Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Spillover Diffusion, Agglomeration andDistance

a Spatial Extension of the Knowledge Production FunctionApproach

Giovanni Guastella1

1MSc in Economics and GeographyUtrecht University

Thesis Dissertation, July 2010

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Motivation

NGT (Romer [20], Lucas [13]) stresses the role ofknowledge spillovers as source of increasing returns (IR).Altough IR are likely to cause divergence, it is argued thatspillovers diffusion may also contribute to convergence,depending on the degree of localization of theseexternalities (Grossman and Helpman [8]).

One problem ...If one one side knowledge cannot be contained within walls, onthe other side it is not accessible from everywhere andeveryone.

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Motivation

NGT (Romer [20], Lucas [13]) stresses the role ofknowledge spillovers as source of increasing returns (IR).Altough IR are likely to cause divergence, it is argued thatspillovers diffusion may also contribute to convergence,depending on the degree of localization of theseexternalities (Grossman and Helpman [8]).

One problem ...If one one side knowledge cannot be contained within walls, onthe other side it is not accessible from everywhere andeveryone.

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Motivation

NGT (Romer [20], Lucas [13]) stresses the role ofknowledge spillovers as source of increasing returns (IR).Altough IR are likely to cause divergence, it is argued thatspillovers diffusion may also contribute to convergence,depending on the degree of localization of theseexternalities (Grossman and Helpman [8]).

One problem ...If one one side knowledge cannot be contained within walls, onthe other side it is not accessible from everywhere andeveryone.

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Motivation

... and another problemAltough the literature on innovavation and geography(Audretsch and Feldman [2]) suggests that spillovers are higherin agglomerated areas and the intensity decreases withdistance, it is not easy to establish a direct link betweengeography, agglomeration and spillover diffusion. This paperattempts to study the way geography, agglomeration andspillovers cause innovative activities.

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Outline

1 Introduction and LiteratureIntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

2 Data and MethodsThe modelA Regional Innovation dataset

3 ResultsBasic ResultsSpatial lagSpatial lag and Spatial Regimes

4 Conclusion and Policy Implications

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Outline

1 Introduction and LiteratureIntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

2 Data and MethodsThe modelA Regional Innovation dataset

3 ResultsBasic ResultsSpatial lagSpatial lag and Spatial Regimes

4 Conclusion and Policy Implications

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Outline

1 Introduction and LiteratureIntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

2 Data and MethodsThe modelA Regional Innovation dataset

3 ResultsBasic ResultsSpatial lagSpatial lag and Spatial Regimes

4 Conclusion and Policy Implications

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Outline

1 Introduction and LiteratureIntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

2 Data and MethodsThe modelA Regional Innovation dataset

3 ResultsBasic ResultsSpatial lagSpatial lag and Spatial Regimes

4 Conclusion and Policy Implications

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

Outline

1 Introduction and LiteratureIntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

2 Data and MethodsThe modelA Regional Innovation dataset

3 ResultsBasic ResultsSpatial lagSpatial lag and Spatial Regimes

4 Conclusion and Policy Implications

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

How do spillovers fit in economic theories

There is no doubt that spillovers determine increasingreturns, and this idea is maintained also in this work. Whatis diffuclt is to define and identify spillovers.Mainstream view: knowledge is a public good accessiblefrom everyone. Social returns from innovative investmentsare higher than private ones.Evolutionary view: there are geographical, social andcultural barriers to knowledge flows. Physical andtechnological distances are considered among the mostimportant obstacles to spillover diffusion.

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

How do spillovers fit in economic theories

There is no doubt that spillovers determine increasingreturns, and this idea is maintained also in this work. Whatis diffuclt is to define and identify spillovers.Mainstream view: knowledge is a public good accessiblefrom everyone. Social returns from innovative investmentsare higher than private ones.Evolutionary view: there are geographical, social andcultural barriers to knowledge flows. Physical andtechnological distances are considered among the mostimportant obstacles to spillover diffusion.

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

How do spillovers fit in economic theories

There is no doubt that spillovers determine increasingreturns, and this idea is maintained also in this work. Whatis diffuclt is to define and identify spillovers.Mainstream view: knowledge is a public good accessiblefrom everyone. Social returns from innovative investmentsare higher than private ones.Evolutionary view: there are geographical, social andcultural barriers to knowledge flows. Physical andtechnological distances are considered among the mostimportant obstacles to spillover diffusion.

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

Definition of spillovers

knowledge cannot be entirely codified (explicit vs tacit)knowledge transfer is costlyDistance is important because

it allows face-to-face contactsit 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

Definition of spillovers

knowledge cannot be entirely codified (explicit vs tacit)knowledge transfer is costlyDistance is important because

it allows face-to-face contactsit 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

Definition of spillovers

knowledge cannot be entirely codified (explicit vs tacit)knowledge transfer is costlyDistance is important because

it allows face-to-face contactsit 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

Definition of spillovers

knowledge cannot be entirely codified (explicit vs tacit)knowledge transfer is costlyDistance is important because

it allows face-to-face contactsit 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

Definition of spillovers

knowledge cannot be entirely codified (explicit vs tacit)knowledge transfer is costlyDistance is important because

it allows face-to-face contactsit 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

Definition of spillovers

knowledge cannot be entirely codified (explicit vs tacit)knowledge transfer is costlyDistance is important because

it allows face-to-face contactsit 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

Definition of spillovers

knowledge cannot be entirely codified (explicit vs tacit)knowledge transfer is costlyDistance is important because

it allows face-to-face contactsit 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

Definition of spillovers

knowledge cannot be entirely codified (explicit vs tacit)knowledge transfer is costlyDistance is important because

it allows face-to-face contactsit 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

Outline

1 Introduction and LiteratureIntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

2 Data and MethodsThe modelA Regional Innovation dataset

3 ResultsBasic ResultsSpatial lagSpatial lag and Spatial Regimes

4 Conclusion and Policy Implications

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch 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 levelLocalized Knowledge Spillovers

Labor mobilityEntrepreneurship and spin-offInter-firms collaborations

Pure vs pecuniary externalities?...what standard methodologies [...] suggest to be pureexternalities, 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch 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 levelLocalized Knowledge Spillovers

Labor mobilityEntrepreneurship and spin-offInter-firms collaborations

Pure vs pecuniary externalities?...what standard methodologies [...] suggest to be pureexternalities, 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch 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 levelLocalized Knowledge Spillovers

Labor mobilityEntrepreneurship and spin-offInter-firms collaborations

Pure vs pecuniary externalities?...what standard methodologies [...] suggest to be pureexternalities, 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch 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 levelLocalized Knowledge Spillovers

