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  1. 1. Introduction and Literature Data and Methods Results Conclusion and Policy Implications Spillover Diffusion, Agglomeration and Distance a Spatial Extension of the Knowledge Production Function Approach Giovanni Guastella1 1 MSc in Economics and Geography Utrecht University Thesis Dissertation, July 2010 Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  2. 2. Introduction and Literature Data and Methods Results Conclusion and Policy Implications Motivation NGT (Romer [20], Lucas [13]) stresses the role of knowledge spillovers as source of increasing returns (IR). Altough IR are likely to cause divergence, it is argued that spillovers diffusion may also contribute to convergence, depending on the degree of localization of these externalities (Grossman and Helpman [8]). One problem ... If one one side knowledge cannot be contained within walls, on the other side it is not accessible from everywhere and everyone. Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  3. 3. Introduction and Literature Data and Methods Results Conclusion and Policy Implications Motivation NGT (Romer [20], Lucas [13]) stresses the role of knowledge spillovers as source of increasing returns (IR). Altough IR are likely to cause divergence, it is argued that spillovers diffusion may also contribute to convergence, depending on the degree of localization of these externalities (Grossman and Helpman [8]). One problem ... If one one side knowledge cannot be contained within walls, on the other side it is not accessible from everywhere and everyone. Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  4. 4. Introduction and Literature Data and Methods Results Conclusion and Policy Implications Motivation NGT (Romer [20], Lucas [13]) stresses the role of knowledge spillovers as source of increasing returns (IR). Altough IR are likely to cause divergence, it is argued that spillovers diffusion may also contribute to convergence, depending on the degree of localization of these externalities (Grossman and Helpman [8]). One problem ... If one one side knowledge cannot be contained within walls, on the other side it is not accessible from everywhere and everyone. Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  5. 5. Introduction and Literature Data and Methods Results Conclusion and Policy Implications Motivation ... and another problem Altough the literature on innovavation and geography (Audretsch and Feldman [2]) suggests that spillovers are higher in agglomerated areas and the intensity decreases with distance, it is not easy to establish a direct link between geography, agglomeration and spillover diffusion. This paper attempts to study the way geography, agglomeration and spillovers cause innovative activities. Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  6. 6. Introduction and Literature Data and Methods Results Conclusion and Policy Implications Outline 1 Introduction and Literature Introduction Economic Theories, Agglomeration and Spillovers Previous Findings Research Hypothesis 2 Data and Methods The model A Regional Innovation dataset 3 Results Basic Results Spatial lag Spatial lag and Spatial Regimes 4 Conclusion and Policy Implications Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  7. 7. Introduction and Literature Data and Methods Results Conclusion and Policy Implications Outline 1 Introduction and Literature Introduction Economic Theories, Agglomeration and Spillovers Previous Findings Research Hypothesis 2 Data and Methods The model A Regional Innovation dataset 3 Results Basic Results Spatial lag Spatial lag and Spatial Regimes 4 Conclusion and Policy Implications Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  8. 8. Introduction and Literature Data and Methods Results Conclusion and Policy Implications Outline 1 Introduction and Literature Introduction Economic Theories, Agglomeration and Spillovers Previous Findings Research Hypothesis 2 Data and Methods The model A Regional Innovation dataset 3 Results Basic Results Spatial lag Spatial lag and Spatial Regimes 4 Conclusion and Policy Implications Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  9. 9. Introduction and Literature Data and Methods Results Conclusion and Policy Implications Outline 1 Introduction and Literature Introduction Economic Theories, Agglomeration and Spillovers Previous Findings Research Hypothesis 2 Data and Methods The model A Regional Innovation dataset 3 Results Basic Results Spatial lag Spatial lag and Spatial Regimes 4 Conclusion and Policy Implications Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  10. 10. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis Outline 1 Introduction and Literature Introduction Economic Theories, Agglomeration and Spillovers Previous Findings Research Hypothesis 2 Data and Methods The model A Regional Innovation dataset 3 Results Basic Results Spatial lag Spatial lag and Spatial Regimes 4 Conclusion and Policy Implications Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  11. 11. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis How do spillovers fit in economic theories There is no doubt that spillovers determine increasing returns, and this idea is maintained also in this work. What is diffuclt is to define and identify spillovers. Mainstream view: knowledge is a public good accessible from everyone. Social returns from innovative investments are higher than private ones. Evolutionary view: there are geographical, social and cultural barriers to knowledge flows. Physical and technological distances are considered among the most important obstacles to spillover diffusion. Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  12. 12. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis How do spillovers fit in economic theories There is no doubt that spillovers determine increasing returns, and this idea is maintained also in this work. What is diffuclt is to define and identify spillovers. Mainstream view: knowledge is a public good accessible from everyone. Social returns from innovative investments are higher than private ones. Evolutionary view: there are geographical, social and cultural barriers to knowledge flows. Physical and technological distances are considered among the most important obstacles to spillover diffusion. Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  13. 13. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis How do spillovers fit in economic theories There is no doubt that spillovers determine increasing returns, and this idea is maintained also in this work. What is diffuclt is to define and identify spillovers. Mainstream view: knowledge is a public good accessible from everyone. Social returns from innovative investments are higher than private ones. Evolutionary view: there are geographical, social and cultural barriers to knowledge flows. Physical and technological distances are considered among the most important obstacles to spillover diffusion. Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  14. 14. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis Definition of spillovers knowledge cannot be entirely codified (explicit vs tacit) knowledge transfer is costly Distance is important because it allows face-to-face contacts it reduces costs of transmission physical distance, cognitive distance, institutional distance, ... ... far more complex than NGT models would predict Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  15. 15. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis Definition of spillovers knowledge cannot be entirely codified (explicit vs tacit) knowledge transfer is costly Distance is important because it allows face-to-face contacts it reduces costs of transmission physical distance, cognitive distance, institutional distance, ... ... far more complex than NGT models would predict Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  16. 16. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis Definition of spillovers knowledge cannot be entirely codified (explicit vs tacit) knowledge transfer is costly Distance is important because it allows face-to-face contacts it reduces costs of transmission physical distance, cognitive distance, institutional distance, ... ... far more complex than NGT models would predict Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  17. 17. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis Definition of spillovers knowledge cannot be entirely codified (explicit vs tacit) knowledge transfer is costly Distance is important because it allows face-to-face contacts it reduces costs of transmission physical distance, cognitive distance, institutional distance, ... ... far more complex than NGT models would predict Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  18. 18. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis Definition of spillovers knowledge cannot be entirely codified (explicit vs tacit) knowledge transfer is costly Distance is important because it allows face-to-face contacts it reduces costs of transmission physical distance, cognitive distance, institutional distance, ... ... far more complex than NGT models would predict Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  19. 19. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis Definition of spillovers knowledge cannot be entirely codified (explicit vs tacit) knowledge transfer is costly Distance is important because it allows face-to-face contacts it reduces costs of transmission physical distance, cognitive distance, institutional distance, ... ... far more complex than NGT models would predict Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  20. 20. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis Definition of spillovers knowledge cannot be entirely codified (explicit vs tacit) knowledge transfer is costly Distance is important because it allows face-to-face contacts it reduces costs of transmission physical distance, cognitive distance, institutional distance, ... ... far more complex than NGT models would predict Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  21. 21. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis Definition of spillovers knowledge cannot be entirely codified (explicit vs tacit) knowledge transfer is costly Distance is important because it allows face-to-face contacts it reduces costs of transmission physical distance, cognitive distance, institutional distance, ... ... far more complex than NGT models would predict Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  22. 22. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis Outline 1 Introduction and Literature Introduction Economic Theories, Agglomeration and Spillovers Previous Findings Research Hypothesis 2 Data and Methods The model A Regional Innovation dataset 3 Results Basic Results Spatial lag Spatial lag and Spatial Regimes 4 Conclusion and Policy Implications Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  23. 23. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis The KPF Approach (Griliches, [7]) More efforts we put, more output we get Ii = f (X1i , X2i , ..., Xni ) (1) Empirical evidences are stronger at aggregate level Localized Knowledge Spillovers Labor mobility Entrepreneurship and spin-off Inter-firms collaborations Pure vs pecuniary externalities? ...what standard methodologies [...] suggest to be pure externalities, will turn out to be, at a more careful scrutiny, knowledge flows that are mediated by market mechanisms... Breschi and Lissoni [5] Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  24. 24. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis The KPF Approach (Griliches, [7]) More efforts we put, more output we get Ii = f (X1i , X2i , ..., Xni ) (1) Empirical evidences are stronger at aggregate level Localized Knowledge Spillovers Labor mobility Entrepreneurship and spin-off Inter-firms collaborations Pure vs pecuniary externalities? ...what standard methodologies [...] suggest to be pure externalities, will turn out to be, at a more careful scrutiny, knowledge flows that are mediated by market mechanisms... Breschi and Lissoni [5] Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  25. 25. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis The KPF Approach (Griliches, [7]) More efforts we put, more output we get Ii = f (X1i , X2i , ..., Xni ) (1) Empirical evidences are stronger at aggregate level Localized Knowledge Spillovers Labor mobility Entrepreneurship and spin-off Inter-firms collaborations Pure vs pecuniary externalities? ...what standard methodologies [...] suggest to be pure externalities, will turn out to be, at a more careful scrutiny, knowledge flows that are mediated by market mechanisms... Breschi and Lissoni [5] Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  26. 26. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis The KPF Approach (Griliches, [7]) More efforts we put, more output we get Ii = f (X1i , X2i , ..., Xni ) (1) Empirical evidences are stronger at aggregate level Localized Knowledge Spillovers Labor mobility Entrepreneurship and spin-off Inter-firms collaborations Pure vs pecuniary externalities? ...what standard methodologies [...] suggest to be pure externalities, will turn out to be, at a more careful scrutiny, knowledge flows that are mediated by market mechanisms... Breschi and Lissoni [5] Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  27. 27. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis The KPF Approach (Griliches, [7]) More efforts we put, more output we get Ii = f (X1i , X2i , ..., Xni ) (1) Empirical evidences are stronger at aggregate level Localized Knowledge Spillovers Labor mobility Entrepreneurship and spin-off Inter-firms collaborations Pure vs pecuniary externalities? ...what standard methodologies [...] suggest to be pure externalities, will turn out to be, at a more careful scrutiny, knowledge flows that are mediated by market mechanisms... Breschi and Lissoni [5] Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  28. 28. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis The KPF Approach (Griliches, [7]) More efforts we put, more output we get Ii = f (X1i , X2i , ..., Xni ) (1) Empirical evidences are stronger at aggregate level Localized Knowledge Spillovers Labor mobility Entrepreneurship and spin-off Inter-firms collaborations Pure vs pecuniary externalities? ...what standard methodologies [...] suggest to be pure externalities, will turn out to be, at a more careful scrutiny, knowledge flows that are mediated by market mechanisms... Breschi and Lissoni [5] Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  29. 29. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis The KPF Approach (Griliches, [7]) More efforts we put, more output we get Ii = f (X1i , X2i , ..., Xni ) (1) Empirical evidences are stronger at aggregate level Localized Knowledge Spillovers Labor mobility Entrepreneurship and spin-off Inter-firms collaborations Pure vs pecuniary externalities? ...what standard methodologies [...] suggest to be pure externalities, will turn out to be, at a more careful scrutiny, knowledge flows that are mediated by market mechanisms... Breschi and Lissoni [5] Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  30. 30. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis Agglomeration and spillovers Concentration of knowledge sources pushes the creation of new knowledge (Jaffe, [11]) Geography is still a Black Box (Distance is Exogenous!!!) However... Externalities have not only positive effects congestion costs spatial and cognitive lock-in What we define agglomeration economies is ... Marshall’s specialization [14] Porter’s competition [19] Jacob’s diversity [10] Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  31. 31. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis Agglomeration and spillovers Concentration of knowledge sources pushes the creation of new knowledge (Jaffe, [11]) Geography is still a Black Box (Distance is Exogenous!!!) However... Externalities have not only positive effects congestion costs spatial and cognitive lock-in What we define agglomeration economies is ... Marshall’s specialization [14] Porter’s competition [19] Jacob’s diversity [10] Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  32. 32. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis Agglomeration and spillovers Concentration of knowledge sources pushes the creation of new knowledge (Jaffe, [11]) Geography is still a Black Box (Distance is Exogenous!!!) However... Externalities have not only positive effects congestion costs spatial and cognitive lock-in What we define agglomeration economies is ... Marshall’s specialization [14] Porter’s competition [19] Jacob’s diversity [10] Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  33. 33. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis Agglomeration and spillovers Concentration of knowledge sources pushes the creation of new knowledge (Jaffe, [11]) Geography is still a Black Box (Distance is Exogenous!!!) However... Externalities have not only positive effects congestion costs spatial and cognitive lock-in What we define agglomeration economies is ... Marshall’s specialization [14] Porter’s competition [19] Jacob’s diversity [10] Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  34. 34. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis Agglomeration and spillovers Concentration of knowledge sources pushes the creation of new knowledge (Jaffe, [11]) Geography is still a Black Box (Distance is Exogenous!!!) However... Externalities have not only positive effects congestion costs spatial and cognitive lock-in What we define agglomeration economies is ... Marshall’s specialization [14] Porter’s competition [19] Jacob’s diversity [10] Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  35. 35. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis Agglomeration and spillovers Concentration of knowledge sources pushes the creation of new knowledge (Jaffe, [11]) Geography is still a Black Box (Distance is Exogenous!!!) However... Externalities have not only positive effects congestion costs spatial and cognitive lock-in What we define agglomeration economies is ... Marshall’s specialization [14] Porter’s competition [19] Jacob’s diversity [10] Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  36. 36. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis Agglomeration and spillovers Concentration of knowledge sources pushes the creation of new knowledge (Jaffe, [11]) Geography is still a Black Box (Distance is Exogenous!!!) However... Externalities have not only positive effects congestion costs spatial and cognitive lock-in What we define agglomeration economies is ... Marshall’s specialization [14] Porter’s competition [19] Jacob’s diversity [10] Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  37. 37. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis Agglomeration and spillovers Concentration of knowledge sources pushes the creation of new knowledge (Jaffe, [11]) Geography is still a Black Box (Distance is Exogenous!!!) However... Externalities have not only positive effects congestion costs spatial and cognitive lock-in What we define agglomeration economies is ... Marshall’s specialization [14] Porter’s competition [19] Jacob’s diversity [10] Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  38. 38. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis Agglomeration and spillovers Concentration of knowledge sources pushes the creation of new knowledge (Jaffe, [11]) Geography is still a Black Box (Distance is Exogenous!!!) However... Externalities have not only positive effects congestion costs spatial and cognitive lock-in What we define agglomeration economies is ... Marshall’s specialization [14] Porter’s competition [19] Jacob’s diversity [10] Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  39. 39. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis Agglomeration and spillovers Concentration of knowledge sources pushes the creation of new knowledge (Jaffe, [11]) Geography is still a Black Box (Distance is Exogenous!!!) However... Externalities have not only positive effects congestion costs spatial and cognitive lock-in What we define agglomeration economies is ... Marshall’s specialization [14] Porter’s competition [19] Jacob’s diversity [10] Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  40. 40. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis Outline 1 Introduction and Literature Introduction Economic Theories, Agglomeration and Spillovers Previous Findings Research Hypothesis 2 Data and Methods The model A Regional Innovation dataset 3 Results Basic Results Spatial lag Spatial lag and Spatial Regimes 4 Conclusion and Policy Implications Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  41. 41. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis At industry-aggregate level Use of WR&D to proxy spatial spillovers elasticity to external R&D is about .07 (.04 to .11) and spatial spillovers are more important of technological ones (Bottazzi and Peri, [3]) elasticity to external R&D is about .025 and spillovers are bounded within 300 km (Bottazzi and Peri, [4]) elasticity to external R&D is about .04; sipllover are bounded within 176 miles and there are no spillovers among technological neighbors (Greunz, [6]) the majority of spillovers are confined within regional borders and, in any case, within 350 km from the origin region (Moreno et al., [16]) Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  42. 42. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis At industry-aggregate level Use of WR&D to proxy spatial spillovers elasticity to external R&D is about .07 (.04 to .11) and spatial spillovers are more important of technological ones (Bottazzi and Peri, [3]) elasticity to external R&D is about .025 and spillovers are bounded within 300 km (Bottazzi and Peri, [4]) elasticity to external R&D is about .04; sipllover are bounded within 176 miles and there are no spillovers among technological neighbors (Greunz, [6]) the majority of spillovers are confined within regional borders and, in any case, within 350 km from the origin region (Moreno et al., [16]) Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  43. 43. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis At industry-aggregate level Use of WR&D to proxy spatial spillovers elasticity to external R&D is about .07 (.04 to .11) and spatial spillovers are more important of technological ones (Bottazzi and Peri, [3]) elasticity to external R&D is about .025 and spillovers are bounded within 300 km (Bottazzi and Peri, [4]) elasticity to external R&D is about .04; sipllover are bounded within 176 miles and there are no spillovers among technological neighbors (Greunz, [6]) the majority of spillovers are confined within regional borders and, in any case, within 350 km from the origin region (Moreno et al., [16]) Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  44. 44. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis At industry-aggregate level Use of WR&D to proxy spatial spillovers elasticity to external R&D is about .07 (.04 to .11) and spatial spillovers are more important of technological ones (Bottazzi and Peri, [3]) elasticity to external R&D is about .025 and spillovers are bounded within 300 km (Bottazzi and Peri, [4]) elasticity to external R&D is about .04; sipllover are bounded within 176 miles and there are no spillovers among technological neighbors (Greunz, [6]) the majority of spillovers are confined within regional borders and, in any case, within 350 km from the origin region (Moreno et al., [16]) Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  45. 45. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis At industry-specific level concentration of economic activities vary across industries, industrial specialization has positive effects and spillovers happen between regions specialized in similar industries (Moreno et al.,[15] positive interregional spillovers and positive effect of specialization (no diversity) Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  46. 46. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis At industry-specific level concentration of economic activities vary across industries, industrial specialization has positive effects and spillovers happen between regions specialized in similar industries (Moreno et al.,[15] positive interregional spillovers and positive effect of specialization (no diversity) Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  47. 47. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis Outline 1 Introduction and Literature Introduction Economic Theories, Agglomeration and Spillovers Previous Findings Research Hypothesis 2 Data and Methods The model A Regional Innovation dataset 3 Results Basic Results Spatial lag Spatial lag and Spatial Regimes 4 Conclusion and Policy Implications Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  48. 48. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis My contribution Enlarged geographical scope - 250 NUTS II regions Explicit role for geography (agglomeration, specialization, competition and diversity) Industry-specific analysis (13 manufacturing industries) Interregional and inter-industry spillovers Differentiation among different regimes based on Human Geography Physical Geography Economic Geography Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  49. 49. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis My contribution Enlarged geographical scope - 250 NUTS II regions Explicit role for geography (agglomeration, specialization, competition and diversity) Industry-specific analysis (13 manufacturing industries) Interregional and inter-industry spillovers Differentiation among different regimes based on Human Geography Physical Geography Economic Geography Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  50. 50. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis My contribution Enlarged geographical scope - 250 NUTS II regions Explicit role for geography (agglomeration, specialization, competition and diversity) Industry-specific analysis (13 manufacturing industries) Interregional and inter-industry spillovers Differentiation among different regimes based on Human Geography Physical Geography Economic Geography Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  51. 51. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis My contribution Enlarged geographical scope - 250 NUTS II regions Explicit role for geography (agglomeration, specialization, competition and diversity) Industry-specific analysis (13 manufacturing industries) Interregional and inter-industry spillovers Differentiation among different regimes based on Human Geography Physical Geography Economic Geography Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  52. 52. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis My contribution Enlarged geographical scope - 250 NUTS II regions Explicit role for geography (agglomeration, specialization, competition and diversity) Industry-specific analysis (13 manufacturing industries) Interregional and inter-industry spillovers Differentiation among different regimes based on Human Geography Physical Geography Economic Geography Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  53. 53. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis My contribution Enlarged geographical scope - 250 NUTS II regions Explicit role for geography (agglomeration, specialization, competition and diversity) Industry-specific analysis (13 manufacturing industries) Interregional and inter-industry spillovers Differentiation among different regimes based on Human Geography Physical Geography Economic Geography Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  54. 54. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis My contribution Enlarged geographical scope - 250 NUTS II regions Explicit role for geography (agglomeration, specialization, competition and diversity) Industry-specific analysis (13 manufacturing industries) Interregional and inter-industry spillovers Differentiation among different regimes based on Human Geography Physical Geography Economic Geography Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  55. 55. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis My contribution Enlarged geographical scope - 250 NUTS II regions Explicit role for geography (agglomeration, specialization, competition and diversity) Industry-specific analysis (13 manufacturing industries) Interregional and inter-industry spillovers Differentiation among different regimes based on Human Geography Physical Geography Economic Geography Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  56. 56. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis My contribution Main idea: use aggregate data to find stronger evidence of spillover My idea: split as much a possible to find evidence of pure spillovers and separate R&D spillovers from other externalities Externality Positive Effect Negative Effect Interreg within industry spillovers industrial competition among regions Inter-ind between industries spillovers regional competition amond industries Agg market potential ongestion costs Spec labor market pooling and low cognitive distance cognitive lock-in Comp more incentives to innovate big firms invest more in research Div cross-industry knowledge exchange too much cognitive distance Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  57. 57. Introduction and Literature Introduction Data and Methods Economic Theories, Agglomeration and Spillovers Results Previous Findings Conclusion and Policy Implications Research Hypothesis My contribution Main idea: use aggregate data to find stronger evidence of spillover My idea: split as much a possible to find evidence of pure spillovers and separate R&D spillovers from other externalities Externality Positive Effect Negative Effect Interreg within industry spillovers industrial competition among regions Inter-ind between industries spillovers regional competition amond industries Agg market potential ongestion costs Spec labor market pooling and low cognitive distance cognitive lock-in Comp more incentives to innovate big firms invest more in research Div cross-industry knowledge exchange too much cognitive distance Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  58. 58. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Outline 1 Introduction and Literature Introduction Economic Theories, Agglomeration and Spillovers Previous Findings Research Hypothesis 2 Data and Methods The model A Regional Innovation dataset 3 Results Basic Results Spatial lag Spatial lag and Spatial Regimes 4 Conclusion and Policy Implications Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  59. 59. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Model specification and assumptions Iij =α0 + α1 R&Dij + α2 UNIi + α3 GOVi + β1 WR&Dij + β2 R&Di,k=j + (2) γ1 AGGi + γ2 SPECij + γ3 COMPij + γ4 DIVi + εi α1 to α3 : home made investments by firms, universities and governments β1 : interregional spillovers β2 : interindustry spillovers γ1 to γ4 : externalities Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  60. 60. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Model specification and assumptions Iij =α0 + α1 R&Dij + α2 UNIi + α3 GOVi + β1 WR&Dij + β2 R&Di,k=j + (2) γ1 AGGi + γ2 SPECij + γ3 COMPij + γ4 DIVi + εi α1 to α3 : home made investments by firms, universities and governments β1 : interregional spillovers β2 : interindustry spillovers γ1 to γ4 : externalities Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  61. 61. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Model specification and assumptions Iij =α0 + α1 R&Dij + α2 UNIi + α3 GOVi + β1 WR&Dij + β2 R&Di,k=j + (2) γ1 AGGi + γ2 SPECij + γ3 COMPij + γ4 DIVi + εi α1 to α3 : home made investments by firms, universities and governments β1 : interregional spillovers β2 : interindustry spillovers γ1 to γ4 : externalities Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  62. 62. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Model specification and assumptions Iij =α0 + α1 R&Dij + α2 UNIi + α3 GOVi + β1 WR&Dij + β2 R&Di,k=j + (2) γ1 AGGi + γ2 SPECij + γ3 COMPij + γ4 DIVi + εi α1 to α3 : home made investments by firms, universities and governments β1 : interregional spillovers β2 : interindustry spillovers γ1 to γ4 : externalities Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  63. 63. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Measuring issues POPi AGGi = Areai R&Dij j R&Dij SPECij = / i R&Dij i j R&Dij FIRMSij COMPij = EMPLOYEESij 2 1 DIVi = j R&Dij − J j R&Dij Choice of W Great circle distance. Which d? K -nearest neighbors. Which k? Physical contiguity. What about islands? Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  64. 64. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Measuring issues POPi AGGi = Areai R&Dij j R&Dij SPECij = / i R&Dij i j R&Dij FIRMSij COMPij = EMPLOYEESij 2 1 DIVi = j R&Dij − J j R&Dij Choice of W Great circle distance. Which d? K -nearest neighbors. Which k? Physical contiguity. What about islands? Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  65. 65. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Measuring issues POPi AGGi = Areai R&Dij j R&Dij SPECij = / i R&Dij i j R&Dij FIRMSij COMPij = EMPLOYEESij 2 1 DIVi = j R&Dij − J j R&Dij Choice of W Great circle distance. Which d? K -nearest neighbors. Which k? Physical contiguity. What about islands? Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  66. 66. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Measuring issues POPi AGGi = Areai R&Dij j R&Dij SPECij = / i R&Dij i j R&Dij FIRMSij COMPij = EMPLOYEESij 2 1 DIVi = j R&Dij − J j R&Dij Choice of W Great circle distance. Which d? K -nearest neighbors. Which k? Physical contiguity. What about islands? Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  67. 67. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Measuring issues POPi AGGi = Areai R&Dij j R&Dij SPECij = / i R&Dij i j R&Dij FIRMSij COMPij = EMPLOYEESij 2 1 DIVi = j R&Dij − J j R&Dij Choice of W Great circle distance. Which d? K -nearest neighbors. Which k? Physical contiguity. What about islands? Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  68. 68. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Measuring issues POPi AGGi = Areai R&Dij j R&Dij SPECij = / i R&Dij i j R&Dij FIRMSij COMPij = EMPLOYEESij 2 1 DIVi = j R&Dij − J j R&Dij Choice of W Great circle distance. Which d? K -nearest neighbors. Which k? Physical contiguity. What about islands? Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  69. 69. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Measuring issues POPi AGGi = Areai R&Dij j R&Dij SPECij = / i R&Dij i j R&Dij FIRMSij COMPij = EMPLOYEESij 2 1 DIVi = j R&Dij − J j R&Dij Choice of W Great circle distance. Which d? K -nearest neighbors. Which k? Physical contiguity. What about islands? Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  70. 70. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Measuring issues POPi AGGi = Areai R&Dij j R&Dij SPECij = / i R&Dij i j R&Dij FIRMSij COMPij = EMPLOYEESij 2 1 DIVi = j R&Dij − J j R&Dij Choice of W Great circle distance. Which d? K -nearest neighbors. Which k? Physical contiguity. What about islands? Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  71. 71. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Weighting spillovers Do spillover depend on the source? I made no differentiation of the source, meaning that all neighbors and all industries contribute with the same weight!!! Be care with the interpretation!!! Equal weight to all neighbors Equal weight to all industries Row standardization Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  72. 72. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Differentiating across regimes η = (α0 , α1 , α2 , α3 , β1 , β2 , γ1 , γ2 , γ3 , γ4 ) η = η1 AC + η2 AWC + η3 NAC + η4 NAWC η = η5 CORE + η6 INTER + η7 PERIP η = η8 NONLAG + η9 POTLAG + η10 LAG Source ESPON project (Copiright ESPON 2006 - http://www.espon.eu) Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  73. 73. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Differentiating across regimes η = (α0 , α1 , α2 , α3 , β1 , β2 , γ1 , γ2 , γ3 , γ4 ) η = η1 AC + η2 AWC + η3 NAC + η4 NAWC η = η5 CORE + η6 INTER + η7 PERIP η = η8 NONLAG + η9 POTLAG + η10 LAG Source ESPON project (Copiright ESPON 2006 - http://www.espon.eu) Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  74. 74. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Differentiating across regimes η = (α0 , α1 , α2 , α3 , β1 , β2 , γ1 , γ2 , γ3 , γ4 ) η = η1 AC + η2 AWC + η3 NAC + η4 NAWC η = η5 CORE + η6 INTER + η7 PERIP η = η8 NONLAG + η9 POTLAG + η10 LAG Source ESPON project (Copiright ESPON 2006 - http://www.espon.eu) Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  75. 75. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Outline 1 Introduction and Literature Introduction Economic Theories, Agglomeration and Spillovers Previous Findings Research Hypothesis 2 Data and Methods The model A Regional Innovation dataset 3 Results Basic Results Spatial lag Spatial lag and Spatial Regimes 4 Conclusion and Policy Implications Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  76. 76. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Patent counts as measure of regional innovation PA are not a good proxy for innovations PA underestimate innovation in small firms (Pakes and Griliches, [17]) Big firms tend to overpatenting innovations Patents do not reflect the economic value of innovation (Hall et al., [9]) Literature based measures better proxy real innovations (Pavitt et al., [18], Kleinknecht, [12]) All successfull innovations are considered Are costly to be produced Comparison depends on how data are collected Does it make the difference at aggregate level? NO!!! Acs et al., [1] provide evidence that in a KPF framework both measures lead to identical conclusions Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  77. 77. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Patent counts as measure of regional innovation PA are not a good proxy for innovations PA underestimate innovation in small firms (Pakes and Griliches, [17]) Big firms tend to overpatenting innovations Patents do not reflect the economic value of innovation (Hall et al., [9]) Literature based measures better proxy real innovations (Pavitt et al., [18], Kleinknecht, [12]) All successfull innovations are considered Are costly to be produced Comparison depends on how data are collected Does it make the difference at aggregate level? NO!!! Acs et al., [1] provide evidence that in a KPF framework both measures lead to identical conclusions Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  78. 78. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Patent counts as measure of regional innovation PA are not a good proxy for innovations PA underestimate innovation in small firms (Pakes and Griliches, [17]) Big firms tend to overpatenting innovations Patents do not reflect the economic value of innovation (Hall et al., [9]) Literature based measures better proxy real innovations (Pavitt et al., [18], Kleinknecht, [12]) All successfull innovations are considered Are costly to be produced Comparison depends on how data are collected Does it make the difference at aggregate level? NO!!! Acs et al., [1] provide evidence that in a KPF framework both measures lead to identical conclusions Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  79. 79. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Patent counts as measure of regional innovation PA are not a good proxy for innovations PA underestimate innovation in small firms (Pakes and Griliches, [17]) Big firms tend to overpatenting innovations Patents do not reflect the economic value of innovation (Hall et al., [9]) Literature based measures better proxy real innovations (Pavitt et al., [18], Kleinknecht, [12]) All successfull innovations are considered Are costly to be produced Comparison depends on how data are collected Does it make the difference at aggregate level? NO!!! Acs et al., [1] provide evidence that in a KPF framework both measures lead to identical conclusions Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  80. 80. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Patent counts as measure of regional innovation PA are not a good proxy for innovations PA underestimate innovation in small firms (Pakes and Griliches, [17]) Big firms tend to overpatenting innovations Patents do not reflect the economic value of innovation (Hall et al., [9]) Literature based measures better proxy real innovations (Pavitt et al., [18], Kleinknecht, [12]) All successfull innovations are considered Are costly to be produced Comparison depends on how data are collected Does it make the difference at aggregate level? NO!!! Acs et al., [1] provide evidence that in a KPF framework both measures lead to identical conclusions Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  81. 81. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Patent counts as measure of regional innovation PA are not a good proxy for innovations PA underestimate innovation in small firms (Pakes and Griliches, [17]) Big firms tend to overpatenting innovations Patents do not reflect the economic value of innovation (Hall et al., [9]) Literature based measures better proxy real innovations (Pavitt et al., [18], Kleinknecht, [12]) All successfull innovations are considered Are costly to be produced Comparison depends on how data are collected Does it make the difference at aggregate level? NO!!! Acs et al., [1] provide evidence that in a KPF framework both measures lead to identical conclusions Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  82. 82. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Patent counts as measure of regional innovation PA are not a good proxy for innovations PA underestimate innovation in small firms (Pakes and Griliches, [17]) Big firms tend to overpatenting innovations Patents do not reflect the economic value of innovation (Hall et al., [9]) Literature based measures better proxy real innovations (Pavitt et al., [18], Kleinknecht, [12]) All successfull innovations are considered Are costly to be produced Comparison depends on how data are collected Does it make the difference at aggregate level? NO!!! Acs et al., [1] provide evidence that in a KPF framework both measures lead to identical conclusions Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  83. 83. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Patent counts as measure of regional innovation PA are not a good proxy for innovations PA underestimate innovation in small firms (Pakes and Griliches, [17]) Big firms tend to overpatenting innovations Patents do not reflect the economic value of innovation (Hall et al., [9]) Literature based measures better proxy real innovations (Pavitt et al., [18], Kleinknecht, [12]) All successfull innovations are considered Are costly to be produced Comparison depends on how data are collected Does it make the difference at aggregate level? NO!!! Acs et al., [1] provide evidence that in a KPF framework both measures lead to identical conclusions Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  84. 84. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Patent counts as measure of regional innovation PA are not a good proxy for innovations PA underestimate innovation in small firms (Pakes and Griliches, [17]) Big firms tend to overpatenting innovations Patents do not reflect the economic value of innovation (Hall et al., [9]) Literature based measures better proxy real innovations (Pavitt et al., [18], Kleinknecht, [12]) All successfull innovations are considered Are costly to be produced Comparison depends on how data are collected Does it make the difference at aggregate level? NO!!! Acs et al., [1] provide evidence that in a KPF framework both measures lead to identical conclusions Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  85. 85. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications R&D data R&D data at regional industry-specific level are not available Regional data are derived from national levels using symplifying assumption R&Dij EMPij = (3) NAT − R&Dj NAT − EMPj NOTE!!! The share of R&D per worker is costant across regions in the same country for each industry Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  86. 86. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications R&D data R&D data at regional industry-specific level are not available Regional data are derived from national levels using symplifying assumption R&Dij EMPij = (3) NAT − R&Dj NAT − EMPj NOTE!!! The share of R&D per worker is costant across regions in the same country for each industry Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  87. 87. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications R&D data R&D data at regional industry-specific level are not available Regional data are derived from national levels using symplifying assumption R&Dij EMPij = (3) NAT − R&Dj NAT − EMPj NOTE!!! The share of R&D per worker is costant across regions in the same country for each industry Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  88. 88. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Reconciling SIC codes with IPC classes Schmoch et al., [21] provided a table to reconcile 4-digit IPC with SIC industries PA data are provided by Eurostat at 3-digit IPC class It may happen that one IPC code belongs to more than one SIC industries I counted the times every IPC appears in a SIC. The share of the count wrt total is the proportion of patents attributed to the SIC Industry SIC IPC Food DA: food A01 C12 C13 A21 A23 A24 Textile DB: textile D04 D06 A41 Leather DC: leather A43 B68 Wood DD: wood B27 E04 Paper DE:paper, pub. and print. B41 B42 B44 D21 Fuels DF: petroleum and nuclear fuel C10 G01 Chemical DG: chemicals A01 A61 A62 ... ... ... ... Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  89. 89. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Reconciling SIC codes with IPC classes Schmoch et al., [21] provided a table to reconcile 4-digit IPC with SIC industries PA data are provided by Eurostat at 3-digit IPC class It may happen that one IPC code belongs to more than one SIC industries I counted the times every IPC appears in a SIC. The share of the count wrt total is the proportion of patents attributed to the SIC Industry SIC IPC Food DA: food A01 C12 C13 A21 A23 A24 Textile DB: textile D04 D06 A41 Leather DC: leather A43 B68 Wood DD: wood B27 E04 Paper DE:paper, pub. and print. B41 B42 B44 D21 Fuels DF: petroleum and nuclear fuel C10 G01 Chemical DG: chemicals A01 A61 A62 ... ... ... ... Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  90. 90. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Reconciling SIC codes with IPC classes Schmoch et al., [21] provided a table to reconcile 4-digit IPC with SIC industries PA data are provided by Eurostat at 3-digit IPC class It may happen that one IPC code belongs to more than one SIC industries I counted the times every IPC appears in a SIC. The share of the count wrt total is the proportion of patents attributed to the SIC Industry SIC IPC Food DA: food A01 C12 C13 A21 A23 A24 Textile DB: textile D04 D06 A41 Leather DC: leather A43 B68 Wood DD: wood B27 E04 Paper DE:paper, pub. and print. B41 B42 B44 D21 Fuels DF: petroleum and nuclear fuel C10 G01 Chemical DG: chemicals A01 A61 A62 ... ... ... ... Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  91. 91. Introduction and Literature Data and Methods The model Results A Regional Innovation dataset Conclusion and Policy Implications Reconciling SIC codes with IPC classes Schmoch et al., [21] provided a table to reconcile 4-digit IPC with SIC industries PA data are provided by Eurostat at 3-digit IPC class It may happen that one IPC code belongs to more than one SIC industries I counted the times every IPC appears in a SIC. The share of the count wrt total is the proportion of patents attributed to the SIC Industry SIC IPC Food DA: food A01 C12 C13 A21 A23 A24 Textile DB: textile D04 D06 A41 Leather DC: leather A43 B68 Wood DD: wood B27 E04 Paper DE:paper, pub. and print. B41 B42 B44 D21 Fuels DF: petroleum and nuclear fuel C10 G01 Chemical DG: chemicals A01 A61 A62 ... ... ... ... Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  92. 