Proposal on the Designation of the Development Regions of Albania DRAFT June 19, 2015 Rudina Toto, Dritan Shutina, Kejt Dhrami, Anila Gjika, Fiona Imami, Ani Shtylla Co-PLAN, Institute for Habitat Development
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Table of Contents I. The context for designating Development Regions in Albania ................................... 3 II. The Methodology for designating Development Regions in Albania ......................... 4 2.1 Definition of the purpose and respective territorial indicators ..................................................... 4 2.2 National databases and studies .................................................................................................................... 8 2.3 Studies conducted locally ................................................................................................................................ 9 2.4 Scientific methodologies .................................................................................................................................. 9 IV. Proposal on the designation of development regions for Albania .......................... 10
4.1 Strengthening of Economic Development, Competitiveness and Resilience ......................... 11 4.1.1 Economic development and regional competitiveness increased; ............................................. 11 4.1.2 Regional economic resilience has increased; .................................................................................... 14 4.2 Strengthening of Regional Social-‐Economic and Territorial Cohesion .................................... 16 4.2.1 More economic cohesion; .......................................................................................................................... 16 4.2.2 Innovative territories potential disclosed; ........................................................................................... 19 4.2.3 Access to services, markets and jobs improved; ............................................................................... 20 4.2.4 More inclusion and better quality of life; ............................................................................................ 21 4.2.5 Regions are attractive and with high ecological values and strong territorial capital; ... 27 4.2.6 Territorial development is integrated and polycentric. .................................................................. 30 4.3 Achieving Environmental Sustainability and Green Economy .................................................... 52 4.3.1 The territorial potential for greener economy and sustainability enhanced and used in a sustainable way ......................................................................................................................................................... 52 4.4 Improving the Accessibility of Regions .................................................................................................. 55 4.4.1 Travel costs decrease; ................................................................................................................................. 56 4.4.2 Cumulated opportunities increase .......................................................................................................... 58 4.4.3 Potential Accessibility improves. ............................................................................................................ 62 4.5 Final Conclusions and the Designation of the Development Regions Boundaries .............. 63
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I. The context for designating Development Regions in Albania The territorial dimension is gaining more and more space in the formulation and implementation of the European policies. Regional development and cohesion policies are the most direct reflection of the territorial approach in policy making, aiming at bringing the horizontal (territorial) perspective as coordination means between sectorial (vertical) instruments and decision-making. The reason behind is rooted in the need for reducing social-economic disparities among regions/territories as another key index of the development, next to sectorial achievements and overall increase of the national GDP. Regional Development (RD) is not a new concept to Europe. However the approach towards RD has progressed and is transformed from a merely state subsidies policy, to a policy that aims at encouraging regions (territories) to produce development, making use of their endogenous resource and by competing among each-other. This approach requested for new development objectives and (policy and financial) instruments, and also raised strongly the necessity of linking spatial/territorial planning with development and governance. The RD objectives that have been identified since at least late 90`s (and are still valid) consist on the reduction of regional disparities while increasing regional cohesion, and strengthening of the competitiveness between regions to boost social-economic and territorial development. Regional Development and Cohesion Policies are key components of the policy-making in the European Union and constitute a target for both, the member countries and those aspiring integration (regardless of the integration stage). EU policy and financial instruments have also set steps that aspiring countries (for instance Albania as a candidate country) are advised to follow for ensuring the merge of domestic policies/instruments for regional development with the EU ones. The experience of the Government of Albania (since at least 2007) with regional development policy-making processes is currently approaching a climax, where there is political and institutional understanding and agreement that there should be a merge between the Albanian RD domestic policy/intentions and the EU cohesion/RD policy requirements and obligations. The Government has set the appropriate context for this merge to happen gradually, through the implementation of the Regional Management Mechanisms. The Government is implementing a plan of actions on this regard, and one of the actions consist of establishing development regions (geographical designation) for the implementation of the RD policy. This proposal provides options on the possible demarcation of the boundaries of these development regions.
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II. The Methodology for designating Development Regions in Albania The team delivering this proposal faced two major challenges: (i) limitations on data for all of the selected indicators. Sometime the data was available but not at the appropriate geographical scale; (i) the very short time for compiling an extensive scientific analysis. Being aware of the limitations, the team followed two major principles: • •
Make use as much as possible of previous studies and proposals related to territorial evidence analysis and regionalization of Albania; Make use of existing methodologies, by simplifying them to a degree where results would be still carefully reflecting the reality. The involvement of a local team, with good knowledge of the territorial development and governance issues was a support factor in this regard.
As a result, the methodology for designating Development Regions in Albania was set to comprise the following components: 1. Definition of the purpose that the designated regions should fulfill, i.e. of the expected role and functions of the regions. This is set through the objectives and the respective territorial indicators of achievement. 2. A quick analysis of the methodologies, databases, data, and studies that national institutions (mainly INSTAT) have developed so far and that provide valuable input to the regions’ designation process. 3. Borrowing from methodologies and studies’ results developed by local organizations and think tanks, with a special focus on the proposal of Co-PLAN for the regionalization of Albania. 4. Contextualizing to the possible extent (given the limitations) the relevant methodologies developed in the ESPON studies. The latter constitute a valuable scientific and practical resource for the achievement of the aim of this proposal. Each component is explained in the following sections. 2.1 Definition of the purpose and respective territorial indicators The Government of Albania is aiming at boosting economic development over the territory, and has prepared a concept for a Regional Management Mechanism (RMM) on this regard. The latter consists broadly of the following: • •
• •
Undertake gradual steps towards the merging of the domestic regional development policy with the EU regional development and cohesion policies; Establish a national Agency responsible on implementing the RMM nationally, and a number of regional Agencies, responsible on implementing the RMM regionally and in accordance with national policies and institutions. Designate development regions, as the territories where each regional agency will operate. Create strategic and legal instruments for the functioning of the RMM.
As it is stated above, these regions are (territorial) development ones, thus nor administrative, neither governance regions. This implies that the regions should fit with at least three key criteria: (i) should be flexible and changeable (through a decision of 4 Co-PLAN, Institute for Habitat Development Tiranë, June 2015
Council of Ministers), if it is necessary for efficiency purposes, after the designation and the implementation of the RMM within their boundaries; (ii) should be outlined in such a way as to fit with the development and cohesion aims and objectives, but not necessarily with the administrative and governance objectives. At a functional level, the regional agencies will carry out only the regional development and management function, without focusing on any governance function; (iii) the regions should not represent sectors or sectorial priorities, otherwise their delineation would go against the regional/territorial development approach, and thus against the following government’s objectives. Based on the above criteria, the development regions will be the areas where the following objectives (at least and in line with EU) should be achieved: • •
Social-economic and territorial cohesion; Strengthening of the regional competitiveness for sustainable development and economic resilience.
In its concept proposal for regional management and development, the Government of Albania (GoA) suggests that regional management shall encompass 5 (territorial development) programs, which embrace the sectorial policies of the line ministries in a crosscutting modus, as proposed in the following table. These programs do reflect the cohesion and competitiveness objectives, providing however a more detailed perspective on the GoA objectives. Table 1. OP1: Transition of sectors to programs CENTRAL(POLICY(PLANNING( LINE(MINISTRIES(((
REGIONAL(MANAGEMENT( RMA(&(ESA(
(
NATIONAL(MODAL(TRANSPORT(STANDARDS(&(INVESTMENTS(
PROGRAM(1:(DEVELOPMENT(OF(ACCESSIBILITY(INFRASTRUCTURE(
WATER(&(SANITATION(STANDARDS(&(MONITORING(
PROGRAM'2:(REGIONAL(COHESION(AND(COOPERATION(
ENVIRONMENTAL(STANDARDS(&(MONITORING(
PROGRAM(3:(SUSTAINABLE(DEVELOPMENT(AND(QUALITY(OF(LIFE(
EDUCATION(&(VET:(STANDARDS(&(MONITORING
PROGRAM(4:(DIGITAL(CONVERGENCE(AND(ENTREPRENEURSHIP(
ECONOMIC(POLICY(&(TURISM(STANDARDS(
PROGRAM(5:'TECHNICAL(ASSISTANCE( (
CULTURAL(NATIONAL(HERITAGE(( HEALTH(STANDARDS(&((HOSPITALS((
Source: Regional Management in Albania, a Vision on the Reform, GoA, 2015. Definition of clear objectives is key to the designation of the regions, because the latter should result in optimal boundaries for achieving these objectives. To make sure that there is a optimal match between objectives and geographical boundaries, it is necessary to analyze the current situation of the indicators that shall be used in the near future for measuring the achievement of the objectives. This will not only help in defining boundaries, it will also set the baseline for future regional management and development Co-PLAN, Institute for Habitat Development Tiranë, June 2015
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monitoring, and if need be, for revising the boundaries. Finally, 4 policy objectives and total of 12 sub-objectives (to be achieved by regional development and management) were set, with the respective indicators to be analyzed on the territory (Table 2). The following table represents an optimal list, and is based on selected ESPON studies (see section 2.4). The list was initially compiled having in mind the potential availability of data, as well as the time limits for accomplishing the assignment. However, after a quick inventory of the data, it was reduced by at least 35% and some indicators were revised in meaning, mainly due to data availability and given time limits for the preparation of the document. Table 2. An optimum list of indicators for territorial analysis No 1
1.1
Policy Objective and SubNo. Indicator Objective Economic Development, Competitiveness and Resilience 1.1.1 GDP per capita 1.1.2 GVA per capita by sectors 1.1.3 Employment rate of population aged 16-64 Economic Development and Competitiveness 1.1.4 Gross expenditure on R&D as % of GDP 1.1.5 Balance of external trade 1.1.6 Economic structure
Economic resilience
1.2.1 1.2.2 1.2.3 1.2.4 1.2.5 1.2.6
GDP per capita change GVA per capita per sector change Total Employment change Total Employment by sector change Change of Unemployment Resilience and territorial typologies
2.1
Economic cohesion
2.1.1 2.1.2 2.1.3 2.1.4 2.1.5
Cohesion Labor productivity in industry Labor productivity in services GDP per capita Overall unemployment rate Age Dependency ratio for 65 and above
2.2
Innovative territories
2.2.1 2.2.2
Population aged 25-64 with tertiary education Employment rate 20-64
Access to services, market and jobs
2.3.1 2.3.2 2.3.3 2.3.4
Access to compulsory school Access to hospitals Access to university Accessibility indicators
Inclusion and quality of life
2.4.1 2.4.2 2.4.3 2.4.4 2.4.5
Disposable household income Life expectancy at birth Proportion of early school leavers Gender imbalances Differences in female-male unemployment rates
1.2
2
2.3
2.4
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2.5
2.6
3
3.1
2.4.6 2.4.7 2.4.8
Ageing index Population with tertiary education Population at risk of poverty
Attractive regions of high ecological values and strong territorial capital
2.5.1 2.5.2 2.5.3 2.5.4 2.5.5 2.5.6 2.5.7
Potential vulnerability to climate change Soil sealing per capita Air pollution: Ozone concentrations Population at risk of flooding Biodiversity Renewable energy potential Greenhouse gas emissions
Integrated polycentric territorial development
2.6.1 2.6.2 2.6.3 2.6.4 2.6.5 2.6.6 2.6.7
Population potential within 30 km radius Net migration rate Cooperation Intensity Cooperation degree Other Demography Demographical changes
Environmental sustainability and green economy Public/private support to SMEs for increased resources efficiency and/or production of green 3.1.1 products and services 3.1.2 Environmental protection expenditure / capita 3.1.3 Wind energy potential
Typology of territorial potential for greener economy and sustainability
3.1.4
PV/solar energy potential
3.1.5
Biomass energy potential
3.1.6
Geothermal energy potential
3.1.7
Percentage of NATURA 2000 areas by Qark % of persons aged 25-64 with upper secondary education attainment % of persons aged 20-24 with upper secondary education attainment Accumulated patents in selected environmental technologies Environmental taxation
3.1.8 3.1.9 3.1.10 3.1.11 4
4.1
Accessibility of regions
Travel costs
4.1.1 4.1.2 4.1.3 4.1.4 4.2.1 4.2.2
4.2
Cumulated opportunities
4.2.3 4.2.4
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Access time of people to motorway exits Access time of freight to freight terminals Travel time of people to regional centers by road and public transport Travel time of people to the nearest hospital Cities>50,000 residents within 60 minutes by road Freight terminals within 2hrs by lorry Jobs accessible within 60 minutes by road and public transport Number of higher secondary schools within 30 minutes travel time
7
4.3
Potential
4.3.1 4.3.2 4.3.3 4.3.4
To national population by road To national GDP by lorry To population by road and public transport Potential accessibility to general practice surgeries
Analyzing these indicators (per each objective) suggests that the final proposal for the designation of the regions will be aiming at considering them simultaneously. This is a crucial assumption of the analysis, because the final product should provide development regions and by no means sectorial regions. If the latter were the case, the designation of the regions would simply go against the purpose for which they were created. The indicators are presented territorially (on maps) at the Qark, municipalities 61 and municipalities/communes level, depending on data availability. The most preferred level is the one of the current 373 local governments, as the analysis at this level provides more details and allows for better understanding of the situation per each indicator. There are also cases in which the territorial unit is either 17 agglomerations and their respective functional urban areas, or 36 urban centers, based on the INSTAT definitions for agglomerations and urban centers, and ESPON and OECD definitions for functional urban areas. Most of the indicators are also presented in tables and/or graphs. Because this is a proposal of territorial delineations (and also because of the reported study limitations), the indicators (with only few exceptions) are not presented in time series; instead they reflect the current situation, or the latest year for which official data are available (between 2012 and 2014).
