IDEAS home Printed from https://ideas.repec.org/a/ags/stagec/119649.html
   My bibliography  Save this article

Conceptualising ‘macro-regions’: Viewpoints and tools beyond NUTS classification

Author

Listed:
  • Ladias, Christos
  • Hasanagas, Nikolaos
  • Papadopoulou, Eleni

Abstract

Definitions are imposed but properties not. The basic question addressed by this paper is how to ‘detect’ objective socio-economic spatial structures instead of ‘defining’ them arbitrarily. The NUTS classification model is rather arbitrary. Not only have the administrative units been structured through ‘accidental’ historical conditions but the reliability of the measurement of the population in an area is disputable as long as the mobility is strengthened and the ‘usual residence’ becomes more and more vague. Concerning the auxiliary criteria, they are also heterogeneous and are rather perceptions imposed by decision makers than physical entities. The quantitative network analysis (QNA) approach is suggested as a tool to detect macro-structures regarded as socio-economic and natural infrastructure of a ‘macro-region’. This is based on algebraic analysis of a number of variables such as flows of people migration, financial means, information, commodities, bio-diversity elements and parameters of the new relationship between urban and rural areas. In this paper, by using algorithms of QNA, such as Density of flows or Betweenness centrality of places, ‘denser” or more “central’ places can be differentiated from others, and thus can be used for a more substantial demarcation of ‘macro-regions’.

Suggested Citation

  • Ladias, Christos & Hasanagas, Nikolaos & Papadopoulou, Eleni, 2011. "Conceptualising ‘macro-regions’: Viewpoints and tools beyond NUTS classification," Studies in Agricultural Economics, Research Institute for Agricultural Economics, vol. 113(2), pages 1-7.
  • Handle: RePEc:ags:stagec:119649
    DOI: 10.22004/ag.econ.119649
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/119649/files/studies_113-2_web_ladias.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.119649?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Krott, Max & Hasanagas, Nicolas D., 2006. "Measuring bridges between sectors: Causative evaluation of cross-sectorality," Forest Policy and Economics, Elsevier, vol. 8(5), pages 555-563, July.
    2. David J. Hand & Heikki Mannila & Padhraic Smyth, 2001. "Principles of Data Mining," MIT Press Books, The MIT Press, edition 1, volume 1, number 026208290x, December.
    3. Leo Katz, 1953. "A new status index derived from sociometric analysis," Psychometrika, Springer;The Psychometric Society, vol. 18(1), pages 39-43, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ilirjana ZYBERI & Antoneta POLO, 2021. "Impact Of Service And E-Service Quality, Price And Image On The Trust And Loyalty Of The Electronic Banking Customers," Regional Science Inquiry, Hellenic Association of Regional Scientists, vol. 0(1), pages 59-68, June.
    2. Christos AMOIRADIS & Mariya STANKOVA & Efstathios VELISSARIOU & Christos Ap. LADIAS, 2021. "Sustainability Analysis Of Greece'S Promotion As A Tourism Destination," Regional Science Inquiry, Hellenic Association of Regional Scientists, vol. 0(2), pages 227-238, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Thomas J. Sargent & John Stachurski, 2022. "Economic Networks: Theory and Computation," Papers 2203.11972, arXiv.org, revised Jul 2022.
    2. Karimi, Fatemeh & Lotfi, Shahriar & Izadkhah, Habib, 2021. "Community-guided link prediction in multiplex networks," Journal of Informetrics, Elsevier, vol. 15(4).
    3. D’Errico, Marco & Battiston, Stefano & Peltonen, Tuomas & Scheicher, Martin, 2018. "How does risk flow in the credit default swap market?," Journal of Financial Stability, Elsevier, vol. 35(C), pages 53-74.
    4. Liu, Xiaodong & Patacchini, Eleonora & Zenou, Yves & Lee, Lung-Fei, 2011. "Criminal Networks: Who is the Key Player?," Research Papers in Economics 2011:7, Stockholm University, Department of Economics.
    5. Agnieszka Rusinowska & Rudolf Berghammer & Harrie de Swart & Michel Grabisch, 2011. "Social networks: Prestige, centrality, and influence (Invited paper)," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00633859, HAL.
    6. Gabrielle Demange, 2018. "Contagion in Financial Networks: A Threat Index," Management Science, INFORMS, vol. 64(2), pages 955-970, February.
    7. Fernandez del Pozo, J. A. & Bielza, C. & Gomez, M., 2005. "A list-based compact representation for large decision tables management," European Journal of Operational Research, Elsevier, vol. 160(3), pages 638-662, February.
    8. Lin, Dan & Wu, Jiajing & Xuan, Qi & Tse, Chi K., 2022. "Ethereum transaction tracking: Inferring evolution of transaction networks via link prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    9. Yao Hongxing & Lu Yunxia, 2017. "Analyzing the Potential Influence of Shanghai Stock Market Based on Link Prediction Method," Journal of Systems Science and Information, De Gruyter, vol. 5(5), pages 446-461, October.
    10. Le, Hong Hanh & Viviani, Jean-Laurent, 2018. "Predicting bank failure: An improvement by implementing a machine-learning approach to classical financial ratios," Research in International Business and Finance, Elsevier, vol. 44(C), pages 16-25.
    11. Zhepeng Li & Xiao Fang & Xue Bai & Olivia R. Liu Sheng, 2017. "Utility-Based Link Recommendation for Online Social Networks," Management Science, INFORMS, vol. 63(6), pages 1938-1952, June.
    12. Sheikhahmadi, Amir & Nematbakhsh, Mohammad Ali & Shokrollahi, Arman, 2015. "Improving detection of influential nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 833-845.
    13. Li, Hui & Sun, Jie, 2009. "Hybridizing principles of the Electre method with case-based reasoning for data mining: Electre-CBR-I and Electre-CBR-II," European Journal of Operational Research, Elsevier, vol. 197(1), pages 214-224, August.
    14. Dequiedt, Vianney & Zenou, Yves, 2017. "Local and consistent centrality measures in parameterized networks," Mathematical Social Sciences, Elsevier, vol. 88(C), pages 28-36.
    15. ,, 2014. "A ranking method based on handicaps," Theoretical Economics, Econometric Society, vol. 9(3), September.
    16. Xue, Puning & Zhou, Zhigang & Fang, Xiumu & Chen, Xin & Liu, Lin & Liu, Yaowen & Liu, Jing, 2017. "Fault detection and operation optimization in district heating substations based on data mining techniques," Applied Energy, Elsevier, vol. 205(C), pages 926-940.
    17. Min-feng Lee & Guey-shya Chen & Shao-pin Lin & Wei-jie Wang, 2022. "A Data Mining Study on House Price in Central Regions of Taiwan Using Education Categorical Data, Environmental Indicators, and House Features Data," Sustainability, MDPI, vol. 14(11), pages 1-15, May.
    18. Ernest Liu & Aleh Tsyvinski, 2021. "Dynamical Structure and Spectral Properties of Input-Output Networks," Working Papers 2021-13, Princeton University. Economics Department..
    19. Richard W. Carney & Travers Barclay Child, 2015. "Business Networks and Crisis Performance: Professional, Political, and Family Ties," Tinbergen Institute Discussion Papers 15-135/V, Tinbergen Institute, revised 20 Feb 2015.
    20. Wu, Tao & Xian, Xingping & Zhong, Linfeng & Xiong, Xi & Stanley, H. Eugene, 2018. "Power iteration ranking via hybrid diffusion for vital nodes identification," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 802-815.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:stagec:119649. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/akiiihu.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.