Influence of Financial Variables on the Development of Rural Communes of Eastern Poland in 2009–2018

Andrzej Pawlik; Paweł Dziekański; Jarosław W. Przybytniowski

doi:10.3390/risks9080145

Influence of Financial Variables on the Development of Rural Communes of Eastern Poland in 2009–2018

Pawlik, Andrzej;Dziekański, Paweł;Przybytniowski, Jarosław W. 2021-08-12 00:00:00 risks Article Inﬂuence of Financial Variables on the Development of Rural Communes of Eastern Poland in 2009–2018 1 1 , 2 Andrzej Pawlik , Paweł Dziekanski ´ * and Jarosław W. Przybytniowski Department of Economics and Finance, Jan Kochanowski University in Kielce, Uniwersytecka 15 str., 25-406 Kielce, Poland; andrzej.pawlik@ujk.edu.pl Department of Management, Jan Kochanowski University in Kielce, Uniwersytecka 15 str., 25-406 Kielce, Poland; jaroslaw.przybytniowski@ujk.edu.pl * Correspondence: pawel.dziekanski@ujk.edu.pl Abstract: Communes are a place of both economic activity and creation development. They have autonomy in making decisions in the ﬁelds of ﬁnancial, human, and material resources. This research was carried out with the use of a synthetic measure. The aim was to show the impact of ﬁnancial variables on the development process of rural communes in eastern Poland. The data were collected in spatial terms for 484 rural communes from the region of eastern Poland. The choice of variables was conditioned by the availability of GUS data for the period 2009–2018. The distribution of the evaluation of the development and ﬁnancial situation of rural communes in eastern Poland was spatially polarized. The reason for the low impact of ﬁnancial conditions on the development of rural communes in eastern Poland is their dependence on income transferred from the state budget. This stiffens and at the same time stabilizes the ﬁnancial economy, making it relatively insensitive to the inﬂuence of other factors. Low independence can be a signiﬁcant barrier to future local development. Finance and the economy are intertwined. Actions taken with respect to these must be based on Citation: Pawlik, Andrzej, Paweł analyses that facilitate making the right decisions. Dziekan ´ ski, and Jarosław W. Przybytniowski. 2021. Influence of Keywords: synthetic measure; rural municipalities; competitiveness; ﬁnancial security; TOPSIS Financial Variables on the Development of Rural Communes of method; public sector Eastern Poland in 2009–2018. Risks 9: 145. https://doi.org/10.3390/ risks9080145 1. Introduction Academic Editor: Tomas Kliestik Municipalities operate in an increasingly complex environment. They are a place of concentration of economic and social activities and a creator of development. They are Received: 4 June 2021 characterized by autonomy in making decisions in terms of ﬁnancial, human, material, and Accepted: 6 August 2021 information resources. The amount and structure of ﬁnancial resources at the disposal of Published: 12 August 2021 municipalities are of particular importance as they affect the economic situation of local governments (Travers 2012). Finance, apart from infrastructure, environmental elements, Publisher’s Note: MDPI stays neutral and social elements, determines the activities of communes. The indicated areas are a set of with regard to jurisdictional claims in inter-related factors that create a multidimensional space. They should be viewed as a set published maps and institutional afﬁl- of interdependent elements. They occur at the same time and within the spatial horizon. iations. The market mode of operation of municipalities manifests itself in the search for new management opportunities aimed at increasing the ability to achieve the assumed goals. Municipalities are at the same time an employer, a principal, a client, and an investor. They shape their individual potential in terms of economic, cultural, and social function- Copyright: © 2021 by the authors. ing. Local resources of units, including the natural, economic, social, and infrastructural Licensee MDPI, Basel, Switzerland. environments used in economic and social relations, are interdependent and occur si- This article is an open access article multaneously. There is a correlation between the functioning of municipalities and the distributed under the terms and quality of life and living conditions of the inhabitants or the activities of enterprises. The conditions of the Creative Commons risk of making negative decisions in this regard should be minimized through analyses Attribution (CC BY) license (https:// that should be multidimensional and support the decision-making process. Communes creativecommons.org/licenses/by/ should be increasingly interested in obtaining and processing information. Information 4.0/). Risks 2021, 9, 145. https://doi.org/10.3390/risks9080145 https://www.mdpi.com/journal/risks Risks 2021, 9, 145 2 of 22 on the condition of communes, resources, and their use is necessary for both diagnostic and strategic operations. These problems require rational choices and optimal decisions from the point of view of the functioning of the individual. In order for decisions to be rational, they cannot be accidental and made intuitively. They should be based on reliable and properly processed information (Drozdowski 2021; Dobrowolski 2020a). The commune’s self-government can shape the development process by using local resources. Its shape is inﬂuenced by many factors, both dependent on and independent of the commune itself (Hall 2015). One of the essential elements of development is the ﬁnancial situation of communes. There is a correlation between development and the ﬁnancial situation. A high level of development of the local economy attracts an inﬂux of new residents and investors. The indicated process further inﬂuences changes in the budgets of communes in the form of, inter alia, increases in the amount of real estate tax, shares in personal taxes (PIT), and corporate income tax (CIT). The income obtained in this way makes it possible to undertake further pro-development projects (Standar 2017). The role of municipalities in the development process requires changes in the local ﬁnancial system and support for endogenous growth potentials. The aim of this article is to evaluate the impact of ﬁnancial variables on the development process of rural communes using a synthetic measure. The Technique of Order Preference by Similarity to the Ideal Solution (TOPSIS) method was used to build the synthetic measure. Empirical data were collected for 484 rural communes in the eastern Poland region. The choice of variables was conditioned by the availability of data in the Local Data Bank of the Central Statistical Ofﬁce for 2009 and 2018. Answers to the following research questions will bring the authors closer to the achievement of the main goal set. The research questions were as follows. Does devel- opment depend on ﬁnancial variables? What is the spatial distribution of development and the ﬁnancial situation? Do transfers from the state budget inﬂuence the development process? It should also be indicated that the weaker the mutual inﬂuence of the ﬁnancial situation and development, the higher the level of transfers from the state budget and current expenditure. A higher level of development means a better ﬁnancial situation and a more attractive commune. The spatial polarization of these phenomena requires considering diagnostic variables in various dimensions and at various levels of detail. 2. Literature Review Actions taken in respect of development should focus on achieving social, economic, and spatial cohesion. It is also important to indicate the development proﬁle of a com- mune, which should become a signiﬁcant asset in the development process. As a rule, rural communes are assigned an agricultural character. Nowadays, these communes are transforming into residential, service, tourist, and recreational facilities, which strengthens the role of individuals in a dynamically changing environment (Standar 2019). The subject of the activities of municipalities is public administration, which is per- formed in a speciﬁc area and by law deﬁned in the scope of tasks aimed at satisfying the needs of residents. It implements these tasks on its own behalf and at its own risk. Factors differentiating the way that particular tasks are performed are their endogenous potential, the ﬁnancial capacity of the commune, and the actual needs of residents and business entities. Commune self-governments carry out various types of tasks related to the current residents’ needs, such as access to healthcare services and education, but they should also create favorable conditions for the development of entrepreneurship and increase the region’s competitiveness. The proper and effective functioning of communes should ensure appropriate ﬁnancial resources, allowing for the implementation of both current and investment projects. Finance is a factor that allows us to evaluate the studied area and make decisions on both current and investment projects that provide the opportunity to create socio-economic development, allow us to increase the innovativeness of communes, and change the current condition of the infrastructure (Głowicka-Wołoszyn et al. 2017). Risks 2021, 9, 145 3 of 22 A commune is an organization operating under changing and unpredictable condi- tions related to its surroundings. The effective performance of tasks requires the provision of funds for their implementation. These funds may be the commune’s own income, general subsidies, or targeted subsidies from the state budget (Ziółkowski 2015). The socio- economic development of communes is inseparably connected to the use of endogenous resources (supported by exogenous resources) in the context of creating new utility func- tions for the inhabitants (Radwan and Paluch 2008). Development is a historic, long-term process of internal, economic, and social transformation. A commune is forced to constantly adapt to changing environmental conditions and look for a competitive advantage in the development process in all aspects of its activity (Rynca ´ 2009). Development is a multidimensional process of qualitative and quantitative (economic, social, and political) changes taking place in the local socio-territorial system. The individ- ual endogenous potential is the (human, innovative, ecological, infrastructural, ﬁnancial, and institutional) capital that has accumulated in a given area that determines the strength of local changes. The potential of communes results from a combination of local condi- tions. It determines the possibilities for and directions of development. Development is a complex concept that includes many changes taking place at a speciﬁc time. Like any speciﬁc process, a socio-economic space is conditioned by a number of factors that may affect this area to varying degrees and with varying degrees of force. The conditions and factors shaping local development are varied and fully dependent on the economic and social processes taking place in a given commune. In addition to processes, changes that cover only certain areas are also of great importance and have an impact on the economy on a global scale. Many authors dealing with theoretical concepts of regional or local development cite various concepts explaining this process. The most popular are: eco- nomic base theory; new trade theory; growth poles theory and the concept of geographical growth centers; the theory of cumulative causality; and the core and peripheries model (Grosse 2004; Malecki 1997). The socio-economic development of communes is inseparably connected to the ex- ploitation of endogenous resources (supported by exogenous resources) in the context of creating new utility functions for residents (Radwan and Paluch 2008). There are areas of both stagnation and even developmental depression, as well as more dynamized develop- mental processes that are shaped by a number of factors (Standar and Kozera 2019). These factors can be grouped into economic, social, spatial, ecological, political, technical, and local factors. On the other hand, new factors of economic growth include, inter alia, inno- vation, achievements in science and technology, modern management styles, cooperation networks, and social capital (Šlander and Ogorevc 2019). Under the conditions of dynamic changes in the external environment, on the local authority there is a special responsibility for the ﬁnancial situation. Assessment of the ﬁ- nancial situation with the use of appropriate tools (including a synthetic measure) provides information on the current situation, allows us to identify differences with respect to other units, and allows us to identify development opportunities (Dylewski 2011). As indicated by Stanny and Strzelczyk (2015), the ﬁnancial situation (as a multidi- mensional phenomenon) represents the possibility to provide public services at least at the current level and to obtain funds from repayable and non-returnable sources for the implementation of future tasks. It is a relative assessment of a commune’s ﬁnances that can ensure its ﬁnancial security. Douglas and Gaddie (2002) indicate that the ﬁnancial situation includes the ability to perform tasks and ensure reliability in terms of the abil- ity to pay off both present and future liabilities. The ﬁnancial situation, as indicated by Perry and Christensen (2015), is the certainty of repayment of liabilities towards, among other things, customers and employees of the authorities. Groves and Valente (1994) deﬁne a ﬁnancial situation as the state of ﬁnances that allows the commune to cover all costs of business in the long term and services at a level ensuring the safety and well-being of the local community. Risks 2021, 9, 145 4 of 22 Assessment of the ﬁnancial situation of municipalities allows us to determine the efﬁciency of a municipality’s functioning, its ability to meet obligations, and the possi- bility of raising the standard of quality of the services it provides to local communities (Głowicka-Wołoszyn and Wysocki 2016). So, it is directly related to access to sources of ﬁnancial supply and depends to a large extent on the possession by municipalities of stable and adequate sources of income (Stanny and Strzelczyk 2018). The ﬁnancial situation of communes is demonstrated by their ability to perform tasks, achieve a budget balance, and increase wealth. It is undoubtedly a complex phenomenon created by the level of income, ﬁnancial independence, amount of capital expenditure, abil- ity to obtain extra-budgetary funds, and ﬁnancial results. There is a feedback loop between the ﬁnancial condition of the commune and the level of development (Sobczyk 2010). 