Transcript Regional Competitiveness in the New Europe

ECONOMIC INTEGRATION, GROWTH
CYCLES AND THE BEHAVIOUR OF
REGIONAL DISPARITIES ACROSS
EUROPE
S. Brettell*, B. Gardiner*, R. Martin** and P. Tyler***
*Cambridge Econometrics
**Department of Geography, University of Cambridge
*** Department of Land Economy, University of Cambridge
Presentation, RSA Conference, Lisbon
April 2007
1
Introduction
• Europe is at historical cross roads
• Challenges of globalisation, intensifying
•
•
•
international competition and new knowledge
economy
Enlargement to include several low income, old
economy states
The reconfiguration of the Structural Funds in
favour of new enlargement states
Key imperative of improving the competitive
position of the EU
2
Introduction
• Three key spatial aims:
• Spatial-economic integration - major
•
•
advances over past 25 years (single
market, monetary union, etc)
Regional cohesion - promoting regional
convergence in per capita GDP
Improving regional competitiveness
throughout the Union
3
Structural Funds:
Convergence and
Competitiveness
Objectives in
EU25
4
European Commission, 2006
Introduction
• Within this context, focus here is on the
•
•
•
•
implications of economic integration for regional
cohesion (regional disparities)
Will economic integration in EU promote regional
convergence or divergence?
Some 15 years ago Krugman (1993) broached
this question by drawing inferences from USA
experience
USA has long been the sort of economic and
monetary union that EU aspires to
So it might hold clues as to what expect in EU as
5
it becomes increasingly integrated
Krugman’s Thesis
• Krugman uses experience of Massachusetts,
and other US regions (and cities) to theorise
about combined impact of 1992 and EMU on EU
regions:
 Integration leads to increased trade which leads to
increased regional economic specialisation
 Specialisation means instability of regional
exports and idiosyncratic regional shocks
 Regional instability reinforced by procyclical
capital movements (export booms reinforced by
investment booms, and vice versa in slumps)
 Factor mobility leads to divergent long-run
6
regional growth
Krugman’s Thesis
• Argument is that EU economic integration will
•
make American-style regional fluctuations more
pronounced
Evidence adduced to support this contention:
 Broad US regions more specialised than European
countries
 Industries far more localised in US than in Europe
 Employment growth much less stable (more cyclical)
in US regions and cities than in EU countries
 Disparities in long-run growth rate of GDP per capita
far greater amongst US regions than amongst EU
countries
7
Krugman’s Thesis
• Problems with Krugman’s argument:
• Comparison of US regions and cities with
•
•
•
European countries misplaced (different sizes,
different types of economic unit)
Level of spatial disaggregation in general too
coarse to pick up localisation effects of increased
economic integration in EU
Analysis only up to late-1980s, and hence not in
period of main EU economic integration
Fails to compare regional convergence/divergence
over time (trends and cycles)
8
Questions
• Given Krugman’s argument, how do regional
•
•
•
disparities in the USA (a long-established economic
and monetary union) behave over growth cycles
(convergence or divergence)?
Has behaviour of regional disparities (convergence
or divergence) in Europe changed as integration
has progressed?
Has Europe’s pattern become more like that of the
US?
How do different types of European region behave
over the economic cycle? Has this pattern changed
with increasing integration?
9
The Evidence
• Look at NUTS 3 data for EU15 ‘established’
•
•
union areas
..and compare with the CSA
(metro/micropolitan) ‘FUR’ data for US
(covering 93% of US population)
1980-2005, in five year growth zones to
capture cyclical content
10
Real GDP growth US and EU
8.0
7.0
6.0
5.0
4.0
3.0
2.0
1.0
0.0
-1.0 1981
-2.0
-3.0
US
1986
1991
1996
2001
EU15
11
High income volatility of the US
states
11
Massachusetts
New York
Illinois
Minnesota
Florida
Texas
Colorado
California
9
7
5
3
1
-1
-3
1970 1975 1980 1985 1990 1995 2000 2005
12
Income per capita US Metropolitan
and Micropolitan FUR Areas, 2005*
Personal income, 2000 $
30,000 to
26,000 to
22,000 to
0 to
No data
Metropolitan: at least one urbanized area
(county) has a population of at least 50,000.
Micropolitan: 10,000-50,000, NB nonCSA=6.6% population, 4.8% personal income
in 2005. *CE projection from 2004 base
62,000
29,999
25,999
21,999
13
US regional income distribution
for 938 CSAs* is even..
