspagen and Fagerberg, 2002, Research Policy
  • Latersubstitutedoraugmentedby patent applications
    • Patents measureinventions but not innovations
    • Patents couldgenerate a premium astheyapproximate „successful R&D“ or „valuableknowledge“ to a certainextent
  • As thevaluedistributionofpatentsisveryskewed, scholarshave also usedforwardcitationsasproxyfor patent value
    • Trajtenberg1990, Hall et al., 2005
measuring knowledge continued
Measuring knowledge continued
  • Knowledge spillovers at both macro and micro level are important to explain the relative growth performance
    • Grossman and Helpman, 1991; Griliches, 1992
  • Knowledge Spillovers are geographically localized
    • Jaffe et al., 1993; Bottazzi and Peri, 2003; Maruseth and Verspagen, 2002; Peri, 2005
  • There are some factors that can explain the geographically localized diffusion of knowledge:
    • importance of face-to-face contacts to spread tacit knowledge
    • labor market (Almeida and Kogut, 1999)
    • inventor mobility and co-invention networks (Breschi and Lissoni, 2009)
measuring knowledge spillovers
Measuring knowledge spillovers
  • Frequently, scholars have tried to control for knowledge spillovers“ using patent citations
  • Justified in US studies, as USPTO applies „duty of candor“
    • Patentees have to cite all relevant prior art in the patent applications
  • At EPO, however, most citations are added by examiners
    • Citations as measure of knowledge flows and thus value of knowledge are questionable
    • Patentee might not have been aware of existing knowledge during the inventive process
our approach
Our approach
  • Knowledgeisembedeed in people
  • Thus, inventormobilityis a moredirectmeasureofknowledgeflows
  • Challenge: howtomeasureinventormobility(see e.g. Trajtenberg‘s NBER WP „The namegame“)
    • Name homonyms
    • Spellingvariations and so forth

 Ourapproach:inventormobilityindexthathas just beenpresentedby Thorsten.

  • 20 Italian regions from 1995 to 2007
  • Dependent variable: %-growth of GDP per capita
  • Variables based on the inventor mobility index:
    • Intra-regional: inventor that „change jobs“ (switch applicants) within the same region.
    • Inter-regional inflow: incomnig inventors that change jobs and move to region i from a different region.
    • Inter-regional outflow: inventors formerly employed in region i that now move to a new job in a different region.
    • Inter-regional net inflow: difference between inflow and outflow.
    • all mobility figures enter regions as ratio: mobility relative to stock of inventors in t-1 (derived by the perpetual inventory method with 15% of obsolescence rate)
      • (Stock is corrected for double counting of inventors)


  • GDP/Capita in previousperiod
  • Total R&D expenditure (public and private) per capita change in „knowledge stock“
  • Patent applications per capitaasproxyfor „successful R&D“ change in stock ofsuccessful R&D
  • Investment intophysicalcapital per capita in previousperiod (change in asset stock)

 both variables measured in million EUR in real terms(GDP deflator)

very preliminary conclusions
Very preliminary conclusions….
  • Inventor mobility appears to explain a change in GDP growth among Italian regions
  • To-Do:
    • Employ a revised version of the inventor mobility index
      • According to the new version of the algorithm there is more mobility among regions
    • Try to collect more data to enable controlling for region fixed-effects
    • Generate patent forward citations to control for heterogeneity in value of patents
      • More recent patent data required
    • Try to handle potential endogeneity of measures such as R&D, patenting and inventor mobility.