Assessment of demographic profile of European Union countries

Ginevičius, Romualdas; Okunevičiūtė Neverauskienė, Laima; Trishch, Roman; Andriušaitienė, Daiva; Stasytytė, Viktorija Article Assessment of demographic profile of European Union countries Amfiteatru Economic Provided in Cooperation with: The Bucharest University of Economic Studies Suggested Citation: Ginevičius, Romualdas; Okunevičiūtė Neverauskienė, Laima; Trishch, Roman; Andriušaitienė, Daiva; Stasytytė, Viktorija (2025) : Assessment of demographic profile of European Union countries, Amfiteatru Economic, ISSN 2247-9104, The Bucharest University of Economic Studies, Bucharest, Vol. 27, Iss. 70, pp. 1109-1126, https://doi.org/10.24818/EA/2025/70/1109 This Version is available at: https://hdl.handle.net/10419/328038 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Economic Interferences AE Vol. 27 • No. 70 • August 2025 1109 ASSESSMENT OF DEMOGRAPHIC PROFILE OF EUROPEAN UNION COUNTRIES Romualdas Ginevičius1, Laima Okunevičiūtė Neverauskienė2 * , Roman Trishch3, Daiva Andriušaitienė4 and Viktorija Stasytytė5 1)4)5) Vilnius Gediminas Technical University, Lithuania 2) Lithuanian Centre for Social Sciences, Vilnius Gediminas Technical University, Lithuania. 3) Mykolas Romeris University, Vilnius, Lithuania Please cite this article as: Ginevičius, R., Okunevičiūtė Neverauskienė, L., Trishch R., Andriušaitienė, D. and Stasytytė, V., 2025. Assessment of Demographic Profile of European Union Countries. Amfiteatru Economic, 27(70), pp. 1109-1126. DOI: https://doi.org/10.24818/EA/2025/70/1109 Article History Received: 11 March 2025 Revised: 29 April 2025 Accepted: 28 June 2025 Abstract The country's demographic situation reflects the role and potential of one of the most important factors of economic development, work, and therefore the quantitative assessment of the country's demographic profile is very important. In the recent period, the dominant indepth but fragmentary studies of demographic issues do not allow to assess the situation in a complex way, integrating multidimensional and different demographic factors of different relevance, basic and dynamic. The purpose of this paper is to present a method of demographic profile assessment for complex analysis, based on a multicriteria method. This is usually done linearly, i.e., the relevance of the indicator does not depend on its value. In real life, this is not the case, so a nonlinear evaluation based on Harrington curves has been applied to the assessment of the demographic profile. The graphical-analytical method of trapezoids is applied to combine block values. In this case, the generalised value is the area under the curve, which is obtained by linearly connecting the dimensionless values of the indicators. The country's demographic profile index was obtained by combining the values of the basic and dynamic blocks in a respective way. In order to link the country's demographic profile index with GDP per capita, a correlation-regression analysis was performed, the results of which confirmed that the demographic status largely depends on the achieved level of economic development. Keywords: demographic profile of the country, nonlinear multicriteria assessment, economic development, macroeconomic policy. JEL Classification: J11; J21; C44; E60. * Corresponding author, Laima Okunevičiūtė Neverauskienė – e-mail: [email protected] This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2025 The Author(s). AE Assessment of Demographic Profile of European Union Countries 1110 Amfiteatru Economic Introduction A country can be treated as a macrolevel system, since by its nature it meets all three characteristics of socioeconomic systems (SES) – wholeness, interaction, and structuring (Bertalanffy, 1973; Ginevičius, 2009). They consist of two parts, social and technical. The first is a complex of interacting people, such as family, company personnel, parties, religious communities, etc. The second is material, technical, informational, financial, etc. resources integrated into the social system. The active part of the SES is social. This means that the results of the entire socioeconomic system depend exclusively on the quality of its functioning. The question arises, what does this quality depend on? In order to answer this question, it is necessary to analyze the structure of the social component of the system in more depth. It can be divided into two parts – quantitative and qualitative. The quantitative part is the size of the population, its structure, population density, etc. The qualitative part reflects the quantitative changes in the population of countries – life expectancy, birth rate, mortality rate, education, employment, etc. Both of these parts form the demographic profile (DP) of the country. Its essence can be formulated in the following way – it is a quantitative and qualitative characteristic of the country's population. The definition of DP shows that it is a complex, multifaceted phenomenon, the holistic understanding of which serves as a guide for attempts to find methodological instruments that help to carry out not only the momentary fragmentary monitoring of basic quantitative indicators, but also to assess the synergy effect, which is largely manifested through changes in qualitative demographic parameters. The importance of such an assessment is inspired by the challenge of qualitative economic development - to increase the resilience of the labor market: a labor force structure that is favorable to socio-economic development (in terms of age, gender, qualifications, etc.), ensuring the compatibility and balance of labor supply and demand, as well as the functionality of the labor market and its ability to recover from economic, technological or