Original scientific paper
https://doi.org/10.5513/JCEA01/25.2.4176
Assessment of regional development level in Romania through Principal component analysis
Ancuţa Simona ROTARU
; Department of Fundamental Science, Faculty of Animal Science and Biotechnology, University of Animal Sciences and Veterinary Medicine Cluj-Napoca, 400372 Cluj-Napoca, Romania
Cristina HEGEDUŞ
; Department of Fundamental Science, Faculty of Animal Science and Biotechnology, University of Animal Sciences and Veterinary Medicine Cluj-Napoca, 400372 Cluj-Napoca, Romania
Ioana Delia POP
; Department of Land Measurements and Exact Sciences, Faculty of Forestry and Cadastre, University of Animal Sciences and Veterinary Medicine Cluj-Napoca, 400372 Cluj-Napoca, Romania
Sorin VÂTCĂ
; Department of Plant Physiology, Faculty of Agriculture, University of Animal Sciences and Veterinary Medicine ClujNapoca, 400372 Cluj-Napoca, Romania
Anamaria VÂTCĂ
; Department of Fundamental Science, Faculty of Animal Science and Biotechnology, University of Animal Sciences and Veterinary Medicine Cluj-Napoca, 400372 Cluj-Napoca, Romania
*
Luisa ANDRONIE
; Department of Land Measurements and Exact Sciences, Faculty of Forestry and Cadastre, University of Animal Sciences and Veterinary Medicine Cluj-Napoca, 400372 Cluj-Napoca, Romania
* Corresponding author.
Abstract
This paper primarily aims to address aspects related to regional development in Romania, which has become a challenge both at the national and global level. The way regional development is approached is different, depending on the particularities of each country, as well as the governing ideologies in each state. However, the goal is common, one aims at shaping a competitive and strong economy, a high standard of living, access to education and medical assistance. The purpose of the paper is to compare socio-economic indicators from two time periods, to highlight similarities and differences and to observe their evolution within a 10-year timespan. The method used is Principal Component Analysis (PCA) to identify groups of statistical indicators (variables) that explain the level of development within a sample, in our case the development regions of Romania. In the context of regional development, PCA can be applied to extract relevant information about economic, social or demographic variability in different regions of the country. Several objectives of regional development analyzed through the lens of this method were pursued: identification of regional disparities, optimization of resource allocation, evaluation of the determining factors of economic development, monitoring of the impact of regional policies. Following the PCA analysis, it was observed that regional development cannot be evaluated by means of variables belonging to a single sector. This method allowed the identification of the variables that have the greatest weight describing economic, social, educational and infrastructure aspects. PCA was applied for two time periods and similar situations were obtained, the first main component called by the authors the economic statistics includes for both periods the indicators: Gross average nominal salary gain, GDP by development regions, Employees from research and development activity at the end of the year, Beds in health facilities (state and private). The second component was called social statistics and includes the indicator Employment rate in working age (15-64 years), and the third component called agricultural statistics includes the indicator Population served by the public water supply system. As a conclusion, we consider that the situations are not overlapping because there are indicators that have undergone changes during the 10 years, which is expected and normal in regional development. For example, the number of graduates decreased due to the continuously decreasing birth rate, the vacancy rate decreased in 2018-2019 compared to 2008-2009 because Romania went through the financial economic crisis.
Keywords
regional development; principal components; correlation matrix; PCA
Hrčak ID:
318563
URI
Publication date:
28.6.2024.
Visits: 322 *