2.2 National databases and studies For most of the indicators, the team has made use of INSTAT (Albanian Institute of Statistics) data, by accessing on line the INSTAT database, the Census 2011 data and studies, and the INSTAT web atlas1. In all cases, the source of the information is also provided on the map, helping to check accuracy and validity of the information. Key studies, especially to the polycentrism analysis were the publications of INSTAT on “A new Urban Rural classification of the Albanian population” (2014) and “The typology of communes and municipalities” (2014). The base map, in all cases, was constructed by making use of the layers provided on line by ASIG (State Authority for Geospatial Information) Geo-portal2. For some of the indicators, mainly those related to accessibility and some of the polycentrism analysis, the team has calculated travel times on line, by using Google maps.
1 2
www.instat.gov.al and www.instatgis.gov.al http://geoportal.asig.gov.al/
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2.3 Studies conducted locally The most resourceful studies that have been conducted locally and served as a basis for further interpretation of the indicators, are: (i) Co-PLAN’s proposal on the Regionalization scenarios for Albania (2014); (ii) and ISD3 study on Regional Disparities in Albania (2009). The contribution of Co-PLAN provides an extensive analysis of the need for administrative and governance regionalization in Albania, together with proposed scenarios for regions’ delineation. This study provides good hints and information to the current proposal. The reason for not using the scenarios of this study right form the outset, is that the purpose for their delineation is rather different and broader – governance regionalization, thus including several functions and criteria that are not subject to the current proposal. However, specific analytical maps of this study provide useful arguments to the current proposal. The publication of ISD on regional disparities provides a very good overview of the distribution of territorial disparities in Albania at Qark and communes/municipalities (373) level, by feeding with territorial evidence the cohesion objective. The information is relatively outdated (time series of 2001-2009); however the study remains relevant and appropriate for use for the following reasons: •
•
Conclusions wise, the situation has not changed much in Albania. Thus, as defined by this study, the disparities are not so pronounced among Qarks (as territorial units), but remain quite sharp at communes/municipalities level; The Coordination unit at the Prime Minister’s Office as updated the indicators of the Regional Development Index, to the latest data available.
2.4 Scientific methodologies The team defined the indicators by making use of ESPON4 and OECD5 studies and methodologies on topics that are relevant to the purpose of the current proposal. ESPON, is an EU program that “aims at promoting and fostering a European territorial dimension in development and cooperation by providing evidence, knowledge transfer and policy learning to public authorities and other policy actors at all levels”6, since 2004. Through its projects, it provides scientific methodologies for analyzing key issues related to the EU policies implementation and monitoring. The team made use of the following studies/projects for the current proposal: 1. KITCASP, Key Indicators for Territorial Cohesion and Spatial Planning, Targeted Analysis 2013/2/20, (Draft) Final Report | Version 31 July 2013, Part D | Appendix F, ESPON. 2. Veneri, P. and V. Ruiz (2013), “Urban-to-Rural Population, Growth Linkages:
3
Integrated Support for Decentralization, an EU and UNDP program.
4 European Spatial Planning Observation Network 5 Organization for Economic Cooperation and Development 6
http://www.espon.eu/main/Menu_Programme/
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Evidence from OECD TL3 Regions”, OECD Regional Development Working Papers, 2013/03, OECD Publishing. http://dx.doi.org/10.1787/5k49lcrq88g7-en 3. INTERCO, Indicators of territorial cohesion, Scientific Platform and Tools Project 2013/3/2, (Draft) Final Report, ESPON 4. ECR2, Economic Crisis: Resilience of Regions, (Draft) Scientific Report | Version 31/03/2014, Applied Research 2013/124/2012, ESPON 5. SGPTD, Second Tier Cities and Territorial, Development in Europe: Performance, Policies and Prospects, Applied Research 2013/1/11, Scientific Report | Version 30/06/2012, ESPON 6. ESPON 2013 I, TRACC, Transport Accessibility at Regional/Local Scale and Patterns in Europe, Applied Research 2013/1/10, Final Report | Version 06/02/2015, Volume 2 TRACC Scientific Report 7. ESPON 1.1.1, 2005, Potentials for polycentric development in Europe, Project report III. Territorial analysis of the Indicators.
IV. Proposal on the designation of development regions for Albania The proposal on the designation of the development regions for Albania is built over the analysis of the indicators of table 2. This table contains indicators for 4 policy objectives (and sub-objectives) that the future development regions should achieve, namely: •
•
•
•
Strengthening of Economic Development, Competitiveness and Resilience; o Economic development and regional competitiveness increased; o Regions are more competitive; o Regional economic resilience has increased; Strengthening of Regional Social-Economic and Territorial Cohesion o More economic cohesion; o Innovative territories potential disclosed; o Access to services, markets and jobs improved; o More inclusion and better quality of life; o Regions are attractive and with high ecological values and strong territorial capital; o Territorial development is integrated and polycentric. Achieving Environmental Sustainability and Green Economy o The territorial potential for greener economy and sustainability enhanced and used in a sustainable way. Improving the Accessibility of Regions o Travel costs decrease; o Cumulated opportunities increase; o Potential Accessibility improves.
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4.1 Strengthening of Economic Development, Competitiveness and Resilience 4.1.1 Economic development and regional competitiveness increased; Increased regional competitiveness is a target in regional development, as competitive regions can attract and maintain successful companies, skilled labor and investments, high living standards, and growth producing economic activities. Because of this, increasing of competitiveness of regions has also become an (policy) objective, rooted in the regional development policy. Any proposal on the designation of development regions in Albania (result of this analysis) will act as guiding tool to the measures that the government has to take to foster growing competitive advantages in the regions. Thus, the government would look at how to support the local/regional businesses for strengthening and becoming more competitive, either through infrastructures and services, or other “soft” means, such as vocational education, etc. Figure 2: Employment rate of population aged 16-64
Figure 1: GDP per capita
Employment rate
Gross Domestic Product per capita, at Qark level
rate of employed persons aged 20-64, at Qark level
KUKËS
KUKËS SHKODËR
SHKODËR
LEZHË
LEZHË
DIBËR
DIBËR DURRËS
DURRËS
TIRANË
TIRANË
ELBASAN
ELBASAN
Legend
Legend
FIER
BERAT
310
0.27 0.28
323
0.34
327
GJIROKASTËR
346
521 650
Prepared by: Co-PLAN, 2015 Source: INSTAT, 2012
GJIROKASTËR
0.36
VLORË
VLORË
0.36
371
481
KORCA
0.23
322
422
BERAT
0.19
KORCA
320
392
FIER
rate
GDP/CAPITA (in 000 ALL)
¯ 0 5 10 20 30 40 Kilometers
0.37 0.39 0.40 0.40 0.43
Prepared by: Co-PLAN, 2015 Source: INSTAT, 2011
¯ 0 5 10 20 30 40 Kilometers
For the purposes of understanding the (current/potential) competiveness of regions, we have captured, from a spatial perspective, the GDP and GVA per capita, on a Qark level, as well as the employment rate for persons aged 20-64. More substantial analysis of the competitiveness is conducted in the ISD study of regional disparities in 2009, where time series were also analyzed to understand the evolution of competitiveness characteristics for Qarks. Co-PLAN, Institute for Habitat Development Tiranë, June 2015
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Figure 3: GDP per capita in 000 Lekë 650 521
481 371
346
310
422
392 322 320 327 323
Source: INSTAT 2012 Figure 4: GVA per capita by sectors VLORË% KORÇE% GJIROKASTER%
0.38% 0.29% 0.35%
0.07%
0.13% 0.02% 0.05% 0.46%
0.16%
0.33%
0.14%
TIRANË% ELBASAN%
0.05%
0.11% 0.03% 0.03%
FIER% BERAT%
0.11%
0.04%
0.05%
0.05%
0.59% 0.31%
0.15%
0.03%0.06% 0.11% 0.04%
0.18%
0.06%
SHKODËR%
0.29%
0.10% 0.04% 0.04%
LEZHË%
0.29%
0.10% 0.03% 0.05%
KUKËS%
0.28%
0.10% 0.02% 0.03%
GVA/CAPITA% GVA/capita%Agriculture%
DURRËS%
0.44%
GVA/capita%Industry% GVA/capita%ConstrucTon% GVA/capita%Transport%Hotels%
0.07% 0.07%
GVA/capita%Services%
0.15%
GVA/capita%Finance% DIBËR% 0.00%
0.27%
0.12% 0.20%
0.06% 0.02% 0.40%
0.60%
0.80%
1.00%
1.20%
1.40%
Source: INSTAT 2011 and Own calculations Tirana, Durrës and Fier are the most competitive in terms of the gross domestic product, while labor force is the highest in Tirana and Elbasan. From a sectorial economic structure point of view, still Tirana and Durrës dominate. However, looking at sectors separately, agriculture seems to dominate the proportions of GVA in several regions, while in Tirana and Durrës the biggest GVA proportion is dedicated to Transport and Co-PLAN, Institute for Habitat Development Tiranë, June 2015
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Hotel services. In overall, the south-west Qarks are the most advantageous and the competitiveness indicators fall gradually, while moving inland, towards the more mountainous regions. Figure 5: GVA per capita at Qark level, 2012
GVA/capita, at Qark level
KUKËS SHKODËR
LEZHË
DIBËR DURRËS
TIRANË
ELBASAN
Legend GVA/capita (in 000 ALL)
