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Institutions, Innovations, and Growth

Tugrul Temel

Agricultural Economics and Rural Policy Group, Wageningen UniversitySchool of Economics, Inholland University

The NetherlandsJuly 2004, Sophia University, Tokyo

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Plan of Presentation

Research agenda Case study

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RESEARCH AGENDA

Issue Conceptual framework Systems approach A grand network of networks Network performance indicators in growth

models Develop hypotheses to address the issue

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Issue

Why in some economies did a process of technological innovation create new wealth and economic growth, while in some other economies the process remained unaffected?

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Conceptual Framework

Innovation system (IS)– a set of agents that jointly/individually contribute to the

generation, diffusion, and use of improved or new knowledge and that directly/indirectly influence the process of technological change

Institutions (IPR, PPP) impact the performance of IS and hence the process of technological change

– K=K(IPR, PPP) : Institutional change affects the organization of K

– T=T(K(IPR, PPP)) : Technological change and growth are endogenous to IS

where technology (T), variable (R), intellectual property rights

(IPR), public-private partnerships (PPP), knowledge generation, diffusion, application (K)

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Systems Approach

A system– is a grand network of networks– has a goal and optimizes it subject to system constraints

An individual network– optimizes its own objective subject to network-specific constraints– objectives of individual networks agree with the system goal– constraints of individual networks agree with the constraints of the

grand network The grand network is greater than the sum of individual

networks.– The grand network must have one new property, which individual

networks cannot support individually. For instance, the spatial arrangement and size structure of individual trees in a forest will create different habitats for wildlife species.

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A Grand Innovation Network

Institutions affect network linkages

Learning through interactions of networks promotes innovations

Innovations yield growth

Social Policy

Economic

Interface

A Grand Innovation Network

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Linkages in a Grand Network

P PE PS PI

EP E ES EI

SP SE S SI

IP IE IS I

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Innovation Network

Institutions affect patterns of knowledge flow

Knowledge generation

Knowledge diffusion

Knowledge application

Knowledge financingKnowledge regulation

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Network Performance

Performance measured by improvement in the grand network goal

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Hypotheses Development

Describe the cause-effect structure of individual networks

Develop hypotheses using this structure Contribution of individual networks to the

grand network goal

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Exogenous Growth Model

The Solow-Swan model – K and L inputs Emphasize the role of capital accumulation Growth compatible with exogenous labor-

augmenting technical progress Growth is unexplained (the Solow residual or TFP) Assumptions: productivity level and the rate of

technical change are the same across nations, empirically not verifiable

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Endogenous Growth Models

Economics of ideas associated with increasing returns and imperfect competition (high fixed cost and low marginal cost)

Relax the assumption of diminishing returns to capital Technological progress endogenous to the model Romer (1986) – R&D gives rise externalities that affect the stock of

knowledge available to firms Production by firm-specific variables (like R&D) and a technology index

(learning by doing) which is a function of knowledge stock available to firms.

Public-good characteristics of knowledge generating activities, ie, R&D R&D based endogenous growth models model innovation (the

accumulation and diffusion of technological knowledge) as the driving force of growth. Ideas are generated by R&D investment of firms

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Evolutionary Growth Models

Model technological advancement as a disequilibrium process involving ex-ante uncertainty, path-dependency, long adjustment processes.

Emphasize on strategic firm-specific capabilities rather than just investment in human capital and R&D – R&D, managerial skills, collective learning, social capital, networking, cooperation with universities, property rights

The specific capabilities are dynamic being the result of strategic decisions

Take into account the institutional framework – strengthen institutions

As capacities are difficult to measure at the aggregate level, it is also difficult to use this approach to measure growth

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CASE STUDYAgricultural Innovation System

Policy units [P] Research & extension organizations [R] Agricultural banks [B] Farmers & their organizations [F] Input suppliers [I] Marketing firms [M] Processing firms [Pr] Consultancy firms [C] NGOs, Donors, Int’l organizations [X]

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Analysis of AIS

• Introduce a graph-theoretic method to assess organizational linkages in a system

• Apply the method to examine the agricultural innovation system of Azerbaijan.

i. Map organizational links in the innovation systemii. Describe the structure of the system (identify

leverage points, dominant, and subordinate organizations)

iii. Suggest ways to improve the workings of the system

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Data and Methodology

• Data collected by structured interviews• A systems methodology is adopted because

i. interaction is essential to diffuse knowledgeii. learning takes place everywhere in society

• Seven graph theoretical concepts are used to identify cause-effect pathways in the system

• Who and where to use the methodi. to assess the impact of alternative interaction

pathways on the system goalii. to identify the constraints of and opportunities for

the system to be effective

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Mapping organizational links

Linkage Matrix described bythree types of linkages: formal (f), informal (i), and mixed (m)four levels of linkage strengths: strong (s), medium (m), weak (w), none (n), andfive groups of linkage mechanisms: planning and review, program activities, resource use, information, & training.

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X00

D0

00F00

0M000

0I00

0000C00

000E

0R

000P

1111

111111

1111

11

11111

1

11

1

fmfmmwfsfwfm

fmmmiwfmmmimim

mwiwimim

mwmmimfm

fwfmfmfmfm

fwfw

fwimiwfwfw

fwimimmmmwfwfw

fmmwfwfwfw

Linkage Matrix

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Mapping organizational links

Not fully identified, i.e. of a total of 72 relations, only 45 are identified,Density: 0.63 (= 45/72)Flexible: of 45 relations, 25 formal, 11 informal, 9 mixedAll relations are formal and weak (fw) between the public components, while relations are mixed and mostly medium between the private componentsInformal relations are common between the public and the private componentsX has relations with all the components in the AIS

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Describing the structure

Linkage Matrix: assign 0.3 to a weak, 0.6 to a medium, and 1 to a strong relation and denote the resulting matrix as S[Scaled]Define the C-E coordinates implied by S[Scaled] and scatter plot them in Figure 1

D is dominant (i.e source of influence), R is highly interactive with the rest of the system, and is followed by X, I, and F. P is subordinate (i.e., sink of influence)

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X6.06.03.01003.06.0

6.0D6.03.06.006.06.06.0

00F3.0003.06.06.0

3.006.0M0006.06.0

3.06.06.00I006.06.0

3.00000C003.0

3.06.03.0000E3.03.0

3.06.06.06.03.003.0R3.0

6.00003.03.03.03.0P

S[Scaled]

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Figure 1. The cause-effect structure of S[Scaled]

X

R

P

I

E

D

M

C

F

0

1

2

3

4

0 1 2 3 4

Cause

Eff

ect

Cause-effect Diagram

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Describing the structure and developing hypotheses

Use only those linkages established through 5 types of linkage mechanisms and denote the resulting matrix as S[Mechanism]Define the C-E coordinates of S[Mechanism] and scatter plot them in Figure 2

D remains to be dominant, which is followed by I.X is the most interactive, followed by F.P remains to be the most subordinate component

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Key conclusions

1. The public component is under construction.lacking sectoral priorities, clear organizational mandates and objectives, qualified human resources, physical and financial resources, and motivation to initiate interactions with the private sector.

2. The private component is attracted to activities of international organizations.

3. The public and private components are isolated and have limited basis for interaction.

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Future research

1. Analysis of cases in which rare but influential interactions take place between the organizations

2. The systems approach should be reformulated as a mathematical model to allow testing of specific hypotheses.