Transnational Observation Danube economies, ecosystems, cross … · 2019-09-12 · Transnational...

Inspire Policy Making with Territorial Evidence

Transnational Observation

Danube economies, ecosystems, cross-border services and territorial challenges

1ESPON // espon.eu

2ESPON // espon.eu

Transnational Observation // Danube economies, ecosystems, cross-border services and territorial challenges

Compared to the most EU regions, the Danube macro-region has a strong SME birth rate most notably in Slovakia, the German states of Bavaria and Baden-Württemberg, Romania’s capital region and Slovenia’s Coastal–Karst, followed by Prague and Bulgaria’s Provinces of Varna, Burgas and Blagoevgrad. The strongest entrepreneurial spirit is palpable in the Slovak regions, where every sixth enterprise active in 2014 was a newborn (Fig. 1). This trend, however, is accompanied by considerable enterprise deaths registered in the same year. At least one out of eight Slovak enterprises had ceased to exist in 2014. Bavaria and Baden-Württemberg, Hungary and the peripheral Bulgarian, Croatian and Czech regions exhibit similar dynamics. Most of the enterprise deaths have been registered in Romania (Fig. 2).

SME patterns, Knowledge Economy and Foreign Direct Investment and the in the Danube macro-region

Figure 1: Birth rate of SMEs in the Danube macro-region

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Birth rate, number of enterprise births divided bythe number of active enterprises, 2014

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Notes - Data for FI, NL relates to 2010 - Data for DE, DK, FR, MT relates to 2013 - Data for BE, PL relates to 2015 - Data for LV, MT relates to NUTS2 - Data for IE relates to NUTS0

Regional level: NUTS 3 / NUTS 2 / NUTS 0 (version 2013)Source: ESPON SME, 2017

Origin of data: Eurostat Business demography, Statistics Belgium Demografie Ondernemingen, Bundesamt für Statistik Unternehmensdemographie, Orbis Database,Gewerbeanzeigenstatistik, Statistics Estonia Business demography, NACE B-S, Financial Agency, Statistics Iceland, Chamber of Commerce, Statistics Norway,

Central Statistical Office of Poland, Statistics Sweden Structural Business Statistics Tillväxtanalys, Statistical Office of the Republic of Slovenia and own calculations (EIM),Office for National Statistics Business Demography SIC 2007 C G-N P-R

CC - UMS RIATE for administrative boundaries

© ESPON, 2017

No data

3ESPON // espon.eu


Figure 2: Death rate of SMEs in the Danube macro-region

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Regional level: NUTS 3 / NUTS 2 / NUTS 0 (version 2013 / 2010)Source: ESPON SME, 2017

Origin of data: Eurostat Business demography, Statistics Belgium Demografie Ondernemingen, Bundesamt für Statistik Unternehmensdemographie, Orbis Database,Gewerbeanzeigenstatistik, Statistics Estonia Business demography, NACE B-S, Financial Agency, Statistics Iceland, Chamber of Commerce, Statistics Norway,

Central Statistical Office of Poland, Statistics Sweden Structural Business Statistics Tillväxtanalys, Statistical Office of the Republic of Slovenia and own calculations (EIM),Office for National Statistics Business Demography SIC 2007 C G-N P-R

CC - UMS RIATE for administrative boundaries

Death rate, number of enterprise deaths divided bythe number of active enterprises, 2014

© ESPON, 2017

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Notes - Data for FI, NL relates to 2010 - Data for DE, DK, FR, M relates to 2013 - Data for BE, PL relates to 2015 - Data for LV, MT relates to NUTS2 - Data for IE relates to NUTS0

Framework conditions that stimulate entrepreneurship range from improved infrastructure, population net gains, accessibility to education, geographical location or foreign direct investment. At the same time, allocative inefficiencies, productivity asymmetries, negative externalities of the transport network as well as outflows of skilled labour adversely affect the entrepreneurial sector.

The Danube region is characterized by an above-average share of employment in micro-enterprises. Exceptions are Bavaria and Baden-Württemberg in Germany where large enterprises are prominent employers as well as the Bulgarian Provinces of Yambol, Sliven, Stara Zagora, Sofia, Plovdiv and Ruse, which exhibit an above-average share of employment in SME.

