Territorial Trends in the Baltic Sea Region 8th VASAB Conference of Ministers Responsible for Spatial Planning and Development of the Baltic Sea Region 26 September 2014, Tallinn, Estonia ESPON BSR-TeMo Tomas Hanell, YTK, Aalto University, Finland
Structure I. Snapshot of territorial trends in the BSR II. BSR divides and territorial cohesion
I. SNAPSHOT OF TERRITORIAL TRENDS IN THE BSR
1. Increasing spatial polarisation of BSR territories A clear trend of increasing spatial polarisation is further aggravating already existing unbalanced regional structures Selected opposite trends indicate a more balanced development with increasing convergence (e.g. rapidly decreasing east-west economic divide in the BSR)
Net migration rate, annual average in % Example: migration 2005-2010 Average annual net migration rate 2005-2010 according to various territorial typologies in the BSR, NUTS level 3 0.6 % Predominantly urban region Capital city region Coast 0.3 % 0.0 % Intermediate region Other region Second-tier metro region Smaller metro region Non-border Border Non-sparse Sparse Inland Predominantly rural region -0.3 % Typology on urban-rural regions Typology on metropolitan regions External border regions Sparsely populated regions Coastal regions Only ten metropolitan areas swallow 47 % of all migration surplus in the BSR
Index 2005=100 Example: jobs gained and lost in the BSR territorially specific spatial patterns Development of employment in the BSR according to the typology on metropolitan regions 2005-2009, index 2005=100, NUTS 3 109 108 107 106 Second-tier metro region Capital city region Smaller metro region 105 104 103 Other region 102 101 100 2005 2006 2007 2008 2009 The most vulnerable areas took the worst beating of the 2008 recession
BSR total employment (in million persons) Coefficient of variation. Example: jobs gained and lost in the BSR macroregional spatial patterns 49.0 48.0 47.0 Development of total BSR employment and the coefficient of variation of employment between NUTS 3 regions in the BSR 2005-2009 (Coefficient of variation = Standard deviation / Mean ) 1.350 Total employment in the BSR (in million persons, left scale) 1.330 1.310 When the nr of jobs in the BSR increased, that increase was beneficial to most regions When the nr of jobs declined (following the credit crunch), the decline hit mostly weaker regions, resulting in increased concentration 46.0 45.0 Coefficient of variation in NUTS 3 employment (right scale) 1.290 1.270 44.0 2005 2006 2007 2008 2009 1.250
2. Aggravated territorial disparities Territorial disparities between contiguous (adjacent) regions have in the past 15 years exploded The urban hierarchy is a decisive factor in dictating the magnitude these disparities Corresponding analysis within a more pronounced social context shows differing patterns
Example: On-theground disparities analysed
3. Specific types of territories In the BSR, specific types of territories, including e.g. rural, peripheral, or border regions: are generally lagging behind in most aspects of socioeconomic development; and harnessing the untapped potential of such territories implies considerable possibilities
Example: GDP per inhabitant in the BSR subdivided by various territorial typologies GDP per capita in PPS, index: EU27=100 ca. 2005 ca. 2009 Development ca. 2005-2009: points change to EU27 average The Baltic Sea Region (BSR) 75 81 +6 of w hich: - w estern BSR 124 122-2 - eastern BSR 50 60 +10 Typology on urban-rural regions Predominantly urban regions 98 109 +11 Intermediate regions 66 71 +5 of w hich: - close to a city 66 71 +5 - remote 71 74 +2 Predominantly rural regions 62 65 +3 of w hich - close to a city 53 57 +4 - remote 86 85-1 Typology on metropolitan regions Specific types of BSR territories are generally lagging behind Most development trends are not cohesive Capital city regions 101 112 +11 Second-tier metro regions 84 89 +5 Smaller metro regions 58 64 +5 Other regions 61 65 +4 Typology on regions in external border programmes Border regions 46 53 +8 Non-border regions 82 88 +6 Typology on sparsely populated regions Sparsely populated regions 90 91 +1 Not sparsely populated regions 74 80 +7 Typology on coastal regions Coastal regions 95 101 +6 Non-coastal regions 62 68 +6