1
cugdprel
0.8
0.6
0.4
0.2
0
0
0.2
0.4
0.6
0.8
1
cupoprel
*Estimated
population = 277m in 2005
Average Personal income per capita = $27,100 2000 prices
14
.. In spite of sustained differences
in US real GDP growth rates
Source: BEA Oct 2006: http://bea.gov/newsreleases/regional/gdp_state/2006/xls/gsp1006.xls
15
accentuated in accelerating GDP
growth rates by US state..
10
y = 0.3567x3 - 2.9913x2 + 8.7825x - 5.6575
2
R = 0.5587
2004-2005 %change GDP
8
6
4
2
0
0
1
2
3
4
5
6
-2
1997-2004% pa change GDP
16
..and income per capita for CBSAs shows
just random shocks over time
8
6
4
2
0
-2 0
200
400
600
800
-4
-6
1985-90
1995-2000
Linear (1995-2000)
17
Migration is the reason:
Population versus income change US states
6
6
5
5
4
4
3
3
2
2
1
1
0
-1 0
1
2
3
4
5
6
7
8
-2
-1
0
-1 0
1
2
3
4
-2
6
5
5
4
4
3
3
2
2
1
1
0
-1 0
1
2
3
4
5
6
7
8
0
-1 0
-2
-2
1990-95
6
7
8
1
2
3
4
5
6
7
1995-2000
6
5
4
3
2
1
0
-1 0
-2
0.5
1
1.5
2
2.5
2000-2005
3
3.5
4
9
1985-90
1980-85
6
5
4.5
18
8
But the pecking order has not changed
very much
US MSA 1980-2005 levels of income and income divergence o
mean rel (SD/mean rank
MSA
)rel US
income
2005 US
rank 2005* diff rank
Bridgeport-Stamford-Norwalk, CT (MSA)
58,989
1.79
1.53
1
1
0
San Francisco-Oakland-Fremont, CA (MSA)
45,754
1.44
1.24
2
2
0
San Jose-Sunnyvale-Santa Clara, CA (MSA)
45,201
1.42
1.42
3
3
0
Washington-Arlington-Alexandria, DC-VA-MD-WV43,812
(MSA)
1.36
1.13
4
4
0
Naples-Marco Island, FL (MSA)
38,491
1.35
1.12
5
11
-6
New York-Northern New Jersey-Long Island, NY-NJ-PA
40,473 (MSA) 1.30
1.14
6
7
-1
Trenton-Ewing, NJ (MSA)
41,584
1.30
1.20
7
6
1
Boston-Cambridge-Quincy, MA-NH (MSA)
43,026
1.29
1.40
8
5
3
Anchorage, AK (MSA)
33,588
1.27
0.36
9
38
-29
Sebastian-Vero Beach, FL (MSA)
36,217
1.24
1.22
10
18
-8
Hartford-West Hartford-East Hartford, CT (MSA) 38,268
1.24
1.03
11
12
-1
Boulder, CO (MSA)
40,325
1.22
1.40
12
8
4
Reno-Sparks, NV (MSA)
36,330
1.21
0.96
13
17
-4
Barnstable Town, MA (MSA)
38,683
1.21
1.17
14
10
4
Napa, CA (MSA)
37,905
1.20
1.14
15
13
2
Minneapolis-St. Paul-Bloomington, MN-WI (MSA)37,893
1.20
1.14
16
14
2
Seattle-Tacoma-Bellevue, WA (MSA)
39,633
1.20
1.24
17
9
8
Ann Arbor, MI (MSA)
35,486
1.19
1.02
18
25
-7
Sarasota-Bradenton-Venice, FL (MSA)
34,940
1.19
1.03
19
28
-9
Denver-Aurora, CO (MSA)
37,573
1.19
1.19
20
15
5
19
So GDP/capita convergence/divergence
oscillates as ‘catch up’ in US states
1980-85
1985-90
y = -0.1257x + 1.3179
R2 = 0.1015
0.3
0.3
0.2
0.2
0.1
0
8.5
9
9.5
10
10.5
y = -0.0246x + 0.3384
R2 = 0.0052
0.4
1985-90
1980-85
0.4
Jackso n, W Y -ID
M icro p o lit an SA
0.1
0
11
8.5
-0.1
-0.1
-0.2
-0.2
9
9.5
10
10.5
11
Raymo nd ville, TX
M icro p o lit an SA
-0.3
-0.3
1985
1980
1990-95
1995-2000
y = -0.0913x + 0.9668
R2 = 0.1137
0.4
y = 0.0747x - 0.6042
R2 = 0.0678
0.5
0.3
0.4
0.2
0.3
1995-2000
1990-95
San Jo se-SunnyvaleSant a Clara, CA (M SA )
0.1
0
8.5
9
9.5
10
10.5
B rid g ep o rt -St amf o rd No rwalk, CT (M SA )
0.2
0.1
11
-0.1
0
-0.2
-0.1
8.5
-0.3
9
9.5
10
Tallulah, LA
M icro p o lit an SA
10.5
-0.2
1990
1995
2000-2005*
y = -0.0989x + 1.0361
