PhD Project Theme: Trough Mountains and valleys – innovation and catching up dynamics I – Introduction The present document describes the proposed investigation PHD project. The first section of this document is the present introduction. The second section consists in a brief description of the project based in economic theories rooted in evolutionary economics, emphasizing the importance of innovation in the studied phenomena. In the third section we try to define the problem behind the investigation. Using the concept of innovation system (SI) we try to analyse the regional growth and development differences through out different regions. In this sense, we’ll introduce the concept of Regional System of Innovation, trying to analyse its importance in recent scientific literature and the way it’s been applied in empiric studies. Afterwards, we’ll analyse the role of innovation in regional economic growth (and its role in the rapid growth phenomena known as catching up). Finally, we try to relate the defined concepts with the Portuguese regions, accounting their disparities and similarities. In the fourth section we define the investigation questions. In the fifth section we present some objectives and an introduction to the methodology we’ll use in the research. The last section describes the bibliographic references used in this early work.
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PhD Project
Theme: Trough Mountains and valleys – innovation and
catching up dynamics
I – Introduction
The present document describes the proposed investigation PHD project.
The first section of this document is the present introduction. The second section
consists in a brief description of the project based in economic theories rooted in
evolutionary economics, emphasizing the importance of innovation in the studied
phenomena.
In the third section we try to define the problem behind the investigation. Using the
concept of innovation system (SI) we try to analyse the regional growth and
development differences through out different regions. In this sense, we’ll introduce the
concept of Regional System of Innovation, trying to analyse its importance in recent
scientific literature and the way it’s been applied in empiric studies. Afterwards, we’ll
analyse the role of innovation in regional economic growth (and its role in the rapid
growth phenomena known as catching up). Finally, we try to relate the defined concepts
with the Portuguese regions, accounting their disparities and similarities.
In the fourth section we define the investigation questions. In the fifth section we
present some objectives and an introduction to the methodology we’ll use in the
research.
The last section describes the bibliographic references used in this early work.
II – Contextualizing the investigation
Innovation is a prevailing concept in the modern times. It’s present in the news, in
political language, in the management language and in economic theory. The
importance of innovation can be observed in the recent growth of scientific research
using the concept and in the formulation of development politics, during the last to
decades, especially in European Union (EU) and in Asia (Fagerberg, 2004).
Despite that, innovation as socio-economic phenomenon is not something new, in fact,
as Fagerberg (2004) refers, innovation is something as old as mankind. Since the
beginning of history that wee use of inventions to produce new or better products,
services and processes, being them new metal swords or virtual prototyping machines
supported by TI services.
But the study of innovation itself, as an economic issue, didn’t exist until very recently.
Although Schumpeter (1934) as used the concept as something central to the economic
development process, something that thrives de growth cycles, it was only in 1960s that
innovation studies emerged as a independent field of research (Fagerberg, 2004).
In the last few years, those studies have been diversified, emphasising the role of
innovation in economic change (in the macro and micro levels). This view brings us
closer to what is known in the literature as evolutionary economics, a concept used to
relate a process of qualitative and economic change that occurs in certain period of time
(Fagerberg, 2002).
The role of innovation is essential in long term perspective of economic growth since its
function implies the introduction of novelty in the economic sphere. If the flux of
innovation was to stop the economies would fall in a steady state, as foreseen in
neoclassical economic literature (but contrary to the empiric evidence), with little or
zero growth (Fagerberg, 2004). This is obviously a very strong role in the definition of
the growth capabilities of different firms, sectors, regions and countries, since
innovation can be used as powerful variable in the explanation of performance
differences (Fagerberg, 2004). Therefore, the most innovative firms will tend to conquer
temporary monopolies or cost advantages or better differentiation skills, obtaining
higher market share and/or business volume.
These factors enlighten the importance of innovation, and how it is created, to both
political authorities and firm managers. But the innovation process is something that
reveals a certain complexity and that requires a multidisciplinary analysis (the academic
research reflects the fact that a single discipline can’t explain the total phenomenon)
(Fagerberg, 2004).
The complexity of the process of generating innovation is clear in its systemic form.
The innovation process involves a broad set of related activities whose results are many
times uncertain. Therefore, firms are not isolated in the production of innovation,
counting on the participation of several actors (publics institutions, laboratories,
Knowledge, Economic Structure, Openness & Absorption, Diffusion and Innovation) to
typify National Innovation systems. This methodology could be adapted to typify
regions instead of countries.
