Transcript Layout Bologna

53nd European Congress of the Regional Science
Association
27st – 30th August, 2013 Palermo
Local Development and Quality of the
Institutions in the EU Regions
Cristina Brasili, Alessandro Lubisco, Lucilla Spinelli
Department of Statistics, University of Bologna
[email protected]
Outline
Local Development and Quality of the Institutions
in the EU Regions
1. Introduction: the role of the quality of institutions for the local
development
2. The economic and social places-based scenario of the EU regions
3. Regions by productive sectors: productive specialization and
“districtual regions”
4. A growth model for the districtual regions conditioned to the quality
of the institutions
5. Concluding remarks
2
1. Introduction:
The role of the quality of institutions for the local development
1. A higher productivity not only depends on the economic
sector but jointly on ‘local environment’ and on technical
and productive characteristics (Becattini, 2012, p.7).
2. The territory has a degree of “productive chorality” not only
based on the proximity of business but, also, on the
homogeneous cultural characteristics of all the families and
the inhabitants of that place, not necessary directly involved
in the local production.
3
2. The economic and social places-based scenario of the EU regions
This paper tries to answer the question if there is a relation between
economic development and quality of the institutions, integrating the
value of the territory, the economic and social scenario and
productive specialization, particularly, in the districtual regions.
Starting from the data matrix, regions by productive sectors, we
would like to verify the thesis of the role of local quality of institutions
in the evolution of the Industrial Districts, being true the Becattini’s
hypothesis about the “productive chorality” instead of the merely
geographical localization jointed to the productive specialization.
The scarcity of territorial data forces us to adopt the regional level
(NUTS 2) for the analysis.
4
2. The economic and social places-based scenario of the EU regions
The specific territorial capital and the social characteristics, will
be linked to the indicator of quality of the institutions (firstly
proposed by Quality of Government Institute of Gothenburg,
2010) and to the economic growth of the UE regions.
This study takes into account the regions of France, Germany,
Italy, Portugal, Spain and United Kingdom in the years from
2000 to 2010.
5
2. The economic and social places-based scenario of the EU regions
Purchasing Power Standard per inhabitant in percentage of the EU average (PPS%EU)
Years 2000-2010, regional minimum, regional maximum and national values (year 2010)
6
)
2. The economic and social places-based scenario of the EU regions
Unemployment rate - Years 2000-2012, regional minimum,
regional maximum and national values (2012)
7
)
2. The economic and social places-based scenario of the EU regions
Percentage of GERD on GDP - Years 1999-2011, regional minimum (2009/2010),
regional maximum (2009/2010) and national values (2011)
8
)
2. The economic and social places-based scenario of the EU regions
Percentage of aged 30-34 with tertiary education - Years 2000-2012, regional minimum,
regional maximum and national values (2012)
9
)
3. Regions by productive sectors: productive specialization and
“districtual regions”
Changes in Productivity, GVA and employment in six sectors - Years 2000-2007,
Average annual change
 Agriculture, forestry and fishing (A);
2.63
TOTAL
1.12
3.79
 Industry, except construction (B-E);
0.54
A
-1.65
-1.13
B-E
-1.07
 Construction (F);
 Wholesale and retail trade, transport,
accommodation and food service activities,
information and communication (G-J);
 Financial and insurance activities, real
estate activities, professional, scientific and
technical activities, administrative and
support service activities (K-N);
 Public administration and defence,
compulsory social security, education,
human health and social work activities,
arts, entertainment and recreation, repair of
household goods and other services (O-U).
