European countries’ typology by the intensity of transboundary cooperation and its impact on the economic complexity level

Author:

Roos Göran1,Voloshenko Ksenia Y.2,Drok Tatiana E.2,Zverev Yury M.2

Affiliation:

1. Australian Industrial Transformation Institute, Flinders University

2. Immanuel Kant Baltic Federal University

Abstract

Over recent years, it has become increasingly obvious that the countries, regions and individual systems are now developing within the framework of the emerging technological paradigm. The key elements for their development are knowledge and capabilities, being transformed into the products exported by a given country, these constitute the core of the economic complexity theory. In this article, the authors attempt to assess the long-term correlations between economic complexity and transboundary intensity drawing on the example of European countries. The authors developed a European Countries’ Typology according to their transboundary cooperation intensity. The paper establishes that the influence of the transboundary factor weakens as the economic complexity increases, and under certain conditions, it has a negative impact. It substantiates that the revealed relationships are due to the increasing role of global processes rather than transboundary ones as the economy becomes more complex and oriented towards the global market.

Publisher

Russian Geographical Society

Subject

Environmental Science (miscellaneous),Geography, Planning and Development

Reference41 articles.

1. A more united and stronger central Europe needs transnational cooperation (2018). Input paper of the Interreg CENTRAL EUROPE Programme. [online]. Available at: www.interreg-central.eu/Content.Node/discover/Input-Paper.pdf [Accessed 11 May 2019].

2. Alshamsi A., Pinheiro F.L. & Hidalgo C.A. (2018). Optimal diversification strategies in the networks of related products and of related research areas. Nature Communications, 9 (1). DOI: 10.1038/s41467-018-03740-9.

3. Aprausheva N.N. & Sorokin S.V. (2015). (Notes on gauss mixtures), VC RAN (in Russian.). DOI: 10.13140/RG.2.2.33609.34404.

4. Baltagi B.H. (2005). Econometric Analysis of Panel Data. John Wiley & Sons. Boschma R. (2017). Relatedness as driver of regional diversification: A research agenda. Regional Studies, 51 (3), 351–364. DOI: 10.1080/00343404.2016.1254767.

5. Brillet J.L. (2011). Structural Econometric Modelling: Methodology and Tools with Applications under EViews 2016. [online]. Available at: www.eviews.com/StructModel/structmodel.pdf [Accessed 14 Apr. 2019].

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Economic complexity and the dynamics of regional competitiveness a systematic review;Competitiveness Review: An International Business Journal;2022-01-27

2. DEVELOPING CROSS-BORDER COOPERATION IN HIGHER EDUCATION: RESEARCH OF DIRECTIONS;IJAEDU- International E-Journal of Advances in Education;2021-12-31

3. Economic Security within the Limits of Economic Complexity;REGIONOLOGY;2021-06-30

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3