An inherent characteristic of socioeconomic systems (SES) is their development, which is a prerequisite for their existence. Analysing the development, as well as comparing the subjects at a variety of levels (companies, countries, regions, etc.) for other purposes requires the development process to be measured in a quantitative manner. The development process is characterised by its dynamics, which in turn may be measured using two indicators: the intensity of the development; and its consistency over the reference period. The former measurement is represented as a ratio between the development values at the beginning of the period and those at the end, while the consistency of the SES economic development will be demonstrated as a ratio of the length of the reference period to the sum of the lengths of the trajectories representing the development over individual time periods. The calculations of the economic development of a number of countries carried out through this research have confirmed that the proposed methodology is appropriate. The methodology has been named, with certain qualifications, the MDDSS (Measuring of the Dynamic of the Development of a Socioeconomic System).

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A country’s competitiveness depends primarily on its economic development which in turn is affected by a number of factors. Some of these, such as investment, favorable business conditions, legal environment, etc., promote economic development, while others, such as low labor productivity, insufficient staff qualification that fails to meet the requirements of the labor market, etc., slow down the pace of economic development. The latter category describes the phenomenon of the shadow economy (SE). Research into shadow economies is dominated by the analysis of the local impact factors. Nevertheless, the results of such analyses do not reveal the general patterns of the shadow economy, without the knowledge of which it is difficult to develop effective preventive measures. The basic determinants of the shadow economy must first and foremost reflect national economic development, as these particular determinants have the most significant impact on the size of the phenomenon of the shadow economy. National economic development can be expressed by employing various indicators, but recently it has most commonly been expressed by GDP per capita. GDP reflects national competitiveness, integrates a number of domestic factors, and is easily accessible and publicly available in national and international statistical sources. In addition, this indicator is calculated by employing a unified methodology, which makes it universal, allowing the comparison of countries in different situations. As presented in this article, the analysis of the relationship between economic development and the size of the shadow economy allows the division of all the EU member states into characteristic groups by the level of their economic development as well as size of the country’s SE. Our research attempts to reveal the regularity of the above-mentioned relationship: the higher the level of national economic development, the lower the size of the shadow economy.

The socio-economic development of economic-territorial units subordinate to administrative-management institutions appears as one of the main tasks. The values of alternative indicators reflecting socio-economic development may differ, which makes it difficult to unambiguously assess the importance of the indicators. The applied available methods are either too receptive or does not provide sufficient accuracy. The proposed FARE-M methodology for determining the importance of indicators is the prolongation of the technique for establishing the importance of FARE (Factor Relationship) weights already used for research purposes. The employed technique is based on the internal balance of system elements that is the essential systemic feature. This allows, unlike in the case of the AHP method, the weights of the indicators to be determined with reference to the first row of the data matrix only.

To this date, insufficient number of reasoned methods for assessing the industrial composition in the country or in the region in an integrated and quantitative manner is on offer. The existing proposals are basically intended for explaining the drivers of change in the industrial composition as well as the reasons thereof. Following this analysis, the most export-oriented industries are determined. Hence, the focus is not on assessing the industrial composition of a country or a region itself in a quantitative manner, but rather the impact of the changes thereof on economic indicators, i.e. derivative measures of industrial composition. The industrial composition of a country or a region can be described through indicators that reflect three key aspects, i.e. the variety of active economic entities by their number, size and types of economic activities. The proposed methodology is suitable for assessing the industrial composition of a country’s region.

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ABSTRACT.A permanent property applicable to every socioeconomic system (SES) is its development. SES development is an integrated process with two sides that can be distinguished, i.e. quantitative and qualitative ones. The quantitative side reflects its static aspect, i.e. the state of the development at a certain point in time. The qualitative side of development reflects its dynamics, i.e. the scope of development changes. In order to make an integrated assessment of the standing of SES development, both these aspects above have to be assessed in a quantitative manner and be further combined into one generalised value. These days, assessment of the standing of SES development is limited to evaluation of the achieved level only, i.e. its quantitative assessment. Due to the fact that all socioeconomic systems are always large and complex systems, they tend to have a multitude of aspects. The indicators that reflect such aspects form a system thereof. It is thus the basis for further multicriteria assessment of the development state. In order to reduce the number of indicators to be assessed simultaneously so that experts could establish the weights thereof in a sufficiently accurate manner, a hierarchically structured system of indicators is developed and presented here. Following this methodology, the level of economic development across Lithuanian regions has been determined. When the scope of development changes was established on that basis, the integrated indicator of the regional development state was calculated following the proposed formula. On the basis of the correlation-regression analysis, it has been determined that the scope of development changes is larger in the regions with lower level of development achieved.

The debate on the presence of economic benefits in the European Union (EU) is not over. The study responds unequivocally to this question, with the intensity of economic development in the countries that joined the European Union in 2004 and beyond twice as high as that of the countries that joined it this year, i.e. the EU’s old ones compared to the new ones; smoothness – 1.1 times and dynamics – 1.6 times. Another important trend for further development is that, as the level of economic development increases, its smoothness is diminishing. In respect of the context of the EP of all EU Members, it turned out that the higher intensity of enlargement was characterised by higher economic levels, with similar homogeneity and almost identical values for the dynamic indicator. The introduction to the article presents the context of the studies, i.e. two groups of EU Community countries are formed according to their level of economic development and the year of their accession to the Community, as well as a survey scheme. The literature review reveals the methods used to analyse the convergence of economic development in these countries, as members of the Community. The research methodology introduces the indicator of economic development of countries and provides a methodology for assessing its dynamics. The empirical part assesses the dynamics of economic development of both groups of countries and identifies trends in terms of convergence. The discussion section summarises the consolidation and destabilising factors in the EU and the importance of the study carried out in this context. The conclusions present the main results of the studies and outline their further directions. The results of the study can be used both in the EU and for the purpose-oriented decisions of its members on further economic development.