3.27
2.17
4.23
F
1.73
6.04
5.37
G-J
-1.43
3.86
5.30
K-N
-0.54
4.74
2.63
O-U
1.21
3.87
-4
-2
Productivity
0
Employement
2
4
6
8
GVA
10
3. Regions by productive sectors: productive specialization and
“districtual regions”
)
Changes in Productivity, GVA and employment in six sectors
2008 to 2009, annual change
2009 to 2010, annual change
-3.32
TOTAL
3.65
TOTAL
-1.75
-0.32
3.32
-5.02
-9.35
A
10.16
A
-3.71
-0.07
10.08
-12.71
-6.17
-6.09
B-E
9.39
B-E
-2.31
6.86
-11.89
0.19
F
-1.88
G-J
-0.86
F
-7.86
-7.68
-4.03
-4.86
4.02
G-J
-3.33
-0.84
3.15
-5.15
1.51
K-N
2.22
0.87
3.11
2.07
1.14
O-U
1.85
1.15
3.02
-5.37
K-N
-3.94
-0.91
O-U
-15
-10
Productivity
-5
Employement
0
GVA
5
-10
-5
Productivity
0
5
Employement
GVA
10
15
11
3. Regions by productive sectors: productive specialization and
“districtual regions”
)
Ranking of the regions for the value of productivity
The first ten (2010)
Country
Region
TOTAL
All NACE
activities
GVA per person employed
Mean=100
A
B-E
F
G-J
K-N
O-U
298
308
188
UK
Inner London
150.68
46
212
187
France
Île de France
88.61
200
136
176
Germany
Hamburg
73.33
80
157
122
162
119
115
Germany
Darmstadt
68.19
74
136
91
111
133
110
Germany
UK
Italy
Oberbayern
North Eastern Scotland
Lombardia
66.33
65.80
64.48
64
76
119
146
187
101
106
133
106
114
113
147
133
108
134
105
91
98
Italy
Valle d'Aosta
63.77
60
109
111
141
164
131
Italy
P. A. di Bolzano
63.40
150
100
103
139
156
123
France
Provence-Alpes-Côte d'Azur
62.91
173
113
128
173
144
13
3. Regions by productive sectors: productive specialization and
“districtual regions”
)
Ranking of the regions for the value of productivity
The last ten (2010)
GVA per person employed
Country
Region
Mean=100
TOTAL
All NACE
activities
39.06
A
69
B-E
80
F
71
G-J
88
K-N O-U
75 73
UK
Shropshire and Staffordshire
Portugal
Lisboa
38.75
60
75
58
84
69
76
UK
West Wales and The Valleys
37.58
19
92
72
75
79
75
UK
Lincolnshire
37.07
173
64
122
79
83
62
UK
Cornwall and Isles of Scilly
35.91
81
72
63
74
95
70
Portugal
Alentejo
33.98
76
81
41
73
83
70
Portugal
Algarve
32.44
83
51
42
74
75
71
Portugal
R. A. dos Açores
31.59
85
49
36
75
83
76
Portugal
Norte
26.30
12
42
39
63
71
70
Portugal
Centro
24.46
11
54
38
66
80
69
14
)
3.
Regions by productive sectors: productive specialization and
“districtual regions”
The Districtual regions in France, Germany, Italy, Spain, United Kingdom and Portugal
In Italy there is a wide literature on the qualitative and quantitative economic
analysis of industrial districts and several methodologies for the identification of
industrial districts have been developed.
1. The most commonly accepted of these methodologies is by Professor
Sforzi and by ISTAT, an algorithm which departing from local labour markets
and activity data, provide a first operative approximation to mapping
industrial districts. The application for the year 2001 identified 156 districts
in Italy (ISTAT 2006).
In United Kingdom, France, Spain, Portugal and German we don’t have the
same methodologies to identify the districts but we have compared the
identification methods to have the number of industrial districts per region.
15
)
3.
Regions by productive sectors: productive specialization and
“districtual regions”
The Districtual regions in France, Germany, Italy, Spain, United Kingdom and Portugal
2. United Kingdom - De Propris (2005) applied the Sforzi-Istat methodology to the United
Kingdom to identify the various forms of the local system and industrial districts. The
application showed the existence of 47 industrial districts in UK.
3. France - In a study for the Délégation à l'Aménagement du Territoire et à l'Action
Régionale (Datar), aimed at promoting local production systems (LPS), Courlet has
attempted to identify industrial districts, specialized "cluster" of the French economy.
The study established the existence of fifty "industrial districts" of which 25 were
selected, of very different sizes and a variety of activities. The list of districts we used
is shown by Bernard Guesnier (2004).
4. Germany - To identify the presence of industrial districts in Germany regions was
based on the Brenner paper (2006), in which he presents a method that allows local
industrial clusters to be identified. A complete list of all local clusters that existed in
Germany in 2001 and are identified by this method is given. This paper provides a
methodology to identify empirically the threshold in the number of firms that separates
those regions containing a local cluster in a certain industry from those that do not.
16
)
3.
Regions by productive sectors: productive specialization and
“districtual regions”
The Districtual regions in France, Germany, Italy, Spain, United Kingdom and Portugal
5. Spain - In a research of Boxand Galletto (2006) an identification of Local
Labour Markets in Spain is performed using the Sforzi-ISTAT’s methodology.