4. BSR migration steered by territory A multivariate analysis of driving forces behind migration patterns in the BSR revealed that handicapped socio-economic structures resulting from permanent locational characteristics play a surprisingly strong role in steering migration flows; and that e.g. the status as the national capital or a secondary city, being a predominantly urban or an intermediate region, as well as lying by the coast, all have stronger effect on net migration than does e.g. GDP/capita
Regression standard coefficient (absolute value) Example, multivariate analysis, driving forces of BSR migration: four socioeconomic variables and territorial typologies Example, driving forces of BSR migration: all four available NUTS 3 variables with full BSR coverage, with territorial typologies 0.500 0.400 Territory matters! 0.300 0.200 0.100 0.000 Region in east BSR, [negative] Capital region Unemployment rate, [negative] Intermediate region (urbanrural typology) Real GDP change Coastal region For following analysed variables, no statistical effect on migration at all (when all others held constant): GDP/capita Employment change Sparse region Predominantly urban region (urban-rural typology) Close to a city (urban-rural typology) Border region Secondary city region Smaller metro region Above 6 variables are (statistically significantly) able to explain 52 % of the variation in net migration rates in the BSR
5. Social inclusion and QoL The eastern BSR displays huge internal variations in e.g. life expectancy and the gap to western BSR is substantial. The development trends are however cohesive In terms of subjective general health, the east-west divide is not clear-cut Economic welfare only partly explains existing patterns in health East-west differences in particularly absolute poverty are very large within the BSR
Example: self-assessed general health status 2010 Light colours: better health, dark colours: worse health Self-assessed health good measurement of effectiveness of health care system, life style, awareness, etc. No clear-cut territorial patterns or trends, but east-west gap is somewhat apparent
Self-assessed general health (Scale 1-5, where 1="very good"; 5="very bad") Life expectancy at birth in years, 2010 Example on bivariate analysis: relative poverty and health Life At-risk expectancy of poverty and rate at-risk and subjective of poverty health rate in in the BSR, 2010, NUTS 2 83.0 2.70 82.0 Schlesw ig-holstein Latvia (2008) Lithuania 81.0 2.50 Slaskie 80.0 79.0 2.30 Lüneburg Lubelskie 78.0 Berlin 77.0 2.10 76.0 75.0 1.90 74.0 Stockholm Zachodniopomorskie Bremen Eastern BSR Western BSR Bad health and poverty hand in hand in eastern BSR 73.0 1.70 0.0 8 5.0 13 10.0 15.0 18 20.0 23 25.0 28 30.0 35.0 At-risk-of-poverty rate, % of total population, 2010 At-risk-of-poverty rate, % of total population, 2010
II. BSR DIVIDES AND TERRITORIAL COHESION
1. Ten indicators for measuring overall Territorial Cohesion in the BSR The ten indicators aiming at measuring Territorial Cohesion in the BSR target general Territorial Cohesion objectives as well as specific BSR challenges can be applied on any variable in order to highlight general mega trends in territorial cohesion in the region ensure a multidimensional approach in applying these, which enables coherent interpretation of mixed, often confusing, signals
Ten indicators measuring Territorial Cohesion in the BSR (1.) The Gini Concentration Ratio (2.) The Atkinson index Distribution/inequality (3.) The 80/20 ratio (4.) Sigma-convergence (5.) Beta-convergence Convergence (6.) The east/west ratio (7.) The south/north ratio (8.) The urban/rural ratio Targeted BSR Territorial Cohesion Indicators (9.) The non-border/border ratio (10.) The coast/inland ratio
Change in GDP/capita in PPS 2005-10 %-units to the EU27 average Coefficient of variance Example: convergence measurements 50 Beta convergence in GDP/capita in the BSR NUTS 3 / SNUTS 2 level 2005-2010 1.60 Development of Sigma convergence or coefficient of variance for GDP, employment and population in the BSR 2005-2011, at NUTS level 3 GDP 40 1.50 1.40 30 1.30 Employment 20 1.20 10 1.10 Population 0 1.00 2004 2005 2006 2007 2008 2009 2010 2011 2012-10 -20-30 0 50 100 150 200 250 GDP/capita in PPS 2005, index EU27=100 Poorer regions in the BSR catch up on the richer ones but simultaneously economic output gets increasingly concentrated (right graph)
