Transcript Presentation 8 Detecting the Parameters of Interaction and - e

University of Thessaly
Department of Planning and Regional Development
Graduate Program in European Regional Development Studies
Fall Semester, 2011-12
Course:
The Geography of European Integration: Economy, Society and
Institutions
Lecturers: Petrakos G., Camhis M., Kotios A., Topaloglou L., Tsipouri L.,
Bogiazides N.
UNIVERSITY OF THESSALY
Department of Planning and Regional Development
Polytechnic School
Post Graduate Program: European Regional Development Studies
Course: The Geography of European Integration: Economy,
Society and Institutions
Detecting the parameters of interaction and
development along the EU Border Space
Dr. Lefteris Topaloglou
12th December 2011, Volos
Introduction
• The abolition of the artificial impediments of cross border
interaction within the EU, has not only reduced barriers of trade
but also brought to the fore a new mix of threats and
opportunities that has put the EU border regions in a state of flux
• Since the role of boundaries as obstacles to interaction
institutionally, at least fades out, the potential of border regions
has to be analyzed not only in relation to their national centers
but also in relation to their neighbors and the enlarged EU space
as well.
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Objective
…detect the economic, spatial and social determinants of growth in
the EU border regions, in order to provide a better insight into
theory and policy making
Methodology
Empirical model for growth performance in the EU border
regions, taking into consideration the pertinent theoretical
discussion and compiling a cross-section econometric model
Estimation Technique
…accounts for growth performance in the 349 EU NUTS III border
regions during the period 2000-2006, incorporating quantitative
and qualitative parameters of growth.
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Economic geography literature (1)
 The intensity of interaction drops where a border crosses a place
(McCallum, 1995; Helliwell, 1997; Bröcker, 1998)
 In a closed economy, border regions are zones of low opportunities due to
their regional character, and distorted areas in terms of market size
(Dimitrov et.al., 2002; Hoover, 1963; Hansen, 1997; Lösch, 1944; Cristaller,
1933 )
• Market size of the neighbouring countries affects significantly the location
decision of firms and consequently the economic geography of borders
(Damijan and Kostevc, 2002; Amiti, 1998; Hanson, 1998; Resmini, 2003;
Fazekas, 2003)
 Placing a border and removing a border is not a symmetric action due to
the significant role of “initial conditions” (Petrakos and Topaloglou, 2008;
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Economic geography literature (2)
 Market potential and proximity to markets of each border region in
the broader European space matters (Harris, 1954; Melchior, 2008).
 Low trade costs and increasing return of scale drive firms closer to
large markets (Weber, 1909).
 In open economies, some places offer cheaper access to foreign
markets, due to locational advantage (Villar, 1999).
 Foreign demand drives domestic firms to relocate closer to the
borders. However, foreign supply drives domestic firms to relocate to
the interior, away from the foreign competitors (Brülhart et al.
(2004).
 Trade opening is associated with spatial divergence or convergence
in border space. Previously less developed regions with better access6
Interdisciplinary approach
 Traditional studies on border areas are often enclaved in a “soledisciplinary approach” or in a “unitary case syndrome” without providing
a substantial added value on border theory (Paasi, 2005, Agnew, 2005).
 Recently, “access” to foreign markets is examined in a broader
framework, taking into consideration transport and telecommunication
networks, institutional factors, and a series of political and cultural
parameters (Topaloglou et. al. 2005).
 Perceptions and images of people occupy a fundamental position to
interpret cross border economic interaction and growth (Van Houtum,
1999, Barjak, 1999).
 Economic potential of border regions is determined among others, by
culture, language, nationality and other socioeconomic and geopolitical
characteristics of border regions (Reitel, et al. , 2002; Arbaret-Schulz et al.,
2004).
The New Economic Geography (NEG)
paradigm
 Firms, tend to move towards the large markets due to reduction in trade
cost and nominal wages (Krugman, 1991, Fujita, 1993).
 Workers are attracted by higher real wages and the wider product variety
found in agglomerations, making the location of firms in the actual place
more profitable (Krugman, 1991, Fujita, 1993).
 Centripetal forces (market size effects, thick labor markets, informational
spillovers) increase the variety of goods, decrease prices and raise profits if
trade costs fall below a critical level (Krugman, 1998).
 However, centrifugal forces (immobile factors, land rents, pure external
diseconomies) come to the fore mainly due to congestions costs and
intensive competition (Tabuchi and Thisse (2002).
Theoretical Model (a)
The economic geography of border regions
BEFORE the abolition of border obstacles
Border
Line
WEST
EAST
ε΄
Producer D
Ζ
Χ
Κ Producer C
Ο
Producer Β
Y
Producer Α
Theoretical Model (b)
The economic geography of border regions
AFTER the abolition of border obstacles (a)
Border
Line
WEST
EAST
ε΄
Producer D
Ζ
Χ
Κ
Producer C
Ο
Producer Β
Y
Producer Α
Theoretical Model (c)
The economic geography of border regions
AFTER the abolition of border obstacles (b)
Border
Line
WEST
EAST
ε΄
Producer D
Ζ
Χ
Κ Producer C
Ο
Producer Β
Y
Producer Α
Empirical model for growth performance (1)
• Cross-section Econometric model for growth performance in EU
border regions
• 349 EU NUTS III border regions.
• Quantitative (“hard”) and qualitative (“soft”) data (sources:
ESPON database 2006 & EXLINEA FP5 Research Project,
National Statistics).
• WLS method (weighting variable: population).