FIER
273.409
BERAT
283.461
KORCA
286.947 288.966 293.231 308.318 330.862
GJIROKASTËR VLORË
349.326 380.830
¯
436.018 464.191 589.916 Prepared by: Co-PLAN, 2015 Source: INSTAT, 2011
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
0 5 10
20
30
40 Kilometers
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4.1.2 Regional economic resilience has increased; The purpose of this analysis is to observe the behavior of regions during and after the economic crisis, in order to measure their recovering and economic resilience ability. Albania was hit by the world economic crisis only in 2010 and the data for measuring resilience (figures and tables below) are available only till 2012. So we are not able to measure whether at a spatial scale, the regions have responded to the crisis by recovering, or are still in decline. The following indicators are a clear evidence of how strongly Albania is hit by the crisis in 2011-2012 in all Qarks. Table 3: GDP per capita 2001-2012 Years and GDP per capita in 000 lekë 2003 2004 2005 2006 2007 2008 2009
2000
2001
2002
2010
2011
2012
Berat
119
152
161
178
199
225
246
267
299
324
375
373
371
Dibër
70
90
95
106
123
150
172
188
216
248
262
286
310
Durrës
195
228
236
252
257
255
268
Elbasan
295
326
339
433
457
481
128
144
151
169
188
212
Fier
230
244
279
287
362
354
346
136
154
163
180
196
213
232
250
273
296
370
446
521
95
140
151
165
183
205
227
242
267
281
393
393
392
Korçë
113
138
146
Kukës
165
180
200
219
245
270
279
324
323
322
87
122
Lezhë
132
145
164
205
258
285
309
335
305
312
320
113
137
146
160
173
188
204
222
248
270
329
328
327
Shkodër
114
140
149
168
185
204
221
235
264
287
334
329
323
Tiranë
312
353
376
419
419
413
430
473
531
545
595
622
650
Vlorë
112
178
192
213
227
236
252
270
301
330
392
407
422
Qarku
Gjirokastër
Source: INSTAT Figure 6: GDP per capita change 0.70% 0.60% 0.50% 0.40% 0.30% 0.20%
Berat% Dibër% Durrës% Elbasan% Fier% Gjirokastër% Korçë% Kukës% Lezhë%
0.00%
Shkodër%
20 00 !2 00 1% 20 01 !2 00 2% 20 02 !2 00 3% 20 03 !2 00 4% 20 04 !2 00 5% 20 05 !2 00 6% 20 06 !2 00 7% 20 07 !2 00 8% 20 08 !2 00 9% 20 09 !2 01 0% 20 10 !2 01 1% 20 11 !2 01 2%
0.10%
!0.10%
Tiranë% Vlorë%
!0.20%
Source: INSTAT Co-PLAN, Institute for Habitat Development Tiranë, June 2015
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Table 4: Total Employment (rate) Qarku Berat Dibër Durrës Elbasan Fier Gjirokastër Korçë Kukës Lezhë Shkodër Tiranë Vlorë
Years and Employment rate 2008 2009 2010 58 56 53 42 36 33 54 49 45 58 56 56 58 55 50 54 54 52 63 62 57 47 42 34 40 19 20 50 40 36 52 54 51 51 55 47
2007 62 47 59 60 62 54 63 53 62 61 51 84
2011 43 28 34 36 39 40 36 19 23 27 40 37
Source INSTAT Figure 7: Total Employment change 0.20% Berat%
0.10%
Dibër% Durrës%
0.00% 2007!2008%
2008!2009%
2009!2010%
2010!2011%
!0.10%
Elbasan% Fier% Gjirokastër%
!0.20%
Korçë% Kukës%
!0.30%
Lezhë% !0.40%
Shkodër% Tiranë%
!0.50%
Vlorë%
!0.60%
Source: INSTAT and Own calculations Figure 8: Change of unemployment 10.00% 9.00% 8.00%
Berat% Dibër%
7.00%
Durrës% 6.00%
Elbasan% Fier%
5.00%
Gjirokastër%
4.00%
Korçë%
3.00%
Kukës% Lezhë%
2.00%
Shkodër% 1.00%
Tiranë% Vlorë%
0.00% 2003!2004%
2004!2005%
2005!2006%
2006!2007%
2007!2008%
2008!2009%
2009!2010%
2010!2011%
!1.00% !2.00%
Source: INSTAT, Indicators by Prefecture, INSTAT GIS Web atlas, Own calculations 15 Co-PLAN, Institute for Habitat Development Tiranë, June 2015
4.2 Strengthening of Regional Social-Economic and Territorial Cohesion 4.2.1 More economic cohesion; Social-economic and territorial cohesion, or reduction of disparities is the other major objective of regional development. The Integrated Support for Decentralization project has provided substantial contribution in measuring regional disparities in Albania for the period 2001-2009. The current analysis will provide simply a snapshot of the regional cohesion situation in Albania for 2011-2012, from a spatial distribution point of view and for a selected number of indicators. Figure 9: Labor productivity in Industry Labour productivity in Industry GVA/no. of employees in Industry, at Qark level
KUKËS SHKODËR
LEZHË
DIBËR DURRËS
TIRANË
ELBASAN
Legend
FIER
Productivity in Industry (in 000000 ALL) BERAT
0.09
KORCA
0.16 0.16 0.17 0.17
GJIROKASTËR
0.19
VLORË 0.23 0.23 0.27 0.29 0.40 0.90
Prepared by: Co-PLAN, 2015 Source: INSTAT, 2011
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
¯ 0 5 10 20 30 40 Kilometers
16
Figure 10: Overall unemployment rate
Overall unemployment rate % out of total, at Municipality 61 level
MALESI E MADHE
TROPOJE
SHKODER
HAS FUSHE ARREZ
PUKE
VAU I DEJES
KUKES
LEZHE MIRDITE DIBER MAT
KURBIN
KRUJE
KLOS BULQIZE
DURRES VORE SHIJAK
KAMEZ TIRANE LIBRAZHD
KAVAJE ELBASAN
RROGOZHINE PEQIN
PERRENJAS
DIVJAKE CERRIK
LUSHNJE BELSH
POGRADEC PUSTEC
GRAMSH
KUCOVE URA VAJGURORE FIER
ROSKOVEC
MALLAKASTER
SELENICE
MALIQ
BERAT
PATOS
KORCE
POLICAN
DEVOLL
SKRAPAR
MEMALIAJ KELCYRE KOLONJE
TEPELENE
VLORE
PERMET
Legend
LIBOHOVE
HIMARE
GJIROKASTER
% out of total 0 - 10.0
DELVINE DROPULL
10.1 - 20.0 20.1 - 30.0
SARANDE LIVADHJA
30.1 - 40.0 KONISPOL
40.1 - 65 Qark Border Manual Ranges
Prepared by: Co-PLAN, 2015 Source: INSTAT, 2011
¯ 0 5 10 20 30 40 Kilometers
The indicators of GDP per capita and all employment related indicators show for quite pronounced disparities at Qark level. This has not been so much the case in the figures of the ISD 2009 study. However it can be explained as an effect of the economic crisis. Co-PLAN, Institute for Habitat Development Tiranë, June 2015
17
Figure 11: Age dependency ratio for people aged 65 and above
Age dependency Ratio For people aged 65 and above, at Qark level
KUKËS SHKODËR
LEZHË
DIBËR DURRËS
TIRANË
ELBASAN
Legend
FIER
age dependency over 65 BERAT
12.39
KORCA
13.59 14.68 14.84 15.79
GJIROKASTËR
17.06
VLORË 17.72 17.75 18.88 20.59 20.79 23.8
Prepared by: Co-PLAN, 2015 Source: INSTAT, 2011
¯ 0 5 10 20 30 40 Kilometers
The disparities between Qark related to age dependency show that the population aged above 65 is more dominant in Shkodra and in the south Qarks (Korçë, Gjirokastër and Vlorë) than in the rest of the country. This may be related to the migration patterns of these Qarks as well as to the low population figures of these Qarks. On the other hand, it also shows competitiveness and convergence advantage for Durrës, Tirana and Co-PLAN, Institute for Habitat Development Tiranë, June 2015
18
Elbasan.Kukës and Dibër seem also to be advantageous, but they also have the highest unemployment figures, for both, males and females. 4.2.2 Innovative territories potential disclosed; Figure 12: Population aged 18-64 with tertiary education
Population with tertiary education % of population aged +15 that has attained tertiary education, in municipality/commune level
KUKËS SHKODËR
LEZHË
DIBËR DURRËS
TIRANË
Legend % of population attaining tertiary education
ELBASAN
FIER
0.4% - 2%
BERAT
KORCA
2.1% - 3% 3.1% - 4% 4.1% - 5% 5.1% - 6% GJIROKASTËR
6.1% - 8% VLORË
8.1% - 10% 10.1% - 15% 15.1% - 30% Qark border Manual Ranges
Prepared by: Co-PLAN, 2015 Source: INSTAT, Census 2011
0 5 10
20
30
¯
40 Kilometers
Innovation is related to several factors, such as education, patents, research and development expenditures, etc. The latter figures are either missing or incomplete for Albania. In terms of tertiary education, we see that the highest concentration is in the core Co-PLAN, Institute for Habitat Development Tiranë, June 2015
19
urban centers and it decreases the more we move towards periphery and in areas with low accessibility. 4.2.3 Access to services, markets and jobs improved; Figure 13: Access to water supply and sewage
Dwellings' accessibility to infrastructure % of dwellings with access to water supply at municipality/commune level
KUKËS SHKODËR
LEZHË
DIBËR DURRËS
TIRANË
ELBASAN
FIER
BERAT
KORCA
Legend % out of total 0.0 - 25.0
GJIROKASTËR VLORË
25.1 - 43.4 43.5 - 58.8 58.9 - 71.9 72.0 - 86.3 86.4 - 100.0 Qark Border Natural Breaks
Prepared by: Co-PLAN, 2015 Source: INSTAT, 2011
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
¯ 0 5 10 20 30 40 Kilometers
20
Accessibility indicators are discussed in section 4.4. Here we have a presentation of households access to water and sewage services, which represents high disparities among communes and municipalities (373). 26% of the local governments have no more than 40% of their dwellings with access to water and sewage services, while 30% only have 80-100 % of their dwelling with access to these services. The distribution is rather uneven, but disparities are more pronounced in the north. Figure 14: Accessibility of dwellings to water and sewage services 114
120
No. dwellings
100
86 75
80 50
60 35
40 20
13
0 <10
10-‐20
20-‐40
40 -‐ 60
60 -‐ 80
80 -‐ 100
% out of total
4.2.4 More inclusion and better quality of life; The following group of indicators shows mainly for disparities among northern and southern Qarks, with those in the north being in a more disadvantageous position. In the case of the proportion of people aged 10+ and with less than 5 years of education, all of the 4 northern Qark have medium to high figures compared to the center Qarks, with 9.7 to 11% out of the total. In the South, Gjirokastra, Korca and Berat are in the worst position for this indicator, and this could be due to both, the topographic patterns (that suggest lower access to education services), and the migration features (the aging index shows for extreme disparities among south and north, with south municipalities reaching above 100%, and in few cases more than 500%). Unemployment maps provide also interesting information. The unemployment is much more higher in the north (around 50%) than south municipalities (8-30%). The previous have also almost equal figures of females and males unemployment, with males’ unemployment being slightly higher. On the other hand, the females’ unemployment is much higher than the males’ unemployment in the south (in several cases reaching 9-27% more).