Muller et al. (2006) refer different regional typologies related to innovation used prior to
their work, such as the typology of Clarysse/Muldur (2001) used in the production of
the second European report on S&T indicators, the typology of regions developed by
PWC Consulting and Tsagaris Consult (2002) consult for DG Research, and the
typology of regional innovation needs by Muller et al. (2001) (on behalf of the DG
research). They use a similar method to classify the new entrant regions in the EU,
using five dimensions: knowledge creation, absorptive capacity, diffusion capacity,
demand and governance capacity. For each dimension they present a set of variables,
and then they proceed with a component analysis. In the end of the statistic process they
find five types of regions.
Similar methodologies have been used on other reports prepared for the European
Commission by various study groups. Usually the studies look through the scientific
literature and from an array of variables that characterize a region they perform a factor-
analysis and they build synthetic indicators that represent some dimension (that as also
some background in academic approaches). Then they use cluster analysis to group
regions, and classify then in terms of performance.
Our aim here is to combine this type of analysis, one that creates composite indicators
that represent the regions’ dynamic capabilities and then, in a second step, try to use
these dimensions as explanatory variables of the GDP per capita from the regions. If
necessary we would include some new variables that are more commonly used on other
type of models. Here we can follow the approach by Rodriguez Pose and Crescenzi
(2006) that tries to cross-fertilize 3 areas of regional studies (the analysis of the link
between investment in R&D, patents, and economic growth; the study of the existence
and efficiency of regional innovation systems; the examination of geographical
diffusion of regional knowledge spillovers) constructing a model of regional
performance (they conduct a multiple regression analysis for all regions of the EU-25,
including measures of R&D investment, proxies for regional innovation systems, and
knowledge and socio-economic spillovers). We have also to mention the Fagerber’s et
al. work (2004) that points out four dimensions to measure competitiveness
(technology, costs, capacity and demand) that can be used as an inspiration to build a
growth model closer to the “classical” econometric perspective. .
Since we proposed to study catching up, we’ll use the model to explain the
phenomenon. Taking inspiration from Fagerberg and Srolec (2005) important work on
catching up, well combine their approach with our model, identifying a set of
“capabilities” which, according to the literature, might be assumed to be of critical
importance for catch up (Fagerberg’s model is somewhat similar to the approaches
referred before since it formulates a synthetic empirical model and, with the help of
factor analysis, he identifies the dimensions and uses them to explain GDP levels and
GDP rates).
This analysis will use data from the Regio database from Eurostat on NUTSII regions
(and additional data from the Portuguese National Institute of Statistics - INE)
The second phase of the research will try to analyse the Great Lisbon urban area. This
will constitute a different article.
On this analysis we’ll explore innovation perspectives linked to the metropolitan
perspective. We’ll start to use our model from the first phase to explain the GDP and
GDP growth rate. If the model fails on this task we’ll try to adapt it to the urban
perspective. Network flows of social-habits, culture, economic factors and knowledge
tend to display a rather important role in the economy of the city (Simmie, 2005), and
will have to take into account these particular facts. Some further empiric work will be
needed, and qualitative data will be collected from interviews with specialists on urban
reality and networks.
We’ll use also quantitative data at the urban level, collected from Eurostat Sabe and
INE.
Finally, the last phase will consist on an extended analyse on metropolitan areas around
the world that stand out from the economic and technological point of view (the so
called mountains), that have some characteristics that allows them to grow rapidly, even
if the rest of the country seems a “depressed” valley. Using our reworked model we’ll
try to analyse some of the important factors that contribute to the catching up process
occurring in these areas.
Summing up the three analyses we should be ready to produce some policy
recommendations that can lead other regions to a catch up process in a near future.