Labor mobilityEntrepreneurship and spin-offInter-firms collaborations

Pure vs pecuniary externalities?...what standard methodologies [...] suggest to be pureexternalities, 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch 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 levelLocalized Knowledge Spillovers

Labor mobilityEntrepreneurship and spin-offInter-firms collaborations

Pure vs pecuniary externalities?...what standard methodologies [...] suggest to be pureexternalities, 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch 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 levelLocalized Knowledge Spillovers

Labor mobilityEntrepreneurship and spin-offInter-firms collaborations

Pure vs pecuniary externalities?...what standard methodologies [...] suggest to be pureexternalities, 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch 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 levelLocalized Knowledge Spillovers

Labor mobilityEntrepreneurship and spin-offInter-firms collaborations

Pure vs pecuniary externalities?...what standard methodologies [...] suggest to be pureexternalities, 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

Agglomeration and spillovers

Concentration of knowledge sources pushes the creationof new knowledge (Jaffe, [11])Geography is still a Black Box (Distance is Exogenous!!!)However...Externalities have not only positive effects

congestion costsspatial 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

Agglomeration and spillovers

Concentration of knowledge sources pushes the creationof new knowledge (Jaffe, [11])Geography is still a Black Box (Distance is Exogenous!!!)However...Externalities have not only positive effects

congestion costsspatial 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

Agglomeration and spillovers

Concentration of knowledge sources pushes the creationof new knowledge (Jaffe, [11])Geography is still a Black Box (Distance is Exogenous!!!)However...Externalities have not only positive effects

congestion costsspatial 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

Agglomeration and spillovers

Concentration of knowledge sources pushes the creationof new knowledge (Jaffe, [11])Geography is still a Black Box (Distance is Exogenous!!!)However...Externalities have not only positive effects

congestion costsspatial 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

Agglomeration and spillovers

Concentration of knowledge sources pushes the creationof new knowledge (Jaffe, [11])Geography is still a Black Box (Distance is Exogenous!!!)However...Externalities have not only positive effects

congestion costsspatial 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

Agglomeration and spillovers

Concentration of knowledge sources pushes the creationof new knowledge (Jaffe, [11])Geography is still a Black Box (Distance is Exogenous!!!)However...Externalities have not only positive effects

congestion costsspatial 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

Agglomeration and spillovers

Concentration of knowledge sources pushes the creationof new knowledge (Jaffe, [11])Geography is still a Black Box (Distance is Exogenous!!!)However...Externalities have not only positive effects

congestion costsspatial 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

Agglomeration and spillovers

Concentration of knowledge sources pushes the creationof new knowledge (Jaffe, [11])Geography is still a Black Box (Distance is Exogenous!!!)However...Externalities have not only positive effects

congestion costsspatial 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

Agglomeration and spillovers

Concentration of knowledge sources pushes the creationof new knowledge (Jaffe, [11])Geography is still a Black Box (Distance is Exogenous!!!)However...Externalities have not only positive effects

congestion costsspatial 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

Agglomeration and spillovers

Concentration of knowledge sources pushes the creationof new knowledge (Jaffe, [11])Geography is still a Black Box (Distance is Exogenous!!!)However...Externalities have not only positive effects

congestion costsspatial 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

Outline

1 Introduction and LiteratureIntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

2 Data and MethodsThe modelA Regional Innovation dataset

3 ResultsBasic ResultsSpatial lagSpatial lag and Spatial Regimes

4 Conclusion and Policy Implications

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

At industry-aggregate level

Use of WR&D to proxy spatial spillovers

elasticity to external R&D is about .07 (.04 to .11) andspatial spillovers are more important of technological ones(Bottazzi and Peri, [3])elasticity to external R&D is about .025 and spillovers arebounded within 300 km (Bottazzi and Peri, [4])elasticity to external R&D is about .04; sipllover arebounded within 176 miles and there are no spilloversamong technological neighbors (Greunz, [6])the majority of spillovers are confined within regionalborders and, in any case, within 350 km from the originregion (Moreno et al., [16])

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

At industry-aggregate level

Use of WR&D to proxy spatial spillovers

elasticity to external R&D is about .07 (.04 to .11) andspatial spillovers are more important of technological ones(Bottazzi and Peri, [3])elasticity to external R&D is about .025 and spillovers arebounded within 300 km (Bottazzi and Peri, [4])elasticity to external R&D is about .04; sipllover arebounded within 176 miles and there are no spilloversamong technological neighbors (Greunz, [6])the majority of spillovers are confined within regionalborders and, in any case, within 350 km from the originregion (Moreno et al., [16])

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

At industry-aggregate level

Use of WR&D to proxy spatial spillovers

elasticity to external R&D is about .07 (.04 to .11) andspatial spillovers are more important of technological ones(Bottazzi and Peri, [3])elasticity to external R&D is about .025 and spillovers arebounded within 300 km (Bottazzi and Peri, [4])elasticity to external R&D is about .04; sipllover arebounded within 176 miles and there are no spilloversamong technological neighbors (Greunz, [6])the majority of spillovers are confined within regionalborders and, in any case, within 350 km from the originregion (Moreno et al., [16])

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

At industry-aggregate level

Use of WR&D to proxy spatial spillovers

elasticity to external R&D is about .07 (.04 to .11) andspatial spillovers are more important of technological ones(Bottazzi and Peri, [3])elasticity to external R&D is about .025 and spillovers arebounded within 300 km (Bottazzi and Peri, [4])elasticity to external R&D is about .04; sipllover arebounded within 176 miles and there are no spilloversamong technological neighbors (Greunz, [6])the majority of spillovers are confined within regionalborders and, in any case, within 350 km from the originregion (Moreno et al., [16])

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

At industry-specific level

concentration of economic activities vary across industries,industrial specialization has positive effects and spillovershappen between regions specialized in similar industries(Moreno et al.,[15]positive interregional spillovers and positive effect ofspecialization (no diversity)

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

At industry-specific level

concentration of economic activities vary across industries,industrial specialization has positive effects and spillovershappen between regions specialized in similar industries(Moreno et al.,[15]positive interregional spillovers and positive effect ofspecialization (no diversity)

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

Outline

1 Introduction and LiteratureIntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

2 Data and MethodsThe modelA Regional Innovation dataset

3 ResultsBasic ResultsSpatial lagSpatial lag and Spatial Regimes

4 Conclusion and Policy Implications

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

My contribution

Enlarged geographical scope - 250 NUTS II regionsExplicit role for geography (agglomeration, specialization,competition and diversity)Industry-specific analysis (13 manufacturing industries)Interregional and inter-industry spilloversDifferentiation among different regimes based on