social shocks. Assessing the importance of this phenomenon for the socio-economic development of the country, it is necessary to strive for a constant improvement of its condition. This is a strategic task for the development of the country. Changes in the current situation can only be evaluated having a possibility to quantitatively assess its condition at a desired point in time (Ginevičius, 2009). Only in this case will it be possible to determine whether the efforts made to improve the situation were meaningful. Thus, a quantitative assessment of the state of a country's demographic profile allows to manage this process in a targeted manner. An analogy is the assessment of a country's economic development by gross domestic product (GDP) per capita. There are two possible ways to assess the state of the DP. In the first case, the state of one important aspect is quantitatively assessed. This type of research is prevalent today. In the second case, the aim is to combine as many indicators that reflect the demographic state of the country, as possible, into one generalizing ratio. This method gives a more accurate result, since the assessment based on one, albeit important, aspect does not convey the state of the DP as a whole. Without knowing this, it is impossible to compare countries with each other. Thus, a task arises that is relevant both in theoretical and practical terms – to comprehensively quantitatively assess the state of the country's demographic profile at the time in question. Its solution is complicated by the fact that the indicators reflecting this phenomenon are of various nature, i.e. they are multidimensional, they change in different directions (an increase Economic Interferences AE Vol. 27 • No. 70 • August 2025 1111 in the value of one indicator improves the situation, another worsens it) and are of different relevance in relation to the DP. Multi-criteria methods are suitable for the quantitative assessment of the state of such a contradictory situation. The aim of the article is to propose a methodology for the quantitative assessment of the state of a country's demographic profile and to verify its suitability based on the situation in European Union (EU) countries. The paper consists of an introduction, a literature review, methodological and empirical parts, and conclusions. The introduction reveals the role of the DP in the country's economic development, the importance of quantitative assessment of its state, and the issues to be addressed in this regard. The literature review analyzes the literature sources on the issues of quantitative assessment of the DP condition. The methodological part presents the methodology for quantitative assessment of this state. In the empirical part, based on the proposed methodology, the level of the demographic profile of EU countries is determined. The conclusions summarize the research results, provide limitations and guidelines for further research topics. The article is based on some results of the “Employment challenges and resilience in the labor market: social and individual resources and directions for their strengthening” project (under Agreement No. S-MIP-24-27 with the Research Council of Lithuania). 1. Literature Review The demographic profile of a country belongs to complex phenomena. In reality, it manifests itself in many different aspects. Due to its importance for the socio-economic development of a country, the science of demography has been formed. The following essential areas of the problems studied can be distinguished: classical, social and economic demography (Lutz, 2021). The first area examines the quantitative characteristics of the population and the relationships between demographic variables, the second area examines the peculiarities of social development and human behavior, and the third – the activation of the population in economic activity. Due to the growing complexity of commercial and economic activity and increasing competition, economic demography is becoming particularly important. It seeks to answer questions about the extent to which the demographic development of society affects the country's economy, environmental development, use of natural resources, etc. On the other hand, it analyzes how economic growth affects demographic development processes. The objects of economic demography research can be conditionally divided into two groups. The first would include purely social-demographic issues (life expectancy and mortality, fertility, other family problems, etc.); the second would include economic-demographic issues (participation of different age groups in economic activity, relationship with economic development trends, labor market, migration problems, etc.). In studies of the first group of problems, considerable attention is paid to examining issues of life expectancy and mortality in the world and in EU countries (Ginevičius, 2022; Woolf, 2023). The second group – demographic aspects of economic development (the relevance of which is constantly growing) – is studied for many reasons: economic activity is becoming more and more complex, the world population is increasing, but the society of countries is AE Assessment of Demographic Profile of European Union Countries 1112 Amfiteatru Economic aging, qualification requirements for the workforce are increasing and this affects the country's economic development (Adams, 2022; Maestas, Mullen and Powell, 2023; Lu, 2024; Okunevičiūtė Neverauskienė, Ginevičius and Danilevičienė, 2024). The expected duration of working life (Tetzlaff et. al., 2022), the impact of economic and technological factors and urbanization on population size and mortality (Adams, 2022; Balaj et. al., 2024; Dowd, Polizzi and Tilstra, 2025; Nguea, 