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
21
Figure 15: Proportion of people with less than 5 years of education
People aged 10+ with less than 5 years of education % out of total, at Qark level
KUKËS SHKODËR
LEZHË
DIBËR DURRËS
TIRANË
ELBASAN
Legend
FIER
% out of total BERAT
1.8
KORCA
1.9 6.9 9.1 9.7
GJIROKASTËR
9.7
VLORË 9.8 10.0 10.4 10.5 11.1 11.3
Prepared by: Co-PLAN, 2015 Source: INSTAT, 2011
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
¯ 0 5 10 20 30 40 Kilometers
22
Figure 16: Females unemployment rates
Female Unemployment Rate % of unemployed females aged +15, to the economically active females, at Municipality 61 level
MALESI E MADHE
TROPOJE
SHKODER
HAS FUSHE ARREZ
PUKE
VAU I DEJES
KUKES
LEZHE MIRDITE DIBER MAT
KURBIN
KRUJE
KLOS BULQIZE
DURRES VORE SHIJAK
KAMEZ TIRANE
Legend % of unemployed females
LIBRAZHD KAVAJE ELBASAN
RROGOZHINE PEQIN
PERRENJAS
DIVJAKE CERRIK
LUSHNJE BELSH
POGRADEC PUSTEC
GRAMSH
KUCOVE URA VAJGURORE FIER
ROSKOVEC
7.9% - 17.9%
MALLAKASTER
18% - 26% SELENICE
26.1% - 32.5% 32.6% - 38.6%
MALIQ
BERAT
PATOS
POLICAN
KORCE
DEVOLL
SKRAPAR
MEMALIAJ KELCYRE KOLONJE
TEPELENE
VLORE
PERMET LIBOHOVE
HIMARE
GJIROKASTER
38.7% - 48.4% DELVINE
48.5% - 62.5% Qark Border
¯
DROPULL
SARANDE LIVADHJA
KONISPOL
Natural Breaks
Prepared by: Co-PLAN, 2015 Source: INSTAT Web Atlas, 2011
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
0 5 10
20
30
Kilometers 40
23
Figure 17: Males unemployment rates
Male Unemployment Rate % of unemployed males aged +15, to the economically active males, at Municipality 61 level
MALESI E MADHE
TROPOJE
SHKODER
HAS FUSHE ARREZ
PUKE
VAU I DEJES
KUKES
LEZHE MIRDITE DIBER MAT
KURBIN
KRUJE
KLOS BULQIZE
DURRES VORE SHIJAK
KAMEZ TIRANE LIBRAZHD
KAVAJE
Legend
ELBASAN
RROGOZHINE PEQIN
PERRENJAS
DIVJAKE
POGRADEC PUSTEC
GRAMSH
KUCOVE URA VAJGURORE FIER
ROSKOVEC
MALLAKASTER
6% - 16.9% 17% - 22.1%
SELENICE
MALIQ
BERAT
PATOS
22.2% - 28.7%
CERRIK
LUSHNJE BELSH
% of unemployed males
POLICAN
KORCE
DEVOLL
SKRAPAR
MEMALIAJ KELCYRE KOLONJE
TEPELENE
VLORE
PERMET
28.8% - 37.7%
LIBOHOVE
HIMARE
GJIROKASTER
37.8% - 50% 50.1% - 64.1% Qark Border
DELVINE
¯
DROPULL
SARANDE LIVADHJA
KONISPOL
Natural Breaks
Prepared by: Co-PLAN, 2015 Source: INSTAT Web Atlas, 2011
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
0 5 10
20
30
Kilometers 40
24
Figure 18: Differences in female-male unemployment rates
Differences in Female-Male Unemployment Rate Difference between the % of unemployed females and males aged +15, at Municipality 61 level
MALESI E MADHE
TROPOJE
SHKODER
HAS FUSHE ARREZ
PUKE
VAU I DEJES
KUKES
LEZHE MIRDITE DIBER MAT
KURBIN
KRUJE
KLOS BULQIZE
DURRES VORE SHIJAK
KAMEZ TIRANE
Legend difference between % of female and male unemployment
LIBRAZHD KAVAJE ELBASAN
RROGOZHINE PEQIN
PERRENJAS
DIVJAKE CERRIK
LUSHNJE BELSH
POGRADEC
-8.6% - -4.5%
PUSTEC
GRAMSH
KUCOVE URA VAJGURORE FIER
ROSKOVEC
MALIQ
BERAT
PATOS
-4.4% - 0.7% MALLAKASTER
POLICAN
KORCE
DEVOLL
SKRAPAR
0.8% - 4.7% SELENICE
MEMALIAJ KELCYRE
4.8% - 9.3%
KOLONJE
TEPELENE
VLORE
PERMET
9.4% - 15.4%
LIBOHOVE
HIMARE
GJIROKASTER
15.5% - 26.9% DELVINE
¯
DROPULL
Qark Border
SARANDE LIVADHJA
KONISPOL
Natural Breaks
Prepared by: Co-PLAN, 2015 Source: INSTAT Web Atlas, 2011
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
0 5 10
20
30
Kilometers 40
25
Figure 19: Poverty
Distribution of poverty % of population that is considered poor, or extremely poor, at Qark level
KUKËS SHKODËR
LEZHË
DIBËR DURRËS
TIRANË
Legend
ELBASAN
% of poverty 10.6%
FIER
11.1% BERAT
11.3%
KORCA
12.3% 12.4% 12.7% 13.9% 15.4%
GJIROKASTËR VLORË
16.5% 17.1%
¯
18.4% 22.5% Prepared by: Co-PLAN, 2015 Source: INSTAT, "Anketa e Matjes se Nivelit te Jeteses", 2012
0 5 10
20
30
40 Kilometers
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
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Figure 20: Ageing Index
Ageing Index % of persons aged +65 to persons aged 0-14, at municipality/commune level
KUKËS SHKODËR
LEZHË
DIBËR DURRËS
TIRANË
ELBASAN
Legend % of persons aged +65 to persons aged 0-14
FIER
BERAT
KORCA
< 30% 30.1% - 40% 40.1% - 50% 50.1% - 60%
GJIROKASTËR VLORË
60.1% - 70% 70.1% - 80% 80.1% - 100% 100.1% - 500% 500.1% - 1500% Qark border Manual Ranges
Prepared by: Co-PLAN Source: INSTAT, Census 2011
0 5 10
20
30
40 Kilometers
¯
4.2.5 Regions are attractive and with high ecological values and strong territorial capital; The ecological values and territorial capital of regions is rather diverse among Qarks in Albania. Ecological values are high in all of the territory, as a result of the diverse terrain, climate zones and rich biodiversity. The latter is more pronounced in the mountainous areas (the maps of protected and emerald areas). On the other hand the territorial capital 27 Co-PLAN, Institute for Habitat Development Tiranë, June 2015
for development is high along the western coast, where the development pressure is the highest. This area is also the most vulnerable one to climate change effects, due to the rising sea levels and the transforming river deltas. Figure 21: Potential vulnerability to climate change – population and area at risk
Potential Vulnerability to Climate Change % of existing population at risk of flooding if the water level rises 30 cm by 2050, at municipality 61 level
MALESI E MADHE
TROPOJE
SHKODER
HAS FUSHE ARREZ
PUKE
VAU I DEJES
KUKES
LEZHE MIRDITE DIBER MAT
KURBIN
Legend
KRUJE
KLOS BULQIZE
DURRES VORE
% out of total
SHIJAK
KAMEZ TIRANE LIBRAZHD
KAVAJE
area flooded by 30 cm rise in sea level
% of population at risk of flooding 0% - 1.2%
ELBASAN
RROGOZHINE PEQIN
CERRIK
LUSHNJE BELSH
1.3% - 15.2%
POGRADEC
15.3% - 29.7% 29.8% - 59.6%
PERRENJAS
DIVJAKE
PUSTEC
GRAMSH
KUCOVE URA VAJGURORE FIER
ROSKOVEC
MALIQ
BERAT
PATOS
59.7% - 83.2% MALLAKASTER
83.3% - 99%
% of flooded area
SELENICE
POLICAN
MEMALIAJ KELCYRE
0% - 4.1% 4.2% - 12.5%
DEVOLL
KORCE SKRAPAR
12.6% - 21.4%
KOLONJE
TEPELENE
VLORE
PERMET LIBOHOVE
HIMARE
GJIROKASTER
21.5% - 33.4% 33.5% - 59% 59.1% - 79.6% municipality 61 border
DELVINE DROPULL
SARANDE LIVADHJA
qark border KONISPOL
Natural Breaks Prepared by: Co-PLAN, 2015 Source: INSTAT Web Atlas, 2011, http://flood.firetree.net/?ll=41.6672,19.8553&zoom=9, accessed on 12/06/2015
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
0 5 10
20
30
40
¯
Kilometers
28
The percentage of population at risk of flooding reaches 30-100% in the western coast Qarks and decreases the more we move inland. Figure 22: Soil sealing per capita Soil Sealing per capita (Buildings and Infrastructure) Area covered by buildings and road infrastructure, per capita, at Qark level
Soil Sealing per capita (Corine) Area covered by artificial land use (Corine), per capita, at Qark level
KUKËS SHKODËR
KUKËS SHKODËR
LEZHË LEZHË
DIBËR DIBËR
DURRËS
DURRËS
TIRANË TIRANË
Legend Legend Soil Sealing /capita (Buildings&Infrastructure) 26
Soil Sealing (CORINE)/capita
FIER
41 BERAT
KORCA
BERAT
KORCA
131
67
176
83
214
84
238
86
GJIROKASTËR
273
GJIROKASTËR
306
VLORË
92
¯
98 200
Prepared by: Co-PLAN, 2015 Source: CORINE land cover; INSTAT, Census 2011
FIER
130
66
87
ELBASAN
Artificial land cover (CORINE)
ELBASAN
0 5 10
20
30
40 Kilometers
VLORË
307
¯
334 336 480 493 Prepared by: Co-PLAN, 2015 Source: CORINE land cover; INSTAT, Census 2011
0 5 10
20
30
40 Kilometers
One of the main features of development in Albania in the last 25 years is the fast urbanization in western coast cities and in the urban cores / administrative urban centers of the 12 Qarks. We have no appropriate figures to calculate the soil sealing in Albania, but we have made an approximation, with two methodologies: one is based on the area covered by buildings (the footprint) and roads; and the other one is calculated based on the artificial land use of Corine. The first method reveals that soil sealing (calculated as m2 per capita) is higher in the north and in Gjirokastra than it is in the most urbanized Qarks. This can be interpreted as a result of the very low population figures in these Qarks compared to the center ones, and the (still) low investments in infrastructure in the center Qarks compared to the population needs. The second methodology shows that Kukës and Dibër have the lowest figures, while all 5 coastal Qark (excluding Tirana) and Gjirokastra have the highest soil sealing figures. This shows that though (as in the 1st method) the infrastructure investments may be low, the fragmentation of the natural and agriculture land by the settlements is high. The second methodology considers as “sealed” all of the area among buildings, in all settlements, including the rural ones.
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
29
Figure 23: Biodiversity â&#x20AC;&#x201C; Environmentally Protected and Emerald areas
4.2.6 Territorial development is integrated and polycentric. Polycentrism is an objective of the European Union territorial development and is profoundly rooted in key policy documents that aim at fostering balanced and cohesive development. Polycentrism is initially presented as an objective of the European Spatial 30 Â Co-PLAN, Institute for Habitat Development TiranĂŤ, June 2015
Development Perspective (ESDP), assuming that “polycentric urban systems are seen as more efficient, more sustainable and more territorially balanced than both monocentricity (all activities concentrated in one center) and dispersion (all activities equally distributed over space)”. Thus, (according ESPON 1.1.1) a polycentric urban/regional/national system would ensure: (i) efficiency – large centers can exploit economies of scale, but suffer negative effects of over-agglomeration, while dispersed centers are too small to support efficiency; (ii) cohesion – spatial polarization and dispersal stand as two extremes of a relationship between competitiveness and segregation, in ones side and equality and lack of social mobility opportunities for citizens; (iii) environment – the use of energy for services and transport in a highly polarized or dispersed system are bound by advantages and several disadvantages that do not support one, or the other. The ESDP objective on polycentric development is: “Macro-regional efforts strengthening a polycentric and more balanced system of metropolitan regions, city clusters and city networks through closer co-operation between structural policy and the policy on the Trans-European Networks (TEN) and improvement of the links between international/national and regional/local transport networks” (ESDP, 1999). At the national level, polycentric development is mainly about encouraging regional specialization and the division of labor between urban regions, and improving access to urban services across the national territory. Co-PLAN has undertaken recently an analysis of the polycentrism features and opportunities in Albania, based on the ESPON project 1.1.1 “Potential for a polycentric development in Europe” methodology. Following this methodology, a first step was that of defining the geographical polygons of the analysis, namely the Functional Urban Areas (figure 24), the 45 minutes isochrones (from FUA centers), the Potential Urban Strategic Horizons (PUSH) and the Potential Integration Areas (PIA). The mapping of FUAs has made use of the INSTAT definitions of the Urban Cores, Urban Agglomerations and commuters catchment areas in Albania, based on the respective data from Census 2011, including the 1km2 grid (raster cells). The (base) maps were accessed through the ASIG platform on line. For the designation of the PUSH areas, the calculation of the 45 minutes (road public transport) isochrones from the FUA center is made through own calculations on the Google map. As a next step, was that of analyzing morphological and functional polycentrism (seven indicators/indexes for each of them) at national and FUA level. The overall analysis is not fully finalized, however, there several findings and conclusions that can be addressed by this proposal as input for the designation of the development regions. Thus, so far, a national polycentricity index is constructed to analyze and present the morphological polycentrism, and out of the 7 indicators of the functional/relational polycentrism, 6 are shown in this analysis/proposal (other indicators are still work in progress).