Human GeographyPhysical GeographyEconomic Geography

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

My contribution

Enlarged geographical scope - 250 NUTS II regionsExplicit role for geography (agglomeration, specialization,competition and diversity)Industry-specific analysis (13 manufacturing industries)Interregional and inter-industry spilloversDifferentiation among different regimes based on

Human GeographyPhysical GeographyEconomic Geography

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

My contribution

Enlarged geographical scope - 250 NUTS II regionsExplicit role for geography (agglomeration, specialization,competition and diversity)Industry-specific analysis (13 manufacturing industries)Interregional and inter-industry spilloversDifferentiation among different regimes based on

Human GeographyPhysical GeographyEconomic Geography

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

My contribution

Enlarged geographical scope - 250 NUTS II regionsExplicit role for geography (agglomeration, specialization,competition and diversity)Industry-specific analysis (13 manufacturing industries)Interregional and inter-industry spilloversDifferentiation among different regimes based on

Human GeographyPhysical GeographyEconomic Geography

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

My contribution

Enlarged geographical scope - 250 NUTS II regionsExplicit role for geography (agglomeration, specialization,competition and diversity)Industry-specific analysis (13 manufacturing industries)Interregional and inter-industry spilloversDifferentiation among different regimes based on

Human GeographyPhysical GeographyEconomic Geography

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

My contribution

Enlarged geographical scope - 250 NUTS II regionsExplicit role for geography (agglomeration, specialization,competition and diversity)Industry-specific analysis (13 manufacturing industries)Interregional and inter-industry spilloversDifferentiation among different regimes based on

Human GeographyPhysical GeographyEconomic Geography

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

My contribution

Enlarged geographical scope - 250 NUTS II regionsExplicit role for geography (agglomeration, specialization,competition and diversity)Industry-specific analysis (13 manufacturing industries)Interregional and inter-industry spilloversDifferentiation among different regimes based on

Human GeographyPhysical GeographyEconomic Geography

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

My contribution

Enlarged geographical scope - 250 NUTS II regionsExplicit role for geography (agglomeration, specialization,competition and diversity)Industry-specific analysis (13 manufacturing industries)Interregional and inter-industry spilloversDifferentiation among different regimes based on

Human GeographyPhysical GeographyEconomic Geography

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

My contribution

Main idea: use aggregate data to find stronger evidence ofspilloverMy idea: split as much a possible to find evidence of purespillovers and separate R&D spillovers from otherexternalities

Externality Positive Effect Negative Effect

Interreg within industry spillovers industrial competition among regionsInter-ind between industries spillovers regional competition amond industriesAgg market potential ongestion costsSpec labor market pooling and low cognitive distance cognitive lock-inComp more incentives to innovate big firms invest more in researchDiv cross-industry knowledge exchange too much cognitive distance

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

IntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

My contribution

Main idea: use aggregate data to find stronger evidence ofspilloverMy idea: split as much a possible to find evidence of purespillovers and separate R&D spillovers from otherexternalities

Externality Positive Effect Negative Effect

Interreg within industry spillovers industrial competition among regionsInter-ind between industries spillovers regional competition amond industriesAgg market potential ongestion costsSpec labor market pooling and low cognitive distance cognitive lock-inComp more incentives to innovate big firms invest more in researchDiv cross-industry knowledge exchange too much cognitive distance

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Outline

1 Introduction and LiteratureIntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

2 Data and MethodsThe modelA Regional Innovation dataset

3 ResultsBasic ResultsSpatial lagSpatial lag and Spatial Regimes

4 Conclusion and Policy Implications

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Model specification and assumptions

Iij =α0 + α1R&Dij + α2UNIi + α3GOVi+

β1WR&Dij + β2R&Di,k 6=j+

γ1AGGi + γ2SPECij + γ3COMPij + γ4DIVi+

εi

(2)

α1 to α3: home made investments by firms, universitiesand governmentsβ1: interregional spilloversβ2: interindustry spilloversγ1 to γ4: externalities

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Model specification and assumptions

Iij =α0 + α1R&Dij + α2UNIi + α3GOVi+

β1WR&Dij + β2R&Di,k 6=j+

γ1AGGi + γ2SPECij + γ3COMPij + γ4DIVi+

εi

(2)

α1 to α3: home made investments by firms, universitiesand governmentsβ1: interregional spilloversβ2: interindustry spilloversγ1 to γ4: externalities

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Model specification and assumptions

Iij =α0 + α1R&Dij + α2UNIi + α3GOVi+

β1WR&Dij + β2R&Di,k 6=j+

γ1AGGi + γ2SPECij + γ3COMPij + γ4DIVi+

εi

(2)

α1 to α3: home made investments by firms, universitiesand governmentsβ1: interregional spilloversβ2: interindustry spilloversγ1 to γ4: externalities

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Model specification and assumptions

Iij =α0 + α1R&Dij + α2UNIi + α3GOVi+

β1WR&Dij + β2R&Di,k 6=j+

γ1AGGi + γ2SPECij + γ3COMPij + γ4DIVi+

εi

(2)

α1 to α3: home made investments by firms, universitiesand governmentsβ1: interregional spilloversβ2: interindustry spilloversγ1 to γ4: externalities

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Measuring issues

AGGi =POPiAreai

SPECij =R&Dij∑i R&Dij

/∑

j R&Dij∑i∑

j R&Dij

COMPij =FIRMSij

EMPLOYEESij

DIVi =∑

j

(R&Dij − 1

J∑

j R&Dij

)2

Choice of WGreat circle distance. Which d?K -nearest neighbors. Which k?Physical contiguity. What about islands?

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Measuring issues

AGGi =POPiAreai

SPECij =R&Dij∑i R&Dij

/∑

j R&Dij∑i∑

j R&Dij

COMPij =FIRMSij

EMPLOYEESij

DIVi =∑

j

(R&Dij − 1

J∑

j R&Dij

)2

Choice of WGreat circle distance. Which d?K -nearest neighbors. Which k?Physical contiguity. What about islands?

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Measuring issues

AGGi =POPiAreai

SPECij =R&Dij∑i R&Dij

/∑

j R&Dij∑i∑

j R&Dij

COMPij =FIRMSij

EMPLOYEESij

DIVi =∑

j

(R&Dij − 1

J∑

j R&Dij

)2

Choice of WGreat circle distance. Which d?K -nearest neighbors. Which k?Physical contiguity. What about islands?

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Measuring issues

AGGi =POPiAreai

SPECij =R&Dij∑i R&Dij

/∑

j R&Dij∑i∑

j R&Dij

COMPij =FIRMSij

EMPLOYEESij

DIVi =∑

j

(R&Dij − 1

J∑

j R&Dij

)2

Choice of WGreat circle distance. Which d?K -nearest neighbors. Which k?Physical contiguity. What about islands?