Gini Concentration Ratio Atkinson index (ε =0.8) 80/20 ratio Example: distribution measurements Development of the Gini Concentration Ratio and the Atkinson index for GDP, employment and population in the BSR 2005-2011, at NUTS level 3 Development of the 80/20 or Kuznets Ratio for GDP, employment and population in the BSR 2005-2011, at NUTS level 3 0.540 0.340 14.5 GDP Atkinson GDP Gini 0.330 14.0 GDP 0.520 0.320 13.5 0.500 Employment Gini Employment Atkinson 0.310 0.300 13.0 Employment 12.5 0.480 0.290 0.280 12.0 0.460 Population Gini Population Atkinson 0.270 0.260 11.5 11.0 Population 0.440 0.250 2004 2005 2006 2007 2008 2009 2010 2011 2012 10.5 2004 2005 2006 2007 2008 2009 2010 2011 2012 Overall trend: increasing segregation among regions Economic output more concentrated that jobs, which are more concentrated than people
2. Assessing the three principal territorial divides of the BSR Both the North-South gap as well as the Urban-Rural gap of the BSR is growing further still The East-West gap also exists, but it is changing form from having been a primarily economic gap sharpest along the former iron curtain, it has now changed into a far more multifaceted divide, where social differences today are possibly the most pronounced ones
Urban/rural ratio East/west ratio South/north ratio Example: measurements addressing the three principal BSR divides 22.0 21.0 20.0 Development of the South/north ratio for GDP, employment and population in the BSR 2005-2011, at NUTS level 3 Population Employment 19.0 18.0 GDP Development of the East/west ratio for GDP, employment and population in the BSR 2005-2011, at NUTS level 3 17.0 2.50 16.0 2.00 Population 15.0 2004 2005 2006 2007 2008 2009 2010 2011 2012 Employment 1.50 Development of the Urban/rural ratio for GDP, employment and population in the BSR 2005-2011, at NUTS level 3 1.00 GDP 2.00 1.90 GDP 0.50 1.80 1.70 0.00 2004 2005 2006 2007 2008 2009 2010 2011 2012 1.60 1.50 Employment The north-south and the urban-rural gaps are growing further 1.40 1.30 1.20 1.10 Population The east-west gap is partially closing 1.00 2004 2005 2006 2007 2008 2009 2010 2011 2012
Severe At-risk-of-poverty material deprivation rate, rate, percentage percentage of total of population total population Example on QoL trends: (relative) poverty and (absolute) deprivation Differences in in severe the at-risk-of-poverty material deprivation rate in in eastern and western BSR Percentage of total population 2005-2011, 2005-2010, NUTS 2 50.0 35.0 45.0 30.0 40.0 35.0 25.0 30.0 20.0 25.0 15.0 20.0 15.0 10.0 10.0 5.0 5.0 0.0 47.7 28.0 28.0 36.0 14.5 14.1 12.4 7.0 Highest region 30.7 M edian region 27.6 27.9 26.2 Lowest region Highest region 31.4 22.3 22.2 21.1 20.4 M edian region 20.1 27.1 27.5 27.4 19.1 26.3 Lowest region 11.8 12.4 12.4 11.0 10.9 9.8 9.1 9.1 9.0 5.2 8.1 3.5 4.4 2.9 3.1 3.1 3.8 8.5 5.6 5.9 4.9 5.0 2005 2006 2006 2007 200720082008 2009 2009 2010 2010 2011 2005 2006 2006 2007 200720082008 2009 2009 2010 2010 2011 Eastern BSR Western BSR
Key messages - Increasing spatial polarisation - Aggravated territorial disparities - Specific BSR territories on the tightrope, but with much untapped potential - For development, territory matters - Increasing concentrational tendencies - North-South and Urban-Rural gaps growing further still - East-West gap also exists, but shifting form from primarily economic to primarily social
Further information: Research team & VASAB CSPD/BSR Project partners Nordregio Lisbeth Greve Harbo, Ole Damsgaard, Linus Rispling, Gunnar Lindberg University of Gdańsk Jacek Zaucha Aalto University, YTK Tomas Hanell Jukka Hirvonen RRG Spatial Planning and Geoinformation Carsten Schürmann Stanislaw Leszczycki Institute of Geography and Spatial Organization Polish Academy of Sciences Piotr Rosik Rafał Wiśniewski Tomasz Komornicki BGI Consulting Ltd. Inga Bartkeviciute Jonas Jatkauskas Geomedia LLC Rivo Noorkõiv VASAB Committee on Spatial Planning and Development of the Baltic Sea Region