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
31
Figure 24: The 17 Functional Urban Areas of Albania
Polycentrism Analysis Functional Urban Areas (FUAs)
MALËSI E MADHE
TROPOJË
SHKODËR
HAS FUSHË ARRËS
PUKË
KUKËS
VAU I DEJËS
LEZHË MIRDITË DIBËR MAT
KURBIN
KLOS
KRUJË
BULQIZË DURRËS DURRËS VORË DURRËS
KAMËZ
SHIJAK TIRANË LIBRAZHD KAVAJË RROGOZHINË PEQIN
ELBASAN PRRENJAS
DIVJAKË LUSHNJE
BELSH
CËRRIK POGRADEC
KUÇOVË URA VAJGURORE FIER
MALIQ
ROSKOVEC PATOS
BERAT
MALLAKASTËR
SELENICË
PUSTEC
GRAMSH
POLIÇAN
KORÇË
DEVOLL
SKRAPAR
MEMALIAJ KËLCYRË KOLONJË
TEPELENË
VLORË
PËRMET
Legend
HIMARË GJIROKASTËR LIBOHOVË
FUA FUA Qark Border
DELVINË DROPULL
SARANDË
Municipality 61 Border
¯
FINIQ
KONISPOL
Prepared by: Co-PLAN, 2015 Source: INSTAT, 2011
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
0 5 10 20
30 40 Kilometers
32
The polycentricity index (table 5) is composed of the size, location and connectivity indexes, each with an equal weight. The size index is built on the prerequisite of polycentricity that there should be a distribution of large and small cities and that a polycentric urban system should not be dominated by one large city. The ideal rank-size distribution in a territory is log-linear and the flatter the rank-size distribution (regression line) is the more polycentric a region is. Table 5: The morphological polycentricity indexes in Albania and Europe – 27 Country
No.FUAs
Size Index
Location Index
17 97.0 28.0 Albania Austria 24 63.3 39.3 Belgium 21 86.6 60.5 Bulgaria 31 77.1 80.2 Switzerland 48 82.9 57.9 Cyprus 4 75.7 100.0 Czech Republic 25 79.2 51.7 Germany 186 86.4 56.1 Denmark 35 71.6 90.9 Estonia 10 64.7 94.8 Spain 105 81.6 30.7 Finland 35 73.9 32.1 France 211 66.4 77.3 Greece 45 36.6 95.9 Hungary 77 61.6 57.7 Ireland 7 63.1 100.0 Italy 253 87.5 52.0 Lithuania 8 76.5 83.5 Latvia 8 35.5 97.0 Netherlands 39 86.0 60.2 Norway 36 75.1 22.3 Poland 48 84.1 83.1 Portugal 44 49.0 55.8 Romania 59 78.3 80.9 Sweden 47 80.4 37.3 Slovenia 6 76.0 91.6 Slovakia 27 83.5 77.0 United Kingdom 146 77.3 55.5 ESPON Space 1588 88.5 35 Source: ESPON 1.1.1, 2005 and own calculations for Albania
Connectivity Index
Polycentricity Index
72.2 77.1 67.1 52.6 62.3 89.1 63.5 75.2 59.3 26.4 62.3 50.6 60.9 73.6 50.4 70.6 65.0 18.5 52.4 73.8 52.7 58.7 73.3 46.6 69.0 72.0 41.6 70.6 57.9
65.1 57.4 70.3 68.5 66.6 87.3 63.6 71.2 72.5 54.3 53.6 49.1 67.6 63.4 56.1 76.1 66.3 48.9 56.3 72.2 44.4 74.0 58.3 66.3 58.9 79.1 64.2 66.8 56.2
The indicators analyzed are two – GDP per capita and population, and for both we calculate the slope of the regression line and the deviation of the largest city from it. The Co-PLAN, Institute for Habitat Development Tiranë, June 2015
33
reason for using two indicators is that the size is measured for both population and economy importance of the regions (FUAs). The analysis of the size index shows that Albania is extremely monocentric, with 26% of the national population and 36% of the country’s GDP is concentrated in the Functional Urban Area of Tirana, and respective primacy rates of 1.3 and 1.9. Figure 25: Regression lines for the population of FUAs, with and without Tirana
Population of FUAs (not including Tirana)
800000
Laç
700000
ALBANIA Slope -‐2.3 Primacy 1.3
600000 500000
y = -‐23094x + 354932
400000 300000 200000
Korçe
Durres
Lezhe
100000
Sarande
0 -‐100000
0
2
4
6
8
10
12
14
16
18
Rank
900000 800000 Population of FUAs
700000 600000
ALBANIA Slope -‐3.1 Primacy 1.3
Tirana Laç
500000 400000 300000 200000
Durres Lezhe
100000
Sarande
0 -‐100000 0
2
4
6
-‐200000
8
10
12
14
16
18
Rank
Source: INSTAT, Census 2011 and own calculations.
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
34
GDP/capita of FUAs (not including Tirana)
Figure 26: Regression lines of FUAs GDP for 2012, with and without Tirana
300,000
ALBANIA Slope -‐0.8 Primacy 1.9
Laç
250,000 200,000
Durres
150,000
Vlore
100,000
Lezhe
50,000
Kuke s
-‐ (50,000)
0
GDP/capita of FUAs (in 000 ALL)
500000
2
4
6
8 10 Rank
Tirana
12
14
16
18
ALBANIA Slope -‐1.5 Primacy 1.9
400000 300000
Lac
200000
Vlore
100000
Lezhe Kukes
0 0
2
4
6
8
-‐100000
10
12
14
16
18
Rank
Source: INSTAT, Census 2011 and own calculations.
The picture of policentricity is a reversed one with regard to the location index, if compared to size index. The location index assumes that a policentric urban system is one, where the main urban centers are equally spaced from each-other and not clustered in one small part of the country. Because of historical reasons and especially as a result of the national policy for a uniform spatial distribution of the urban centers during 1950s1980s, the location index of Albania shows for a moderate policentrism. Tecnically speaking, the location index (in this case) is the Gini coefficient of inequality of the size of the thiessen polygons of the 17 FUAs centers. The closer the Gini is to 0, the more equal is the distribution of the sizes of the areas of the 17 FUAs and the more polycentric a region/country is. The map of the thiessen polygons (figure 28) and the Gini coeficient (included in the Lorenz curve of the polygons’ sizes values) show that the geographical location of the centers is rather uniform. However, this should not be interpreted as an indicator of polycentrism, but as a good opportunity for Albania to develop in a polycentric manner due to favourable locations of the urban centers. A uniform distribution of cities across a territory is more appropriate for a polycentric urban system Co-PLAN, Institute for Habitat Development Tiranë, June 2015
35
than a highly polarized one. Figure 27: National Size Index of Albania versus EU – 27 countries
Size Index
IS
FI
NO
RU SE
EE
LV DK
UK IE
LT BY
UK
PL
NL
UA
DE
BE
CZ
LU
SK AT
CH LI
FR
SI
RS
BA
BG ME
VA
ES
RO
HR
IT
AD PT
HU
SM
MC
MD
AL
MK TR
GR IT
IT
GI
Legend
MT
63.4 - 66.4
80.5 - 84.1
66.5 - 73.9
84.2 - 87.5
35.5 - 49.0
74.0 - 77.3
87.6 - 97.0
49.1 - 63.3
77.4 - 80.4
no data
Size Index
Natural Breaks
¯ 0
140 280
560
840
1,120 Kilometers
Prepared by: Co-PLAN, 2015 Source: ESPON 1.1.1, 2005, "Potentials for polycentric development in Europe"; INSTAT, 2011, own calculations
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
36
Figure 28: Thiessen polygons of the 17 FUAs
Polycentrism Analysis Service Areas of Functional Urban Areas (FUAs)
SHKKODER KUKES
LEZHE
PESHKOPI
LAC
DURRES
TIRANE
KAVAJE
ELBASAN
LUSHNJE POGRADEC
FIER BERAT KORCE
VLORE
GJIROKASTER
Legend FUA Center Service Area of FUA
SARANDE
Prepared by: Co-Plan, 2015 Source: INSTAT, 2011
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
¯ 0 5 10 20 30 40 Kilometers
37
Figure 29: The Lorenz curve of the FUAs size and Gini coefficient of inequality 100% 90% 80%
Gini of the service area = 0.28
70% 60% 50% 40% 30% Equality Lorenz
20% 10% 0% 0%
10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Source: Own calculations The third index is the connectivity one, which assumes that there should be e functional division of labor between cities. The latter implies that the channels of interaction between urban centers must be short and efficient. To measure the connectivity index, we used the potential accessibility of FUAs (figure 30), i.e. the potential accessibility that each urban core in a FUA has to the rest of the country (all the other FUAs). The potential accessibility of an urban center is higher, the higher the population (or GDP) that it reaches in the other urban centers is and the fastest the reaching routes are (travel time used for travel costs). The slope of the potential accessibility regression line and the Gini coefficient are the two sub-indicators used on this regard. The two sub-indicators (figures 31 and 32) have a similar meaning: the flatter the regression line, the more accessible are lower-level centers compared to the primary city, and the lower the Gini coefficient, the less polarized is the distribution of accessibility. The connectivity index of Albania is 72.2 and shows for week polycentricity patterns. The dominant FUA is (interestingly) that of Laç, which stands around 30% above the average. The FUA of Saranda has the lowest accessibility, more than 40% below the average. Laç is the second largest FUA in terms of population and is better located than Tirana in terms of time connections with the largest FUAs in the country. On the other hand, the accessibility of Laç to Tirana is higher than the other way around, because Tirana has a larger population. This argument reinforces the fact that the Tirana remains dominant and forces the overall system to be polarized rather than polycentric. Last, but not least, the FUAs of Durrës, Tiranë, Laç and Lezhë are the ones to have overlapping areas of influence among each-other and this shows for their higher potential of creating a polycentric system, getting thus polarized more and more from the rest of the country.
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
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Figure 30: Potential accessibility of 17 FUAs 140% 130% 120% 110% 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%
Source: INSTAT Census 2011, own calculations, Google map Figure 31: Regression line and slope of potential accessibility Potential Accessibility of FUAs
2,000,000
Slope of potential accessibility = 1,3
1,800,000 1,600,000 1,400,000 1,200,000 1,000,000 800,000
y = 1.3295x + 843448
600,000 400,000 200,000 -‐
-‐
100,000 200,000 300,000 400,000 500,000 600,000 700,000 800,000 Population of FUAs
Source: INSTAT Census 2011, own calculations, Google map
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
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Figure 32: The Lorenz curve of potential accessibility and the Gini coefficient 1 0.9
Gini of potential accessibility = 0.14
0.8 0.7 0.6 0.5 0.4 0.3
Equality
0.2
Lorenz
0.1 0 0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Source: INSTAT Census 2011, own calculations, Google map In conclusion to this section of the polycentricity analysis, Albania is a rather polarized country (figure 33) in overall and it is extremely polarized in terms of economic potential. Still, because of the low values of the location index, it has a good potential to become polycentric. However, it will fail to do so, if the economic potential will remain locked in Tirana and in the Durrës – Tirana – Laç triangle. The latter will contribute to further increase of domestic regional disparities and further weakening of the territorial cohesion patterns.
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
40
Figure 33: Polycentricity index of Albania versus EU – 27 countries
Polycentricity Index
IS
FI
NO
RU SE
EE
LV DK
UK IE
LT BY
UK
PL
NL
UA
DE
BE
CZ
LU
SK
FR
AT
CH LI
SI
RS
BA
BG ME
VA
ES
RO
HR
IT
AD PT
HU
SM
MC
MD
AL
MK TR
GR IT
IT
GI
Legend
MT
54.4 - 57.4
68.6 - 71.2
Polycentricity Index
57.5 - 58.9
71.3 - 74.0
44.4 - 49.1
59.0 - 65.1
74.1 - 79.1
49.2 - 54.3
65.2 - 68.5
no data
Natural Breaks
¯ 0
140 280
560
840
1,120 Kilometers
Prepared by: Co-PLAN, 2015 Source: ESPON 1.1.1, 2005, "Potentials for polycentric development in Europe"; INSTAT, 2011, own calculations
A next step in the polycentric system/potential analysis is the one of the functional specialization (and as a result relations between) of the regions (FUAs). Functional specialization is important as it ensures the diversity among cities, while also making sure that there is integration, synergies and cooperation. The mapping of the functional specialization of the FUAs in Albania is faced with data limitations. The analysis Co-PLAN, Institute for Habitat Development Tiranë, June 2015
41
conducted so far (within the limitations) for the following dimensions reveals that: 1. Decision-making in the public sector: All of the 17 urban cores are municipalities – local governments that function within a decentralization policy and legislation. 12 out of the 17 are Qark centers (the 2nd tier of local governance in Albania); all 17 urban cores used to be district centers (previous units and denominations for local governance); in some of the FUAs there are more than one district center. Because of the last three classifications, within the territory of these FUAs are located several regional branches of the national government / line ministries. So, from a decision-making in public sector point of view, the FUAs do not differ in specialization. 2. Decision-making in the private sector: The figures are given on the location of the 50 biggest companies in Albania. 28 out of them are located in Tirana (municipality) and 14 in Durrës (municipality). The large companies do influence the development of an urban system, and the strength of the latter relies also on its current attractiveness to private investors and companies. In the case of Albania, the current location shows that decision-making in the private sector remains highly concentrated in the Tirana-Durrës metropolitan area. 3. Population: the number of inhabitants represents the level of economic activities in a region, both for intensity and diversity. In Albania, at least 1/3 of the population is located in the Tirana-Durrës metropolitan area, thus in two overlapping FUAs, and so are most of the services and activities provided to/delivered from the population. 4. Tourism: this sector is an indicator for the attractiveness (current or potential) of the regions. Albania has an enormous touristic potential in terms of natural resources to offer. However, the development of infrastructures and accessibility, including the concentration of the private investments in the Tirana-Durrës metropolitan area, are correlated with the location of the hotels. Thus, 42 of the hotels (+3 stars) are located in the metropolitan area. Only 11% of the hotels are located in the North (from Kruja and above). There is also a concentration of hotels along the western coast cities/FUAs with 70% of the hotels. From a geographical point of view, it is clear that there is no correlation between the location of hotels (investments and services) and the touristic attractions (natural sites and leisure activities). 5. Industry: The strongest FUAs in terms of the gross value added in the industry sector are Elbasan, Fier, Shkoder and Durrës. This is certainly are linked to the industrial activities located in these Qarks and show for a potential of further urban transformations to take place in these areas. 6. Knowledge: For this function we have calculated the number of students attending higher education institutions. The capital/FUA of Tirana is clearly the strongest in terms of knowledge, but there is a relatively uniform distribution in some of the Qark (FUA) centers across the territory. While figures show for some balance, the quality of the institutions is not necessarily uniform, and these figures include only the public universities.
