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Marek Cierpial-Wolan
 

Marek Cierpial-Wolan

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    Marek Cierpial-Wolan Marek Cierpial-Wolan Presentation Transcript

    • Statistical Office in RzeszowCOHERENT RESEARCH SYSTEMFOR TRANSBORDER AREAS - CBC INDEX Marek Cierpiał-Wolan, PhD
    • Why is transborder statistics so important for in-transition and post-transitioncountries? It should deliver tools in order to measure phenomena tricky to estimate. For countries with ongoing process of liberalisation of crossing the border (e.g. introduction of Shoengen zone). Many information gaps pertaining socio-economic phenomena. For countries where there is tightening of the rules of crossing the border. Higher dynamics of socio-economic processes in transborder regions and higher intensity of non-registered socio-economic phenomena. 2
    •  MONITORING of socio-economic phenomena in transborder areas on the basis of administrative registers and statistical databases. SAMPLE SURVEYS at the border and in the neighbourhood:  Questionnaire survey at the border  Survey of travelling foreigners in tourist accommodation establishments.  Household survey – e.g. modules concerning international tourism, unregistered work, volume of unregistered purchase).  Survey of unregistered economy (e.g. market points, retail sales points), with the use of experience of Gray Economy Research Centre. 3
    • Entities of the national economy per 1000 population in border area byThe monitoring has been carried out on the website voivodships and gminas in 2010 As of 31 IIIsince March 2008 at the address http://www.stat.gov.pl/rzesz/Statistical information and elaborations:  Area and population in border areas by the European Union’s external border on the territory of Poland;  Vital statistic and migration of population in border areas by the European Union’s external border on the territory of Poland;  Entities of the national economy located in border areas by the European Union’s external border on the territory of Poland;  Labour market;  Tourism;  Health care;  Environmental protection. 4
    • Dynamics of newly registered entities of the national economy in Podkarpackie Voivodship (I-VI 2005=100)250 POLAND200 PODKARPACKIE VOIVODSHIP Powiats (LAU 1): Bieszczadzki150 Jarosławski100 Lubaczowski 50 Przemyski 0 Przemyśl city I-VI 2005 I-VI 2006 I-VI 2007 I-VI 2008 I-VI 2009 I-VI 2010 I-VI 2011 5
    • Dynamics of average employment (DG-1) (I-VII 2007=100) 112 110 108 106 104 102 100 98 96 94 I-VII 2007 I-VII 2008 I-VII 2009 I-VII 2010 I-VII 2011 Podkarpackie Voivodship border powiatsData concern economic entities employing more than 9 persons. Podkarpackie voivodship – 1571, border powiats - 196 6
    • 295,1 RUSSIA 151,0 183,3 498,5 Obwód LITHUANIA kaliningradzki Gronowo Grzechotki Skandawa Braniewo Bezledy Gołdap Warmińsko- RudawkaPurpose of the survey – obtaining -mazurskie Obwód 2051,6 Kuźnica grodzieński 227,7information about the expenses of Podlaskie Bobrowniki BELARUS 1101,6 108,2foreigners in Poland and Poles Siemianówka Czeremchaabroad (scale and structure), purpose Białowieża Obwód Połowce Mazowieckie Kukuryki brzeskiof visit, distance from the place of 2254,0 Terespol 361,1 POLAND Sławatyczeresidence and place of purchase 1640,0 Dorohusk Obwódfrom the border and frequency of Lubelskie wołyński 528,7 Zosincrossing the border. The survey is 653,1 Hrubieszów 656,7 Hrebenneconducted on 15 border crossings. 1699,0 613,5 Podkarpackie Werchrata 1660,7 Korczowa UKRAINE 396,9 Przemyśl Obwód 2597,8 Medyka lwowski 968,6 511,6 Krościenko 995,1 Foreigners Poles (thous. people) Passenger border traffic at crossings at the EU’s external border in 2010 7
    • Countries: Countries: 38.0 1.3 Russia Russia 10.8 0.1 173.4 23.9 Belarus Belarus 9.3 2.1 277.8 18.5 Ukraine Ukraine 41.2 4.2 mln € % 0 50 100 150 200 250 300 40 30 20 10 0 Expenses: Foreigners Poles Foreigners expenses/export relation Poles expenses/import relation 8
    • DISTANCE FROM THE BORDER TOTHE PLACE OF RESIDENCE OF POLESAND FOREIGNERS CROSSING THEEUROPEAN UNION’S BORDER ON THETERRITORY OF POLAND The highest number of foreigners and Poles covered by the survey was residing at the distance of up to 50 km from the border – around 74% and above 96% respectively, with almost 61% foreigners and 50% Poles in the zone of up to 30 km. 9