R2 = 0.0929
0.4
0.3
2000-2005*
0.2
0.1
0
8.5
9
9.5
10
10.5
11
-0.1
-0.2
20
-0.3
2000
11
US CSA Growth and convergence by
growth phases 1980-2005
4
3
λ% pa
2
g% pa
1
λ% pa spatial
0
1980-85 1985-90 1990-95
-1
19952000
20002005*
v e rs io n
-2
gy = c – (1-e-βt)ln(y0) + Xδ + γWgy + ε
λ = -ln(1+β)/t
21
..but a rising trend sigma plot for US
CSAs as incomes grow over time
SD(log income
per capita)
US % pa
6
5
4
3
2
1
0
-1
0.14
-2
19
80
19
81
19
82
19
83
19
84
19
85
19
86
19
87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
0.22
0.21
0.2
0.19
0.18
0.17
0.16
0.15
22
..but disparate contributions from
the richest and poorest regions
SD(log income
per capita)
0.25
0.2
0.15
0.1
0.05
sigma US CSAs
Q1
Q2
Q3
Q4
04
20
02
20
00
20
98
19
96
19
94
19
92
19
90
19
88
19
86
19
84
19
82
19
19
80
0
Q5
23
Phase residual correlations from
US CSA Beta convergence plots
0.3
0.2
0.1
2000-2005
0
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
-0.1
-0.2
-0.3
1995-2000
24
Enlargement phases of the EU –
EU15 a test bed for Krugman?
(GDP/cap relative EU=100 in 2004)
EU6 (1951) =149.8
Pop
GDP
EU9 (1973) New
Members=132.1
EU12 (1986) (GR81) New
Members=84.7
EU15 (1995) New
Members=183.9
EU25 (2004) New
Members=28.8
EU27 (2007) New
Members=10.9
EU27+HR+MK+TR
Proposed Members=17.4
1973, Denmark, Ireland and the United Kingdom, 1981, Greece 1986, Spain and Portugal 1995, Austria, Finland
and Sweden
2004, 10 countries of Central and Eastern Europe and the Mediterranean: Czech Republic, Estonia, Cyprus,
Latvia, Lithuania, Hungary, Malta, Poland, Slovakia and Slovenia.
2007 Romania and Bulgaria
25
EU NUTS3 regional distribution of
GDP per capita 2005
GDP Per Capita,
2005, EU25=100
116.4 to 606.4
98.3 to 116.3
85.1 to 98.2
71.0 to 85.0
0.0 to 70.9
No data
26
EU NUTS 3 Employment Growth,
1980-1995
Employment Growth,
1980-1995, % pa
0.7 to 34.7
0.2 to 0.6
0.0 to 0.1
-0.8 to -0.1
-7.0 to -0.9
No data
27
EU NUTS 3 Employment Growth,
1995-2005
Employment Growth,
1995-2005, % pa
1.4 to 26.3
1.0 to 1.3
0.5 to 0.9
0.1 to 0.4
-16.0 to 0.0
No data
28
EU NUTS 3 GDP Per Capita Growth
1980-1995
GDP Per Capita,
1980-1995, % pa
2.0 to 11.7
1.5 to 1.9
1.0 to 1.4
0.1 to 0.9
-4.0 to 0.0
No data
29
EU NUTS 3 GDP Per Capita Growth,
1995-2005
GDP Per Capita,
1995-2005, % pa
2.5 to 11.0
2.0 to 2.4
1.5 to 1.9
1.1 to 1.4
-4.0 to 1.0
No data
30
EU15 regional cumulative GVA
distribution 967 EU15 NUTS3* regions
1
0.8
0.6
0.4
0.2
0
0
0.2
0.4
0.6
0.8
1
*Excluding
Eastern Laender DE, extra continental
Portugal, France, Spain, Flevoland NL - estimated
population = 380m in 2005
Average GVA per capita = €24,808 at 2000 prices
31
EU15 regional GDP/cap growth
ranking NUTS3 regions
0.6
0.4
0.2
0
0
200
400
600
800
-0.2
-0.4
1985-1990
1995-2000
Linear (1995-2000)
32
EU15 regional employment growth
ranking NUTS3 regions
10
5
0
0
200
400
600
-5
-10
1985-90
*excluding
1995-2000
Linear (1995-2000)
regions with less than 50,000 employment in 2005
33
1985-1990
1980-1985
y = -0.0366x + 0.1601
R2 = 0.0299
0.8
y = -0.0523x + 0.2887
R2 = 0.0427
0.8
0.6
0.6
0.4
0.4
0.2
0.2
0.0
0.0