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
42
Figure 34: GVA/capita for the industry sector at Qark level
GVA / capita in the Industry Sector, at Qark level
KUKËS SHKODËR
LEZHË
DIBËR DURRËS
TIRANË
ELBASAN
Legend
FIER
gva/capita (in 000 ALL) BERAT
25
KORCA
36 56 58 93
GJIROKASTËR
124
VLORË 127 129 138 148 263 656
Prepared by: Co-PLAN, 2015 Source: INSTAT, 2011
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
¯ 0 5 10 20 30 40 Kilometers
43
Figure 35: Distribution of hotels per FUA
Polycentrism Analysis Distribution of 3+ star hotels in Albania per FUA
KUKËS SHKODËR
LEZHË
DIBËR
Legend
DURRËS
number of hotels 1 2
TIRANË
TIRANE
4 5 ELBASAN
6 7 10
FIER
11 BERAT
KORÇË
13 16
18
GJIROKASTËR VLORË
60 Municipality 61 Border Qark Border
Prepared by: Co-PLAN, 2015 Source: www.albania-hotel.com
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
¯ Kilometers 0 5 10 20 30 40
44
Figure 36: No. of students per FUA
Polycentrism Analysis Number of students attending tertiary education
MALËSI E MADHE
TROPOJË
SHKODËR
HAS FUSHË ARRËS
PUKË
KUKËS
VAU I DEJËS
LEZHË MIRDITË DIBËR MAT
KURBIN
KLOS
KRUJË
BULQIZË DURRËSDURRËS VORË DURRËS
KAMËZ
SHIJAK TIRANË LIBRAZHD KAVAJË
Legend
RROGOZHINË PEQIN
ELBASAN PRRENJAS
DIVJAKË LUSHNJE
no. of students
BELSH
CËRRIK POGRADEC
0
KUÇOVË
435
URA VAJGURORE FIER
458
MALIQ
ROSKOVEC PATOS
436
BERAT
MALLAKASTËR
POLIÇAN
728 2233
SELENICË
10092
DEVOLL
KËLCYRË KOLONJË
TEPELENË
VLORË
PËRMET HIMARË GJIROKASTËR LIBOHOVË
14447 14829 68170
KORÇË SKRAPAR
MEMALIAJ
3156 9627
PUSTEC
GRAMSH
DELVINË DROPULL
SARANDË
71922 Municipality 61 Border
Prepared by: Co-PLAN Source:
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
FINIQ
KONISPOL
¯ 0 5 10 20 30 40 Kilometers
45
Figure 37: Population density
Population density No.of inhabitants /km2 at Municipality 61 level
MALESI E MADHE
TROPOJE
SHKODER
HAS FUSHE ARREZ
PUKE
VAU I DEJES
KUKES
LEZHE MIRDITE DIBER MAT
KURBIN
KRUJE
KLOS BULQIZE
DURRES VORE SHIJAK
KAMEZ TIRANE LIBRAZHD
KAVAJE ELBASAN
RROGOZHINE PEQIN
PERRENJAS
DIVJAKE CERRIK
LUSHNJE BELSH
POGRADEC PUSTEC
GRAMSH
KUCOVE URA VAJGURORE
Legend
FIER
ROSKOVEC
Population density
MALIQ
BERAT
PATOS
MALLAKASTER
POLICAN
KORCE
DEVOLL
SKRAPAR
density 8 - 22 23 - 35
MEMALIAJ
SELENICE
KELCYRE
Text
KOLONJE
TEPELENE
VLORE
PERMET
36 - 51 52 - 73
LIBOHOVE
HIMARE
GJIROKASTER
74 - 164 165 - 315
DELVINE DROPULL
316 - 520 521 - 2605
SARANDE LIVADHJA
Qark border
¯
KONISPOL
Natural Breaks
Prepared by: Co-PLAN, 2015 Source: INSTAT Census 2011
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
0 5 10
20
30
Kilometers 40
46
Figure 38: Population potential within 30 km radius
Population Potential within 30 km Number of persons reachable from FUA centers, within 30 km of linear distance
SHKODËR KUKËS
LEZHË
PESHKOPI
DURRËS
Legend Qark border
TIRANË
KAVAJË
ELBASAN
317117
Municipality 61 border PUSH Areas
LUSHNJE
351684
FUA centers
Population potential Population within 30 km linear distance
POGRADEC
474882
FIER BERAT
540646
KORÇË
74482 VLORË
81381 95172
737035
100495 149659
1210740
167664 GJIROKASTËR
206718 217601
1252360
¯
SARANDË
312078
Prepared by: Co-PLAN, 2015 Source: Google Maps, own calculations
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
0 5 10
20
30
40 Kilometers
47
Figure 39: Population of FUA versus PUSH Comparison*of*PUSH*popula2on*figures*with*na2onal*sta2s2cs*on*FUAs% 1100"
y"="0.9587x"+"128.46"
1000"
PUSH%Popula+on%(in%1,000)%
900" 800" 700" 600" 500" 400" 300" 200" 100" 0" 0"
50"
100" 150" 200" 250" 300" 350" 400" 450" 500" 550" 600" 650" 700" 750" 800" FUAs%Popula+on%(in%1,000)%
Source: INSTAT, Census 2011 and Raster cells, Own calculations The morphological and functional analysis of polycentrism (conducted so far) is descriptive to the current situation, which we may want to keep alike or change in the future. The future changes would depend on several factors, but at least, we need to know where there could be more potential for development towards a more polycentric urban system. Thus, where can we identify potential for new functional entities and increased territorial cooperation, rather than in the current urban nodes/centers. The analyses conducted on this regard remains still morphological, and as such, the results do not guarantee that cooperation will happen right where the analysis identifies the potential. However, this could be an indication to planning (spatial, development and financial) policies and instruments. Thus the results are indicative and may be used as guide for further changing patterns of territorial cooperation and development. Based on ESPON 1.1.1, this analysis designates for each FUA, areas that can be reached within 45 minutes by road travel (the 45 min isochrones). This time limit is widely recognized as the most appropriate for daily commuting (work catchment areas), and the areas included within the commuting radius provide cities with a better opportunity for functional integration. The hypothesis is that “cities with overlapping travel-to-workareas have the best potential for developing synergies” (ESPON 1.1.1, 2005). These areas are then approximated to municipal boundaries, as municipalities are the potential building blocks in polycentric development strategies. The areas thus established are called Potential Urban Strategic Horizons (PUSH) and their further integration forms the so-called Potential Integration Areas (PIAs) (figures 40 and 41).
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
48
Figure 40: Push intersecting – the 45 minutes isochrones areas
Polycentrism Analysis Potential Urban Strategic Horizons (PUSH) intersection 45 min Isochrone
MALËSI E MADHE
TROPOJË
SHKODËR
HAS
FUSHË ARRËS
VAU I DEJËS
PUKË
KUKËS
LEZHË MIRDITË DIBËR MAT
KURBIN
KLOS
KRUJË
BULQIZË
DURRËS DURRËS VORËKAMËZ SHIJAK TIRANË
LIBRAZHD KAVAJË RROGOZHINË PEQIN
ELBASAN PRRENJAS
CËRRIK DIVJAKË LUSHNJEBELSH
POGRADEC
URA VAJGURORE FIER ROSKOVEC PATOS BERAT
MALIQ
MALLAKASTËR POLIÇAN SKRAPAR
Legend
SELENICË
KORÇË
DEVOLL
MEMALIAJ KËLCYRË
number of PUSHs intersecting 5
PUSTEC
GRAMSH
KUÇOVË
4 3 2 0
KOLONJË
TEPELENË
VLORË
PËRMET HIMARË GJIROKASTËR LIBOHOVË DELVINË SARANDË
Municipality 61 Border
DROPULL FINIQ
KONISPOL
Prepared by: Co-PLAN, 2015 Source: Google Map, own calculations
¯ 0 5 10 20 30 40 Kilometers
In Albania, 20% of the new municipalities or 23% of the territory are not covered by any PUSH polygon at all. This is also the most mountainous area of the country. The 49 Co-PLAN, Institute for Habitat Development Tiranë, June 2015
municipalities in the middle of Albania (from Durrës and Tirana in the north to Fier and Lushnje in south) remain advantageous in overall (similarly to the FUAs situation). However, the most interesting finding is that the highest number of intersections is found for Krujë, Shijak, Peqin, Lushnje, Belsh, Cërrik, Roskovec and Ura Vajgurore. These are some of the smallest municipalities with 11% of the population of Albania and with the exception of Lushnje, are not urban cores to any agglomerate or FUA. However, their location is very strategic and they are in the commuting basins of at least 5 FUAs/Urban cores. This increases the opportunity for these municipalities to be integrated in a polycentric urban system, through serious investments in infrastructure and services. If investment strategies would follow the logic of this analysis Tirana, Fier, Shkodra and Elbasan (some of the biggest FUAs and major urban cores currently) could in fact be just the corners of a future urban core for Albania. On the other hand, the above secondary or even tertiary cities do have a potential for hosting functional specialization that the current urban cores do not have, but do need to complement with their major functions and activities. As a conclusion of the polycentrism analysis so far, we notice that Albania has a monocentric spatial structure. This is strongly supported by the figures on population and GDP. It also has a good potential for developing a polycentric urban system and spatial structure, supported by the uniform location of urban centers across the territory, the potential of the secondary and tertiary urban for more development due to their advantageous location between and close to the main centers, and the diverse distribute of the specialized functions. The latter represents both, an opportunity (not every function is concentrated in Tirana) and a risk (most of the functions are located along the coastal cities) due to accessibility and geographical patterns. Making use of the potential and avoiding risks (also the increase of disparities) requires for instruments to push further the development towards the inland and eastern/more mountainous urban centers. These should be policy, planning and financial instruments. The latter should be used based on programs that aim at enhancing the development potential of the development regions that this proposal will help designating. Last, but not least, the strengthening of the polycentric system (resulting on reduced disparities, strengthening of the economic development, competitiveness and cohesion) requires also for healthy flows of cooperation between urban centers, regardless of their level in the network of the urban nodes. The information on flows of cooperation is extremely limited, but as limited as it is, it shows (figure 42) that most of the interactions (often donor supported or promoted by) happen in the central part of Albania and Shkodër. Thus, while natural resources may be well located across Albania, capacities and cooperation flows (needed to make uniform use of resources) are concentrated in some major urban centers, leaving the 2nd and 3rd tier weak and un-stabilized in this regard.