    • DISTANCE FROM THE BORDER TOTHE PLACE OF PURCHASE OFPOLES AND FOREIGNERS CROSSINGTHE EUROPEAN UNION’S BORDERON THE TERRITORY OF POLAND The highest number of foreigners and Poles was making purchase at the distance of up to 50 km from the border – around 71% and 96% respectively. With almost 55% foreigners and about 94% Poles making purchase in the zone of up to 30 km. 10
    •  Local  delivering information for entrepreneurs in order to take effective decisions concerning setting up firms or branches in transborder areas (e.g. Korczowa Dolina – modern distribution-trading complex located 2.5 km from the Ukrainian border, within the limits of the Polish- Ukrainian visa-free traffic zone, important trading hub in the region),  delivering information for local authorities in order to facilitate development of entrepreneurship and improvement of infrastructure (e.g. local tax reliefs, designation of additional lands for economic activity); Regional  delivering information to self-government and government institutions in order to lead politics increasing the competitiveness of a region (awareness of large scale economic activity in transborder areas makes this domain an important element of regional development strategies); National  delivering information which influence Balance of Payments consistency; International  delivering information which enable taking common or compatible decisions on both sides of the border (e.g. new border crossings, legislation on Local Border Traffic, infrastructural investments). 11
    •  Taxonomic measure of development – towards transborder index Analytic Hierarchy Process (AHP) 12
    • Indicators NUTS 2 (LAU 1):1. Population per 1 sq km2. Population at age 15-64 in % of total population3. Net migration per 1000 population4. Infant deaths per 1000 live births5. Natural increase per 1000 population6. Students per 1000 population7. Doctors per 10 thousand population8. Average monthly gross wages and salaries9. Entities of national economy per 10 thousand population10. Gross domestic expenditures on R&D per 1000 population11. Number of beds per 1000 population12. Number of foreign tourists per 1000 population13. Tourist traffic intensity index by Charvat14. Percentage of employed persons in market services15. Employed persons per 1000 population16. Dwellings completed per 1000 population17. Unemployment rate18. Gross Domestic Product per capita19. Area of national and landscape parks in % of grand total area of unit20. Emission of particulate pollutants from plants generating substantial air pollution per 1 sq km21. Emission of gaseous pollutants from plants generating substantial air pollution per 1sq km22. Forest cover in % 13
    • LU BELSKIE VOLYN OBLAST PO L AN D Ś LĄSKI E MAŁ OPOLSKI E PODKARPACKIE LVIV OBLAST VÝCHODNÉ S LOVE NSKO UK R A I N ES L OV A K I A S TREDNÉ SLOVENSK O IVANO-FRANKIVSK OBLAST ZA KARPATTIA OB LAST REGION TMRi MAŁOPOLSKIE VOIVODSHIP 0,629 ŚLĄSKIE VOIVODSHIP 0,492 STREDNÉ SLOVENSKO 0,439 VÝCHODNÉ SLOVENSKO 0,408 PODKARPACKIE VOIVODSHIP 0,392 LUBELSKIE VOIVODSHIP 0,335 LVIV OBLAST 0,329 ZAKARPATTIA OBLAST 0,236 IVANO-FRANKIVSK OBLAST 0,222 VOLYN OBLAST 0,209 14
    • Biała Podlaska Lublin Chełm POLAND Lp. REGION TMRi Częstochowa 1. Liptovský Mikuláš (SK) 0,548 Zamość Tarnobrzeg 2. Poprad (SK) 0,506 3. powiat tatrzański (PL) 0,501 Tychy 4. Kraków (PL) 0,373 Kraków 5. Krupina (SK) 0,330 Tarnów Rzeszów 6. Jaremcze (UA) 0,329 Przemyśl 7. powiat leski (PL) 0,326 Krosno Nowy Sącz 8. powiat cieszyński (PL) 0,325 9. Ružomberok (SK) 0,312 Svidnik Zilina Bardejov 10. Tvrdošin (SK) 0,310 Poprad .... ..................... ............SLOVAKIA Presov Humenne 232. Radziechów (UA) 0,044 Banska Bystrica Brezno 233. Lokachi (UA) 0,042 Roznava Kosice- -okolie 234. Busk (UA) 0,040 Banska Stravnica Trebisov 235. Horodenka (UA) 0,038 236. Horokhiv (UA) 0,037 237. Turka (UA) 0,033 0,548 - 0,448 238. Turiisk (UA) 0,032 0,447 - 0,348 239. Żydaczów (UA) 0,031 0,347 - 0,248 240. Przemyślany (UA) 0,008 0,247 - 0,148 241. Rohatyn (UA) -0,013 0,147 - 0,070 15