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Measuring issues

AGGi =POPiAreai

SPECij =R&Dij∑i R&Dij

/∑

j R&Dij∑i∑

j R&Dij

COMPij =FIRMSij

EMPLOYEESij

DIVi =∑

j

(R&Dij − 1

J∑

j R&Dij

)2

Choice of WGreat circle distance. Which d?K -nearest neighbors. Which k?Physical contiguity. What about islands?

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Measuring issues

AGGi =POPiAreai

SPECij =R&Dij∑i R&Dij

/∑

j R&Dij∑i∑

j R&Dij

COMPij =FIRMSij

EMPLOYEESij

DIVi =∑

j

(R&Dij − 1

J∑

j R&Dij

)2

Choice of WGreat circle distance. Which d?K -nearest neighbors. Which k?Physical contiguity. What about islands?

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Measuring issues

AGGi =POPiAreai

SPECij =R&Dij∑i R&Dij

/∑

j R&Dij∑i∑

j R&Dij

COMPij =FIRMSij

EMPLOYEESij

DIVi =∑

j

(R&Dij − 1

J∑

j R&Dij

)2

Choice of WGreat circle distance. Which d?K -nearest neighbors. Which k?Physical contiguity. What about islands?

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Measuring issues

AGGi =POPiAreai

SPECij =R&Dij∑i R&Dij

/∑

j R&Dij∑i∑

j R&Dij

COMPij =FIRMSij

EMPLOYEESij

DIVi =∑

j

(R&Dij − 1

J∑

j R&Dij

)2

Choice of WGreat circle distance. Which d?K -nearest neighbors. Which k?Physical contiguity. What about islands?

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Weighting spillovers

Do spillover depend on the source?I made no differentiation of the source, meaning that allneighbors and all industries contribute with the same weight!!!Be care with the interpretation!!!

Equal weight to allneighborsRow standardization

Equal weight to allindustries

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Differentiating across regimes

η′ = (α0, α1, α2, α3, β1, β2, γ1, γ2, γ3, γ4)

η = η1AC + η2AWC + η3NAC + η4NAWCη = η5CORE + η6INTER + η7PERIPη = η8NONLAG + η9POTLAG + η10LAG

Source ESPON project (Copiright ESPON 2006 -http://www.espon.eu)

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Differentiating across regimes

η′ = (α0, α1, α2, α3, β1, β2, γ1, γ2, γ3, γ4)

η = η1AC + η2AWC + η3NAC + η4NAWCη = η5CORE + η6INTER + η7PERIPη = η8NONLAG + η9POTLAG + η10LAG

Source ESPON project (Copiright ESPON 2006 -http://www.espon.eu)

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Differentiating across regimes

η′ = (α0, α1, α2, α3, β1, β2, γ1, γ2, γ3, γ4)

η = η1AC + η2AWC + η3NAC + η4NAWCη = η5CORE + η6INTER + η7PERIPη = η8NONLAG + η9POTLAG + η10LAG

Source ESPON project (Copiright ESPON 2006 -http://www.espon.eu)

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Outline

1 Introduction and LiteratureIntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

2 Data and MethodsThe modelA Regional Innovation dataset

3 ResultsBasic ResultsSpatial lagSpatial lag and Spatial Regimes

4 Conclusion and Policy Implications

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Patent counts as measure of regional innovation

PA are not a good proxy for innovationsPA underestimate innovation in small firms (Pakes andGriliches, [17])Big firms tend to overpatenting innovationsPatents 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 consideredAre costly to be producedComparison 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 frameworkboth measures lead to identical conclusions

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Patent counts as measure of regional innovation

PA are not a good proxy for innovationsPA underestimate innovation in small firms (Pakes andGriliches, [17])Big firms tend to overpatenting innovationsPatents 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 consideredAre costly to be producedComparison 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 frameworkboth measures lead to identical conclusions

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Patent counts as measure of regional innovation

PA are not a good proxy for innovationsPA underestimate innovation in small firms (Pakes andGriliches, [17])Big firms tend to overpatenting innovationsPatents 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 consideredAre costly to be producedComparison 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 frameworkboth measures lead to identical conclusions

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Patent counts as measure of regional innovation

PA are not a good proxy for innovationsPA underestimate innovation in small firms (Pakes andGriliches, [17])Big firms tend to overpatenting innovationsPatents 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 consideredAre costly to be producedComparison 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 frameworkboth measures lead to identical conclusions

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Patent counts as measure of regional innovation

PA are not a good proxy for innovationsPA underestimate innovation in small firms (Pakes andGriliches, [17])Big firms tend to overpatenting innovationsPatents 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 consideredAre costly to be producedComparison 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 frameworkboth measures lead to identical conclusions

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Patent counts as measure of regional innovation

PA are not a good proxy for innovationsPA underestimate innovation in small firms (Pakes andGriliches, [17])Big firms tend to overpatenting innovationsPatents 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 consideredAre costly to be producedComparison 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 frameworkboth measures lead to identical conclusions

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Patent counts as measure of regional innovation

PA are not a good proxy for innovationsPA underestimate innovation in small firms (Pakes andGriliches, [17])Big firms tend to overpatenting innovationsPatents 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 consideredAre costly to be producedComparison 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 frameworkboth measures lead to identical conclusions

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Patent counts as measure of regional innovation

PA are not a good proxy for innovationsPA underestimate innovation in small firms (Pakes andGriliches, [17])Big firms tend to overpatenting innovationsPatents 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 consideredAre costly to be producedComparison 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 frameworkboth measures lead to identical conclusions

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Patent counts as measure of regional innovation

PA are not a good proxy for innovationsPA underestimate innovation in small firms (Pakes andGriliches, [17])Big firms tend to overpatenting innovationsPatents 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 consideredAre costly to be producedComparison 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 frameworkboth measures lead to identical conclusions

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

R&D data

R&D data at regional industry-specific level are notavailableRegional data are derived from national levels usingsymplifying assumption

R&Dij

NAT − R&Dj=

EMPij

NAT − EMPj(3)

NOTE!!!The share of R&D per worker is costant across regions in thesame country for each industry

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

R&D data

R&D data at regional industry-specific level are notavailableRegional data are derived from national levels usingsymplifying assumption

R&Dij

NAT − R&Dj=

EMPij

NAT − EMPj(3)

NOTE!!!The share of R&D per worker is costant across regions in thesame country for each industry

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

R&D data

R&D data at regional industry-specific level are notavailableRegional data are derived from national levels usingsymplifying assumption

R&Dij

NAT − R&Dj=

EMPij

NAT − EMPj(3)

NOTE!!!The share of R&D per worker is costant across regions in thesame country for each industry

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Reconciling SIC codes with IPC classes

Schmoch et al., [21] provided a table to reconcile 4-digitIPC with SIC industriesPA data are provided by Eurostat at 3-digit IPC classIt may happen that one IPC code belongs to more thanone SIC industriesI counted the times every IPC appears in a SIC. The shareof the count wrt total is the proportion of patents attributedto the SIC

Industry SIC IPCFood DA: food A01 C12 C13 A21 A23 A24Textile DB: textile D04 D06 A41Leather DC: leather A43 B68Wood DD: wood B27 E04Paper DE:paper, pub. and print. B41 B42 B44 D21Fuels DF: petroleum and nuclear fuel C10 G01Chemical DG: chemicals A01 A61 A62 ...... ... ...

