Month: June 2022

MAPPING CLUSTERS IN CENTRAL AND EASTERN EUROPEAN REGIONS BASED ON FDI, REMITTANCES AND EMPLOYMENT – A SPATIAL STATISTICS GROUPING ANALYSIS

Cristina LINCARU

Dr, FeRSA, Department of Labour Market, National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania

cristina.lincaru@yahoo.de

ORCID ID: 0000-0001-6596-1820

Speranța PÎRCIOG

Dr Scientific Director, National Scientific Research Institute for Labour and Social Protection, Bucharest, Romania

pirciog@incsmps.ro

ORCID ID: 0000-0003-0215-038X

Abstract

Central and Eastern European (CEE) and Visegrad countries transform and develop in different spatial patterns in a global economy. Host labour markets benefit directly from Foreign Direct Investment (FDI) inward flows through jobs creation or increased productivity. On the other side, the labour force rises its geographical mobility and benefits from jobs in FDI’s source countries, sending personal remittances. Global integration marks that the “receipts of remittances have become an important and stable source of funds that exceeds FDI” (indexmundi.com). Are the CEE /Visegrad countries similar concerning their spatiotemporal pattern of FDI inflows? These countries are identical in their development model, described by the coordinates of FDI, remittances and Employment? We applied for 35 European countries from 2013-to 2019 the Similarity check –Grouping Analysis ARC GIS-tool from the Spatially Constrained Multivariate Clustering (Spatial Statistics) family. The FDI inflow as input proves to be more inertial, according to the categories set by EuroVoc. Simultaneously, the FDI inward as output (employment growth or labour productivity growth) differentiate CEE countries next to labour/ human capital mobility as personnel remittances in more heterogeneous categories.

In conclusion, for CEE countries, capital mobility and labour & human capital mobility create different development patterns globally. Therefore, it is not enough to build policies to attract capital (FDI) and attract high human capital.

Keywords: CEE, inward FDI rates, personal remittances receipt as GDP rate, employment rate, Similarity check –Grouping Analysis, spatial statistics

JEL classification: C23, F21, F22, F24, J21, J24, O52

 pp. 67-104

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DIGITALIZATION OF ECONOMY AND LIVING STANDARDS OF POPULATION IN RUSSIAN REGIONS

Nadezda Vasilievna SEDOVA

Dr. Plekhanov Russian University of Economics, Russia

nadseva@mail.ru

Lidia Sergeevna ARKHIPOVA

Ph.D. Plekhanov Russian University of Economics, Russia

Arkhipova.LS@rea.ru

Darya Mikhailovna MELNIKOVA

Ph.D. Plekhanov Russian University of Economics, Russia

Melnikova.D@rea.ru

Irina Fedorovna ALESHINA

Ph.D. Plekhanov Russian University of Economics, Russia

Aleshina.IF@rea.ru

Abstract

The study of territorial inequality in the modern economic space corroborates the relevance of the strategic goals of enhancing the living standards of the population amid digitalization of the economy. Despite the regional disparities in the social and economic development of the Russian regions, favorable factors for the responsiveness to digitalization in various economic and social spheres formed. They include the high quality of human capital, a relatively sufficient level of Internet access among population, modern infrastructure in a significant number of the regions, increased organizational costs for the introduction and use of digital technologies, etc. Therefore, the purpose of the research is to assess the indicators of digitalization in the regions, their territorial disparities and model the indicators of living standards as well as the use of information and communication technologies by the population and in organizations. The research features a typology of regions according to the main indicators of digitalization with the identification of the top regions, where capital territorial entities of the Russian Federation and the northern regions with a high household income, an economy dominated either by processing and knowledge-intensive industries, or with a raw-material focus, stand out. It has been noted that over the past fifteen years, interregional differentiation by digitalization indicators has been decreasing, however, problems persist in the eastern remote and underdeveloped regions in the south of the country. The research is of practical value in terms of economic and mathematical modeling of digitalization and internetization process in relation to living standards of the population.

Keywords: digitalization, region (RF subject), indicators, human capital, internetization, modeling

JEL classification: R23, J610

 pp. 47-65

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DOES EUROPEAN UNION MEMBERSHIP RESULT IN QUALITY-OF-LIFE CONVERGENCE?

Joel I. DEICHMANN*¹

Professor of Global Studies

jdeichmann@bentley.edu

Dominique HAUGHTON¹

Professor of Mathematical Sciences

dhaughton@bentley.edu

Mingfei LI¹

Professor of Mathematical Sciences

mli@bentley.edu

Heyao WANG¹

Graduate Research Assistant

wang_heya@bentley.edu

*Corresponding Author

¹Members of the Data Analytic Research Team (DART)

Bentley University Waltham, MA 02452 USA

Abstract

This paper employs European Quality-of-life Survey (EQLS) responses from 2003, 2008, 2012, and 2016 to examine whether European Union (EU) enlargement helps meet the objectives of improved living standards and overall quality-of-life across the continent. The data set includes responses to forty questions across nine dimensions for all twenty-eight pre-Brexit EU member states, along with eight non-member states. Insights are captured through the systematic comparison of self-reported perceptions pooled at the country level before and after accession, as well as between member states and non-member states. Special attention is paid to the eleven post-communist countries that joined the EU in 2004, 2007, and 2013, which together represent the addition of one hundred million EU citizens. These include Estonia, Latvia, and Lithuania, Poland, Czech Republic, Slovakia, Hungary, Slovenia, Bulgaria, Romania, and Croatia. Based upon these findings, the paper concludes with speculation upon popular support for further enlargement in the wake of the 2007-08 Global Financial Crisis, the 2016-2020 Brexit process, and ongoing COVID-19 pandemic.

Keywords: European Union, Central and Eastern Europe, economic integration, European convergence

JEL classification: O10, O47, P20, P48, R11

 pp. 31-46

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