    • AHP allows one to assess the validity of the factors affecting the development of localunits (strengths and weaknesses as well as opportunities and threats), to determine theirsynthetic assessments of internal and external conditions, and on this basis, to identify thetypes of developmental units.Types of strategies1. Aggressive strategy (maxi-maxi) is created for areas where strengths and opportunities prevail in their environment. This is a strategy of strong expansion and diversified development.2. Conservative strategy (maxi-mini) is based on the large internal potential but must also attempt to overcome the threats from the outside.3. Competitive strategy (mini-maxi) is created for areas where strengths overweigh weaknesses, and the layout of external conditions is favorable.4. Defensive strategy (mini-mini) is created for areas where there are fewer developmental opportunities than in areas belonging to other strategies. These areas exist in less favourable surroundings and their potential for growth is weaker. This strategy is mainly to provide them such a position that is currently in the country and minimize risks and weaknesses occurring within the area.5. Mixed strategy for other areas that do not have clear strengths and weaknesses mix strategy is created. 16
    • 1.5 Competitive strategy Aggressive strategy Opportunities małopolskie 1 małopolskie stredne slovensko stredne slovensko 0.5 vychodne slovensko iwano-frankowski wołyńskiWeaknesses vychodne slovensko Strengths śląskie podkarpackie lwowski 0 -0.1 -0.08 -0.06 -0.04 -0.02 0 0.02 0.04 0.06 0.08 0.1 wołyński lwowski iwano-frankowski zakarpacki lubelskie Mixed strategy -0.5 podkarpackie śląskie zakarpacki -1 lubelskie Threats Defensive strategy Traditional strategy -1.5 17
    • 1 Competitive strategy Aggressive Opportunities strategy brzozowski 0.8 lubelski Użgorod Lutsk brzozowski Volodymyr- rzeszowski Volynskyi 0.6 Krupina Turčianske Lutsk bielski lubelski Użgorod rzeszowski Teplice Stryj Liptovský Mikuláš Turčianske 0.4 Teplice sanocki Jaremcze Przemyśl Kovel Medzilaborce 0.2Weaknesses Strengths Rohatyn Horokhiv sanocki 0 Medzilaborce -0.3 -0.2 -0.1 0 0.1 0.2 0.3 Ivanych Mixed strategy parczewski Liuboml Borysław -0.2 Żydaczów kolbuszowski hrubieszowski Morszyn rycki Lokachi Czop kolbuszowski Przemyślany Turka -0.4 Volodymyr- Żory Morszyn Volynskyi Busk hrubieszowski Jastrzębie-Zdrój Košice III -0.6 Borysław Košice III Turka Jastrzębie-Zdrój -0.8 Przemyślany Żory Defensive strategy -1 Traditional strategy Threats 18 -1.2
    • Biała Podlaska LUBELSKIE Lub lin OLYN OBLAS T V Chełm P O L AN D ŚLĄSKI ęstochowa POLA ND Cz E Zamość Tarnobrzeg MAŁ OPOLSKIE PODK ARPACKIE Biała Podl as ka Tychy LV IV O BLA ST Kraków Tarnów Rzeszów U K RAI NE VÝCHODNÉ SLOVENSKO Przemyśl Krosno S L O VA K IA Nowy Sącz STREDNÉ SLOVENSKO Lublin Ch ełm IVANO-FRANKIVSK Zilina Svidnik Bardejov OBLAST POLANDLUBE LSKIE VOLY N OBLA ST ZAKARPATTIA Częstochowa Poprad OBLAST P O L AN D Zamość Strategy: Ś LĄSKIESLOVAKIA Presov Hume nne Tarno brzeg mixed Banska Bystrica Brezno aggressive Roznava Kosi ce- -okolie Tychy PODKA RPACK IE competitive Trebisov MAŁ OPOLSKIE Kraków Banska St ravnica Tarnó w Rzeszów defensive LVIV OBLAST Strategy: mixed traditional Przemyśl Krosno Nowy Sącz U K R AI N E aggressive VÝCHOD NÉ SLOVENSKO competitive STREDNÉ SL OVENSKO Sv idnik Bardejov Zilina S L O VA K IA IVANO-FRANKIVSK defensive Poprad OBLAST Presov Humenne ZAKARPATTIA traditional SLOVAKIA OBLAST Bans ka Bystrica B rezno Roznava Kosice- -okolie B anska S travnica Trebisov 19
    • Directions for creating a coherent research system:  determination of the specificity and creation of a typology of border areas:  specification of the most important endogenous and exogenous factors affecting the economy and regional development (entrepreneurship, labour market, exchange rates, price levels, environmental protection, living conditions, migration, tourism, etc.),  clustering of border crossings and border areas in terms of similarity. 20
    •  inventory of information resources of official statistics; use of extra-statistical sources of information (e.g.mobile telephone operators, travel agencies, regional offices – permits to work issued for foreigners, foreign administrative sources); combining information from the registers and sample surveys; preparing methodological reports (e.g. for CBC Index – choosing of spatial units, selecting of variables and methods) ; cooperation between countries in:  conducting joint research;  creating a uniform information infrastructure (knowledge base on transborder areas);  undertaking initiatives, preparation and implementation of projects with the use of the EU’s funds. 21
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