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Reconciling SIC codes with IPC classes

Schmoch et al., [21] provided a table to reconcile 4-digitIPC with SIC industriesPA data are provided by Eurostat at 3-digit IPC classIt may happen that one IPC code belongs to more thanone SIC industriesI counted the times every IPC appears in a SIC. The shareof the count wrt total is the proportion of patents attributedto the SIC

Industry SIC IPCFood DA: food A01 C12 C13 A21 A23 A24Textile DB: textile D04 D06 A41Leather DC: leather A43 B68Wood DD: wood B27 E04Paper DE:paper, pub. and print. B41 B42 B44 D21Fuels DF: petroleum and nuclear fuel C10 G01Chemical DG: chemicals A01 A61 A62 ...... ... ...

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Reconciling SIC codes with IPC classes

Schmoch et al., [21] provided a table to reconcile 4-digitIPC with SIC industriesPA data are provided by Eurostat at 3-digit IPC classIt may happen that one IPC code belongs to more thanone SIC industriesI counted the times every IPC appears in a SIC. The shareof the count wrt total is the proportion of patents attributedto the SIC

Industry SIC IPCFood DA: food A01 C12 C13 A21 A23 A24Textile DB: textile D04 D06 A41Leather DC: leather A43 B68Wood DD: wood B27 E04Paper DE:paper, pub. and print. B41 B42 B44 D21Fuels DF: petroleum and nuclear fuel C10 G01Chemical DG: chemicals A01 A61 A62 ...... ... ...

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

The modelA Regional Innovation dataset

Reconciling SIC codes with IPC classes

Schmoch et al., [21] provided a table to reconcile 4-digitIPC with SIC industriesPA data are provided by Eurostat at 3-digit IPC classIt may happen that one IPC code belongs to more thanone SIC industriesI counted the times every IPC appears in a SIC. The shareof the count wrt total is the proportion of patents attributedto the SIC

Industry SIC IPCFood DA: food A01 C12 C13 A21 A23 A24Textile DB: textile D04 D06 A41Leather DC: leather A43 B68Wood DD: wood B27 E04Paper DE:paper, pub. and print. B41 B42 B44 D21Fuels DF: petroleum and nuclear fuel C10 G01Chemical DG: chemicals A01 A61 A62 ...... ... ...

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Basic ResultsSpatial lagSpatial lag and Spatial Regimes

Outline

1 Introduction and LiteratureIntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

2 Data and MethodsThe modelA Regional Innovation dataset

3 ResultsBasic ResultsSpatial lagSpatial lag and Spatial Regimes

4 Conclusion and Policy Implications

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Basic ResultsSpatial lagSpatial lag and Spatial Regimes

Basic model

Food Textile Leather Wood Paper Fuels Chem Rubber Nonmet Metal Mach Elect TransInt .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 22.46R2 − Adj .2553 .2591 .0783 .0448 .4457 .3634 .6308 .5528 .4480 .5082 .6984 .4439 .5733

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Basic ResultsSpatial lagSpatial lag and Spatial Regimes

Simple model with spillovers

Food Textile Leather Wood Paper Fuels Chem Rubber Nonmet Metal Mach Elect TransInt .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 22.89R2 − Adj .3012 .2922 .1880 .0848 .4997 .5443 .6328 .6233 .5694 .5317 .7107 .4546 .6201

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Basic ResultsSpatial lagSpatial lag and Spatial Regimes

Outline

1 Introduction and LiteratureIntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

2 Data and MethodsThe modelA Regional Innovation dataset

3 ResultsBasic ResultsSpatial lagSpatial lag and Spatial Regimes

4 Conclusion and Policy Implications

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Basic ResultsSpatial lagSpatial lag and Spatial Regimes

Simple Spatial Lag

Industry Spillovers ExternalitiesHome 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Basic ResultsSpatial lagSpatial lag and Spatial Regimes

Outline

1 Introduction and LiteratureIntroductionEconomic Theories, Agglomeration and SpilloversPrevious FindingsResearch Hypothesis

2 Data and MethodsThe modelA Regional Innovation dataset

3 ResultsBasic ResultsSpatial lagSpatial lag and Spatial Regimes

4 Conclusion and Policy Implications

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Basic ResultsSpatial lagSpatial lag and Spatial Regimes

Density regime - Agglomerated with Centres

Industry Spillovers ExternalitiesHome 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Basic ResultsSpatial lagSpatial lag and Spatial Regimes

Density regime - Agglomerated Without Centres

Industry Spillovers ExternalitiesHome Interreg Inter-ind Agg Spec Comp Div

FoodTextile +Leather + -Wood - + + + -PaperFuelsChemicalRubber + -Non Metal +Metal + -Machinery + + -Electrical +Transport +

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Basic ResultsSpatial lagSpatial lag and Spatial Regimes

Density regime - Non Agglomerated with Centres

Industry Spillovers ExternalitiesHome Interreg Inter-ind Agg Spec Comp Div

Food + - +Textile +Leather + -Wood + - + -Paper + -FuelsChemical - +Rubber + - +Non Metal +Metal + - + + -Machinery + -Electrical +Transport + -

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Basic ResultsSpatial lagSpatial lag and Spatial Regimes

Density regime - Non Agglomerated Without Centres

Industry Spillovers ExternalitiesHome 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Basic ResultsSpatial lagSpatial lag and Spatial Regimes

Accessibility regime - Core

Industry Spillovers ExternalitiesHome Interreg Inter-ind Agg Spec Comp Div

Food - -TextileLeather +Wood +Paper + - + +Fuels - + - +Chemical + - - - -Rubber + + +Non Metal + + -Metal + - +Machinery + - - +Electrical + - - - +Transport + + +

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Basic ResultsSpatial lagSpatial lag and Spatial Regimes