VI – Work Plan
1st Phase – Research and bibliographical analysis on the state of the problem; data
collecting;
2nd Phase – Model construction and statistic validation;
3rd Phase – Interpretation of the first results; remarks on Portuguese regions and
catching up;
4th Phase –New data collection, possible field work on the social analysis of the city;
analysing the innovation urban perspective;
5th Phase - Re-writing the model at the city scale; remarks on Great Lisbon economic
and technological performance;
6th phase – Data collecting and reapplying the model at various “mountains” in the
world;
7th phase – Interpretation of results, remarks on urban catching up phenomenon around
the globe
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DIMETIC - Strasbourg – 29 March 2007
PhD ProjectTheme: Trough Mountains and valleys –
innovation and catching up dynamics
Vítor Hugo Ferreira
Technique Institute Leiria
ISEG – Technical University of Lisbon
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Presentation Structure
1. Introduction
2. Situating the Research
3. Theoretical Background – a brief review
4. Research Motivation
5. Research Questions
6. Exploring the Methodologies
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Introduction
The first phase of the Project aims to analyse theperformance of several regions in Portugal.
The second phase aims to analyse the urban areaof Lisbon, the Portuguese “region” with higherincome (about 140% of the mean).
The last goal is to build a theoretical model that wecan apply to the several “mountains” ofdevelopment, explaining the development of theseareas, comparing monocentric countries likePortugal to other similar countries.
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Situating the ResearchInnovation – a systemic view Innovation process involves a broad set of related activities whose
results are many times uncertain; Firms are not isolated, counting on the participation of several
Rosenberg (1976, p.75) confirms this systemic vision: “Not a single well defined act but a series of acts closely linked to
the inventive process. An innovation acquires economicsignificance only through an extensive process of redesign,modification and a thousand small improvements”.
Nowadays, innovation is understood as something that resultsfrom a “model” that integrates a set of systems, composed bynetworks of firms and institutions (innovation systems theory);
But... it seems that the systemic perspective still needs arefinement (Edquist, 2005).
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Theoretical BackgroundInnovation Systems – the Territory Perspectives
National Innovation Systems (NIS) Some commonly cited definitions: Lundvall (1992), Freeman (1987)
Nelson (1993) Patel and Pavitt (1994), Metcalfe(1995), Edquist (2005);
“the system of interacting private and public firms (either large or small),universities, and government agencies aiming at the production of scienceand technology within national borders. Interaction among these units maybe technical, commercial, legal, social, and financial, in as much as thegoal of the interaction is the development, protection, financing, orregulation of new science and technology”,(Niosi, Saviotti, Bellon and Crow, 1993);
New forms of innovation systems tend to emerge- geographical(Regional Innovation System – RIS) and economical (SectoralInnovation System);
Since 90’s, the geographical perspective has gained a rather largeimportance, both among the academic research and the politicalauthorities, (this view is rather evident within the EU) (Doloreaux andParto, 2004).
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Theoretical BackgroundInnovation Systems – the Territory Perspectives
Regional Innovation Systems - OriginsThe origin of the concept can be traced back from two main fields of
research (Doloreaux and Parto, 2004):1. The first one accounts for innovation systems theory that is based on
evolutionary theories of economic and technological change, and triesto conceptualize innovation as an evolving complex process (Edquist,2004). The social aspect of innovation is related with the collectivelearning process between several departments of a firm, as well asexternal collaboration with other firms, financial institutions, universities,technological centres, etc (Cooke et al. 2000);
2. The second body of literature is connected to regional science and itsmain concern with the understanding of the social-institutionalenvironment where innovation arises (Doloreaux and Parto, 2004).Regional science deals simultaneously with the role of proximity (thebenefits from local advantage and spatial concentration) and with theset of norms through which the process of knowledge creation occurs(Kirat and Lung, 1999; Doloreaux and Parto, 2004).
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Theoretical BackgroundInnovation Systems – the Territory Perspectives
Regional Innovation Systems – the concept RIS: a set of private and public agents, formal institutions
and other organizations that interact (through formal andinformal relations) whose interactions lead to theproduction, diffusion and utilisation of knowledge(Doloreux, 2003; Doloreaux and Parto, 2004);
The concept enhances the fact that firm trajectories, interms of learning and innovation are results of socialinteraction. These interactions exceed the industrialenvironment and reach the area linked to universities,research laboratories, learning and technology transferinstitutions (Doloreaux and Parto, 2004).