Yr ,T  a 0   (a X  , r , t )   r , t
 1

Y: dependent variable, X: set of λ independent variables, aλ: set of
estimators of the λ independent variables, a0: constant term, ε:
disturbance term, r: region, t: initial year (2000), T: period (2000-2006).
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Empirical model for growth performance (2)
• Dependent variable (2000-2006): per capita GDP real growth
performance in the EU (PCGDPGR0006)
• Independent variables (2000):
 Per capita GDP (PCGDP00)
 Number of employees in the primary sector (PRIMEMP00)
 Spatial structure (SPATSTRU00); ESPON data, dummy variable (1:
city core region, very densely populated region, 0: rural region, less
densely populated region)
 Accessibility (ACCESS00); categorical variable, ESPON data (0-4,
combined effect of geographical position and location advantage
provided by the transport system)
 Coast (COAST00); dummy variable (1: coastal region, 0: landlocked
region)
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Empirical model for growth performance (3)
• Independent variables (2000) (cont.):
 Environmental hazards (ENVHAZ00), composite ESPON variable
 Minorities (MINOR00); dummy variable (1: strong presence, 0: weak /
no presence)
 Religion (RELIG00); dummy variable (1: common / similar religion
with the neighboring region, 0: different religion with the neighboring
region)
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Determinants of growth performance (1)
Independents
PCGDP00
PCGDP00^2
PRIMEMP00
SPASTRU00
ACCESS00
COAST00
ENVHAZ00
MINOR00
RELIG00
2
R adj
F
N
Dependant variable: PCGDPGR0006
b-estimator
t-statistic
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-3.78 10
-10.21***
-10
6.35 10
6.93***
-0.001
-1.85*
0.049
1.73*
0.074
3.69***
0.067
2.05**
-0.001
-3.14***
0.199
2.40**
0.185
2.31**
0.733
101.37
329
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Determinants of growth performance (2)
• Determinants of growth performance:
 PCGDP00: non-linear pattern of growth; after a threshold (29,764
euros / inh.) the most dynamic border regions (9 regions) grow faster,
and divergence forces dominate; co-existence of convergence and
divergence forces in different proportions
 PRIMEMP00: negative impact; primary sector is a low-productivity
sector
 SPATSTRU00: positive impact; core and more densely populated
border regions generate higher rates of growth performance
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Determinants of growth performance (3)
• Determinants of growth performance (cont.):
 ACCESS00: positive impact; transport infrastructure endowments
generate higher growth performance, contributing to the coherence of
border areas
 COAST00: positive impact; advantage of the coastal border regions
over the non coastal
 ENVHAZ00: negative impact; environmental hazards put economic
prosperity in danger
 MINOR00: positive impact; strong presence of minorities contributes to
growth
 RELIG00: positive impact; common/similar religion contributes to
growth: confirmation of earlier arguments e.g. Weber, 1930
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Conclusions
Methodology:
• The study broadens the discussion on the growth determinants of
border regions, taking into consideration not only quantitative (“hard”)
but also qualitative (“soft”) parameters.
Theory:
• The study of border regions needs an interdisciplinary approach.
• Co-existence of convergence and divergence forces; Non-linear growth
pattern; Coexistence of neoclassical and “cumulative” approaches?
Policy Making:
• What should be the mix of cross-border policies in order to contribute
to the decline of economic heterogeneity, to the increase of spatial
coherence, and to growth?
• The principle “one size fits all” does no longer seem appropriate.
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Some Policy Recommendations for discussion
Establishing Environmental Trust
Set up of “Clever” Actions
Joint Cross Border Planning
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Thank you for your attention!
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