Bavaria and Baden-Württemberg in Germany as well as Vorarlberg, Tyrol and Salzburg have the highest share of SMEs in the macro-region. Three to five SME per 1,000 inhabitants are typical for Bulgaria, Austria (Carinthia, Styria, Upper and Lower Austria, Vienna and Burgenland), the Czech regions of Plzeň, Hradec Králové, Pardubice, Olomouc, South Moravian and Zlín, the Romanian’s capital Bucharest and the regions Timiș, Bihor, Cluj, Sibiu and Brașov.

In addition to the traditional high-tech sectors in Austria, SMEs acting in services and tourism are thriving. In Romania, the Czech Republic, Slovakia and parts of Hungary, the ICT sectors gain traction through small and medium-sized business.

The Timiș county in Western Romania has the highest density of enterprises and exporters in Romania and is also the largest agricultural region which is predominately foreign owned. Considering the impact that the 2008 financial and economic crisis had on industries such as ICT, automotive, wood processing, pharmaceuticals and textiles, entrepreneurial activity in Timiș is recovering, notably in the ICT sector.

4ESPON // espon.eu


Figure 3: Types of knowledge economy and share of people with higher education vs net migration

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Regional level: NUTS 2 (version 2013)Source: ESPON EMPLOYMENT, 2017

Origin of data: Eurostat, 2016UMS RIATE for administrative boundaries

© ESPON, 2017

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Bratislava is home to one out of every four SMEs in Slovakia, providing jobs for three quarters of the active labour force. The capital city attracts 65 per cent of total Foreign Direct Investment in Slovakia. Over the past eight years, the ICT sector has been on the rise while the low-carbon industry remains underdeveloped.

Split-Dalmatia county (Croatia) has been slow to adapt to emerging markets, suffering from a mismatch between the needs of labour markets and educational offers. The region, however, is a good example of the ability to repurpose regional capital to serve new demands amidst a growing tourism sector in Croatia, leaving behind the traditional agricultural industry.

The knowledge economy continues to dominate the western parts of the Danube macro-region in contrast to Romania, Bulgaria, Slovakia and Hungary, resulting in an uneven distribution of the skilled labour force (Fig. 3 and Fig. 4).

Creative industries and ICT have experienced growth in Styria, with new business domains including smart production, digitalisation and renewable energies following suit. Since the 2000s, Styria has undergone a shift from traditional industries to technology and knowledge-intensive sectors. Smart mobility, green-tech and healthcare are some of the main themes outlined in the regional specialisation strategy.

In Pfaffenhofen an der Ilm (DE), SMEs have an annual birth rate of 16-18 per cent (1,400 per year). Upper Bavaria employs nearly one fifth of its active workforce in the knowledge or creative economy. Employment in the low-carbon economy amounts to nearly 15 per cent of the active workforce, followed by the ICT sector with a share of nearly 12 per cent. Further growth in these sectors is impeded by limited availability of land for business, high living costs, insufficient broadband access and lengthy administrative processes.

The Nuremberg Metropolitain Region is a magnet for SMEs, enjoying high accessibility, a broad industrial base, a high-quality of life and strong R&D clusters. The downfalls for Foreign Direct Investment (FDI) in Nuremberg are the high corporate taxes (30 per cent), non-competitive digital infrastructure, language barriers and the aging society.

Shifting from a linear to a circular economy in the Danube macro-region requires new forms of consumption that connect business to business, business to customer and customer to customer. Material and technology providers are the bridge between the linear and circular economy. Technology Providers (TPs) encourage cyclical resource flows and more efficient use of materials through innovative technologies and value chains geared towards resource saving. More specifically, they produce value by recovering and restoring materials as well as recycling and remanufacturing durables through technological provisions that will ultimately be used for output by Material Providers (MP).

TPs also include the production of consumables from eco-friendly materials, such as natural fibres, bio-plastics or composite materials, or technologies for the generation of renewable raw materials or energy, as well as installations and machinery for the treatment of material streams. Rural regions are better placed to

5ESPON // espon.eu


Figure 4: Types of knowledge economy and share of people with higher education vs net migration

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Regional level: NUTS 2 (version 2013)Source: ESPON EMPLOYMENT, 2017

Origin of data: Eurostat, 2016UMS RIATE for administrative boundaries

© ESPON, 2017

Types of competitive knowledge economies

KE Cluster-Analysis (2012-2015)

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introduce effective policies and programmes aiming to boost the bio-economy which offers opportunities for regional economic growth.