Accessibility regime - Intermediate

Industry Spillovers ExternalitiesHome Interreg Inter-ind Agg Spec Comp Div

FoodTextile + -Leather + +Wood + +Paper + - + - + -Fuels +Chemical + - +Rubber + + +Non Metal + + + - +Metal + - +Machinery + + +Electrical +Transport + -

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Basic ResultsSpatial lagSpatial lag and Spatial Regimes

Accessibility regime - Periphery

Industry Spillovers ExternalitiesHome Interreg Inter-ind Agg Spec Comp Div

FoodTextileLeather +WoodPaper + -Fuels +Chemical + -Rubber +Non Metal + - +Metal - +Machinery + - +Electrical +Transport + +

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Basic ResultsSpatial lagSpatial lag and Spatial Regimes

Labor Market regime - Non Lagging

Industry Spillovers ExternalitiesHome 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

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Basic ResultsSpatial lagSpatial lag and Spatial Regimes

Labor Market regime - Potentially Lagging

Industry Spillovers ExternalitiesHome Interreg Inter-ind Agg Spec Comp Div

FoodTextileLeather +WoodPaperFuels +ChemicalRubber + - +Non Metal + -MetalMachinery -Electrical +Transport

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Basic ResultsSpatial lagSpatial lag and Spatial Regimes

Labor Market regime - Lagging

Industry Spillovers ExternalitiesHome Interreg Inter-ind Agg Spec Comp Div

FoodTextileLeatherWoodPaperFuelsChemicalRubberNon MetalMetal -Machinery -ElectricalTransport

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in a nut!

The analysis started with the consideration that innovationpolicies may represent a source of catch-up for poorregions if:

there is a balance between knowledge spillovers andcompetition effectthere is a balance between localization and dispersion ofspillovers

With respect to these two points, results indicate thatno positive interregional spillovers in poor and peripheralregionsnegative spillovers in non agglomerated regions (probablydue to competition among neighbors)positive inter-industry spillovers (extremely localized)knowledge is more likely to flow in rich, central and denselypopulated regions reinforcing the cumulative causation

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in a nut!

The analysis started with the consideration that innovationpolicies may represent a source of catch-up for poorregions if:

there is a balance between knowledge spillovers andcompetition effectthere is a balance between localization and dispersion ofspillovers

With respect to these two points, results indicate thatno positive interregional spillovers in poor and peripheralregionsnegative spillovers in non agglomerated regions (probablydue to competition among neighbors)positive inter-industry spillovers (extremely localized)knowledge is more likely to flow in rich, central and denselypopulated regions reinforcing the cumulative causation

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in a nut!

The analysis started with the consideration that innovationpolicies may represent a source of catch-up for poorregions if:

there is a balance between knowledge spillovers andcompetition effectthere is a balance between localization and dispersion ofspillovers

With respect to these two points, results indicate thatno positive interregional spillovers in poor and peripheralregionsnegative spillovers in non agglomerated regions (probablydue to competition among neighbors)positive inter-industry spillovers (extremely localized)knowledge is more likely to flow in rich, central and denselypopulated regions reinforcing the cumulative causation

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in a nut!

The analysis started with the consideration that innovationpolicies may represent a source of catch-up for poorregions if:

there is a balance between knowledge spillovers andcompetition effectthere is a balance between localization and dispersion ofspillovers

With respect to these two points, results indicate thatno positive interregional spillovers in poor and peripheralregionsnegative spillovers in non agglomerated regions (probablydue to competition among neighbors)positive inter-industry spillovers (extremely localized)knowledge is more likely to flow in rich, central and denselypopulated regions reinforcing the cumulative causation

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in a nut!

The analysis started with the consideration that innovationpolicies may represent a source of catch-up for poorregions if:

there is a balance between knowledge spillovers andcompetition effectthere is a balance between localization and dispersion ofspillovers

With respect to these two points, results indicate thatno positive interregional spillovers in poor and peripheralregionsnegative spillovers in non agglomerated regions (probablydue to competition among neighbors)positive inter-industry spillovers (extremely localized)knowledge is more likely to flow in rich, central and denselypopulated regions reinforcing the cumulative causation

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in a nut!

The analysis started with the consideration that innovationpolicies may represent a source of catch-up for poorregions if:

there is a balance between knowledge spillovers andcompetition effectthere is a balance between localization and dispersion ofspillovers

With respect to these two points, results indicate thatno positive interregional spillovers in poor and peripheralregionsnegative spillovers in non agglomerated regions (probablydue to competition among neighbors)positive inter-industry spillovers (extremely localized)knowledge is more likely to flow in rich, central and denselypopulated regions reinforcing the cumulative causation

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in a nut!

The analysis started with the consideration that innovationpolicies may represent a source of catch-up for poorregions if:

there is a balance between knowledge spillovers andcompetition effectthere is a balance between localization and dispersion ofspillovers

With respect to these two points, results indicate thatno positive interregional spillovers in poor and peripheralregionsnegative spillovers in non agglomerated regions (probablydue to competition among neighbors)positive inter-industry spillovers (extremely localized)knowledge is more likely to flow in rich, central and denselypopulated regions reinforcing the cumulative causation

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in a nut!

The analysis started with the consideration that innovationpolicies may represent a source of catch-up for poorregions if:

there is a balance between knowledge spillovers andcompetition effectthere is a balance between localization and dispersion ofspillovers

With respect to these two points, results indicate thatno positive interregional spillovers in poor and peripheralregionsnegative spillovers in non agglomerated regions (probablydue to competition among neighbors)positive inter-industry spillovers (extremely localized)knowledge is more likely to flow in rich, central and denselypopulated regions reinforcing the cumulative causation

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in more detail: the issue of heterogeneity

Heterogeneity is the keyword to understand technologicalchange

results differ across industries (industrial specializationmatters)industrial structure influences the innovative performance(market externalities)

Two main implications from thisfor scholars: heterogeneity is lost at industry-aggregatelevel and inter-industry spillovers as well. So be carefullmeasuring spilloversfor policy-makers: regional innovation policies may failachieving their goals (industrial and spatial policies)

The present work is only a first attempt to use regionalindustry-specific data testing the KPF approachThere is obviously a need for more relyiable data

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in more detail: the issue of heterogeneity

Heterogeneity is the keyword to understand technologicalchange

results differ across industries (industrial specializationmatters)industrial structure influences the innovative performance(market externalities)

Two main implications from thisfor scholars: heterogeneity is lost at industry-aggregatelevel and inter-industry spillovers as well. So be carefullmeasuring spilloversfor policy-makers: regional innovation policies may failachieving their goals (industrial and spatial policies)

The present work is only a first attempt to use regionalindustry-specific data testing the KPF approachThere is obviously a need for more relyiable data

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in more detail: the issue of heterogeneity