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Theoretical BackgroundInnovation Systems – the Territory Perspectives
RIS - Empirical ApproachesWe can distinguish two lines of investigation (Doloreaux and Parto,
2004):1. One tries to explore some aspects of the regional innovation
capabilities, as a way to analyse the main elements of the system(the institutions, the firms and the innovation profile of the region –accounting its levels of education, the regional R&D, thetechnological outputs, etc.) (Doloreaux and Parto, 2004). Anothergoal is to explain the regional differences in terms of innovationactivities and competitiveness;
2. The second builds upon the notion that a RIS can exist in everyregion (Doloreaux and Parto, 2004). A RIS is identified from acombination of key indicators on several aspects that include frominstitutional capability, regional competence to innovation capabilitiesand the interaction between actors (Cooke et al., 1998; Doloreauxand Parto, 2004).
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Theoretical BackgroundRegions, Economic and Technological Development and“Catching Up”
Regional Growth Regional economic growth theory shows us that there are basic dimensions
that explain economic growth that include economic and technologicalaspects (Ho, 2004);
The traditional growth theory (Solow, 1956) and the new growth theory(Romer, 1990), conclude that the growth path oh each region and countrywill converge (conditional or unconditionally) to a certain point, even thoughthey emphasize the role of technological change in this process;
Some more recent literature, with a “Schumpeterian”/Evolutionaryfoundation, argues that technological change is a strong distortion factor ongrowth paths, opening the door to regional disparities;
Dalum, Laursen and Verspagen (1999) examined the relation betweentechnological development and economic growth, demonstrating thatspecializing in different technologies and sectors has an important impact ineconomic growth;
Economic literature tells us that the pattern of technological development asa crucial importance in the comprehension of regional development.
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Theoretical BackgroundRegions, Economic and Technological Development and“Catching Up”
Catch Up “Catch up” defines the country or region’s ability to shorten the difference of
productivity and income to another region or country more developed.(Godinho and Fagerberg, 2004);
Several authors tried to identify some situations where the catching upprocess as occurred – USA and Germany in the second half of the XIXcentury seem evident situations, as well as the Japan of the first half of theXXth century. Korea, Taiwan and Ireland are other much cited cases;
Other authors try to explain why and how this phenomenon does occur:- Abramovitz (1986, 1994) is one of the lead authors of this approach;- But Fagerberg (1988) and Verspagen (1991), whose work integrate the
importance of innovation, imitation and other efforts linked to thecommercialization of technology, as producers of economic growth, are thereference to this project.
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Research MotivationPortuguese Regions and their growth paths
Are there Portuguese Regions?
When we mention the concept of RIS we are implicitly using theconcept of region. This way the cultural and historic background(culture, language ands territory) can be vital on the definition ofregion (for example, the Basque region). The definition of region canalso be built upon a distinctive political and administrative division (asthe German federalism and other regions inside centralizeddemocracies like France and Italy). A RIS should include the notionof how can the institutional and cultural environment speeds ordelays the innovation process (Wolfe, 2002);
Taking into account these definitions, it’s difficult to find in a smalland homogeneous country like Portugal regions that can isolatethemselves from the remaining portion of the country, at a cultural,social and historic level. Therefore, we can only ´look at the politicaladministrative division perspectives.
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GDP per capita Evolution, 1995-2003
•Source: Mateus (2006)
Research MotivationPortuguese Regions and their growth paths
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Research MotivationPortuguese Regions and their growth paths
Productivity Evolution, 1995-2003
•Source: Mateus (2006)
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Research MotivationPortuguese Regions and their growth paths
Source: Laranja (2006)
R&D intensity in the 90s
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Industrial GVA (Gross Value Added) in High/medium technology sectors as a % of the total industry (1995 and 2000)
Research MotivationPortuguese Regions and their growth paths
Source: Laranja (2006)
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Research MotivationUrban Area of Lisbon
Some Facts: Great Lisbon GDP’s per capita, measured in purchasing power
standards (pps), was, in 2002, higher than the one from Madrid andBarcelona (Godinho, 2006). In 2002, the values for those three citieswere 28, 27 and 26 thousand euros per inhabitant (Godinho, 2006).
This is a remarkable fact that surpasses the mere traditional regionalanalysis. What explains that Lisbon excels so much?
One might argue that industrial specialization, human resources,levels of education technological performance can be some of thereasons behind this fact, and our aim is to fully understand thisurban phenomenon;
At a global scale we can find many other examples: Shanghai’s GDPper capita is fifteen times higher than the poorest region in China(Godinho, 2006). In India, the region of Banglore, in Brazil the areaof São Paulo, in Mexico the area of Monterey, are other examples of“mountains” of economic performance that underwent a “catching up”process.