The eastern and western regions (Karlovy Vary, Usti and Northern Moravia) of the Czech Republic have the highest concentration of people employed by TP providers, followed by Bavaria in Germany and Upper Austria (Fig. 5).

About 4 per cent of the total European economy is generated by Material and Technology Providers with an annual turnover of almost a trillion Euros. TP services play an increasing role in the Czech Republic, Slovakia, parts of Hungary, eastern Romania and Croatia. Their commonality is the large number of people employed in the repair of fabricated metal products, machinery and equipment as well as waste collection and recycling services.

The Danube macro-region, in particular the Czech Republic, Slovakia, Central Slovenia, northern Hungary, Bulgaria and Romania, attract considerable volumes of extra-European FDI (Fig. 6). In addition to job creation, foreign firms have a positive impact on the host region by enhancing the competitiveness and growth of local enterprise through productivity spill-over effects, i.e. the transfer of technical, operational and managerial knowledge from abroad. FDIs not only inject capital into the domestic economy allowing SMEs to scale up their knowledge base, they also create networks to foreign markets and greater opportunities for high-quality services and high-end firms to thrive.

6ESPON // espon.eu


Figure 5: Employment by Technology Providers

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Regional level: NUTS 2 (version 2013)Source: ESPON CIRCTER, 2018

Origin of data: Eurostat, accessed 2018, calculated by Prognos AGCC-UMS RIATE for administrative boundaries

Employment by Technology Providers (2015)

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Austria invests about 50 million EUR more in the European economy than it receives from European investors inwards. The outward direct investments of Germany to other European countries exceeds the total of intra-European inward investments by ca. 150 m EUR. On the other end of the spectrum, the Czech Republic, Croatia, Slovakia, Bulgaria, Hungary and Romania are net recipients of intra-European FDI. Notably Hungary and Romania benefit from direct investment, reaching a net value of ca. 100 m EUR.

Between 2003 and 2015, extra-European FDI inflows ranging between 1 bn and 5 bn EUR have been registered in the Czech Republic, Austria, Slovakia, Hungary, Romania, Bulgaria and Serbia. Interregional territorial clusters with high values of extra-European FDI can be observed in the Western parts of the Czech Republic (Ústí nad Labem, Karlovy Vary, Plzeň, Central Bohemia and Prague) as well as in Bulgaria (Varna, Burgas and Yambol). The Danube macro-region has developed a pattern of transnational and cross-border areas that share comparable levels of attractiveness to non-European investors. The transnational territorial cluster stretches from Lower Austria, South Moravia and Moravia-Silesia in the Czech Republic to the Slovak regions of Bratislava, Trnava, Nitra, Trenčín and Žilina as well as Central and Western Transdanubia in Hungary. The cross-border territorial clusters link Košice in Slovakia with Northern Hungary as well as North and Central Banat in Serbia with Timiș county in Romania. Both the transnational and cross-border territorial clusters have attracted up to 5 bn EUR from non-European investors between 2003 and 2015. The largest recipient of extra-European FDI in the Danube macro-region is Munich district with values exceeding 5 bn EUR.

7ESPON // espon.eu


Figure 6: Extra-European FDI inflows into the Danube macro-region

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Extra-European FDI inflows by sector across European regions 2003-2015

Regional level: NUTS 3 (2013)Source: The World in Europe, global FDI flows towards Europe, 2017

Origin of data: Copenhagen Economics based on BvD´s Zephyr and the Financial Times databases, 2016UMS RIATE for administrative boundaries

© ESPON, 2017

Value of extra-European FDI inflowsto European regions in 2003-2015(in million euro, 2015 value)

Absence of information on deal valueNo data

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Green Infrastructure (GI) is a strategically planned network of natural and semi-natural areas. GI consists of ecological networks, made up of areas of natural vegetation, other open space or areas of known ecological value, and links that connect these areas to one another.