92. Introduction and Literature Basic Results Data and Methods Spatial lag Results Spatial lag and Spatial Regimes Conclusion and Policy Implications Outline 1 Introduction and Literature Introduction Economic Theories, Agglomeration and Spillovers Previous Findings Research Hypothesis 2 Data and Methods The model A Regional Innovation dataset 3 Results Basic Results Spatial lag Spatial lag and Spatial Regimes 4 Conclusion and Policy Implications Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  93. 93. Introduction and Literature Basic Results Data and Methods Spatial lag Results Spatial lag and Spatial Regimes Conclusion and Policy Implications Basic model Food Textile Leather Wood Paper Fuels Chem Rubber Nonmet Metal Mach Elect Trans Int .097 .113 .038 .097 .065 .101 .032 .087 .113 .112 .091 .042 .047 (4.19) (7.70) (6.28) (5.31) (4.60) (7.05) (2.47) (3.96) (2.15) (6.44) (4.21) (3.09) (5.75) R&D .383 .599 .334 .215 .599 .230 .755 .740 1.089 .369 .770 .423 .416 (4.38) (8.02) (3.92) (1.24) (11.05) (1.53) (4.63) (6.67) (5.37) (4.58) (7.99) (7.76) (3.65) UNI .206 .017 .051 .013 -.088 .253 -.004 .094 .029 -.009 -.032 .025 .008 (1.80) (.32) (.88) (.11) (-1.64) (2.70) (-.08) (1.25) (.33) (-.18) (-.58) (.62) (.21) GOV .174 .012 -.014 .109 -.033 .174 .047 -.002 .006 -.031 .017 .059 -.024 (2.08) (.025) (-.27) (.74) (-.76) (1.86) (1.37) (-.03) (.09) (-.80) (.55) (1.88) (-.72) AGG -.069 .033 -.010 -.097 .031 -.220 .011 -.123 -.141 -.054 -.064 -.008 -.073 (-.38) (.42) (-.122) (-1.29) (.38) (-2.06) (.23) (-2.10) (-2.01) (-1.44) (-1.18) (-.14) (-2.31) SPEC -.088 -.251 -.330 -.284 -.186 -.144 -.056 -.261 -.474 -.235 -.115 -.064 -.066 (-1.01) (-4.36) (-4.44) (-.52) (-2.46) (-2.55) (-1.54) (-3.97) (-4.32) (-4.61) (-2.66) (-1.64) (-3.08) COMP -.080 -.152 -.105 -.069 -.069 -.199 -.038 -.155 .172 -.096 -.069 -.043 .032 (-1.69) (-2.83) (-1.24) (-1.71) (-1.53) (-4.03) (-0.57) (-2.27) (.66) (-2.70) (-1.34) (-1.09) (.41) DIV .273 .154 .238 -.040 .446 1.049 .097 .647 .556 .433 .310 .341 .604 (.478) (1.51) (2.21) (.34) (4.71) (1.86) (.62) (2.34) (1.00) (3.26) (1.44) (4.69) (3.07) BP-test 26.97 9.15 1.71 23.17 8.45 15.23 101.81 27.75 34.69 29.96 35.96 1.76 22.46 R 2 − Adj .2553 .2591 .0783 .0448 .4457 .3634 .6308 .5528 .4480 .5082 .6984 .4439 .5733 Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  94. 94. Introduction and Literature Basic Results Data and Methods Spatial lag Results Spatial lag and Spatial Regimes Conclusion and Policy Implications Simple model with spillovers Food Textile Leather Wood Paper Fuels Chem Rubber Nonmet Metal Mach Elect Trans Int .041 .081 .035 .056 .039 .021 .030 -.007 -.027 .078 .053 .011 .019 (1.88) (4.62) (2.64) (2.81) (2.22) (1.51) (2.01) (-.32) (-.53) (5.32) (2.59) (.59) (1.78) R&D .130 .444 .064 .147 .824 -.136 .723 .417 .590 .248 .577 .340 .256 (.92) (5.14) (.57) (.86) (4.35) (-.66) (3.25) (3.65) (3.57) (2.31) (4.33) (4.54) (2.77) WR&D .305 .063 .294 -.023 -.458 -.241 .136 .538 .669 .049 .226 -.048 .279 (1.82) (.407) (1.06) (-.17) (-3.20) (-1.60) (1.08) (3.32) (3.49) (.73) (1.76) (-0.65) (3.43) R&Dnonj .238 .192 .267 .235 .177 .591 -.031 .168 .355 .181 .075 .128 .047 (2.40) (3.26) (3.14) (2.92) (1.58) (6.66) (-.59) (2.20) (3.67) (2.39) (.85) (2.60) (1.01) UNI .102 -.053 -.077 -.066 -.070 .076 -.009 -.009 -.097 -.056 -.087 .023 -.035 (.90) (-.935) (-1.49) (-.54) (-1.41) (.87) (-.19) (-.11) (-1.11) (-1.21) (-1.45) (.567) (-.71) GOV .178 .018 -.011 .107 -.038 .156 .054 -.005 .027 -.031 .012 .056 -.006 (2.43) (.396) (-.23) (-.72) (-.97) (2.22) (1.50) (-.08) (.50) (-.89) (.384) (1.79) (-.19) AGG -.034 .070 .087 -.044 -.046 -.091 .011 -.048 -.057 -.025 -.008 -.023 -.033 (-.24) (.901) (1.14) (-.61) (-.66) (-1.16) (.23) (-.89) (-.73) (-.96) (-.14) (-.43) (-1.00) SPEC .039 -.157 -.091 -.163 -.105 .042 -.066 -.033 -.158 -.143 -.053 .003 -.038 (.50) (-2.53) (-1.07) (-.52) (-1.06) (.81) (-1.34) (-.43) (-1.72) (-3.00) (-1.10) (.06) (-1.67) COMP -.034 -.134 -.083 -.008 -.022 -.113 -.030 -.000 .331 -.063 -.017 -.008 .069 (-.72) (-2.53) (-1.13) (-.21) (-.48) (-3.49) (-.47) (-.01) (1.35) (-2.10) (-.33) (-.19) (.86) DIV -.008 -.063 -.084 -.227 .277 .384 .117 .351 .087 .255 .221 .254 .619 (-.019) (-.539) (-.82) (-1.25) (.95) (1.94) (.64) (3.58) (.44) (3.58) (1.77) (3.19) (2.44) BP-test 30.81 9.47 21.03 26.63 15.14 24.79 106.68 33.56 43.21 30.41 47.80 2.77 22.89 R 2 − Adj .3012 .2922 .1880 .0848 .4997 .5443 .6328 .6233 .5694 .5317 .7107 .4546 .6201 Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  95. 95. Introduction and Literature Basic Results Data and Methods Spatial lag Results Spatial lag and Spatial Regimes Conclusion and Policy Implications Outline 1 Introduction and Literature Introduction Economic Theories, Agglomeration and Spillovers Previous Findings Research Hypothesis 2 Data and Methods The model A Regional Innovation dataset 3 Results Basic Results Spatial lag Spatial lag and Spatial Regimes 4 Conclusion and Policy Implications Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  96. 96. Introduction and Literature Basic Results Data and Methods Spatial lag Results Spatial lag and Spatial Regimes Conclusion and Policy Implications Simple Spatial Lag Industry Spillovers Externalities Home Interreg Inter-ind Agg Spec Comp Div Food + Textile + + - Leather + Wood + - Paper + - + + Fuels - + + Chemical + - - Rubber + + + + Non Metal + + + - + Metal + - + - + Machinery + - + + Electrical + + + Transport + - + Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  97. 97. Introduction and Literature Basic Results Data and Methods Spatial lag Results Spatial lag and Spatial Regimes Conclusion and Policy Implications Outline 1 Introduction and Literature Introduction Economic Theories, Agglomeration and Spillovers Previous Findings Research Hypothesis 2 Data and Methods The model A Regional Innovation dataset 3 Results Basic Results Spatial lag Spatial lag and Spatial Regimes 4 Conclusion and Policy Implications Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  98. 98. Introduction and Literature Basic Results Data and Methods Spatial lag Results Spatial lag and Spatial Regimes Conclusion and Policy Implications Density regime - Agglomerated with Centres Industry Spillovers Externalities Home Interreg Inter-ind Agg Spec Comp Div Food + - Textile + + Leather + Wood + Paper + + Fuels - + - + Chemical + - Rubber + + + Non Metal + + + - Metal + + Machinery + + + Electrical + + Transport + + + Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
  99. 99. Introduction and Literature Basic Results Data and Methods Spatial lag Results Spatial lag and Spatial Regimes Conclusion and Policy Implications Density regime - Agglomerated Without Centres Industry Spillovers Externalities Home Interreg Inter-ind Agg Spec Comp Div Food Textile + Leather + - Wood - + + + - Paper Fuels Chemical Rubber + - Non Metal + Metal + - Machinery + + - Electrical + Transport + Giovanni Guastella Spillover Diffusion, Agglomeration and Distance
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