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Research Questions
Regions and technological and economicprogress
What is the growth dynamic of Portugueseregions?
What type of RIS are the PortugueseRegions? (stagnating, growing?)
Which factors explain their growth disparities?(bottlenecks or good actors?)
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Research QuestionsExploring the Methods of analyses I
First step – shift-share analyses – Are the regions growing/stagnating because of their structureor because their industries perform better than the same industries in other regions?
We have a study area in which employment and population are evolving. Total employment inour area is e, and that in the ith activity is ei . We have a larger frame reference area, usually thenation, where total employment is E, and that in the ith activity is Ei . The shift-share model saysthat growth in the study area’s ith activity employment is a function of:
The study area’s share of national (or regional) growth. The mix change in activities. And the shift change of activities toward the study area. This says that change in employment in the study area’s ith activity from time t to time t+n can be
measured:
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Second Step – What type of RIS can we find? Our analysis builds upon the fact that we can classify regions from their
systemic indicators and then weigh the explanatory power of theseindicators on different GDP levels and growth rates.
Freeman (1995) and Cook (2003) point out five dimensions linked toEducation, Knowledge Transfer, Business R&D, Linkages, Investment andCommunications, that can be used as composite innovation systemsindicators.
Godinho et al. (2006) build up a framework of analysis that uses 30variables in 8 dimensions (Market conditions, Institutional conditions,Investment climate, Scientific Knowledge, Economic Structure, Openness &Absorption, Diffusion and Innovation) to typify National Innovation systems.This methodology could be adapted to typify regions instead of countries.
Muller et al. (2006) use a similar method using five dimensions: knowledgecreation, absorptive capacity, diffusion capacity, demand and governancecapacity. For each dimension they present a set of variables, and then theyproceed with a component analysis. In the end of the statistic process theyfind five types of regions.
Research QuestionsExploring the Methods of analyses I
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Research QuestionsExploring the Methods of analyses IMeasuring RIS - example
Source: Muller et al. (2006)
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Our aim here is to combine this type of analysis, one that createscomposite indicators that represent the regions’ dynamiccapabilities and then, in a second step, try to use these dimensionsas explanatory variables of the GDP per capita from the regions;
Since we proposed to study catching up, we’ll use the model toexplain the phenomenon. Taking inspiration from Fagerberg andSrolec (2005) important work on catching up, well combine theirapproach with our model, identifying a set of “capabilities” which,according to the literature, might be assumed to be of criticalimportance for catch up (Fagerberg’s model formulates a syntheticempirical model and, with the help of factor analysis, he identifies thedimensions and uses them to explain GDP levels and GDP rates);
This analysis will use data from the Regio database from Eurostaton NUTSII regions (and additional data from the INE)
Research QuestionsExploring the Methods of analyses I
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II – Great Lisbon II – Great Lisbon
How to explain the level of wealth of GreatLisbon?
What is the social-historical role of the city ininnovation, and hence, in economic growth?
Research Questions
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Research QuestionsExploring the Methods of analyses II Quantitative analyse with foundation on the urbanization economies
(i.e. the benefits coming to firms by being located in a heterogeneousindustrial environment – specialized suppliers, demanding market,experienced labours, knowledge organizations, etc) + RIS analysesbased on previous model;
Network flows of social-habits, culture, economic factors andknowledge tend to display a rather important role in the economy ofthe city (Simmie, 2005), and will have to take into account theseparticular facts. Some further empiric work will be needed, andqualitative data will be collected from interviews with specialists onurban reality and networks;
We’ll use also quantitative data at the urban level, collected fromEurostat Sabe and INE.
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Great cities and Growth
How does Great Lisbon compare to otherregions? (Lisbon within Portugal vis-à-visother capitals on small monocentriccountries).
How the growth in Lisbon can have an affecton other regions in Portugal?
Research Questions
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The first question can use themodel/methodology developed in theprevious moments.
The second question is difficult to analyseempirically. One idea can be to use data thatrelates firms in other regions with Lisbon, andsee if they use the previous as a source ofinnovation.
Research QuestionsExploring the Methods of analyses III