3. Materials and Methods One of the solutions for researching multifaceted phenomena with the use of aggre- gated values of diagnostic features is the use of a synthetic measure. It allows for the numerical description of complex phenomena. This enables a multidimensional view of the level of this phenomenon in individual examined objects and allows us to con- duct comparative analyses in spatial and time terms, linear ordering, and classiﬁcation (Lenormand and Deffuant 2013; Dziekanski ´ 2016). However, caution should be exercised when interpreting obtained results because these measures have certain limitations, e.g., they lead to simpliﬁed arrangements and do not take into account qualitative and non- measurable aspects of local or regional development (Strahl 2006). 3.1. Selection of Variables Describing the Studied Phenomenon. Determining the Direction of Variable Preferences in Relation to the Analyzed Phenomenon (Indication of a Stimulant and Destimulant) The development process, ﬁnancial situation, and demographic potential are shaped at the same time by, inter alia, economic, environmental, infrastructural, and social factors (Fang et al. 2018). They determine the multi-element space of functioning of communes. They often appear and work together at the same time for the beneﬁt of the local community. Therefore, they are interdependent and should be considered jointly (Ngo Dang et al. 2018; Tang and Wang 2018). The selection of variables for the study was conditioned by the availability at the commune level of data within the BDL CSO. Some data were incomplete and did not cover all communes. Therefore, in this study, the authors focused on the selected variables described in Table 1. The activities of municipalities are operational, tactical, and strategic. They are carried out in a multidimensional space of functioning. They refer to endogenous and exogenous re- sources, the use of which ensures qualitative and quantitative changes in the local economy. The socio-economic space of communes is a multi-element system, which includes, inter alia, local community, enterprises, ﬁnancial resources, natural resources, infrastructure, labor, and capital. It should be noted that the analyzed diagnostic variables (Table 1) can be associated with the three dimensions of cohesion described in the EU objective of public authorities’ actions under the implementation of regional policy: X16–X20 and X30–X31 for economic cohesion, X27–X29 for social cohesion, and X32–X40 for territorial cohesion. Communes have different income and expenditure capacities. Differences arise be- tween them in the amount of their income and actual expenses for public tasks. The level and structure of communes’ incomes and expenses are shaped by their ﬁnancial situation (variables X1–X15), which determines the timely fulﬁllment of obligations and the quality and continuity of services. Entrepreneurship (variables X16–X20) and its potential shape the quality of life of the inhabitants and the social and material security of the residents. The number of economic entities shapes the number of employed and unemployed inhabitants as well as the economic situation of the region. Risks 2021, 9, 145 5 of 22 Table 1. List of variables describing the ﬁnancial situation and economic and social development of communes. Variables Unit S/D X1 Operating surplus/total revenues (budget solvency ratio) % S X2 Personal income/total income (ﬁnancial independence indicator) % S Share in taxes constituting state budget revenues */number of inhabitants (index of ﬁscal wealth X3 PLN S per capita) X4 Income from local taxes/population (ﬁscal wealth indicator) PLN S X5 Local tax revenue/current income (tax autonomy indicator) % S X6 Investment expenditure/total expenditure (investment attractiveness index) % S X7 Transfer income/total income (state ﬁnancial interference index) % D X8 Expenditures on education and upbringing/number of inhabitants PLN S X9 Expenditures on housing/population PLN S X10 Healthcare expenditure/population PLN S X11 Expenditure on the municipal economy and environmental protection/population PLN S X12 Public safety and ﬁre protection expenditure/population PLN S X13 Public administration expenditure/number of inhabitants PLN D X14 Expenditure on agriculture and hunting/population PLN S X15 Interest/personal income (debt service ratio) % D X16 Entities entered in the REGON register per 1000 inhabitants pcs. S X17 Units newly registered in the REGON register per 1000 inhabitants pcs. S X18 Units removed from the REGON register per 1000 inhabitants pcs. D X19 Natural persons conducting economic activity per 1000 inhabitants pcs. S X20 Foundations, associations, and social organizations per 1000 inhabitants pcs. S X21 Population per 1 library (person) person S X22 Population for a public pharmacy person S X23 % of the population using the sewage network % S X24 % of the population using the water supply system % S X25 % of the population using the gas network % X26 Apartments per 1000 inhabitants pcs. S X27 Demographic dependency ratio for the elderly person D X28 Population growth per 1000 inhabitants person S X29 Migration rate per 1000 inhabitants person S X30 Unemployed persons registered in communes per 1000 inhabitants person D X31 Employed persons per 1000 inhabitants person S X32 Total forest area ha/person S X33 Area of farms in the total area % S X34 Areas legally protected in the total area % S X35 Total water consumption in households (water from water supply systems per capita) m /person D X36 Mixed waste collected during the year in the total per capita kg/person D X37 Wastewater treated during the year treated together dam S X38 Emissions of dust pollution t/r D X39 Emissions of gaseous pollutants t/r D X40 % Of the population using sewage treatment plants % S S, stimulant; D, destimulant; operating surplus = total income property income current expenditure; REGON, Register of the National Economy; National Journal of the National Economy Register, a register kept by the President of the Central Statistical Ofﬁce. The term REGON is also understood as the REGON identiﬁcation number, i.e., the nine-digit identiﬁer assigned to the entity in this register. * Communes have a share in the personal income tax (PIT) and corporate tax (CIT); Source: own research based on data from the Central Statistical Ofﬁce of Poland, Stanny and Strzelczyk (2018), Dziekanski ´ and Prus (2020), and Pawlik and Dziekanski ´ (2020), Barthelemy and Toint (2013), Dziekanski ´ and Pawlik (2019). The condition of infrastructure (X21–X26) determines the attractiveness of municipali- ties, attracts new companies, and shapes the quality of life of residents and the quality of business activities. Infrastructure shapes the economic activity of communes as well as the openness of the region and its development. Demographic potential (X27–X31) is important for the identiﬁcation of development policy determinants. According to Rosner ’s research, there is a close relationship between population processes (population number, age and occupational structure, birth rate, balance of migration, and population density) and the level of socio-economic development. The age structure of the population shapes the situation in the labor market, and this indirectly affects the local infrastructural and ﬁnancial potential. In a positive way, it Risks 2021, 9, 145 6 of 22 should be used to assess the decrease in the number of unemployed persons in all groups and the increase in the number of employed persons, business entities, and natural persons. The natural environment (X32–X40), as a component of the wealth of communes, is an important factor shaping the quality of life of the inhabitants of municipalities. It is a source of raw materials and energy and a geographic space for economic activity, leisure, and places of residence. Some variables were dropped because their higher values did not necessarily indicate the level of socio-economic development. In the case of variables such as, for example, water consumption per capita or population per library facility, due to the lack of an unambiguous reference to the studied phenomenon, the phenomenon was abandoned. Among other variables shaping the operation of communes, one can indicate road networks, the availability and diversity of the service base, educational and cultural institutions, farmland, legally protected areas, and gas pollution. In the case of these variables, there is no information at the level of communes within the BDL CSO. In order to ensure the representativeness of the variables, the ﬁnal set was supple- mented with variables that are more discriminatory in a given category and are not very strongly correlated with others in this category. Two features that strongly correlate with each other are carriers of similar information, so one of them is redundant (Eini et al. 2015). The description of the selected set may be presented in the form of an observation matrix X in the form: ij 2 3 x x . . . x 11 12 1m 6 7 x x . . . x 21 22 2m 6 7 X = , (1) ij 4 5 . . . . . . . . . . . . x x . . . x nm n1 n2 where X denotes the value of the j-th feature for the i-th object, i denotes the object number ij (i = 1, 2, . . . , n), and j denotes the variable number (j = 1, 2, . . . , m). After selecting the variables, the nature of each variable was examined, i.e., it was determined whether the variable was a stimulant or destimulant. Most of the variables were obvious, resulting from the substantive experience of the researchers and the analysis of the literature. In doubtful cases, we used the procedure by Grabinski ´ (1985), which uses the fact that stimulants should be positively correlated with each other, similarly to destimulants, and negatively correlated with destimulants. The value of the coefﬁcient of variation of the variables used in terms of ﬁnancial potential ranged from about 0.15 to 2.05. The greatest differentiation was noted in the variables X10 and X9; the smallest difference occurred in the cases of X7 and X8 (see Table 2). The analysis of the data in Table 2 shows that almost all variables are characterized by positive asymmetry. The variable X7 presents negative asymmetry, which in the case of a stimulant is not a favorable situation as it means that a greater number of communes have values of these variables that are lower than their average value. Table 2. Statistical characteristics of the diagnostic variables for the ﬁnancial potential of rural communes in eastern Poland (in 2018). Variable Range Mean Deviation Variability Asymmetry X1 0.31 0.08 0.04 0.48 0.75 X2 0.59 0.28 0.10 0.34 1.55 X3 0.42 0.09 0.05 0.54 2.62 X4 2.11 0.10 0.14 1.36 8.14 X5 0.62 0.11 0.06 0.56 2.89 X6 0.47 0.21 0.09 0.45 0.42 X7 0.64 0.64 0.10 0.15 1.05 X8 3301.95 1368.67 304.66 0.22 2.53 X9 933.04 65.77 108.86 1.66 4.04 X10 569.52 16.80 34.44 2.05 10.49 X11 3712.70 431.05 391.39 0.91 2.95 Risks 2021, 9, 145 7 of 22 Table 2. Cont. Variable Range Mean Deviation Variability Asymmetry X12 684.28 60.87 51.40 0.84 5.27 X13 961.19 481.96 145.77 0.30 1.78 X14 2611.15 251.89 292.99 1.16 3.10 X15 0.09 0.02 0.02 0.79 1.16 Source: own research based on data from the Local Data Bank. Dziekanski ´ and Prus (2020). 3.2. Standardization of Variables According to the Zero Unitarization Method The reliability of the ﬁnal results depends on the quality of the set of variables. The selected variables should be, among other things, unambiguous, strictly deﬁned, and accurate with high information content and low internal correlation (Fischer 2004). The replacement of the destimulant with the stimulant was done according to the formula (Nelson and Shavitt 2002): X = , (2) ij ij where X is the original value of the variable and X’ is the value of the variable converted ij ij into the stimulant. The selected variables were subjected to the procedure of zero unitarization using the following formula: x min x ij i ij Z = , where x 2 S, (3) ij i max x min x i ij i ij where max 6= min , S is the stimulant, x denotes the value of the j-th feature for the i-th xij xij ij object, max{x } is the maximum value of the j-th variable, min{x } is the minimum value of ij ij the j-th variable, and the normalized value is j-th feature for the i-th object. The value of Z is in the range [0; 1]. A value of 1 means that the variable ob- ij tained the maximum value among all objects tested during the entire testing period (Hendershot 2011). As a result of the transformations, a matrix of uniformized variable values was obtained: 2 3 z z . . . z 11 12 1m 6 7 z z . . . z 21 22 2m 6 7 Z = , (4) ij 4 5 . . . . . . . . . . . . z z . . . z n2 nm n1 where Z denotes the unitary value of the j-th feature for the i-th object. ij 3.3. Determining the Synthetic Measure According to the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) Method for Individual Objects For the assessment of the multidimensional phenomenon (the ﬁnancial situation), a synthetic measure was built. For this purpose, we used the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method (Abidin et al. 2016). It is a reference method in which the reference points of objects in a multidimensional space are: a pattern (=1) and an anti-pattern (=0). Then, the Euclidean distances of individual objects from the pattern and anti-pattern were calculated according to the following formulas: u 1 + + d = Z Z , (5) å i j i j j=1 d = Z Z , (6) å i j i j j=1 Risks 2021, 9, 145 8 of 22 where n is the number of variables forming the pattern or anti-pattern; Z denotes the i j unitized value of the j-th feature for the tested unit; and Z /Z is the pattern or anti- j j pattern object (Behzadian et al. 2012; Bak ˛ 2018). The value of the synthetic measure for individual objects was estimated using aggre- gate functions, based on the formula: q = , where 0 q 1, i = 1, 2, . . . , n, (7) i i d + d i i where q 2 [0; 1] is the value of the synthetic measure; d is the distance of the object from the anti-pattern (from 0); and d is the distance of the object from the pattern (from 1). A higher value of the measure indicates a better situation of an individual in the studied area (Eini et al. 2015). Then, the average value of the synthetic measure was determined, indicating the development potential of the commune. It was calculated based on the formula: i=1 X = , (8) where X is the arithmetic mean as a value of the synthetic measure of development, q is the synthetic value of the category of a speciﬁc potential, and n is the number of tested potentials (categories). The value of the arithmetic mean is the quotient of the total value of all studied endogenous potentials of communes and the number of them. The conducted analysis allowed for the elimination of the problem of variable re- peatability within the examined categories. The applied TOPSIS method made it possible to conduct an evaluation using many criteria, to present the results in numerical form, and to organize objects in a linear manner (building a ranking of units). An important advantage of the classic TOPSIS method is its computational simplicity, the indication of a positive and negative pattern, and the large number of alternative criteria (Kim et al. 2013; Velasquez and Hester 2013). 