2023; Hejkal, Ravikumar and Vandenbroucke, 2024; Zhao et al., 2024), population aging and changes in entrepreneurship (Zhang and Kang, 2025) and changes in household structure and behavioral patterns, changes in risk aversion (Bayon and Lamotte, 2020; Beltrán-Sánchez et al., 2022; Wang, Yao and Zhao, 2024), the impact on the development of individual economic activities (e.g., the tourism sector) (Abedin and Mitra, 2024) and many other aspects are particularly relevant issues for the current economy. The solutions are being sought for these challenges. The macro-level scientific works of this group examine the growing scale of migration as a global problem and the related consequences for the development of the global economy. Young people migrate, therefore, countries face a brain drain (Djajić, Docquier and Michael, 2019; Zhao and Zhong, 2019); as the country's population ages, new undesirable social security problems arise (Skjerpen and Tonnessen, 2021); climate change is becoming one of the crucial factors for migration flows and demographic processes (Mueller et al., 2020; Hauer, Jacobs and Kulp, 2024; Udemba, Khan and Shah, 2024); family size and its changes affect migration decisions (Stark and Szczygielski, 2019; Zhao et al., 2024). Various methods are used to study the aforementioned economic-demographic problems, depending on the scope of the analysis and the research problems. The research methods used in the reviewed publications (Gries and Grundmann, 2018; de Albuquerque, Caiado and Pereira, 2020; Murtin and Diaz, 2020; Patterson, Margolis and Verdery, 2020; Muttarak, 2021; Kashnitsky, de Beer and Van Wissen, 2021; Enroth et al., 2022; Lange et al., 2022; Murtin et. al., 2022; Widmer, 2022) can be conditionally divided into two groups. The first group studies demographic problems and uses specific methods for this purpose – demographic models of reproductive processes, factor population risks, index methods, panel cointegration analysis, statistical modeling, microsimulation methods, etc. (Jasilionis et al., 2015; Cristea et. al., 2020; Skjerpen and Tonnessen, 2021; Mitra and Abedin, 2021; Ciganda and Todd, 2022). The second group studies socio-economic problems based on a selected demographic cross-section and applies methods such as balance sheet calculations, index method, correlation-regression, multifactor, cluster analysis, forecasting methods (Abdesselam, Bonnet and Renou-Maissant, 2020; Poplawski-Ribeiro, 2020), and others. The review of literature sources allows us to draw the following conclusions that are important for further research. Two fundamental shortcomings of the quantitative assessment of economic-demographic issues and problems can be distinguished – it is unsystematic and uncomplex. Unsystematicity is manifested in the fact that a unified methodology for assessing such a complex phenomenon as the country's demographic profile (DP) is not provided. This leads to the other aforementioned drawback – as indicated, DP is a complex phenomenon, which in reality manifests itself in a large number of aspects of various kinds. In order to be able to quantitatively assess its state, these aspects need to be formalized and transformed into indicators. Only in this way is a system of indicators formed that adequately reflects the phenomenon under consideration. Since this is not the case today, the literature only examines local aspects of the DP – life expectancy, mortality, fertility, migration, etc. Based on such studies, although they are relevant and interesting, it is impossible to obtain a general picture of the DP of a country. At the same time, there is no possibility of comparing Economic Interferences AE Vol. 27 • No. 70 • August 2025 1113 individual countries with each other. This is also confirmed by literature sources, which indicate a tool to increase the adequacy of the quantitative assessment of DP state – increasing the complexity of assessment methods (Ruggles et al., 2015; Goujon et al., 2016). As a result, the aim of the article can be formulated – to propose and approve a methodology for quantitative assessment of the state of the demographic profile of countries, the complexity of which would maximally correspond to the complexity of the phenomenon under consideration. 2. Research Methodology In order to quantitatively assess the state of such a complex phenomenon as demographic profile, it is necessary, first of all, to form a system of indicators that adequately reflect it. This can be done based on various sources – scientific literature, information provided by statistical databases, expert surveys, etc. However, the main source is scientific literature analyzing this topic. Research publications provide a list of possible DP indicators. An analysis of their nature shows that their relationship to the phenomenon under consideration is different. Some of them reflect the structure of the country's population at the time under consideration. These indicators include age, the share of women in the total population, population density, etc. They can be defined as basic, since they reflect a more quantitative side of DP. The other group of indicators is derived from the first. It is characterized by more intense and frequent changes; therefore, these indicators can be named dynamic. In essence, they reflect the qualitative side of the phenomenon under consideration. The examples of these indicators would be life expectancy, mortality, birth rate, education, etc. Based on this, a system of indicators reflecting the country's demographic profile was formed, adapted for the quantitative assessment of its condition (Figure no. 1). Figure no. 1. The system of country demographic profile indicators AE Assessment of Demographic Profile of European