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
1.0
-0.2
-0.2
-0.4
-0.4
-0.6
-0.6
1.5
2.0
2.5
3.0
1995-2000
1990-1995
3.5
4.0
4.5
y = -0.0318x + 0.2088
R2 = 0.0223
y = -0.0543x + 0.1888
R2 = 0.0569
0.6
0.6
0.5
0.4
0.4
0.3
0.2
0.2
0.0
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
-0.2
0.1
0.0
1.0
1.5
2.0
2.5
3.0
3.5
4.0
-0.1
-0.4
-0.2
-0.6
-0.3
2000-2005
y = -0.0433x + 0.1872
R2 = 0.0464
0.5
0.4
0.3
0.2
0.1
0.0
-0.1
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
-0.2
-0.3
-0.4
-0.5
34
4.5
EU15 NUTS 3 convergence by
growth phases 1980-2005
4
EU15 λ % pa
3
g %pa
2
λ %pa spatial
1
v e r s io n
0
1980-1985 1985-1990 1990-1995 1995-2000 2000-2005
-1
with border
effect
gravity weights
-2
35
Phase residual correlations from
EU15 NUTS3 convergence plots
0.4
0.3
0.2
0.1
2000-2005
0
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
-0.1
-0.2
-0.3
1995-2000
36
The level of spatial detail in
measurement is important
4
3
EU15 NUTS2 λ %pa
2
EU15 g %pa
1
EU15 NUTS2 λ %pa
0
s p a t ia l v e r s io n
1980-1985 1985-1990 1990-1995 1995-2000 2000-2005
-1
-2
37
US/EU15 comparative convergence
by growth phases 1980-2005
4
3.5
3
2.5
2
1.5
1
0.5
0
-0.5
-1
-1.5
US g% pa
US λ% pa spatial
v e r s io n
EU g %pa
EU λ %pa spatial
v e r s io n
1980-85
1985-90
1990-95 1995-2000
20002005*
38
EU27? 1272 NUTS 3 regions
convergence 1990-2005
5
EU27 λ % pa
4
3
EU27 g % pa
2
EU27 λ % pa
1
s p a t ia l v e r s io n
0
EU27 λ %pa
1980-1985 1985-1990 1990-1995 1995-2000 2000-2005
-1
s p a t ia l P T / E S
dum m y
-2
39
Sigma convergence– EU15 NUTS3
comparison with US
0.55
0.5
0.45
0.4
0.35
0.3
sdlnGVA/Pop
US
0.25
0.2
19
80
19
83
19
85
19
88
19
91
19
94
19
97
20
00
20
03
0.15
40
Sigma convergence – EU15 NUTS3
productivity decomposition
0.6
0.5
0.4
0.3
0.2
logGVA/Pop
sdlogGVA/EMP
sdlogEMP/Pop
scdProdDep
0.1
19
80
19
83
19
86
19
89
19
92
19
95
19
98
20
01
20
04
0
41
Sigma plots decomposed
EU15 NUTS3
0.7
0.6
0.5
logGVA/Pop
0.4
logGVAmfg/Empmfg
0.3
0.2
logEmpser/Emptot
0.1
19
80
19
83
19
86
19
89
19
92
19
95
19
98
20
01
20
04
logEmptot/Pop
42
Sigma plots contributions
EU15 NUTS3 extremes
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
GVA/Pop
top quintile
quintile 2
quintile 3
quintile 4
quintile 5
19
80
19
83
19
86
19
89
19
92
19
95
19
98
20
01
20
04
0
43
What does the Evidence show?
• Convergence in GVA per caput in US and EU
•
•
is mainly down to the contribution of
productivity
Adjustment processes in the US are complex
but strongly mediated by migration, with
‘escape’ of the high income regions generating
‘catch up’ by the poorest
EU regions remain very unresponsive by US
standards but some small evidence of a
transition for the ‘established’ union regions in
the last decade
44
Questions raised by the
Evidence?
• What explains the apparent cessation of
•
•
regional convergence in the EU from the mid1990’s onwards?
How accurate is Krugman’s depiction of the US
regional growth pattern and how relevant is the
Thesis in EU case?
Is sectoral competition in the EU15 becoming
more important than spatial competition?
45