3.4. Division of the Surveyed Population into Typological Groups and Evaluation of the Obtained Results In the last stage of the research, a division into typological groups was used to interpret the obtained measures. The threshold values were percentiles (2, 4, 6, and 8; 5 groups were formed). The size of the synthetic measure in the ﬁrst group indicates the unit that is better in the following groups—the weaker units. A correlation analysis was also performed (Pearson’s coefﬁcient), a scatter plot with a ﬁt line was made, and a linear regression analysis was performed (Trojak and Tokarski 2013; Kumari and Yadav 2018). Regression analysis is the study of the relationship between the variables of interest and aims at the construction of a model that reﬂects this relationship well. It allows us to indicate the relationships between the dependent variables (Y) and the independent variables (X). The linear regression model is described by the following formula: y = b x + a, i = 1,2, . . . , n, (9) i i In the case of the multiple regression model, when we had more predictors, we used the following formula for the regression line: y = b x + b x + . . . + b x + a, i = 1, 2, . . . , n, (10) i 1 1 2 2 i i where: b is the regression coefﬁcient calculated for individual predictors in the model; x is the independent variable; y is the dependent variable in the model; and a is an intercept. Risks 2021, 9, 145 9 of 22 Regression analysis allows us to check whether the built model signiﬁcantly predicts the value of the explained variable and determine which variables predict it signiﬁcantly. In the regression model, the autocorrelation of variables should be excluded. The (corrected) R2 statistic, which indicates the degree to which the estimated regression function explains the variability in the variable y, takes values from 0 to 1 (Gigerenzer 2004). 4. Results The area of eastern Poland includes the following provinces: Lubelskie, Podlaskie, Podkarpackie, Swietokrzyskie, ˛ and Warminsko-Mazurskie. ´ It is characterized by the lowest level of economic development in Poland and is also one of the weakest regions in the European Union. The problems that have a negative impact on the socio-economic development to a large extent have a structural dimension, being a consequence of historical conditions. Regarding the developmental potential of the macroregion, the unfavorable conditions include poor infrastructure related to limited professional activity, the low effectiveness of the structure of the economy and the labor market, a constant outﬂow of inhabitants to other regions (e.g., the migration of mainly young people), and a low level of innovation. The classiﬁcation of rural communes in eastern Poland according to their ﬁnancial situation is shown in Figure 1. The white color in the ﬁgure indicates urban and urban– rural communes not covered by the study. The black color indicates the best units, and the lighter color indicates weaker units. The division of communes was based on quartiles, which constituted the threshold values for subsequent groups. The rural communes in eastern Poland are characterized by signiﬁcant disproportions in terms of development and ﬁnancial situation. The units distinguished by a better ﬁnancial situation have a higher rate of development. The synthetic measure of development (qi) ranged from 0.16 to 0.51 in 2018 and from 0.15 to 0.46 in 2009 (in the case of the ﬁnancial standing measure 0.09–0.39 in 2009 and 0.14–0.51 in 2018). The increase in the range of the measure from 0.31 to 0.35 Risks 2021, 9, x FOR PEER REVIEW 10 of 22 and the increase in the ﬁnancial situation measure from 0.30 to 0.37 conﬁrm the increase in the differentiation of individuals in terms of development. AB Figure 1. Cont. CD q (r) development measure (A 2009, B 2018); q (f) financial situation measure (C 2018, D 2009). Figure 1. Synthetic measure of the financial situation of rural communes in eastern Poland in 2009 and 2018. Source: own research. By analyzing the internal conditions of municipalities divided into five typological groups (statistically similar to each other, according to the percentile values 2, 4, 6, and 8), they were characterized as follows: Risks 2021, 9, x FOR PEER REVIEW 10 of 22 Risks 2021, 9, 145 10 of 22 AB CD q (r) development measure (A 2009, B 2018); q (f) financial situation measure (C 2018, D 2009). Figure 1. Synthetic measure of the ﬁnancial situation of rural communes in eastern Poland in 2009 and 2018. Source: own research. q (r) development measure (A 2009, B 2018); q (f) ﬁnancial situation Figure 1. Synthetic measure of the financial situation of rural communes in eastern Poland in 2009 and 2018. Source: own research. measure (C 2018, D 2009). By analyzing the internal conditions of municipalities divided into ﬁve typological By analyzing the internal conditions of municipalities divided into five typological groups (statistically similar to each other, according to the percentile values 2, 4, 6, and 8), groups (statistically similar to each other, according to the percentile values 2, 4, 6, and 8), they were characterized as follows: they were characterized as follows: (1) Group 1 communes are no longer typically agricultural, as evidenced by the number of economic entities and natural persons running a business. Thus, the multifunc- tionality of rural areas contributes to their development. The use of the rent of the location in relation to urban areas (local development centers) creates opportunities for their rapid development. (2) The communes in Group 1 (the best group), in relation to the communes of the fourth and ﬁfth groups (the weakest groups), were characterized by lower ﬁnancial ratio values, which allow for a conclusion about the lower freedom of use of ﬁnancial resources and, thus, the smaller ﬁnancial possibilities of these communes. (3) The group with the best ﬁnancial situation consisted of 33 communes (28% of all rural communes in the provinces of eastern Poland). These communes were characterized by the highest share of the population per 2 km in relation to the weakest communes. (4) The communes in the best ﬁnancial situation (Group 1 communes) obtained higher ratios of the share of personal incomes in total incomes than the weakest communes. (5) The poorer the ﬁnancial situation of communes, the smaller was the importance of income sources. (6) The budget of the weakest communes was the most supported by income from transfers (which weakens their independence). (7) The main reason for the low impact of ﬁnancial conditions on the socio-economic development of communes is their dependence on income transferred from the state budget and the amount of current expenditure. These circumstances stiffen and stabilize the ﬁnancial economy, making it relatively insensitive to the inﬂuence of other factors. Risks 2021, 9, 145 11 of 22 (8) The low independence constitutes a barrier to the local development of rural com- munes. (9) The growing importance of transfers from the state budget in the group with poor ﬁnancial standing proves the declining level of ﬁnancial independence (see Table 3). Table 3. Values of indicators describing the socio-economic and ﬁnancial situation of rural communes in eastern Poland in 2009 and 2018. 2009 2018 I II II IV V I II III IV V q development 0.32 0.26 0.24 0.21 0.19 0.37 0.30 0.27 0.24 0.21 Number of communes 102 116 76 98 92 97 127 90 112 58 Determinants of the socio-economic situation Population per km 87 53 50 43 44 96 57 45 40 38 Migration balance per 1000 people 2.4 0.5 1.9 2.9 3.4 2.6 1.9 2.9 4.7 4.5 Unemployed persons registered in 70 71 61 56 58 37 38 41 38 44 communes per 1000 inhabitants Employed persons per 107 80 66 59 54 117 94 80 61 59 1000 inhabitants Entities entered into the REGON 57 51 47 42 40 76 65 57 52 50 register per 1000 inhabitants Natural persons conducting economic activity per 48 41 36 33 31 62 51 43 40 38 1000 inhabitants Determinants of the ﬁnancial situation q ﬁnancial situation 0.18 0.16 0.17 0.16 0.15 0.21 0.19 0.20 0.19 0.18 Personal income/total income 0.34 0.27 0.26 0.24 0.23 0.35 0.29 0.28 0.25 0.24 Investment 0.21 0.18 0.21 0.20 0.18 0.22 0.21 0.20 0.20 0.20 expenditure/total expenditure Transfer income/total income 0.63 0.69 0.69 0.73 0.75 0.58 0.64 0.65 0.68 0.68 Source: own research. Figure 2 shows the distribution model for the synthetic measure of development and ﬁnancial situation. In the case of the development measure, we observed a right-hand distribution of 0.29 > 0.28 in 2018 and 0.25 > 0.24 in 2009. In the case of the ﬁnancial standing measure, we observed a right-hand distribution of 0.17 > 0.16 in 2009 and a symmetrical distribution of 0.19 = 0.19 in 2018. The right-hand skewness indicates that a greater number of communes have values of these variables that are lower than their average value. The largest range in 2018 for the development measure was 0.25–0.30 (155, 32%), and the largest range in 2018 for the ﬁnancial standing measure was 0.15–0.20 (327, 68%). There was a predominance in the indicated ranges. The statistical characteristics of the synthetic measure of the ﬁnancial situation, as well as the income from local taxes of rural communes in eastern Poland in 2018 compared to 2009, do not indicate the stability of this phenomenon in the analyzed area. The analysis of the dispersion of the measure of economic security in rural communes in eastern Poland in 2009 and 2018 shows a slight increase in differentiation. This is indicated by the range of 0.31–0.35 for development and 0.30–0.37 for the ﬁnancial situation; the quarterly range of 0.07–0.08 for development and 0.04–0.04 for the ﬁnancial situation; and the standard deviation of 0.05–0.06 for development and 0.04–0.04 for the ﬁnancial situation. The stability of the phenomenon is indicated by the coefﬁcient of variation of 0.20– 0.20 for development and 0.22–0.20 for the ﬁnancial situation; and the quarter deviation of 0.04–0.04 for development and 0.02–0.02 for the ﬁnancial situation. Additionally, it should be noted that almost all variables (except for transfer income/total income—the state’s ﬁnancial interference rate) show a positive asymmetry, which is not a favorable situation for stimulants. This means that a larger number of communes have values of these variables that are lower than their average, indicating the weakness of the analyzed region in the indicated area (see Table 4). Risks 2021, 9, x FOR PEER REVIEW 12 of 22 greater number of communes have values of these variables that are lower than their average value. The largest range in 2018 for the development measure was 0.25–0.30 (155, Risks 2021, 9, 145 12 of 22 32%), and the largest range in 2018 for the financial standing measure was 0.15–0.20 (327, 68%). There was a predominance in the indicated ranges. qi measure of development qi measure of development 208; 43% 155; 32% 152; 31% 118; 24% 95; 20% 90; 19% 51; 11% 48; 10% 17; 4% 18; 4% 2; 0% 1; 0% 12; 2% 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 1; 0% 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 qi measure of financial situation qi measure of financial situation 350 240 327; 68% 220 216; 45% 216; 45% 101; 21% 40 35; 7% 32; 7% 12; 2% 12; 2% 8; 2% 3; 1% 2; 0% 2; 0% 1; 0% 1; 0% 0 0 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 2018 2009 Figure 2. The synthetic measure of the financial situation of rural communes in eastern Poland in 2009 and 2018. Source: Figure 2. The synthetic measure of the ﬁnancial situation of rural communes in eastern Poland in 2009 and 2018. Source: own research. own research. The statistical characteristics of the synthetic measure of the financial situation, as Table 4. Statistical characteristics of the synthetic measure of the ﬁnancial situation of rural communes in eastern Poland in well as the income from local taxes of rural communes in eastern Poland in 2018 compared 2009 and 2018. to 2009, do not indicate the stability of this phenomenon in the analyzed area. Financial Investment The analysis of the dispersion of the measure of economic security in rural communes q Financial State Financial q Development Independence Attractiveness in eastern Poland in 2009 and 2018 shows a slight increase in differentiation. This is Situation Interference Index Indicator Index indicated by the range of 0.31–0.35 for development and 0.30–0.37 for the financial 2009 2018 2009 2018 2009 2018 2009 2018 2009 2018 situation; the quarterly range of 0.07–0.08 for development and 0.04–0.04 for the financial situation; and the standard deviation of 0.05–0.06 for development and 0.04–0.04 for the Min 0.15 0.16 0.09 0.14 0.09 0.11 0.00 0.01 0.18 0.20 Max 0.46 financial 0.51 situation. 0.39 The st0.51 ability of0.81 the phen 0.70 omenon0.71 is indicate 0.48d by the co 0.88 efficient 0.85 of Mean 0.25 0.29 0.17 0.19 0.27 0.28 0.20 0.21 0.70 0.65 variation of 0.20–0.20 for development and 0.22–0.20 for the financial situation; and the Median 0.24 0.28 0.16 0.19 0.24 0.26 0.19 0.20 0.73 0.66 quarter deviation of 0.04–0.04 for development and 0.02–0.02 for the financial situation. Standard deviation 0.05 0.06 0.04 0.04 0.11 0.10 0.11 0.09 0.11 0.10 Additionally, it should be noted that almost all variables (except for transfer income/total Quarter deviation 0.04 0.04 0.02 0.02 0.06 0.05 0.07 0.07 0.07 0.06 income—the state’s financial interference rate) show a positive asymmetry, which is not a Coefﬁcient of variation 0.20 0.20 0.22 0.20 0.40 0.34 0.54 0.45 0.16 0.15 favorable situation for stimulants. This means that a larger number of communes have Positional coefﬁcient 0.15 0.15 0.13 0.11 0.25 0.19 0.37 0.33 0.09 0.09 of variation values of these variables that are lower than their average, indicating the weakness of the Range 0.31 0.35 0.30 0.37 0.72 0.59 0.71 0.47 0.70 0.65 analyzed region in the indicated area (see Table 4). Quartile range 0.07 0.08 0.04 0.04 0.12 0.10 0.14 0.13 0.13 0.12 Skewness (asymmetry) 0.80 0.61 1.80 2.63 1.58 1.56 0.85 0.41 1.38 1.06 Table 4. Statistical characteristics of the synthetic measure of the financial situation of rural communes in eastern Poland Kurtosis (measure of in 2009 and 2018. 