Union Countries 1114 Amfiteatru Economic The indicators presented in Figure 1 differ in three essential respects – dimensions, direction of change and relevance. The first circumstance implies that they are incomparable due to different units of measurement and therefore cannot be combined into a single summary value. Different directions of change mean that some of them are maximizing, others are minimizing, i.e., that an increase in the value of some of them improves the situation (e.g., life expectancy, education, etc.), while others worsen (e.g., mortality, divorce, etc.). The different relevance of indicators means that their impact on the phenomenon under consideration is unequal, so some of them can be classified as essential, others as secondary. Figure 1 shows that the state of a country's demographic profile can only be determined by knowing the value of the basic and dynamic indices. The first is obtained by combining the basic indicators, the second – dynamic indicators. The system of the above-mentioned indicators consists of indicators of various types. Multicriteria methods are suitable for combining such values into one generalizing quantity – an index. They differ from each other in their complexity (Hwang and Yoon, 1987; Opricovic, 1998; Opricovic and Tzeng, 2004; Ginevičius et al., 2022; Ginevičius et al, 2021; Trishch et al., 2021). On the other hand, they all have one particular characteristic – the assessment is carried out in a linear manner. This means that the relevance of indicators does not depend on their value. This is a simplified, inaccurate assessment. In real life, all processes develop non-linearly. For example, if unemployment in a country is low, then a slight increase in it will not fundamentally change the situation. Similarly, when its scale is very large, then again, its insignificant increase will not have a significant impact, either. Thus, in both of these cases, the relevance of unemployment for the economic and social condition of the country will be insignificant. Meanwhile, changes in unemployment between these two extreme states can have a significantly greater impact. At the same time, the relevance of this indicator also increases. Graphically, this whole situation can be represented using the Harrington curve (Figure 2) (Harrington, 1965). Figure no. 2. Graphical representation of the dependence of the relevance of an indicator on its value Source: compiled by the authors based on Harrington, 1965 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 -3 -2.6 -2.2 -1.8 -1.4 -1 -0.6 -0.2 0.2 0.6 1 1.4 1.8 2.2 2.6 3 Y Relevance of the indicator Dimensionless values of the indicator X Economic Interferences AE Vol. 27 • No. 70 • August 2025 1115 Thus, it can be concluded that the time has come to move from a linear assessment of the state of development of socio-economic phenomena to a nonlinear one. The tests conducted have confirmed the possibilities of its successful application (Ginevičius et al., 2021; Ginevičius et al., 2022). The curve shown in Fig. 2 can be expressed mathematically as follows: , (-  < x <  ) (1) here – the transformed (dimensionless) indicator value of the first zone on the OY axis; x – the initial value of the indicator. If the indicator value is in zone 3, the function would look as follows: (2) here – the transformed (dimensionless) indicator value of the second zone. From Figure 2 it can be seen that function (1) reflects the situation characterized by the distribution of the smallest values in a statistical population or its sample, and function (2) – the largest values. The value of the indicator x on the OY axis evaluates both its initial value and relevance. This is a great advantage compared to linear assessment, since expert estimation of the relevance of indicators becomes unnecessary, i.e. it is no longer a subjective, but an objective assessment. Calculation costs are reduced, adequacy increases. Another essential advantage of nonlinear assessment is that normalization (i.e. transformation into comparable ones) of the initial values of indicators becomes unnecessary. Functions (1) and (2) are constructed based on the principle of symmetry. This means that, having the distribution functions of the minimum and maximum values of the data array, the sections between them on the OX axis can be divided into a number of curves reflecting the relevance of the indicators. This methodology is unique due to its universality. For example, it is possible to obtain a function that divides this section into two equal parts: (3) here – transformed (dimensionless) indicator value of the third zone. Thus, we have not a point, but an interval assessment of indicators. Depending on the chosen function in a non-dimensional scale, the value of the OX indicator can either be increased or decreased. The graphical interpretation of equations (1-3) is shown in Figure 3 (Trishch et al., 2021; Ginevičius et al., 2022). AE Assessment of Demographic Profile of European Union Countries 1116 Amfiteatru Economic Figure no. 3. Graphical representation of functions (1-3) From Figure 3 it can be seen that these asymptotic distributions can be applied to interval estimation of the values of the indicator under consideration, when its value is fixed, and to point estimation when its average values are known. The size of the interval L depends on the value of the indicator and is determined as follows: (4) A graphical representation of the interval width between the functions (1) and (2) is given in Figure 4. Figure no. 4. Graphical representation of the interval width between (1) and (2) functions Another property of dependencies (1) and (2) is that the quantity X varies from -3 to +3. 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