Heterogeneity is the keyword to understand technologicalchange

results differ across industries (industrial specializationmatters)industrial structure influences the innovative performance(market externalities)

Two main implications from thisfor scholars: heterogeneity is lost at industry-aggregatelevel and inter-industry spillovers as well. So be carefullmeasuring spilloversfor policy-makers: regional innovation policies may failachieving their goals (industrial and spatial policies)

The present work is only a first attempt to use regionalindustry-specific data testing the KPF approachThere is obviously a need for more relyiable data

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in more detail: the issue of heterogeneity

Heterogeneity is the keyword to understand technologicalchange

results differ across industries (industrial specializationmatters)industrial structure influences the innovative performance(market externalities)

Two main implications from thisfor scholars: heterogeneity is lost at industry-aggregatelevel and inter-industry spillovers as well. So be carefullmeasuring spilloversfor policy-makers: regional innovation policies may failachieving their goals (industrial and spatial policies)

The present work is only a first attempt to use regionalindustry-specific data testing the KPF approachThere is obviously a need for more relyiable data

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in more detail: the issue of heterogeneity

Heterogeneity is the keyword to understand technologicalchange

results differ across industries (industrial specializationmatters)industrial structure influences the innovative performance(market externalities)

Two main implications from thisfor scholars: heterogeneity is lost at industry-aggregatelevel and inter-industry spillovers as well. So be carefullmeasuring spilloversfor policy-makers: regional innovation policies may failachieving their goals (industrial and spatial policies)

The present work is only a first attempt to use regionalindustry-specific data testing the KPF approachThere is obviously a need for more relyiable data

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in more detail: the issue of heterogeneity

Heterogeneity is the keyword to understand technologicalchange

results differ across industries (industrial specializationmatters)industrial structure influences the innovative performance(market externalities)

Two main implications from thisfor scholars: heterogeneity is lost at industry-aggregatelevel and inter-industry spillovers as well. So be carefullmeasuring spilloversfor policy-makers: regional innovation policies may failachieving their goals (industrial and spatial policies)

The present work is only a first attempt to use regionalindustry-specific data testing the KPF approachThere is obviously a need for more relyiable data

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in more detail: the issue of heterogeneity

Heterogeneity is the keyword to understand technologicalchange

results differ across industries (industrial specializationmatters)industrial structure influences the innovative performance(market externalities)

Two main implications from thisfor scholars: heterogeneity is lost at industry-aggregatelevel and inter-industry spillovers as well. So be carefullmeasuring spilloversfor policy-makers: regional innovation policies may failachieving their goals (industrial and spatial policies)

The present work is only a first attempt to use regionalindustry-specific data testing the KPF approachThere is obviously a need for more relyiable data

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in more detail: the issue of heterogeneity

Heterogeneity is the keyword to understand technologicalchange

results differ across industries (industrial specializationmatters)industrial structure influences the innovative performance(market externalities)

Two main implications from thisfor scholars: heterogeneity is lost at industry-aggregatelevel and inter-industry spillovers as well. So be carefullmeasuring spilloversfor policy-makers: regional innovation policies may failachieving their goals (industrial and spatial policies)

The present work is only a first attempt to use regionalindustry-specific data testing the KPF approachThere is obviously a need for more relyiable data

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in more detail: pure and pecuniary

It is recognized that innovative activity is the result not only ofinvestments but also of spillovers and externalities. However:

Differentiating among them in empirical analysis is reallydifficultWe tryed to isolate spillovers from externalitiesResults are converging to some extent

inter-industry spillovers go together with industrial diversityinterregional spillovers go together with low specializationand strong competition (think about machinery)at industry specific level it is however out-out

Again be carefull in identifying spillovers

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in more detail: pure and pecuniary

It is recognized that innovative activity is the result not only ofinvestments but also of spillovers and externalities. However:

Differentiating among them in empirical analysis is reallydifficultWe tryed to isolate spillovers from externalitiesResults are converging to some extent

inter-industry spillovers go together with industrial diversityinterregional spillovers go together with low specializationand strong competition (think about machinery)at industry specific level it is however out-out

Again be carefull in identifying spillovers

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in more detail: pure and pecuniary

It is recognized that innovative activity is the result not only ofinvestments but also of spillovers and externalities. However:

Differentiating among them in empirical analysis is reallydifficultWe tryed to isolate spillovers from externalitiesResults are converging to some extent

inter-industry spillovers go together with industrial diversityinterregional spillovers go together with low specializationand strong competition (think about machinery)at industry specific level it is however out-out

Again be carefull in identifying spillovers

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in more detail: pure and pecuniary

It is recognized that innovative activity is the result not only ofinvestments but also of spillovers and externalities. However:

Differentiating among them in empirical analysis is reallydifficultWe tryed to isolate spillovers from externalitiesResults are converging to some extent

inter-industry spillovers go together with industrial diversityinterregional spillovers go together with low specializationand strong competition (think about machinery)at industry specific level it is however out-out

Again be carefull in identifying spillovers

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in more detail: pure and pecuniary

It is recognized that innovative activity is the result not only ofinvestments but also of spillovers and externalities. However:

Differentiating among them in empirical analysis is reallydifficultWe tryed to isolate spillovers from externalitiesResults are converging to some extent

inter-industry spillovers go together with industrial diversityinterregional spillovers go together with low specializationand strong competition (think about machinery)at industry specific level it is however out-out

Again be carefull in identifying spillovers

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in more detail: pure and pecuniary

It is recognized that innovative activity is the result not only ofinvestments but also of spillovers and externalities. However:

Differentiating among them in empirical analysis is reallydifficultWe tryed to isolate spillovers from externalitiesResults are converging to some extent

inter-industry spillovers go together with industrial diversityinterregional spillovers go together with low specializationand strong competition (think about machinery)at industry specific level it is however out-out

Again be carefull in identifying spillovers

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in more detail: pure and pecuniary

It is recognized that innovative activity is the result not only ofinvestments but also of spillovers and externalities. However:

Differentiating among them in empirical analysis is reallydifficultWe tryed to isolate spillovers from externalitiesResults are converging to some extent

inter-industry spillovers go together with industrial diversityinterregional spillovers go together with low specializationand strong competition (think about machinery)at industry specific level it is however out-out

Again be carefull in identifying spillovers

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in more detail: spatial heterogeneity

Spillover mechanism (when such!!!) are not homogeneousacross areas

In developed, central and urbanized regions: diversityand/or inter-industry spilloversIn regions not so far from the core: specialization andcompetition and/or interregional spilloversIn peripheral and rural regions: competition among regions

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in more detail: spatial heterogeneity