The application of the adapted methodology produced 806 local labour
systems in the year 2001, and 205 of them would show characteristics of
Marshallian industrial district. Industrial districts are concentrated in the centre
and the east of Spain.
6. Portugal - The industrial districts of Portugal were derived from work carried
out by Cerejeira da Silva (2002). In that work they intend to carry out the
segmentation of the entire country into “concelho” groups, slightly
homogeneous in order to identify those that might be regarded as industrial
districts. They use multivariate statistics and as classification technique they
use the cluster analysis with an appropriate variant for the spatial analysis.
17
)
3. Regions by productive sectors: productive specialization and
“districtual regions”
Number of industrial districts per region
Industrial Districts
Germany
Spain
Italy
France
Portugal
United Kingdom
Total
439
205
156
25
16
47
888
18
)
4. A growth model for the districtual regions conditioned to the quality
of the Institutions
The European Quality of Governament Index - 2009
Regional variations of the European
Quality of Governament Index, 2009
19
)
4. A growth model for the districtual regions conditioned to the quality
of the Institutions
yi =  + yi + QoGi + IndProd + (IndProd*NDistricts)i + Xi + i
Dependent Variable: DLOG(GDP)
Method: Panel Least Squares
Sample (adjusted): 2001 2010
Periods included: 10
Cross-sections included: 122
Total panel (unbalanced) observations: 997
Variable
C
LOG(GDP(-1))
QualIst(-1)
DLOG(IndProd)
DLOG(IndProd)*
NDistricts
LOG(GERD(-1))
LOG(Tertiary(-1))
Unemployment(-1)
ES
DE
PT
UK
IT
Period fixed (dummy variables)
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
Coefficient
-0.026627
-0.008603
0.023374
0.100950
Std. Error
0.020833
0.004153
0.009131
0.011605
t-Statistic
-1.278102
-2.071430
2.559779
8.698818
Prob.
0.2015
**0.0386
*0.0106
**0.0000
0.002970
0.000963
-0.001578
0.001349
0.009252
0.004063
0.000679
0.000216
0.007569
0.002515
0.011181
0.002593
0.012831
0.004311
-0.010749
0.002503
0.010134
0.004995
Effects Specification
3.084652
-1.169955
2.277149
3.144348
3.009382
4.311832
2.976135
-4.294865
2.028889
**0.0021
0.2423
*0.0230
**0.0017
**0.0027
**0.0000
**0.0030
**0.0000
*0.0427
0.290550
0.275270
0.020733
0.419093
2460.863
19.01452
0.000000
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
-0.006697
0.024354
-4.892404
-4.784175
-4.851263
2.027195
20
Concluding Remarks - 1
In order to address the topic about the role of the quality of institutions in the
districtual regions, this paper tries to answer to the question if there is relation
between economic development, convergence and the quality of institutions.
 The analysis shows a wide differences among the regions of the same country, for
example taking into account GDP per capita but, in others cases, as for unemployment,
the wider differences are between Mediterranean regions and Northern ones.
 In the years of economic crisis, in fact, unemployment increases rapidly in Spain, Portugal
and, enough broadly, in Italy. It is more stable in France. It increased less in United
Kingdom, while in Germany unemployment grew up to 2005 and then constantly
decreases, also in the years of the crises.
 The percentage of intramural R&D expenditure on GDP is enough stable on the decade
2000-2010 but it has very different level in the countries: a quite uniform low level in the
Mediterranean countries and higher values, but also a wide variability, among the regions
of France, Germany and United Kingdom.
21
Concluding Remarks - 2
The estimated model (including the variable related to the productive specialization
of the regions) highlights that there is a positive and significative connection
between the quality of institutions and the growth of regional GDP per capita. This
decade shows a very low growth and convergence and the variation rate of
productivity in the industrial sector and the interaction with the number of the
districts give a (quite small) positive contribute to the growth and convergence.
Further research....
This study has to be improve and deepen in different directions. The chronic lack
of data at regional level puts serious limits to the development of this study.
 First of all, in fact, we would have to split the data of industrial sector in order to
deeply analyse the specialization of the different industrial districts.
 To define “productive chorality” we need some more economic, more
disaggregated and updated data
 Another important factor that we will have to consider is the specialization of the
regions to the export to evidence the level of competitiveness of the territories.
 A longer and updated time series variables allows to split the analysis before
and after the crisis (at the present time only three years, from 2008 to 2010, are
available).
22
Cristina Brasili
Department of Statistics, University of Bologna
[email protected]
www.unibo.it