0.66 0.01 5.81 12.49 3.34 3.12 1.21 0.19 2.36 1.70 concentration) Financial Financial independence indicator = personal income/total income; investment attractiveness index = investment expenditure/total q Financial Investment State Financial expenditure; state ﬁnancial interference index = transfer income/total income. Source: own research. q Development Independence Situation Attractiveness Index Interference Index Indicator Financial independence is an important factor in socio-economic development 2009 2018 2009 2018 2009 2018 2009 2018 2009 2018 (Przybytniowski 2019), especially in rural municipalities. These units are characterized by a lower income potential (lower ﬁnancial independence). As a result, it may constitute a barrier to multifunctional development (Mölders 2014). At the same time, there is a signiﬁcant diversiﬁcation in the socio-economic development of rural communes. Rural number of observations number of observations number of observations number of observations Risks 2021, 9, x FOR PEER REVIEW 13 of 22 Min 0.15 0.16 0.09 0.14 0.09 0.11 0.00 0.01 0.18 0.20 Max 0.46 0.51 0.39 0.51 0.81 0.70 0.71 0.48 0.88 0.85 Mean 0.25 0.29 0.17 0.19 0.27 0.28 0.20 0.21 0.70 0.65 Median 0.24 0.28 0.16 0.19 0.24 0.26 0.19 0.20 0.73 0.66 Standard deviation 0.05 0.06 0.04 0.04 0.11 0.10 0.11 0.09 0.11 0.10 Quarter deviation 0.04 0.04 0.02 0.02 0.06 0.05 0.07 0.07 0.07 0.06 Coefficient of variation 0.20 0.20 0.22 0.20 0.40 0.34 0.54 0.45 0.16 0.15 Positional coefficient of 0.15 0.15 0.13 0.11 0.25 0.19 0.37 0.33 0.09 0.09 variation Range 0.31 0.35 0.30 0.37 0.72 0.59 0.71 0.47 0.70 0.65 Quartile range 0.07 0.08 0.04 0.04 0.12 0.10 0.14 0.13 0.13 0.12 Skewness (asymmetry) 0.80 0.61 1.80 2.63 1.58 1.56 0.85 0.41 −1.38 −1.06 Kurtosis (measure of 0.66 0.01 5.81 12.49 3.34 3.12 1.21 −0.19 2.36 1.70 concentration) Financial independence indicator = personal income/total income; investment attractiveness index = investment expenditure/total expenditure; state financial interference index = transfer income/total income. Source: own research. Financial independence is an important factor in socio-economic development (Przybytniowski 2019), especially in rural municipalities. These units are characterized by a lower income potential (lower financial independence). As a result, it may constitute a barrier to multifunctional development (Mölders 2014). At the same time, there is a significant diversification in the socio-economic development of rural communes. Rural Risks 2021, 9, 145 13 of 22 communes with the highest personal incomes are characterized by a much higher level of development. They determine the degree of financial independence of municipalities, and an increase or decrease in them affects the planning and implementation of investment activities. The impact on the level of financial independence of communes is also communes with the highest personal incomes are characterized by a much higher level of determined by the scope of the rights to freely spend the generated income (Heller and development. They determine the degree of ﬁnancial independence of municipalities, and Fa an rel incr nik 2 ease 013) or. decrease in them affects the planning and implementation of investment ac- tivities. At the sa The impact me time, l on the oca level l governments a of ﬁnancial independence re powered b ofy communes income transf is also erred to them, determined by the scope of the rights to freely spend the generated income (Heller and Farelnik 2013). often for a specific purpose (thus limiting the expenditure independence of local At the same time, local governments are powered by income transferred to them, often government units). The transfer income includes grants and subsidies. These funds are for a speciﬁc purpose (thus limiting the expenditure independence of local government characterized by the fact that they are transferred to a specific unit and constitute its source units). The transfer income includes grants and subsidies. These funds are characterized of income (Oates 2008). They are used to equip local government units with additional by the fact that they are transferred to a speciﬁc unit and constitute its source of income resources and constitute an instrument of state interference in the activities of this unit. (Oates 2008). They are used to equip local government units with additional resources and By employing this transfer income, the state ensures that it has an influence on the constitute an instrument of state interference in the activities of this unit. By employing directions of the implementation of the local financial economy. According to the measure this transfer income, the state ensures that it has an inﬂuence on the directions of the shown in Figure 3, a negative correlation (−0.438, in both analyzed years) was observed Risks 2021, 9, 0 14 of 24 implementation of the local ﬁnancial economy. According to the measure shown in Figure 3, between the measure of development and the financial index of interference in rural a negative correlation (0.438, in both analyzed years) was observed between the measure communes in eastern Poland. of development and the ﬁnancial index of interference in rural communes in eastern Poland. 2018, y = 0.1507 + 0.1501*x; r = 0.2136; p = 0.00000; r2 = 0.0456 2009, y = 0.1129 + 0.2118*x; r = 0.2950; p = 0.0000; r2 = 0.0870 0.55 0.45 0.50 0.40 0.45 0.35 0.40 0.30 0.35 0.25 0.30 0.20 0.25 0.15 0.20 0.10 0.15 Risks 2021, 9, x FOR PEER REVIEW 14 of 22 0.10 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 qi measure of development qi measure of development 2009, y = 0.0376 + 0.9291*x; r = 0.4348; p = 0.0000; r2 = 0.1890 2018, y = 0.0655 + 0.7591*x; r = 0.4365; p = 0.0000; r2 = 0.1905 0.9 0.8 0.8 0.7 0.7 0.6 0.6 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0.0 0.0 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 qi measure of development qi measure of development 2009, y = 0.1403 + 0.2285*x; r = 0.1070; p = 0.0186; r2 = 0.0114 2018, y = 0.15 + 0.1951*x; r = 0.1165; p = 0.0103; r2 = 0.0136 0.5 0.8 0.7 0.4 0.6 0.5 0.3 0.4 0.2 0.3 0.2 0.1 0.1 0.0 0.0 -0.1 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 -0.1 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 qi measure of development qi measure of development 2018, y = 0.8676 - 0.7781*x; r = - 0.4385; p = 0.0000; r2 = 0.1923 2009, y = 0.947 - 1.0095*x; r = - 0.4386; p = 0.0000; r2 = 0.1923 0.9 1.0 Figure 3. Cont. 0.9 0.8 0.8 0.7 0.7 0.6 0.6 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 qi measure of development qi measure of development Figure 3. Dispersion of the synthetic measure of the financial situation of rural communes in eastern Poland in 2009 and Figure 3. Dispersion of the synthetic measure of the ﬁnancial situation of rural communes in eastern Poland in 2009 and 2018. Source: own research. 2018. Source: own research. As shown in Table As shown in Table 5 5,, the the development development measur measure e w was as most c most closely losely corre correlated lated in in the the f ﬁnancial inancial s situation ituation w withith th the ﬁnancial e finanindependence cial independ ratio enceand rati the o an state d th ﬁnancial e state f interfer inanence cial interferen ratio. Personal ce ratio. income Person shows al income the economic shows the activity economi of inhabitants c activity ofand inha the bita state nts a of nd their the state of their possessions. possess They depend ions. They depend on the economic on the econo development mic deve of an lopindividual, ment of an in expanding dividual, expanding the economic base and increasing the income of local governments. A high value of the correlation with the share of transfers may indicate the dependence of a commune on revenues from the state budget. This stiffens the financial economy of the commune, making it relatively insensitive to the influence of other factors. According to Rosner’s (2012) research, there is a close relationship between the processes regarding a population and the level of socio-economic development. The age structure of the population shapes the situation of the labor market and has an impact on local finances and development (Antony et al. 2017; Banwo et al. 2017). Rural communes in eastern Poland are characterized by a low correlation measure (below 0.5) of development with the natural increase in and balance of migration. The number of economic entities proves the level of entrepreneurship in the region, which is confirmed by the correlation measure being above 0.5. There is a clear disproportion between the own income / total income transfer income / total income inv es tm ent expenditure / total ex pens es qi measure of financial situation investment expenditure / total expenses transfer income / total income own income / total income qi measure of financial situation Risks 2021, 9, x FOR PEER REVIEW 13 of 22 Min 0.15 0.16 0.09 0.14 0.09 0.11 0.00 0.01 0.18 0.20 Max 0.46 0.51 0.39 0.51 0.81 0.70 0.71 0.48 0.88 0.85 Mean 0.25 0.29 0.17 0.19 0.27 0.28 0.20 0.21 0.70 0.65 Median 0.24 0.28 0.16 0.19 0.24 0.26 0.19 0.20 0.73 0.66 Standard deviation 0.05 0.06 0.04 0.04 0.11 0.10 0.11 0.09 0.11 0.10 Quarter deviation 0.04 0.04 0.02 0.02 0.06 0.05 0.07 0.07 0.07 0.06 Coefficient of variation 0.20 0.20 0.22 0.20 0.40 0.34 0.54 0.45 0.16 0.15 Positional coefficient of 0.15 0.15 0.13 0.11 0.25 0.19 0.37 0.33 0.09 0.09 variation Range 0.31 0.35 0.30 0.37 0.72 0.59 0.71 0.47 0.70 0.65 Quartile range 0.07 0.08 0.04 0.04 0.12 0.10 0.14 0.13 0.13 0.12 Skewness (asymmetry) 0.80 0.61 1.80 2.63 1.58 1.56 0.85 0.41 −1.38 −1.06 Kurtosis (measure of 0.66 0.01 5.81 12.49 3.34 3.12 1.21 −0.19 2.36 1.70 concentration) Financial independence indicator = personal income/total income; investment attractiveness index = investment expenditure/total expenditure; state financial interference index = transfer income/total income. Source: own research. Financial independence is an important factor in socio-economic development (Przybytniowski 2019), especially in rural municipalities. These units are characterized by a lower income potential (lower financial independence). As a result, it may constitute a barrier to multifunctional development (Mölders 2014). At the same time, there is a significant diversification in the socio-economic development of rural communes. Rural communes with the highest personal incomes are characterized by a much higher level of development. They determine the degree of financial independence of municipalities, and an increase or decrease in them affects the planning and implementation of investment activities. The impact on the level of financial independence of communes is also determined by the scope of the rights to freely spend the generated income (Heller and Farelnik 2013). At the same time, local governments are powered by income transferred to them, often for a specific purpose (thus limiting the expenditure independence of local government units). The transfer income includes grants and subsidies. These funds are characterized by the fact that they are transferred to a specific unit and constitute its source of income (Oates 2008). They are used to equip local government units with additional resources and constitute an instrument of state interference in the activities of this unit. By employing this transfer income, the state ensures that it has an influence on the directions of the implementation of the local financial economy. According to the measure shown in Figure 3, a negative correlation (−0.438, in both analyzed years) was observed Risks 2021, 9, 0 14 of 24 between the measure of development and the financial index of interference in rural communes in eastern Poland. 2018, y = 0.1507 + 0.1501*x; r = 0.2136; p = 0.00000; r2 = 0.0456 2009, y = 0.1129 + 0.2118*x; r = 0.2950; p = 0.0000; r2 = 0.0870 0.55 0.45 0.50 0.40 0.45 0.35 0.40 0.30 0.35 0.25 0.30 0.20 0.25 0.15 0.20 0.10 0.15 Risks 2021, 9, x FOR PEER REVIEW 14 of 22 0.05 0.10 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 qi measure of development qi measure of development 2009, y = 0.0376 + 0.9291*x; r = 0.4348; p = 0.0000; r2 = 0.1890 2018, y = 0.0655 + 0.7591*x; r = 0.4365; p = 0.0000; r2 = 0.1905 0.9 0.8 0.8 0.7 0.7 0.6 0.6 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0.0 0.0 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 qi measure of development qi measure of development 2009, y = 0.1403 + 0.2285*x; r = 0.1070; p = 0.0186; r2 = 0.0114 2018, y = 0.15 + 0.1951*x; r = 0.1165; p = 0.0103; r2 = 0.0136 0.8 0.5 0.7 0.4 0.6 0.5 0.3 0.4 0.2 0.3 0.2 0.1 0.1 0.0 Risks 2021, 9, 145 14 of 22 0.0 -0.1 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 -0.1 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 qi measure of development qi measure of development 2018, y = 0.8676 - 0.7781*x; r = - 0.4385; p = 0.0000; r2 = 0.1923 2009, y = 0.947 - 1.0095*x; r = - 0.4386; p = 0.0000; r2 = 0.1923 0.9 1.0 0.9 0.8 0.8 0.7 0.7 0.6 0.6 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 qi measure of development qi measure of development Figure 3. Figure 3. Di Dispersion spersion ofof the the synthetic measur synthetic measur e of e of the the financial ﬁnancial situation situation of of rural communes rural communes in in ea eastern stern PPoland in oland in 2009 2009 and and Figure 3. Dispersion of the synthetic measure of the ﬁnancial situation of rural communes in eastern Poland in 2009 and 2018. Source: own research. 2018. Source: own research. 2018. Source: own research. As shown in Table 5, the development measure was most closely correlated in the As shown in Table As shown in Table 5 5,, the the development development measur measure e w was as most c most closely losely corre correlated lated in in the the ﬁnancial situation with the ﬁnancial independence ratio and the state ﬁnancial interference f ﬁnancial inancial s situation ituation w withith th the ﬁnancial e finanindependence cial independ ratio enceand rati the o an state d th ﬁnancial e state f interfer inanence cial ratio. Personal income shows the economic activity of inhabitants and the state of their interferen ratio. Personal ce ratio. income Person shows al income the economic shows the activity economi of inhabitants c activity ofand inha the bita state nts a of nd their the possessions. They depend on the economic development of an individual, expanding state of their possessions. possess They depend ions. They depend on the economic on the econo development mic deve of an lopindividual, ment of an in expanding dividual, the economic base and increasing the income of local governments. A high value of the expanding the economic base and increasing the income of local governments. A high correlation with the share of transfers may indicate the dependence of a commune on value of the correlation with the share of transfers may indicate the dependence of a revenues from the state budget. This stiffens the ﬁnancial economy of the commune, commune on revenues from the state budget. This stiffens the financial economy of the making it relatively insensitive to the inﬂuence of other factors. commune, making it relatively insensitive to the influence of other factors. Table 5. Correlation between the ﬁnancial situation and development measures and socio-economic variables in rural According to Rosner’s (2012) research, there is a close relationship between the communes of eastern Poland (co. Pearson; 2009–2018). processes regarding a population and the level of socio-economic development. The age structure of the population shapes the situation of the labor market and has an impact on Speciﬁcation q Development local finances and development (Antony et al. 2017; Banwo et al. 2017). Rural communes Financial independence indicator 0.4077 in eastern Poland are characterized by a low correlation measure (below 0.5) of State ﬁnancial interference index 0.359 development with the natural increase in and balance of migration. The number of Entities entered in the