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
50
Figure 41: PIA intersections
Polycentrism Analysis Potential Integration Area (PIA), at Municipality 61 level
MALËSI E MADHE
TROPOJË
SHKODËR
HAS FUSHË ARRËS
PUKË
KUKËS
VAU I DEJËS
LEZHË MIRDITË DIBËR MAT
KURBIN
KLOS
KRUJË
BULQIZË DURRËS
VORË
KAMËZ
SHIJAK TIRANË LIBRAZHD KAVAJË RROGOZHINË PEQIN
ELBASAN PRRENJAS
DIVJAKË LUSHNJE
CËRRIK
BELSH
POGRADEC KUÇOVË
FIER
BERAT
MALLAKASTËR
Legend No. of PIAs over a Municipality
MALIQ
ROSKOVEC PATOS
SELENICË
PUSTEC
GRAMSH
URA VAJGURORE
POLIÇAN
KORÇË
DEVOLL
SKRAPAR
MEMALIAJ KËLCYRË KOLONJË
TEPELENË
VLORË
PËRMET
0 HIMARË
1
GJIROKASTËR LIBOHOVË
2 DELVINË
3 4
DROPULL
SARANDË FINIQ
5 Qark Border
Prepared by: Co-PLAN Source: Google Map, own calculations
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
KONISPOL
¯ Kilometers 0 5 10 20 30 40
51
Figure 42: Cooperation degree
Cooperation degree No. of cooperation projects
Kelmend
Shkoder
Kukës
Velipoje Shëngjin Lezhë Peshkopi
Legend Qark border Municipality 61 border
VoreKamez Durres
Municipality/commune 373 border
Tirane
Kavajë Elbasan
No. of intercommunal cooperation projects
Lushnje
1
Kuçovë
2
Fier Levan
Berat
3 4
5
Tepelene
7
¯
16 Prepared by: Co-PLAN, 2015 Source: Prime Minister Office, 2014
0 5 10
20
30
Kilometers 40
4.3 Achieving Environmental Sustainability and Green Economy 4.3.1 The territorial potential for greener economy and sustainability enhanced and used in a sustainable way The sustainable use of natural resources is key to the environmental resilience of the Co-PLAN, Institute for Habitat Development Tiranë, June 2015
52
territories. Regions should not simply think in terms of economic development, but also of green economies as a policy oriented concept that leads to the operationalization of the sustainable development (refer GREECO, 2013). The measurement of the green economy in Albania is a rather limited task due to data availability (either in terms of indicators, or time series). For instance, it is impossible (currently) to describe and analyze in full the regions from a environmental quality of life point of view (i.e. environmentally induced health problems and related costs, exposure to industrial risks and related economic losses, etc.); or for economic opportunities and policy responses (environmentally related taxation, patents of importance to GGs, etc.). In overall, it is known that Albania has a significant natural asset base, such as freshwater resources, forest resources, minerals, wildlife, etc. The water resources are organized in 6 official river basins flowing from the east to west (almost all parallel, due to the geographical shape and features of Albania), providing a good water base for all regions. Forest cover almost 2/3 of the country from north to south and east to west. Below, we have analyzed from a spatial perspective the energy potential of Albania (considering all of the renewable resources, not water) and we can realize that most of the potential is concentrated along the coast, with gradual decrease while advancing inland towards the east. Letâ&#x20AC;&#x2122;s keep in mind that the coast is the most urbanized area of Albania and also where most of the economic activities (services, transportation, tourism, administration, etc.) are concentrated. The analysis of the environmentally protected and Emerald Areas (figure 23), shows for a distribution of the biodiversity, which is rather different from the energy potential. Regions in the north-east and south-east have a stronger weight compared to the center and the coast. While it is difficult to measure the performance of Albania in terms of green economy, we can simply show that there is great potential for embarking on economic development policies and solutions that are environmentally sound and do guarantee resilience. However, the analysis so far, shows as well that the pressure towards some of the key environmental resources and potentials is extremely high in Albania and regional development policies should be oriented towards programs and projects that not only mitigate the pressure, but also have green economy as a policy target.
 Co-PLAN, Institute for Habitat Development TiranÍ, June 2015
53
Figure 43: Energy Potential in Albania (overlay of the highest values per each potential)
Interpretation of the Energy Potential in Albania
Legend M ALESI E M AD H E
T R O P O JE
Municipality 61 border Qark border
SHKO DER
4500-5250 min val.
HAS
FUSHE ARREZ
windy hours VA U I D E J E S
PUKE
1000
KUKES
sunshine hours LEZH E
2600
M IR D IT E
2800 min val.
D IB E R
2100
average wind speed (m/s) 3.4
M AT
K U R B IN
KR U JE
KLO S B U L Q IZ E
DURRES VO RE
3.8
KAM EZ
S H IJ A K T IR A N E
4.3 min val.
1.5
heat flow density (mW/m2) 57
L IB R A Z H D K AVA JE
ELBASAN
R R O G O Z H IN E P E Q IN
PE R R E N JA S
D IV J A K E
C E R R IK BELSH
LU S H N JE
PO GRADEC
63 min val.
5
temp. at 3000m depth (ºC)
PUSTEC
GRAM SH
KUCO VE U R A VA J G U R O R E F IE R
ROSKOVEC PAT O S
75
M A L IQ
B E R AT
M ALLAKASTER
P O L IC A N
KO RCE
D EVO LL
S K R A PA R
80 min val.
30
temp. at 100m depth (ºC) 18
S E L E N IC E
M E M A L IA J KELC YR E KO LO N JE
VLO R E
TEPELEN E PERM ET L IB O H O V E
H IM A R E
G J IR O K A S T E R
19 min val.
6
D E LV IN E D R O PU LL
daily solar radiation (kWh/m2)
¯
S A R A N D E L IV A D H J A
4.6
K O N IS P O L
4.7 min val.
3.29
0 5 10
20
30
40 Kilometers
Prepared by: Co PLAN, 2015 Source: Co-PLAN, 2007: "Study on Assessment of Renewable Energy Sources Potentials in Albania"
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
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Figure 44: No. of nature monuments per Qark 136& 115& 92&
90&
95&
91&
81&
71& 40&
37&
28&
Ë& SH KO DË R& TI RA NË & VL OR Ë&
&
LE ZH
KU KË S
CA &
ËR &
KO R
OK AS T
FI ER & IR
BE RA T& DI BË R& DU RR ËS & EL BA SA N&
14&
GJ
nature&monuments&
Source: Ministry of Environment and ASIG, 2015 Figure 45: % of environmentally protected and Emerald areas per Qark 15.6%& 11.2%&
10.0%& 7.4%& 4.7%&
6.6%&
10.1%& 6.3%&
6.6%&
ËS & BA SA N& GJ FI E IR OK R& AS TË R& KO RC A& KU KË S& LE ZH Ë& SH KO DË R& TI RA NË & VL OR Ë&
3.9%&
EL
RR
R&
DU
BË DI
RA
T&
2.4%&
BE
15.3%&
Source: Source: Ministry of Environment and ASIG, Own calculations, 2015 4.4 Improving the Accessibility of Regions The analysis of accessibility was partially considered in the polycentricity assessment in section 4.2.6. From that analysis, Albania resulted with a high connectivity index – i.e. low connectivity that is interpreted as a measure for polarization of the center and weak spatial polycentricity patterns. The following analysis, is aiming at providing few more information (due to data limitations we could not exploit all indicators listed by TRACC, 2015, which served as a reference) on accessibility, looking at three types of indicators: the travel costs, the cumulated opportunities and again potential accessibility. According to the reference study, “accessibility is the main product of a transport system and it determines the locational advantage of an areas relative to other areas” (TRACC, ESPON, 55 Co-PLAN, Institute for Habitat Development Tiranë, June 2015
2015). Through looking at the indicators (below) we do not simply verify (to a certain extent) the locational advantage or disadvantage of the regions, but also draw a straightforward conclusion on the regions that the future transport policy should focus more and redirect most of the investments. 4.4.1 Travel costs decrease; The travel cost indicator (in this case measured as time of people living in the 61 municipalities to motorway exits) assumes that not all possible destinations are relevant for the accessibility of an area, but only a specified set. The destinations in this case are the motorway exits, assuming that once people reach the exit to a high speed road, they either enter the commuting area of main urban centers, or are able to travel to their destinations and back within the day. For this map we considered only those axes where the travel speed can remain unchanged at values above 70km/hr for more the 50% of the trip. The map of accessing motorways exits is helpful in identifying the regions that are not accessible and have low access. It also helps understanding that Albania needs a transport network investment strategy that will ensure the penetration of the motorway axes from west to east, meaning further integration into the Balkan area and better connections between the Western Europe and the eastern countries. The highway segment from Laç to Kukës and the one from Tirana to Elbasan, are clear evidence supporting the reinforcement of this conclusion.
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
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Figure 46: Access time of people to motorways exists
Access time to motorway exits Distance from the centers of the 61 municipalities to the nearest motorway exit (min)
( !
BAJRAM CURRI ( !
KOPLIK
( !
KRUMË
( !
SHKODËR
( !
( !
( !
KUKËS
PUKË
( !
VAU I DEJËS
( !
( ! LEZHË RRËSHEN ( !
PESHKOPI
( !
LAÇ
( !
BURREL ( !
( !
KRUJË
( !
KLOS
( ! ! ( ( VORË ! ! ( ( SHIJAK !
TIRANË
( !
( !
KAVAJË
LIBRAZHD ( !
ELBASAN
( ! ( !
Legend
PEQIN
( !
DIVJAKË
( !
PRRENJAS
( ! !CËRRIK (
(BELSH-QENDËR ! LUSHNJE
( !
POGRADEC
( !
time distance to nearest motorway exit (min)
LIQENAS ( !
( !
MALIQ
BERAT
( !
( !
( ! ( ! ( !
SELENICË
( !
ÇOROVODË
VLORË
46 - 60
( !
centers of Municipalities 61 motorway network Qark border
ERSEKË ( !
91 - 120 > 121
( !
MEMALIAJ ( ! ( ! KËLCYRË
61 - 90
( !
( !
KORÇË BILISHT
POLIÇAN
BALLSH
16 - 30
( !
( ! KUÇOVË
( !
( !
FIER! ( PATOS
0 - 15
31 - 45
GRAMSH
( !
PËRMET ( !
HIMARË
( !
GJIROKASTËR ( ! LIBOHOVË ( ! DELVINË ( ! ( ! FINIQ
( !
¯
Manual Ranges
Prepared by: Co-PLAN, 2015 Source: Google Map, own calculations
( !
KONISPOL 0
10
20
40
60
80 Kilometers
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
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Figure 47: Travel time of people to regional centers by road and public transport
Accessibility of People Travel time of people from the municipality/commune center to the Qark Center, by road and public transport
KUKËS SHKODËR
LEZHË
DIBËR DURRËS
TIRANË
ELBASAN
FIER
BERAT
KORCA
Legend Qark center Qark border
time to Qark center (min)
GJIROKASTËR VLORË
0 - 25 26 - 45 46 - 80 81 - 120 121 - 190 Manual Ranges
0 5 10
20
30
¯
40 Kilometers
Prepared by: Co-PLAN, 2015 Source: Google Map, own interpretations
4.4.2 Cumulated opportunities increase This indicator is based on the assumption that people are interested to go to destinations that they can reach with a fixed budget for travel (in this case expressed as the time limit that one accepts to travel – 60 minutes). Thus people who commute or travel on Co-PLAN, Institute for Habitat Development Tiranë, June 2015
58
daily/routine basis would prefer to travel not more than a given amount of time, and as a result go to those destinations / urban centers than can be reached within that time (conclude a business trip). In this analysis we have identified the urban centers equal to or with more than 10,000 residents that can be reached within 60 minutes by the Qark centers. The following figure x shows for a clear dominance of Tirana and Durrës, then a vertical division between west and east and coast and mountainous areas. Korca is the only one to make a difference in the picture, due to the fact that a good proportion of its territory is rather plain, though in high altitude above the sea levels. Figure 48: Cities with at least 10,000 residents within 60 minutes by road
Availability of urban functions No. of cities with a population >10,000, located in Qark with a distance 60 minutes or less from the Qark center
KUKËS SHKODËR
LEZHË
DIBËR DURRËS
TIRANË
ELBASAN
Legend no of centers >= 10000 that reach the Qark center in < 60 min
FIER
BERAT
KORCA
1 2 3 4 5
GJIROKASTËR VLORË
8 Communes with population >= 10 000
¯
Qark Centers Municipality/commune border Qark border Prepared by: Co-PLAN, 2015 Source: INSTAT, Census 2011, Google Maps
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
0 5 10
20
30
Kilometers 40
59
Figure 49: Number of higher secondary schools within 30 minutes walk travel time
Access to higher secondary schools No. of higher secondary schools within 30 minutes walk, from existing urban centers (36)
(
BAJRAM CURRI
Legend no of schools accessible in 30 min walk from municipality center
(
0
(
1
(
2
KOPLIK
3
(
4
(
5
(
6
( (
KRUMË
((
KUKËS
((
SHKODËR
PUKË
FUSHË-ARRËZ
VAU I DEJËS
( ((
LEZHË RUBIK RRËSHEN
(
PESHKOPI
( ( ( ( (( ((( ((( ( LAÇ
BURREL
MAMURRAS
(
KRUJË FUSHË-KRUJË
KLOS
BULQIZË
MANËZ
VORË KAMËZ SUKTH I RI SHIJAK TIRANË DURRËS
(
(
KAVAJË
(
( ( ( (( (
(
LIBRAZHD
ELBASAN
RROGOZHINË PEQIN
DIVJAKË
(
(
PRRENJAS
CËRRIK
BELSH-QENDËR
LUSHNJE
8
(
(
(
9
POGRADEC
( ((( ( ( ( ( ( (( ( ( FIER
ROSKOVEC
(
(
Qark border Urban Centers (36) higher secondary schools
MALIQ
(
KORÇË
POLIÇAN
SELENICË
ÇOROVODË
VLORË
MEMALIAJ
ORIKUM
16
(
BERAT
PATOS
BALLSH
10
(
(
GRAMSH
KUÇOVË
areas covering 30 min walk from urban centers (36)
!