The underlying principle of GI is that the same area of land can offer many environmental, social, cultural and economic benefits at the same time, provided its ecosystems are in a healthy condition. GI functions include food and water production, energy supply, climate regulation, air purification and tourism.

Valuable Danube ecosystems, however, are being degraded by land fragmentation, urban expansion and the building of transport and energy infrastructure. This affects habitats and species and reduces the

Danube’s green infrastructure and ecosystem services

8ESPON // espon.eu


Figure 7: Spatial distribution of potential green infrastructure network at landscape level

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Regional level: NUTS 2/3 (2013)Source: ESPON GRETA, 2019

Origin of data: CLC 2012, Copernicus HRL Impervious 2012, OSM 2017, Natura 2000 (EEA 2012), Emerald Network 2012, HNVF (EEA 2015), Ecosystem types map (ETC-SIA 2015)

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Spatial distribution of potential GI network at landscape level

© ESPON, 2019

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spatial and functional coherence of the landscape. Degraded ecosystems have lower species richness and are unable to offer the same services as healthy ecosystems.

A number of policy instruments aligning economic investments, territorial planning, legislation and governance within the Danube macro-region have been devised to protect GI and allow for a network effect. The Slovak Territorial System of Ecological Stability (TSES), for instance, seeks to protect biodiversity, maintain ecosystem services and promote stabilization of landscape and climate. At the local level, municipalities in Hungary have adopted green infrastructure as an intrinsic part of spatial planning and have rolled out green-network development programmes.

The eastern Alpine region (Austria, Slovenia) stretching to the western Balkan countries (coastal regions of Croatia, Bosnia and Herzegovina and Montenegro) display the highest potential for GI networks in the Danube macro-region, having at the same time the lowest share of protected core areas (Fig. 7). This requires priority actions for the conservation of unprotected links in those regions, accompanied by awareness raising as well as empirical and spatial data. Stakeholders who possess a better understanding of the positive externalities of ecosystem services (i.e. food, water and energy supply, pollination; carbon sequestration, detoxification, waste decomposition, water and air purification; flood / climate regulation; leisure and tourism) and consequently of the net gains of protection, are likely to make better informed decisions about protective measures and investments.

Cross-border public services (CPS) in the Danube region address market failures by compensating for shortages in domestic public services and reduce allocative inefficiencies caused by identical services on both sides of the border. Furthermore, Danube CPS mitigate negative externalities of borders and at the same time create positive externalities for people and businesses.

Since the 2000s, the CPS have grown in popularity among countries in the Danube macro-region, and joint operations now exist on the German-Czech, Austrian-German, Austrian-Hungarian and Slovenian borders. Other borders in the Danube region, such as Hungary-Romania and Bulgaria-Romania have very few or no CPS in place. Danube CPS range from environmental protection to transport services, medical emergency care and bilateral hospital cooperation (Fig. 8).

Public services in Danube border regions

9ESPON // espon.eu


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Figure 8: Cross border services: numbers and types

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10ESPON // espon.eu


The uneven distribution of CPS among the westerns and Eastern Danube regions can be explained by the different levels of experience in cross-border cooperation. Evidence shows that the number of CPS in Europe is slowly but steadily increasing with an average of 5 to 10 new CPS per year. Since 1990, several leaps in CPS establishments have been ascertained: 1998, 2002, and 2013 respectively. This increase coincides with the introduction of Interreg back in 1990. The ESPON research team behind the targeted analysis on cross-border public services has catalogued the common solutions practiced in different border areas to reduce obstacles, compounding these in categories including stakeholder involvement and needs assessment, infrastructure, legal frameworks as well as management and organisation. All identified solutions have the characteristics of Interreg cross-border projects, which leads to the conclusion that Interreg can serve as a leverage for durable operation of CPS.

An Interreg Danube project aimed at protecting the environment and floodplain management demonstrates the willingness of stakeholders from Hungary, Croatia, Slovenia and Serbia to work transnationally on the Mura-Drava-Danube Transboundary Biosphere Reserve.

The European Exchange School Alliance has been initiated to foster cooperation among educational facilities in Hungary, Slovakia, Romania and Ukraine.