REGON register per 1000 inhabitants 0.580 Units newly registered in the REGON register per 1000 inhabitants 0.5206 economic entities proves the level of entrepreneurship in the region, which is confirmed Natural persons conducting economic activity per 1000 inhabitants 0,5759 by the correlation measure being above 0.5. There is a clear disproportion between the % of the population using the sewage network 0.8514 % of the population using the water supply system 0.3698 % of the population using the gas network 0.4957 Population growth per 1000 inhabitants 0.4354 Migration rate per 1000 inhabitants 0.3948 Wastewater treated during the year treated together 0.7098 % of the population using sewage treatment plants 0.8292 Financial independence indicator = personal income/total income; state ﬁnancial interference index = transfer income/total income. Key: Linear correlation coefﬁcients for observations from sample 1 to 4840; critical value (with a two-sided 5% critical area) = 0.0282 for n = 4840. Source: own research. According to Rosner’s (2012) research, there is a close relationship between the pro- cesses regarding a population and the level of socio-economic development. The age structure of the population shapes the situation of the labor market and has an impact on local ﬁnances and development (Antony et al. 2017; Banwo et al. 2017). Rural communes in eastern Poland are characterized by a low correlation measure (below 0.5) of development with the natural increase in and balance of migration. The number of economic entities proves the level of entrepreneurship in the region, which is conﬁrmed by the correla- tion measure being above 0.5. There is a clear disproportion between the density of the distribution of economic entities in urban centers as compared with rural communes. Pearson’s correlation coefﬁcient between the value of the synthetic measure of devel- opment and the measure of ﬁnancial standing in 2018 was 0.213 (0.295 in 2009), while the ﬁnancial independence index was 0.436 and 0.434 in 2018 and 2009, respectively. A low level of the indicated relation was observed in the case of the investment attractiveness own income / total income transfer income / total income inv es tm ent expenditure / total ex pens es qi measure of financial situation investment expenditure / total expenses transfer income / total income own income / total income qi measure of financial situation Risks 2021, 9, 145 15 of 22 index (0.116; 0.107). Other correlation values are shown in Table 5. This may conﬁrm that the spatial differentiation of the studied area was quite stable, and the units reacted similarly to changes taking place in the economy. In order to assess the impact of the variables of the ﬁnancial situation of rural com- munes in eastern Poland on the differentiation of development measures (taking into account the values of correlation measures between the selected variables), a regression model was estimated (see Table 6). The ﬁt of the model was measured using the indi- cators: coefﬁcient of determination R-squared value: 0.359698; and corrected R-squared value: 0.358106. This means that 35% of the variation in the model was explained by the variability of the independent variables. No collinearity was found in the explanatory variables (non-redundancy was assessed by the correlation coefﬁcient). The coefﬁcient of determination measures how much of the overall variability in the dependent variable is explained by the linear regression. One must therefore be careful in its interpretation, because the ﬁt of the model does not increase with the number of variables. There is an essential impact on the dependent variable. Further increasing the multidimensionality of the model would cause the R2 value to increase slightly (the bigger the better). For the model, this could lead to the inclusion of statistically insigniﬁcant variables. We can add a large number of irrelevant variables and the actual process will show that the model does not correctly describe the modeled phenomenon. The adjusted coefﬁcient of determination did not reach 60%. This may indicate the need to extend the range of variables with socio-economic elements to characterize the economic security in a multidimensional way. The F statistic (12, 4827) of 225.9688 is statistically signiﬁcant (the p-value for the F test was 0.000000), meaning that the construction of the linear model is correct. Table 6. Results of the regression analysis between the ﬁnancial situation (q) and the variables of development of rural communes in eastern Poland. Description Coefﬁcient Standard Error Student’s t Test p-Value Constant 0.382410 0.00639275 59.82 <0.0001 State ﬁnancial interference index 0.128171 0.00704407 18.20 <0.0001 Index of ﬁscal wealth per capita 0.136306 0.0247880 5.499 <0.0001 Agricultural tax 0.214572 0.00791490 27.11 <0.0001 Forest tax 0.203985 0.0263104 7.753 <0.0001 Vehicle tax 0.158478 0.0411964 3.847 0.0001 Investment expenditure 0.0525267 0.00804685 6.528 <0.0001 Expenditures on education and upbringing/number 5 6 2.84325 10 2.83874 10 10.02 <0.0001 of inhabitants 5 6 Apartments per 1000 inhabitants 6.986 <0.0001 5.07479 10 7.26467 10 Expenditures on the municipal economy and 6 6 5.38541 10 2.39585 10 2.248 0.0246 environmental protection/population Public safety and ﬁre protection 5 5 2.53834 10 1.15646 10 2.195 0.0282 expenditure/population Public administration expenditure/number 5 6 7.61551 10 6.97651 10 10.92 <0.0001 of inhabitants 5 6 Expenditure on agriculture and hunting/population 1.93975 10 2.85645 10 6.791 <0.0001 Arithmetic mean of Standard deviation of the dependent 0.266829 0.054140 dependent variable variable Sum of residual squares 9.081804 Residual standard error 0.043376 Coefﬁcient of determination 0.359698 Corrected R-square 0.358106 R-square F (12, 4827) 225.9688 P-value for the F test 0.000000 Logarithm of credibility 8326.059 Akaike Information criterion 16,626.12 Bayesian information 16,541.82 Crit. Hannana–Quinna 16,596.52 criterion Schwarza State ﬁnancial interference index = transfer income/total income; index of ﬁscal wealth per capita = share in taxes constituting state budget revenues/number of inhabitants; observations from sample 1 to 4840 used; dependent variable (Y): TOPSIS development; linear correlation coefﬁcients for observations from sample 1 to 4840; critical value (with a two-sided 5% critical area) = 0.0282 for n = 4840. Source: own research. Risks 2021, 9, 145 16 of 22 5. Discussion The socio-economic diversity of municipalities should be analyzed frequently. Re- search in this area is often focused on the search for and identiﬁcation of factors shaping the development process (analyses covering one area, e.g., ﬁnance, the economy, infras- tructure, human capital). The analyses carried out also concern a synthetic measure, e.g., of development or ﬁnancial situation. Spatial differentiation in the level of development results in different conditions for running a business and a different quality of life and living conditions for inhabitants (Capello 2014). Socio-economic development is associated with the economic, demographic, and natural aspects as well as with the geographical location (Saviotti et al. 2020). The develop- mental potential of communes is built by ﬁnancial resources, the professional activities of inhabitants, the local labor market, entrepreneurship, infrastructure, and the condition of the natural environment (Vermeulen and Pyka 2018). Financial resources are the basis for an individual’s activities. They are a prerequisite for the successful implementation of local tasks (related to the needs of residents). Endogenous resources are becoming more and more important in the development of communes. The progressive decentralization of power, competence, and management makes it possible to speak about the growing importance of local, material, and intangible resources. The endogenous potential of a region, which results from a combination of local conditions, determines its possibilities and directions of development (Churski and Kołsut 2017). As in- dicated by Milczarek (2005), it is the sum of, among other things, geographic, demographic, economic, and social elements. Kiniorska (2014) distinguishes three types: demographic, economic, and infrastructural elements. The analyses conducted by Churski et al. (2013), Stanny and Strzelczyk (2015), and Dziekan ´ ski and Prus (2020) show that an important en- dogenous element influencing development opportunities is financial potential. The ﬁnancial potential of communes is conditioned by many factors, including legal and spatial conditions, the level of urbanization of the area, and the potential demographic and economic conditions of a given local government unit. Most rural communes that still exist perform a function typical of rural areas—agriculture (forestry), which translates into a low level of ﬁnancial potential. Under the conditions of European integration, however, the functions performed by rural communes have changed from typically agricultural to residential, service, tourist, and recreational, which strengthens the role of units in a dynamically changing environment and determines the level and structure of income (Rosner and Stanny 2016). Filipiak (2009) also points to the importance of the spatial development of an area as a factor inﬂuencing the ﬁnancial condition of municipalities through creating favorable conditions for the development of economic activity and thus encouraging settlement and increasing the potential of human capital. Local authorities should take care of the condition of the infrastructure. This may increase the attractiveness of the area and attract new entrepreneurs or improve the quality of life of the inhabitants. Infrastructure contributes to the economic activation of the region. Knowledge of the social potential, the labor market, and changes in it is of importance to the determinants of a development policy. Human capital is one of the key elements of development (Quaranta et al. 2016; Jutengren et al. 2020). The quality of the natural environment is an important element that enables the proper functioning of economic processes. For economic reasons, it constitutes one of the sources of raw materials and energy and provides geographical space, a place for economic activity, and a place to live or rest. The ﬁnancial situation of communes determines the possibilities for the fulﬁllment of ﬁnancial obligations, ensuring continuity in the provision of services. Finance allows for a multi-element assessment of the commune’s activities, its development possibilities, and the implementation of public tasks. According to Stanny and Strzelczyk (2018), the ﬁnancial situation is an assessment of the commune’s ﬁnances, i.e., the possibilities to ensure ﬁnancial security. This security includes the ability to perform tasks and reliability in terms of the ability to pay off liabilities. Risks 2021, 9, 145 17 of 22 Hendrick (2004) relates the ﬁnancial situation to the ability to raise a sufﬁcient amount of funds, deliver public services, and manage debt. Financial standing relates to the overall level of economic development (Przybytniowski 2016; Drozdowski 2017; Dobrowolski 2020b). It indicates a commune’s ability to meet its own administrative and investment needs, which means maintaining and developing its own assets in line with the current and future demand for public services (Aleksandrova-Zlatanska 2019). The ﬁnancial situation, according to Cabaleiro et al. (2013), is a complex phenomenon and is inﬂuenced by many factors. Knowledge of the state of ﬁnances allows local authorities to make comparisons with other entities and helps them make ﬁnancial decisions. Standar (2019) analyzed the relationship between the location of communes in rural areas in relation to cities with county status and the ﬁnancial results achieved by them. As a result of the research, it was proved that the smaller the distance from an urban center, the greater the ﬁnancial independence, ﬁnancial liquidity, and investment execution becomes, albeit at a higher level of debt. Dziekanski ´ and Wyszkowski (2018), in their research on the diversiﬁcation of the ﬁnancial situation of communes in rural areas of the Swietokrzyskie ˛ province, used a synthetic measure based on a deliberately selected set of diagnostic variables. The synthetic measure conﬁrmed the diversiﬁcation of the ﬁnancial situation of the analyzed rural communes. Data analysis showed that the ﬁnancial situation was inﬂuenced by the level of income from taxes and local fees as well as income from participation in PITs and CITs. The low share of personal income in the total income of the Swietokrzyskie ˛ communes proves their low income independence. Dziekanski ´ (2014) undertook the construction of a synthetic measure allowing for the measurement of a multidimensional phenomenon and the linear ordering of the studied units. In this way, the author assessed the level of local development by assessing the ﬁnancial situation, infrastructure, and natural environment of rural communes in the Swietokrzyskie ˛ province. Dziekanski ´ and Prus (2020) indicate in their research the growing role and importance of communes in the local economy. The analysis showed that rural communes of eastern Poland are characterized by signiﬁcant disproportions in their ﬁnancial situation. Rural communes that are in the best ﬁnancial situation are characterized by a higher share of personal income in total income and a higher level of income from premises and the taxes obtained from the share in the tax on natural and legal persons. The analyses carried out by Głowicka-Wołoszyn and Wysocki (2016) showed that there are signiﬁcant differences in the level and structure of municipalities’ income. Rural communes of good ﬁnancial standing were characterized by a higher share of personal income in total income, a higher level of income from taxes on real estate, and income obtained from participation in the tax on natural persons. The revenues of communes with the best ﬁnancial situation played the greatest role in supplying their budgets, ensuring the independence of local self-governments in decision-making on spending directions. Stanny and Strzelczyk (2018) presented a number of empirical indicators (covering ﬁscal solvency, liabilities, dependence on transfers from the state budget, and the degree of ﬁnancing of public services) used in the assessment of the ﬁnancial situation. It was proved that communes characterized by a relatively good ﬁnancial situation were mainly concentrated in suburban zones of large province centers (on the center-periphery line). It was also indicated that the level of socio-economic development and the ﬁnancial condition are interdependent. Wang et al. (2017) indicate that the socio-economic environment is a factor that should be taken into account when analyzing the ﬁnancial situation. Berne and Schramm (1986) include among the main determinants of the ﬁnancial situation the needs of the local community, the directions of the distribution of local public goods and services, and the society’s afﬂuence. Ladd (1992) emphasizes the impact of demographic conditions on the condition of local government ﬁnances. Rodríguez Bolívar et al. (2016) identiﬁed the main factors shaping the ﬁnancial situation, including the state of and changes in the size of the Risks 2021, 9, 145 18 of 22 population, the local labor market conditions, increases in local government spending, and public ﬁnance management. 