(
TEPELENË
(
BILISHT
(
ERSEKË
KËLCYRË
(
PËRMET
(
LESKOVIK
(
HIMARË
((
GJIROKASTËR LIBOHOVË
( (
DELVINË
¯
SARANDË
Prepared by: Co-PLAN, 2015 Source: ASIG, Ministry of Education
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
(
KONISPOL
0 5 10
20
30
Kilometers 40
60
Figure 50: Number of higher secondary schools within 45 minutes travel time by public transport
Access to higher secondary schools No. of higher secondary schools within 45 minutes travel by road and public transport, from FUA centers
!
!
! ! !
!
!
!
!
!
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! !
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SHKODËR
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!
!!!! ! ! ( ! !
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42 - 47
!
!
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!
! !! ! ! ! ! FIER
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36 - 41
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8 - 15 16 - 35
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!
!
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(! !
!
! ! ELBASAN ! !
! ! ! !! ! !
! ! !
45 min from FUA centers
! !
!
!
!!!!
No. of higher secondary schools
!
!
!
! KAVAJË
Legend
!
! ( !
!
!
! ( ! !! ! ! !! ! ! ! !! ! !!! ! (! ! ! ! !!! ! ! ! !! !! !! !
! ( !
!
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48 - 69
! !
!
!
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!
!
!
!
! ! !
higher secondary schools isochromes 45 min from FUA centers
!
!
GJIROKASTËR
! ( !
! !!! !
!
!
!
!
¯
! ( !
Qark border
SARANDË
!
! ( !
Natural Breaks
!
Prepared by: Co-PLAN, 2015 Source: ASIG, Ministry of Education
!
! ( !
0 5 10
20
30
Kilometers 40
The cumulated opportunities are analyzed also for the number of higher secondary schools reached within 30 and 45 minutes of travel (walk and public transportation). In the second case we see that the opportunities are concentrated in the coast (Shkodra to Vlora) and especially in Tirana. Appart from better accessibility of this areas, this may also be due to the fact that most of the high schools are located in these regions where the population density is the highest. 61 Co-PLAN, Institute for Habitat Development Tiranë, June 2015
4.4.3 Potential Accessibility improves. As it was presented in the polycentricity analysis, potential accessibility measures the accessibility of a region to the other/s based on the size (population or GDP) of the regions to be accessed and the travel time to go there. The analysis in the section 4.2.6 reveals that the triangle Lezhë – Elbasan – Fier has the highest accessibility. Figure 51: Potential Accessibility of FUAs Polycentrism Analysis Accessibility Potential Index
KUKËS SHKODËR
LEZHË
DIBËR DURRËS
Legend TIRANË
index 0.618 0.672
ELBASAN
0.748 0.759 0.87 0.927
FIER
0.94
BERAT
KORÇË
0.948 1.021 1.111 1.116 1.197 1.218
GJIROKASTËR VLORË
1.23 1.246 1.25 1.296 Kufiri_i_Qarkut Prepared by: Co-PLAN, 2015 Source: Google Map & own calculations
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
¯ 0 5 10 20 30 40 Kilometers
62
4.5 Final Conclusions and the Designation of the Development Regions Boundaries The above analysis provides conclusions for all 4 objectives as the following: 1. Economic competitiveness is more pronounced in the center Qarks and weaker in the more mountainous and rural areas. In terms also of polycentric development, the designation of the future development regions should be such as to include Qarks with different competitiveness factors within one region. This would help for better access to the EU funds, especially for the more disadvantageous regions. 2. Disparities remain high and have increased more. The northern Qarks are in a higher disadvantage in terms of employment rates, GVA per sector and poverty. However these qarks do still have the advantage of the young population that is though dependent on high unemployment figures for both males and females. 3. Access to services shows for high disparities among municipalities and communes (373), with the Qarks centers being in a clear advantage compared to the peripheral local governments. 4. Transport accessibility is depended on the following variables: the penetration of the high speed road network inland (from the western coast to the eastern centers), which seems to be as yet very low; the size (population and GDP) of the cities/urban cores, which is much bigger along the coast and especially in the Laç – Elbasan – Fier triangle; and on the distribution of (mainly administrative and education) functions (the diversity of the latter being more dominant in the Qark centers). Any future development region should consider an infrastructure investment strategy that will extend this network towards the north and south-east, by connecting fast not only the Ionian-Adriatic corridor with the eastern parallel corridor, but also Tirana, Shkodra, Durrës and Vlora with the rest Balkan cities in the east and south of Albania. 5. The coastal regions have a pronounced territorial capital (both environmental and urban), but are also the most disadvantageous in the terms of urban development pressures and climate change effects. Their resilience, especially the environmental one, is at extremely high risk. Any future development region should consider that each segment of this at-high-risk area is counterbalanced by safer regions located inland and towards the mountainous / rural areas of northeast and southeast. 6. The spatial polycentricity analysis shows that Albania is monocentric in overall, and highly polarized in terms of the concentration of the GDP and population in the TiranaDurrës metropolitan area. This supports also the findings for relatively high disparities among local governments and among Qarks. However, Albania has a good potential for moving towards a more balanced spatial structure, because of the uniform distribution of the urban centers across the territory (due to historical reasons). The latter should be supported by: more investments in infrastructure, especially transport, so as to increase the accessibility of regions; and better planning for the areas that have a high potential for urban integrations – those urban centers or local governments that are within 45 minutes of commuting travel time from at least 4 or more urban cores (FUAs centers). Co-PLAN, Institute for Habitat Development Tiranë, June 2015
63
Based on the above conclusions and on the assumption that the future development regions should not be sector but territory oriented, so as to ease the implementation and the success of regional development policies, the proposal of their designation is based on the following criteria: 1. Should not favor one sector to the others, on the contrary should be integrative and favoring polycentric territorial development. This criteria is really crucial as otherwise we would not be addressing regional development, but sectorial development; 2. Should be able to facilitate the achievement of all RD objectives: increase competitiveness; promote convergence, cohesion and resilience; make sustainable use of the natural resources; promote polycentric spatial development and increase the accessibility of regions; 3. Should (preferably) match with current Qark borders (because most of the RD data are generated at this level), or at least with the borders of the 61 municipalities. These criteria is rather optional, because the designation of the development regions, would be the appropriate moment to also take decisions on the generation of data at LAU and NUTS 3 levels, by also revising the NUTS 3 boundaries, if necessary for better regional development. 4. Should form development regions where there is a mixture of best and worst performers (in terms of social-economic indicators). The GDP per capita is often used as an indicator for allocating development funds and as such it can favor certain regions, while discriminating others, based on the fund allocation policy. Currently, Albania is at a development stage, where all regions need significant funds for development. 5. Should allow for cross-border regions. Thus, the final designation should be such that the future development projects for each region do relate to the crossborder development. The conclusions and the criteria are summarized in the following map. This map shows the distribution of the key findings over the territory and how the development corridors could extend to connect places and lead towards regions. The analysis finally leads to 3 options for designation of the borders of the development regions, for which there are statistics provided below. In all three options, two regions remain the same and the differences appear in the southern regions.
 Co-PLAN, Institute for Habitat Development TiranÍ, June 2015
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Figure 52: Findings and criteria conceptualized
 Co-PLAN, Institute for Habitat Development TiranÍ, June 2015
65
Figure 53: Proposal 1 for designation of the boundaries of development regions in RMA version 1 Albania
KUKËS SHKODËR KUKËS
SHKODËR
$
$
LEZHË LEZHË
$
PESHKOPI
$
LAÇ
$
DIBËR
DURRËS
TIRANË
DURRËS
$
$
TIRANË KAVAJË
$
ELBASAN
$
ELBASAN LUSHNJE
$ FIER FIER
$
POGRADEC
$ BERAT
$
BERAT
KORÇË
$
KORCA
VLORË
$
Legend $
FUA centers Qark border
GJIROKASTËR VLORË GJIROKASTËR
$
Municipality 61 border
RMA division Shkoder-Kukes-Lezhe
SARANDË
$
¯
Durres-Tirane-Peshkopi Fier-Lushnje-Berat-Elbasan-Korce Sarande-Vlore-Gjirokaster 0 5 10
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
20
30
40 Kilometers
66
Figure 54: Proposal 2 for designation of the boundaries of development regions in RMA version 3 Albania
KUKËS SHKODËR KUKËS
SHKODËR
$
$
LEZHËLEZHË
$
PESHKOPI
$
LAÇ
$
DIBËR
DURRËS
TIRANË
DURRËS
$
$
TIRANË KAVAJË
$
ELBASAN
$
ELBASAN LUSHNJE
$ FIER
$FIER
POGRADEC
$ BERAT
$
BERAT
KORÇË
$
KORCA
VLORË
$
Legend $
FUA centers Qark border Municipality 61 border
GJIROKASTËR VLORË GJIROKASTËR
$
RMA division Shkoder-Kukes-Lezhe Durres-Tirane-Peshkopi
SARANDË
$
¯
Elbasan-Korce Fier-Lushnje-Berat Sarande-Vlore-Gjirokaster 0 5 10
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
20
30
40 Kilometers
67
Figure 55: Proposal 3 for designation of the boundaries of development regions in RMA version 4 Albania
KUKËS SHKODËR KUKËS
SHKODËR
$
$
LEZHËLEZHË
$
PESHKOPI
$
LAÇ
$
DIBËR
DURRËS
TIRANË
DURRËS
$
$
TIRANË KAVAJË
$
ELBASAN
$
ELBASAN LUSHNJE
$ FIER
$FIER
POGRADEC
$ BERAT
$
BERAT
KORÇË
$
KORCA
VLORË
$
Legend $
FUA centers
GJIROKASTËR VLORË
qarqe
GJIROKASTËR
$
BASHKITE
RMA division Shkoder-Kukes-Lezhe
SARANDË
$
¯
Durres-Tirane-Peshkopi Elbasan-Korce Fier-Lushnje-Berat-Sarande-Vlore-Gjirokaster 0 5 10
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
20
30
40 Kilometers
68
Statistics on each proposal:
Proposal 1 SH-KU-LE • 7,401 km2 • 434,666 inh. DR-TR-PE • 4,869 km2 • 1,149,197 inh. FR-LU-BR-EL-KO • 10,467 km2 • 968,459 inh. SR-VL-GJ • 5,535 km2 • 247,816 inh.
Proposal 2 SH-KU-LE • 7,401 km2 • 434,666 inh. DR-TR-PE • 4,869 km2 • 1,149,197 inh. EL-KO • 6,814 km2 • 516,184 inh. FR-LU-BR • 3,653 km2 • 452,275 inh. SR-VL-GJ • 5,535 km2 • 247,816 inh.
Co-PLAN, Institute for Habitat Development Tiranë, June 2015
Proposal 3 SH-KU-LE • 7,401 km2 • 434,666 inh. DR-TR-PE • 4,869 km2 • 1,149,197 inh. EL-KO • 6,814 km2 • 516,184 inh. SR-VL-GJ-FR-LU-BR • 9,188 km2 • 700,091 inh.
69