Lower Austria and South Bohemia launched a pilot for cross-border health care treatment of Czech patients at the Gmünd hospital in Lower Austria to provide a closer option for services than the nearest Czech hospital (60 km away). The project was co-funded by Interreg to eliminate the high costs that Czech patients would normally incur for receiving treatment in Austria and since 2017 the number of Czech patients treated at Gmünd hospital reached 4,000. The success of this CPS has led to another agreement between Czech and Austria regarding rescue services, which was signed in 2016.

The success rate of Interreg projects supporting a CPS development can be increased through seed money prior to the application stage that can support the analysis of financial sustainability of a CPS beyond an Interreg project.

Evidence shows that projects concentrating on a certain service and/or border segment can have a negative impact on other border segments and/or sectors. Complementary calls within the same programme or across programmes covering different priorities and border segments can result in complementary projects that increase the CPS sectoral and geographical coverage.

While Interreg projects are the main lever for prospective CPS, different stages of the CPS evolution might need different complementary support mechanisms. Interreg cross-border cooperation has thus proven to work well in the case of stakeholder reconciliation, feasibility studies, pilot actions and market roll-out, meanwhile the prototyping and testing of technological solutions can benefit from engineering capacity in the context of research and innovation grants.

Inner peripheries (IP) are areas associated with low economic potential in relation to neighbouring regions, poor accessibility (transport) and weak connectivity to decision-making and investment opportunities, which suggests that peripherality is not only determined by geography but also by non-spatial factors. In the Danube region, large continuous areas of inner peripheries can be found in Slovakia, Bulgaria, Hungary and Romania as a result of the socio-economic situation, whereas in Germany and Austria smaller IPs exist and are mostly related to inadequate access to centres or services (Fig. 9).

Inner Peripheries

11ESPON // espon.eu


Figure 9: Inner peripheries in the Danube macro-region

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Regional level: Grid level (2.5x2.5 km)Source: ESPON PROFECY, 2017

Origin of data: TCP International Accessibility Model, 2017 UMS RIATE for administrative boundaries

© ESPON, 2017

Delineations of inner peripheries according to the main socio-economics drivers

The large-scale inner peripheralization in the Eastern parts of the Danube macro-region can be partly attributed to the normative centralised spatial planning culture in these areas. Germany and Austria possess a well-functioning multiscale and self-government systems that are better positioned to tackle IPs.

Nevertheless, IPs suffering from poor socio-economic conditions and/or poor connectivity and access to services, can be found in all parts of the macro-region. Wolfsberg in Austria, for instance, is home to nine IPs. The region’s main characteristics include high levels of unemployment and a brain-drain compounded by insufficient digital technologies and transport infrastructure. The tourism sector could be yielding greater prosperity, however, the lack of cooperation among adjacent localities is further exacerbating the problem.

Development of the Tamasi area in Hungary is adversely affected by a poor road network, partly caused by natural barriers such as hills, valleys and forest. Low levels of connectivity have ramifications for both the labour market and the provision of services. Tamasi is a sparsely populated area with severe demographic challenges. The local authorities have recognised, however, that transport investments alone are unlikely to recoup the lost human capital and create a multiplier effect pulling additional investments to the region. In an effort to induce entrepreneurship, local decision makers have embarked on a shift from the traditional agriculture sector to services.

ESPON 2020

ESPON EGTC4 rue Erasme, L-1468 LuxembourgGrand Duchy of LuxembourgPhone: +352 20 600 280Email: [email protected]

The ESPON EGTC is the Single Beneficiary of the ESPON 2020 Cooperation Programme. The Single Operation within the programme is implemented by the ESPON EGTC and co-financed by the European Regional Development Fund, the EU Member States and the Partner States, Iceland, Liechtenstein, Norway and Switzerland.

Disclaimer: The content of this publication does not necessarily reflect the opinion of the ESPON 2020 Monitoring Committee.ISBN: 978-99959-55-75-5 © ESPON 2019

Reproduction is authorised provided that the source is acknowledged and a copy is sent to the ESPON EGTC

Editorial team: Vassilen Iotzov, Kelsey Todter, ESPON EGTC; INOVA+

Published in March 2019

Inspire Policy Making with Territorial Evidence

Transnational Observation Danube economies, ecosystems, cross … · 2019-09-12 · Transnational...

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