6. Conclusions The activities of municipalities are a multidimensional process implemented in a set of elements, including demographic, economic, ﬁnancial, and environmental elements, and the links between these elements. Each spatial decision and each process for formulating conditions and directions of development is based on speciﬁc premises and information. Having information is a fundamental condition for making correct spatial decisions (in- cluding risk minimization). An evaluation of a commune’s activities, due to the variety of undertakings, may be performed with the use of a synthetic measure. It should also provide local authorities with information on the use of public resources or the possibility of making operational or investment decisions. The distribution of the evaluation of the development and ﬁnancial situation of rural communes in eastern Poland was spatially polarized. The results show that the development of the surveyed communes is related to a better ﬁnancial situation. Local authorities should ﬁrst of all take care to improve the economic potential, which would increase the attractiveness of the area and attract new entrepreneurs. The synthetic measure of development (qi) ranged from 0.15 to 0.46 in 2009, while in 2018 it ranged from 0.16 to 0.51. The ﬁnancial standing measure ranged from 0.09 to 0.39 in 2009 and from 0.14 to 0.51 in 2018. Taking into account the increase in the range of the measure, these results indicate an increase in the differentiation of units in terms of development from 0.31 to 0.35 and in terms of the ﬁnancial situation measure from 0.30 to 0.37. The correlation coefﬁcient between the values of the synthetic measure indicates the stability of spatial differentiation in terms of development. A similar situation can be seen in the reaction of communes to changes in the economy. Pearson’s correlation coefﬁcient between the value of the synthetic measure of development and the measure of ﬁnancial standing in 2018 was 0.213 (0.295 in 2009), and the ﬁnancial independence index was 0436 and 0.434 in 2018 and 2009, respectively. A low level of the indicated relation was observed in the case of the investment attractiveness index: 0.116 and 0.107, respectively. Between the measure of development and the rate of state ﬁnancial interference, a negative correlation coefﬁcient (0.438) was observed in both 2009 and 2018. The surveyed communes are characterized by a low measure of the correlation be- tween development and the natural increase in the population, and a migration balance of less than 0.5. On the other hand, the number of economic entities proves the appropriate level of entrepreneurship in the region (over 0.5). It seems that the main reason for the relatively low impact of ﬁnancial conditions on the development of rural communes in eastern Poland is their strong dependence on income transferred from the state budget. This stiffens and at the same time stabilizes the ﬁnancial economy, making it relatively insensitive to the inﬂuence of other factors. Low independence may be a signiﬁcant barrier to future local development. The results of this study allow local governments to compare their development with the situation of neighboring communes. Conclusions drawn on this basis may allow local authorities to deﬁne potential directions for the optimization of the development process. The obtained results conﬁrm the usefulness of synthetic measures for the assessment of the endogenous potential of the examined communes. They can be an important source of information for local government authorities on disproportions between units, and their effect may be the use of these analyses as a source of knowledge for more effective management of local government units. One should look for regularities explaining the spatial differentiation of the development of communes, as well as their structures and local conditions. At the same time, the obtained results indicate the directions of future research, which include, among other things, comparison of the results of the linear ordering based on a larger number of empirical data sets, comparison of the results of the linear ordering based on the simulation of data sets with speciﬁc statistical distributions, conducting a Risks 2021, 9, 145 19 of 22 dynamic analysis in a speciﬁed period of time in order to learn about the trend of changes, and comparing the results of rankings based on other methods of linear ordering. A commune’s self-government is the subject of economic development. Its course is inﬂuenced by many factors (including infrastructural, economic, demographic, and ﬁnancial factors) both dependent on and independent of the commune itself. Between development and endogenous resources there is a feedback loop (Hall 2015). An inﬂux of new residents, investors, and enterprises will occur where an area is economically developed. This entails further budget revenues in the form of, e.g., a real estate tax, shares in personal taxes (PIT), and legal revenue (CIT), which enable the undertaking of further pro-development projects (Standar 2017). Parysek (1997) points out that certain factors are common, while others may be present and interact only in certain places and at certain moments in time. Development is related directly to meeting the growing needs of society. In a diversiﬁed economic structure, individuals create a speciﬁc development climate in which the conditions for taking up business are created by new entities and the conditions for cooperation with others shape these entities. The issue of the development of rural communes in eastern Poland is very speciﬁc, and the villages have undergone a process of intense transformation since Poland’s accession to the EU. The research results (for 2008–2019) show that inequality has stabilized the development and ﬁnancial situation in the rural areas of the surveyed provinces. In the presented studies, particular attention was paid to the relationship between the ﬁnancial situation and socio-economic diagnostic variables of the development process in 484 rural communes in eastern Poland (in the research carried out so far, they most often included single communes of provinces in eastern Poland; i.e., communes of a speciﬁc county). This approach allows us to assess in a wider area the inﬂuence of ﬁnancial variables on the development process. The wider range of ﬁnancial variables (X1–X15, Table 1) indicate that the main reason for the relatively low impact of these conditions on ﬁnancial resources for the development of rural communes in eastern Poland is their strong dependence on income transferred from the state budget. This stiffens and at the same time stabilizes the ﬁnancial economy, making it relatively insensitive to the inﬂuence of other factors. Low ﬁnancial independence may be a signiﬁcant barrier to future local development. The important development problem of rural communes is to recognize the worsening demographic situation, which is shaping the ﬁnancial situation in a negative way. Author Contributions: Conceptualization, A.P., P.D. and J.W.P.; methodology, A.P. and P.D.; software, A.P., P.D. and J.W.P.; validation, A.P., P.D. and J.W.P.; formal analysis, A.P. and P.D.; investigation, A.P., P.D. and J.W.P.; resources, A.P., P.D. and J.W.P.; data curation, A.P., P.D. and J.W.P.; writing— original draft preparation, A.P., P.D. and J.W.P.; writing—review and editing, A.P., P.D. and J.W.P.; visualization, A.P., P.D. and J.W.P.; supervision, A.P., P.D. and J.W.P.; project administration, A.P., P.D. and J.W.P.; funding acquisition, A.P., P.D. and J.W.P. 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Abstract

risks Article Inﬂuence of Financial Variables on the Development of Rural Communes of Eastern Poland in 2009–2018 1 1 , 2 Andrzej Pawlik , Paweł Dziekanski ´ * and Jarosław W. Przybytniowski Department of Economics and Finance, Jan Kochanowski University in Kielce, Uniwersytecka 15 str., 25-406 Kielce, Poland; andrzej.pawlik@ujk.edu.pl Department of Management, Jan Kochanowski University in Kielce, Uniwersytecka 15 str., 25-406 Kielce, Poland; jaroslaw.przybytniowski@ujk.edu.pl * Correspondence: pawel.dziekanski@ujk.edu.pl Abstract: Communes are a place of both economic activity and creation development. They have autonomy in making decisions in the ﬁelds of ﬁnancial, human, and material resources. This research was carried out with the use of a synthetic measure. The aim was to show the impact of ﬁnancial variables on the development process of rural communes in eastern Poland. The data were collected in spatial terms for 484 rural communes from the region of eastern Poland. The choice of variables was conditioned by the availability of GUS data for the period 2009–2018. The distribution of the evaluation of the development and ﬁnancial situation of rural communes in eastern Poland was spatially polarized. The reason for the low impact of ﬁnancial conditions on the development of rural communes in eastern Poland is their dependence on income transferred from the state budget. This stiffens and at the same time stabilizes the ﬁnancial economy, making it relatively insensitive to the inﬂuence of other factors. Low independence can be a signiﬁcant barrier to future local development. Finance and the economy are intertwined. Actions taken with respect to these must be based on Citation: Pawlik, Andrzej, Paweł analyses that facilitate making the right decisions. Dziekan ´ ski, and Jarosław W. Przybytniowski. 2021. Influence of Keywords: synthetic measure; rural municipalities; competitiveness; ﬁnancial security; TOPSIS Financial Variables on the Development of Rural Communes of method; public sector Eastern Poland in 2009–2018. Risks 9: 145. https://doi.org/10.3390/ risks9080145 1. Introduction Academic Editor: Tomas Kliestik Municipalities operate in an increasingly complex environment. They are a place of concentration of economic and social activities and a creator of development. They are Received: 4 June 2021 characterized by autonomy in making decisions in terms of ﬁnancial, human, material, and Accepted: 6 August 2021 information resources. The amount and structure of ﬁnancial resources at the disposal of Published: 12 August 2021 municipalities are of particular importance as they affect the economic situation of local governments (Travers 2012). Finance, apart from infrastructure, environmental elements, Publisher’s Note: MDPI stays neutral and social elements, determines the activities of communes. The indicated areas are a set of with regard to jurisdictional claims in inter-related factors that create a multidimensional space. They should be viewed as a set published maps and institutional afﬁl- of interdependent elements. They occur at the same time and within the spatial horizon. iations. The market mode of operation of municipalities manifests itself in the search for new management opportunities aimed at increasing the ability to achieve the assumed goals. Municipalities are at the same time an employer, a principal, a client, and an investor. They shape their individual potential in terms of economic, cultural, and social function- Copyright: © 2021 by the authors. ing. Local resources of units, including the natural, economic, social, and infrastructural Licensee MDPI, Basel, Switzerland. environments used in economic and social relations, are interdependent and occur si- This article is an open access article multaneously. There is a correlation between the functioning of municipalities and the distributed under the terms and quality of life and living conditions of the inhabitants or the activities of enterprises. The conditions of the Creative Commons risk of making negative decisions in this regard should be minimized through analyses Attribution (CC BY) license (https:// that should be multidimensional and support the decision-making process. Communes creativecommons.org/licenses/by/ should be increasingly interested in obtaining and processing information. Information 4.0/). Risks 2021, 9, 145. https://doi.org/10.3390/risks9080145 https://www.mdpi.com/journal/risks Risks 2021, 9, 145 2 of 22 on the condition of communes, resources, and their use is necessary for both diagnostic and strategic operations. These problems require rational choices and optimal decisions from the point of view of the functioning of the individual. In order for decisions to be rational, they cannot be accidental and made intuitively. They should be based on reliable and properly processed information (Drozdowski 2021; Dobrowolski 2020a). The commune’s self-government can shape the development process by using local resources. Its shape is inﬂuenced by many factors, both dependent on and independent of the commune itself (Hall 2015). One of the essential elements of development is the ﬁnancial situation of communes. There is a correlation between development and the ﬁnancial situation. A high level of development of the local economy attracts an inﬂux of new residents and investors. The indicated process further inﬂuences changes in the budgets of communes in the form of, inter alia, increases in the amount of real estate tax, shares in personal taxes (PIT), and corporate income tax (CIT). The income obtained in this way makes it possible to undertake further pro-development projects (Standar 2017). The role of municipalities in the development process requires changes in the local ﬁnancial system and support for endogenous growth potentials. The aim of this article is to evaluate the impact of ﬁnancial variables on the development process of rural communes using a synthetic measure. The Technique of Order Preference by Similarity to the Ideal Solution (TOPSIS) method was used to build the synthetic measure. Empirical data were collected for 484 rural communes in the eastern Poland region. The choice of variables was conditioned by the availability of data in the Local Data Bank of the Central Statistical Ofﬁce for 2009 and 2018. Answers to the following research questions will bring the authors closer to the achievement of the main goal set. The research questions were as follows. Does devel- opment depend on ﬁnancial variables? What is the spatial distribution of development and the ﬁnancial situation? Do transfers from the state budget inﬂuence the development process? It should also be indicated that the weaker the mutual inﬂuence of the ﬁnancial situation and development, the higher the level of transfers from the state budget and current expenditure. A higher level of development means a better ﬁnancial situation and a more attractive commune. The spatial polarization of these phenomena requires considering diagnostic variables in various dimensions and at various levels of detail. 