Spillover mechanism (when such!!!) are not homogeneousacross areas

In developed, central and urbanized regions: diversityand/or inter-industry spilloversIn regions not so far from the core: specialization andcompetition and/or interregional spilloversIn peripheral and rural regions: competition among regions

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in more detail: spatial heterogeneity

Spillover mechanism (when such!!!) are not homogeneousacross areas

In developed, central and urbanized regions: diversityand/or inter-industry spilloversIn regions not so far from the core: specialization andcompetition and/or interregional spilloversIn peripheral and rural regions: competition among regions

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in more detail: when knowledge flows

Innovation is a process that needs time and resources andis characterized by uncertaintyKnowledge can be exchanged

at the beginning of the process WR&Dat the end of the process WPA (always positive andsignificant)

WPA as a measure of spillovers?To some extent yes! However ia also accounts for unobservedheterogeneity and estimates strongly depend on modelspecification. Finally it is impossible to distinguish pure frompecuniary externalities and also there are no techniquesavailable to let the parameter vary across regimes

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in more detail: when knowledge flows

Innovation is a process that needs time and resources andis characterized by uncertaintyKnowledge can be exchanged

at the beginning of the process WR&Dat the end of the process WPA (always positive andsignificant)

WPA as a measure of spillovers?To some extent yes! However ia also accounts for unobservedheterogeneity and estimates strongly depend on modelspecification. Finally it is impossible to distinguish pure frompecuniary externalities and also there are no techniquesavailable to let the parameter vary across regimes

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Results... in more detail: when knowledge flows

Innovation is a process that needs time and resources andis characterized by uncertaintyKnowledge can be exchanged

at the beginning of the process WR&Dat the end of the process WPA (always positive andsignificant)

WPA as a measure of spillovers?To some extent yes! However ia also accounts for unobservedheterogeneity and estimates strongly depend on modelspecification. Finally it is impossible to distinguish pure frompecuniary externalities and also there are no techniquesavailable to let the parameter vary across regimes

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Problems and extension

I do not take into account Human CapitalI do not account for Trade

Aggregate level trade (Interregional spillovers)Industry level trade (Inter-industries spillovers)

Altough LR statistics indicate Lag is better than Error,residuals are usually autocorrelated

Wrong W matrixStart from a more general specification (Spatial Durbin)

Models need also to be corrected for heteroschedasticity:it is difficult to adjust SE within Spatial Econometricsavailable routines

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Problems and extension

I do not take into account Human CapitalI do not account for Trade

Aggregate level trade (Interregional spillovers)Industry level trade (Inter-industries spillovers)

Altough LR statistics indicate Lag is better than Error,residuals are usually autocorrelated

Wrong W matrixStart from a more general specification (Spatial Durbin)

Models need also to be corrected for heteroschedasticity:it is difficult to adjust SE within Spatial Econometricsavailable routines

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Problems and extension

I do not take into account Human CapitalI do not account for Trade

Aggregate level trade (Interregional spillovers)Industry level trade (Inter-industries spillovers)

Altough LR statistics indicate Lag is better than Error,residuals are usually autocorrelated

Wrong W matrixStart from a more general specification (Spatial Durbin)

Models need also to be corrected for heteroschedasticity:it is difficult to adjust SE within Spatial Econometricsavailable routines

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Problems and extension

I do not take into account Human CapitalI do not account for Trade

Aggregate level trade (Interregional spillovers)Industry level trade (Inter-industries spillovers)

Altough LR statistics indicate Lag is better than Error,residuals are usually autocorrelated

Wrong W matrixStart from a more general specification (Spatial Durbin)

Models need also to be corrected for heteroschedasticity:it is difficult to adjust SE within Spatial Econometricsavailable routines

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Problems and extension

I do not take into account Human CapitalI do not account for Trade

Aggregate level trade (Interregional spillovers)Industry level trade (Inter-industries spillovers)

Altough LR statistics indicate Lag is better than Error,residuals are usually autocorrelated

Wrong W matrixStart from a more general specification (Spatial Durbin)

Models need also to be corrected for heteroschedasticity:it is difficult to adjust SE within Spatial Econometricsavailable routines

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Problems and extension

I do not take into account Human CapitalI do not account for Trade

Aggregate level trade (Interregional spillovers)Industry level trade (Inter-industries spillovers)

Altough LR statistics indicate Lag is better than Error,residuals are usually autocorrelated

Wrong W matrixStart from a more general specification (Spatial Durbin)

Models need also to be corrected for heteroschedasticity:it is difficult to adjust SE within Spatial Econometricsavailable routines

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Problems and extension

I do not take into account Human CapitalI do not account for Trade

Aggregate level trade (Interregional spillovers)Industry level trade (Inter-industries spillovers)

Altough LR statistics indicate Lag is better than Error,residuals are usually autocorrelated

Wrong W matrixStart from a more general specification (Spatial Durbin)

Models need also to be corrected for heteroschedasticity:it is difficult to adjust SE within Spatial Econometricsavailable routines

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

Problems and extension

I do not take into account Human CapitalI do not account for Trade

Aggregate level trade (Interregional spillovers)Industry level trade (Inter-industries spillovers)

Altough LR statistics indicate Lag is better than Error,residuals are usually autocorrelated

Wrong W matrixStart from a more general specification (Spatial Durbin)

Models need also to be corrected for heteroschedasticity:it is difficult to adjust SE within Spatial Econometricsavailable routines

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

List of References I

J. Z. Acs, L. Anselin, and A. Varga.Patents and innovation counts as measure of regionalproduction of new knowledge.Research Policy, 31:1069–85, 2002.

D. B. Audretsch and M. P. Feldman.Knowledge Spillovers and the Geography of Innovation,chapter 138-164.Elsevier B. V., 2004.

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

List of References II

L. Bottazzi and G. Peri.Innovation, demand and knowledge spillovers: theory andevidence from european regions.SSRN eLibrary, http://ssrn.com/paper=170590, 1999.Working Paper article.

L. Bottazzi and G. Peri.Innovation and spillovers in regions: Evidence fromeuropean patent data.European Economic Review, 47:687–710, 2003.

Giovanni Guastella Spillover Diffusion, Agglomeration and Distance

Introduction and LiteratureData and Methods

ResultsConclusion and Policy Implications

List of References III

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ResultsConclusion and Policy Implications

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R. Moreno, R. Paci, and S. Usai.Geographical and sectoral clusters of innovation in europe.Annals of Regional Sciences, 39:715–739, 2005.

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K. Pavitt, M. Robson, and J. Townsend.The size distribution of innovating firms in the uk:1945-1984.Journal of Industrial Economics, 55:291–316, 1987.

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Giovanni Guastella Spillover Diffusion, Agglomeration and Distance