2. Literature Review Actions taken in respect of development should focus on achieving social, economic, and spatial cohesion. It is also important to indicate the development proﬁle of a com- mune, which should become a signiﬁcant asset in the development process. As a rule, rural communes are assigned an agricultural character. Nowadays, these communes are transforming into residential, service, tourist, and recreational facilities, which strengthens the role of individuals in a dynamically changing environment (Standar 2019). The subject of the activities of municipalities is public administration, which is per- formed in a speciﬁc area and by law deﬁned in the scope of tasks aimed at satisfying the needs of residents. It implements these tasks on its own behalf and at its own risk. Factors differentiating the way that particular tasks are performed are their endogenous potential, the ﬁnancial capacity of the commune, and the actual needs of residents and business entities. Commune self-governments carry out various types of tasks related to the current residents’ needs, such as access to healthcare services and education, but they should also create favorable conditions for the development of entrepreneurship and increase the region’s competitiveness. The proper and effective functioning of communes should ensure appropriate ﬁnancial resources, allowing for the implementation of both current and investment projects. Finance is a factor that allows us to evaluate the studied area and make decisions on both current and investment projects that provide the opportunity to create socio-economic development, allow us to increase the innovativeness of communes, and change the current condition of the infrastructure (Głowicka-Wołoszyn et al. 2017). Risks 2021, 9, 145 3 of 22 A commune is an organization operating under changing and unpredictable condi- tions related to its surroundings. The effective performance of tasks requires the provision of funds for their implementation. These funds may be the commune’s own income, general subsidies, or targeted subsidies from the state budget (Ziółkowski 2015). The socio- economic development of communes is inseparably connected to the use of endogenous resources (supported by exogenous resources) in the context of creating new utility func- tions for the inhabitants (Radwan and Paluch 2008). Development is a historic, long-term process of internal, economic, and social transformation. A commune is forced to constantly adapt to changing environmental conditions and look for a competitive advantage in the development process in all aspects of its activity (Rynca ´ 2009). Development is a multidimensional process of qualitative and quantitative (economic, social, and political) changes taking place in the local socio-territorial system. The individ- ual endogenous potential is the (human, innovative, ecological, infrastructural, ﬁnancial, and institutional) capital that has accumulated in a given area that determines the strength of local changes. The potential of communes results from a combination of local condi- tions. It determines the possibilities for and directions of development. Development is a complex concept that includes many changes taking place at a speciﬁc time. Like any speciﬁc process, a socio-economic space is conditioned by a number of factors that may affect this area to varying degrees and with varying degrees of force. The conditions and factors shaping local development are varied and fully dependent on the economic and social processes taking place in a given commune. In addition to processes, changes that cover only certain areas are also of great importance and have an impact on the economy on a global scale. Many authors dealing with theoretical concepts of regional or local development cite various concepts explaining this process. The most popular are: eco- nomic base theory; new trade theory; growth poles theory and the concept of geographical growth centers; the theory of cumulative causality; and the core and peripheries model (Grosse 2004; Malecki 1997). The socio-economic development of communes is inseparably connected to the ex- ploitation of endogenous resources (supported by exogenous resources) in the context of creating new utility functions for residents (Radwan and Paluch 2008). There are areas of both stagnation and even developmental depression, as well as more dynamized develop- mental processes that are shaped by a number of factors (Standar and Kozera 2019). These factors can be grouped into economic, social, spatial, ecological, political, technical, and local factors. On the other hand, new factors of economic growth include, inter alia, inno- vation, achievements in science and technology, modern management styles, cooperation networks, and social capital (Šlander and Ogorevc 2019). Under the conditions of dynamic changes in the external environment, on the local authority there is a special responsibility for the ﬁnancial situation. Assessment of the ﬁ- nancial situation with the use of appropriate tools (including a synthetic measure) provides information on the current situation, allows us to identify differences with respect to other units, and allows us to identify development opportunities (Dylewski 2011). As indicated by Stanny and Strzelczyk (2015), the ﬁnancial situation (as a multidi- mensional phenomenon) represents the possibility to provide public services at least at the current level and to obtain funds from repayable and non-returnable sources for the implementation of future tasks. It is a relative assessment of a commune’s ﬁnances that can ensure its ﬁnancial security. Douglas and Gaddie (2002) indicate that the ﬁnancial situation includes the ability to perform tasks and ensure reliability in terms of the abil- ity to pay off both present and future liabilities. The ﬁnancial situation, as indicated by Perry and Christensen (2015), is the certainty of repayment of liabilities towards, among other things, customers and employees of the authorities. Groves and Valente (1994) deﬁne a ﬁnancial situation as the state of ﬁnances that allows the commune to cover all costs of business in the long term and services at a level ensuring the safety and well-being of the local community. Risks 2021, 9, 145 4 of 22 Assessment of the ﬁnancial situation of municipalities allows us to determine the efﬁciency of a municipality’s functioning, its ability to meet obligations, and the possi- bility of raising the standard of quality of the services it provides to local communities (Głowicka-Wołoszyn and Wysocki 2016). So, it is directly related to access to sources of ﬁnancial supply and depends to a large extent on the possession by municipalities of stable and adequate sources of income (Stanny and Strzelczyk 2018). The ﬁnancial situation of communes is demonstrated by their ability to perform tasks, achieve a budget balance, and increase wealth. It is undoubtedly a complex phenomenon created by the level of income, ﬁnancial independence, amount of capital expenditure, abil- ity to obtain extra-budgetary funds, and ﬁnancial results. There is a feedback loop between the ﬁnancial condition of the commune and the level of development (Sobczyk 2010). 3. Materials and Methods One of the solutions for researching multifaceted phenomena with the use of aggre- gated values of diagnostic features is the use of a synthetic measure. It allows for the numerical description of complex phenomena. This enables a multidimensional view of the level of this phenomenon in individual examined objects and allows us to con- duct comparative analyses in spatial and time terms, linear ordering, and classiﬁcation (Lenormand and Deffuant 2013; Dziekanski ´ 2016). However, caution should be exercised when interpreting obtained results because these measures have certain limitations, e.g., they lead to simpliﬁed arrangements and do not take into account qualitative and non- measurable aspects of local or regional development (Strahl 2006). 3.1. Selection of Variables Describing the Studied Phenomenon. Determining the Direction of Variable Preferences in Relation to the Analyzed Phenomenon (Indication of a Stimulant and Destimulant) The development process, ﬁnancial situation, and demographic potential are shaped at the same time by, inter alia, economic, environmental, infrastructural, and social factors (Fang et al. 2018). They determine the multi-element space of functioning of communes. They often appear and work together at the same time for the beneﬁt of the local community. Therefore, they are interdependent and should be considered jointly (Ngo Dang et al. 2018; Tang and Wang 2018). The selection of variables for the study was conditioned by the availability at the commune level of data within the BDL CSO. Some data were incomplete and did not cover all communes. Therefore, in this study, the authors focused on the selected variables described in Table 1. The activities of municipalities are operational, tactical, and strategic. They are carried out in a multidimensional space of functioning. They refer to endogenous and exogenous re- sources, the use of which ensures qualitative and quantitative changes in the local economy. The socio-economic space of communes is a multi-element system, which includes, inter alia, local community, enterprises, ﬁnancial resources, natural resources, infrastructure, labor, and capital. It should be noted that the analyzed diagnostic variables (Table 1) can be associated with the three dimensions of cohesion described in the EU objective of public authorities’ actions under the implementation of regional policy: X16–X20 and X30–X31 for economic cohesion, X27–X29 for social cohesion, and X32–X40 for territorial cohesion. Communes have different income and expenditure capacities. Differences arise be- tween them in the amount of their income and actual expenses for public tasks. The level and structure of communes’ incomes and expenses are shaped by their ﬁnancial situation (variables X1–X15), which determines the timely fulﬁllment of obligations and the quality and continuity of services. Entrepreneurship (variables X16–X20) and its potential shape the quality of life of the inhabitants and the social and material security of the residents. The number of economic entities shapes the number of employed and unemployed inhabitants as well as the economic situation of the region. Risks 2021, 9, 145 5 of 22 Table 1. List of variables describing the ﬁnancial situation and economic and social development of communes. Variables Unit S/D X1 Operating surplus/total revenues (budget solvency ratio) % S X2 Personal income/total income (ﬁnancial independence indicator) % S Share in taxes constituting state budget revenues */number of inhabitants (index of ﬁscal wealth X3 PLN S per capita) X4 Income from local taxes/population (ﬁscal wealth indicator) PLN S X5 Local tax revenue/current income (tax autonomy indicator) % S X6 Investment expenditure/total expenditure (investment attractiveness index) % S X7 Transfer income/total income (state ﬁnancial interference index) % D X8 Expenditures on education and upbringing/number of inhabitants PLN S X9 Expenditures on housing/population PLN S X10 Healthcare expenditure/population PLN S X11 Expenditure on the municipal economy and environmental protection/population PLN S X12 Public safety and ﬁre protection expenditure/population PLN S X13 Public administration expenditure/number of inhabitants PLN D X14 Expenditure on agriculture and hunting/population PLN S X15 Interest/personal income (debt service ratio) % D X16 Entities entered in the REGON register per 1000 inhabitants pcs. S X17 Units newly registered in the REGON register per 1000 inhabitants pcs. S X18 Units removed from the REGON register per 1000 inhabitants pcs. D X19 Natural persons conducting economic activity per 1000 inhabitants pcs. S X20 Foundations, associations, and social organizations per 1000 inhabitants pcs. S X21 Population per 1 library (person) person S X22 Population for a public pharmacy person S X23 % of the population using the sewage network % S X24 % of the population using the water supply system % S X25 % of the population using the gas network % X26 Apartments per 1000 inhabitants pcs. S X27 Demographic dependency ratio for the elderly person D X28 Population growth per 1000 inhabitants person S X29 Migration rate per 1000 inhabitants person S X30 Unemployed persons registered in communes per 1000 inhabitants person D X31 Employed persons per 1000 inhabitants person S X32 Total forest area ha/person S X33 Area of farms in the total area % S X34 Areas legally protected in the total area % S X35 Total water consumption in households (water from water supply systems per capita) m /person D X36 Mixed waste collected during the year in the total per capita kg/person D X37 Wastewater treated during the year treated together dam S X38 Emissions of dust pollution t/r D X39 Emissions of gaseous pollutants t/r D X40 % Of the population using sewage treatment plants % S S, stimulant; D, destimulant; operating surplus = total income property income current expenditure; REGON, Register of the National Economy; National Journal of the National Economy Register, a register kept by the President of the Central Statistical Ofﬁce. The term REGON is also understood as the REGON identiﬁcation number, i.e., the nine-digit identiﬁer assigned to the entity in this register. * Communes have a share in the personal income tax (PIT) and corporate tax (CIT); Source: own research based on data from the Central Statistical Ofﬁce of Poland, Stanny and Strzelczyk (2018), Dziekanski ´ and Prus (2020), and Pawlik and Dziekanski ´ (2020), Barthelemy and Toint (2013), Dziekanski ´ and Pawlik (2019). The condition of infrastructure (X21–X26) determines the attractiveness of municipali- ties, attracts new companies, and shapes the quality of life of residents and the quality of business activities. Infrastructure shapes the economic activity of communes as well as the openness of the region and its development. Demographic potential (X27–X31) is important for the identiﬁcation of development policy determinants. According to Rosner ’s research, there is a close relationship between population processes (population number, age and occupational structure, birth rate, balance of migration, and population density) and the level of socio-economic development. The age structure of the population shapes the situation in the labor market, and this indirectly affects the local infrastructural and ﬁnancial potential. In a positive way, it Risks 2021, 9, 145 6 of 22 should be used to assess the decrease in the number of unemployed persons in all groups and the increase in the number of employed persons, business entities, and natural persons. The natural environment (X32–X40), as a component of the wealth of communes, is an important factor shaping the quality of life of the inhabitants of municipalities. It is a source of raw materials and energy and a geographic space for economic activity, leisure, and places of residence. Some variables were dropped because their higher values did not necessarily indicate the level of socio-economic development. In the case of variables such as, for example, water consumption per capita or population per library facility, due to the lack of an unambiguous reference to the studied phenomenon, the phenomenon was abandoned. Among other variables shaping the operation of communes, one can indicate road networks, the availability and diversity of the service base, educational and cultural institutions, farmland, legally protected areas, and gas pollution. In the case of these variables, there is no information at the level of communes within the BDL CSO. In order to ensure the representativeness of the variables, the ﬁnal set was supple- mented with variables that are more discriminatory in a given category and are not very strongly correlated with others in this category. Two features that strongly correlate with each other are carriers of similar information, so one of them is redundant (Eini et al. 2015). The description of the selected set may be presented in the form of an observation matrix X in the form: ij 2 3 x x . . . x 11 12 1m 6 7 x x . . . x 21 22 2m 6 7 X = , (1) ij 4 5 . . . . . . . . . . . . x x . . . x nm n1 n2 where X denotes the value of the j-th feature for the i-th object, i denotes the object number ij (i = 1, 2, . . . , n), and j denotes the variable number (j = 1, 2, . . . , m). After selecting the variables, the nature of each variable was examined, i.e., it was determined whether the variable was a stimulant or destimulant. Most of the variables were obvious, resulting from the substantive experience of the researchers and the analysis of the literature. In doubtful cases, we used the procedure by Grabinski ´ (1985), which uses the fact that stimulants should be positively correlated with each other, similarly to destimulants, and negatively correlated with destimulants. The value of the coefﬁcient of variation of the variables used in terms of ﬁnancial potential ranged from about 0.15 to 2.05. The greatest differentiation was noted in the variables X10 and X9; the smallest difference occurred in the cases of X7 and X8 (see Table 2). The analysis of the data in Table 2 shows that almost all variables are characterized by positive asymmetry. The variable X7 presents negative asymmetry, which in the case of a stimulant is not a favorable situation as it means that a greater number of communes have values of these variables that are lower than their average value. Table 2. Statistical characteristics of the diagnostic variables for the ﬁnancial potential of rural communes in eastern Poland (in 2018). Variable Range Mean Deviation Variability Asymmetry X1 0.31 0.08 0.04 0.48 0.75 X2 0.59 0.28 0.10 0.34 1.55 X3 0.42 0.09 0.05 0.54 2.62 X4 2.11 0.10 0.14 1.36 8.14 X5 0.62 0.11 0.06 0.56 2.89 X6 0.47 0.21 0.09 0.45 0.42 X7 0.64 0.64 0.10 0.15 1.05 X8 3301.95 1368.67 304.66 0.22 2.53 X9 933.04 65.77 108.86 1.66 4.04 X10 569.52 16.80 34.44 2.05 10.49 X11 3712.70 431.05 391.39 0.91 2.95 Risks 2021, 9, 145 7 of 22 Table 2. Cont. Variable Range Mean Deviation Variability Asymmetry X12 684.28 60.87 51.40 0.84 5.27 X13 961.19 481.96 145.77 0.30 1.78 X14 2611.15 251.89 292.99 1.16 3.10 X15 0.09 0.02 0.02 0.79 1.16 Source: own research based on data from the Local Data Bank. Dziekanski ´ and Prus (2020). 3.2. Standardization of Variables According to the Zero Unitarization Method The reliability of the ﬁnal results depends on the quality of the set of variables. The selected variables should be, among other things, unambiguous, strictly deﬁned, and accurate with high information content and low internal correlation (Fischer 2004). The replacement of the destimulant with the stimulant was done according to the formula (Nelson and Shavitt 2002): X = , (2) ij ij where X is the original value of the variable and X’ is the value of the variable converted ij ij into the stimulant. The selected variables were subjected to the procedure of zero unitarization using the following formula: x min x ij i ij Z = , where x 2 S, (3) ij i max x min x i ij i ij where max 6= min , S is the stimulant, x denotes the value of the j-th feature for the i-th xij xij ij object, max{x } is the maximum value of the j-th variable, min{x } is the minimum value of ij ij the j-th variable, and the normalized value is j-th feature for the i-th object. The value of Z is in the range [0; 1]. A value of 1 means that the variable ob- ij tained the maximum value among all objects tested during the entire testing period (Hendershot 2011). As a result of the transformations, a matrix of uniformized variable values was obtained: 2 3 z z . . . z 11 12 1m 6 7 z z . . . z 21 22 2m 6 7 Z = , (4) ij 4 5 . . . . . . . . . . . . z z . . . z n2 nm n1 where Z denotes the unitary value of the j-th feature for the i-th object. ij 3.3. Determining the Synthetic Measure According to the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) Method for Individual Objects For the assessment of the multidimensional phenomenon (the ﬁnancial situation), a synthetic measure was built. For this purpose, we used the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method (Abidin et al. 2016). It is a reference method in which the reference points of objects in a multidimensional space are: a pattern (=1) and an anti-pattern (=0). Then, the Euclidean distances of individual objects from the pattern and anti-pattern were calculated according to the following formulas: u 1 + + d = Z Z , (5) å i j i j j=1 d = Z Z , (6) å i j i j j=1 Risks 2021, 9, 145 8 of 22 where n is the number of variables forming the pattern or anti-pattern; Z denotes the i j unitized value of the j-th feature for the tested unit; and Z /Z is the pattern or anti- j j pattern object (Behzadian et al. 2012; Bak ˛ 2018). The value of the synthetic measure for individual objects was estimated using aggre- gate functions, based on the formula: q = , where 0 q 1, i = 1, 2, . . . , n, (7) i i d + d i i where q 2 [0; 1] is the value of the synthetic measure; d is the distance of the object from the anti-pattern (from 0); and d is the distance of the object from the pattern (from 1). A higher value of the measure indicates a better situation of an individual in the studied area (Eini et al. 2015). Then, the average value of the synthetic measure was determined, indicating the development potential of the commune. It was calculated based on the formula: i=1 X = , (8) where X is the arithmetic mean as a value of the synthetic measure of development, q is the synthetic value of the category of a speciﬁc potential, and n is the number of tested potentials (categories). The value of the arithmetic mean is the quotient of the total value of all studied endogenous potentials of communes and the number of them. The conducted analysis allowed for the elimination of the problem of variable re- peatability within the examined categories. The applied TOPSIS method made it possible to conduct an evaluation using many criteria, to present the results in numerical form, and to organize objects in a linear manner (building a ranking of units). An important advantage of the classic TOPSIS method is its computational simplicity, the indication of a positive and negative pattern, and the large number of alternative criteria (Kim et al. 2013; Velasquez and Hester 2013). 3.4. Division of the Surveyed Population into Typological Groups and Evaluation of the Obtained Results In the last stage of the research, a division into typological groups was used to interpret the obtained measures. The threshold values were percentiles (2, 4, 6, and 8; 5 groups were formed). The size of the synthetic measure in the ﬁrst group indicates the unit that is better in the following groups—the weaker units. A correlation analysis was also performed (Pearson’s coefﬁcient), a scatter plot with a ﬁt line was made, and a linear regression analysis was performed (Trojak and Tokarski 2013; Kumari and Yadav 2018). Regression analysis is the study of the relationship between the variables of interest and aims at the construction of a model that reﬂects this relationship well. It allows us to indicate the relationships between the dependent variables (Y) and the independent variables (X). The linear regression model is described by the following formula: y = b x + a, i = 1,2, . . . , n, (9) i i In the case of the multiple regression model, when we had more predictors, we used the following formula for the regression line: y = b x + b x + . . . + b x + a, i = 1, 2, . . . , n, (10) i 1 1 2 2 i i where: b is the regression coefﬁcient calculated for individual predictors in the model; x is the independent variable; y is the dependent variable in the model; and a is an intercept. Risks 2021, 9, 145 9 of 22 Regression analysis allows us to check whether the built model signiﬁcantly predicts the value of the explained variable and determine which variables predict it signiﬁcantly. In the regression model, the autocorrelation of variables should be excluded. The (corrected) R2 statistic, which indicates the degree to which the estimated regression function explains the variability in the variable y, takes values from 0 to 1 (Gigerenzer 2004). 4. Results The area of eastern Poland includes the following provinces: Lubelskie, Podlaskie, Podkarpackie, Swietokrzyskie, ˛ and Warminsko-Mazurskie. ´ It is characterized by the lowest level of economic development in Poland and is also one of the weakest regions in the European Union. The problems that have a negative impact on the socio-economic development to a large extent have a structural dimension, being a consequence of historical conditions. Regarding the developmental potential of the macroregion, the unfavorable conditions include poor infrastructure related to limited professional activity, the low effectiveness of the structure of the economy and the labor market, a constant outﬂow of inhabitants to other regions (e.g., the migration of mainly young people), and a low level of innovation. The classiﬁcation of rural communes in eastern Poland according to their ﬁnancial situation is shown in Figure 1. The white color in the ﬁgure indicates urban and urban– rural communes not covered by the study. The black color indicates the best units, and the lighter color indicates weaker units. The division of communes was based on quartiles, which constituted the threshold values for subsequent groups. The rural communes in eastern Poland are characterized by signiﬁcant disproportions in terms of development and ﬁnancial situation. The units distinguished by a better ﬁnancial situation have a higher rate of development. The synthetic measure of development (qi) ranged from 0.16 to 0.51 in 2018 and from 0.15 to 0.46 in 2009 (in the case of the ﬁnancial standing measure 0.09–0.39 in 2009 and 0.14–0.51 in 2018). The increase in the range of the measure from 0.31 to 0.35 Risks 2021, 9, x FOR PEER REVIEW 10 of 22 and the increase in the ﬁnancial situation measure from 0.30 to 0.37 conﬁrm the increase in the differentiation of individuals in terms of development. AB Figure 1. Cont. CD q (r) development measure (A 2009, B 2018); q (f) financial situation measure (C 2018, D 2009). Figure 1. Synthetic measure of the financial situation of rural communes in eastern Poland in 2009 and 2018. Source: own research. By analyzing the internal conditions of municipalities divided into five typological groups (statistically similar to each other, according to the percentile values 2, 4, 6, and 8), they were characterized as follows: Risks 2021, 9, x FOR PEER REVIEW 10 of 22 Risks 2021, 9, 145 10 of 22 AB CD q (r) development measure (A 2009, B 2018); q (f) financial situation measure (C 2018, D 2009). Figure 1. Synthetic measure of the ﬁnancial situation of rural communes in eastern Poland in 2009 and 2018. Source: own research. q (r) development measure (A 2009, B 2018); q (f) ﬁnancial situation Figure 1. Synthetic measure of the financial situation of rural communes in eastern Poland in 2009 and 2018. Source: own research. measure (C 2018, D 2009). By analyzing the internal conditions of municipalities divided into ﬁve typological By analyzing the internal conditions of municipalities divided into five typological groups (statistically similar to each other, according to the percentile values 2, 4, 6, and 8), groups (statistically similar to each other, according to the percentile values 2, 4, 6, and 8), they were characterized as follows: they were characterized as follows: (1) Group 1 communes are no longer typically agricultural, as evidenced by the number of economic entities and natural persons running a business. Thus, the multifunc- tionality of rural areas contributes to their development. The use of the rent of the location in relation to urban areas (local development centers) creates opportunities for their rapid development. (2) The communes in Group 1 (the best group), in relation to the communes of the fourth and ﬁfth groups (the weakest groups), were characterized by lower ﬁnancial ratio values, which allow for a conclusion about the lower freedom of use of ﬁnancial resources and, thus, the smaller ﬁnancial possibilities of these communes. (3) The group with the best ﬁnancial situation consisted of 33 communes (28% of all rural communes in the provinces of eastern Poland). These communes were characterized by the highest share of the population per 2 km in relation to the weakest communes. (4) The communes in the best ﬁnancial situation (Group 1 communes) obtained higher ratios of the share of personal incomes in total incomes than the weakest communes. (5) The poorer the ﬁnancial situation of communes, the smaller was the importance of income sources. (6) The budget of the weakest communes was the most supported by income from transfers (which weakens their independence). (7) The main reason for the low impact of ﬁnancial conditions on the socio-economic development of communes is their dependence on income transferred from the state budget and the amount of current expenditure. These circumstances stiffen and stabilize the ﬁnancial economy, making it relatively insensitive to the inﬂuence of other factors. Risks 2021, 9, 145 11 of 22 (8) The low independence constitutes a barrier to the local development of rural com- munes. (9) The growing importance of transfers from the state budget in the group with poor ﬁnancial standing proves the declining level of ﬁnancial independence (see Table 3). Table 3. Values of indicators describing the socio-economic and ﬁnancial situation of rural communes in eastern Poland in 2009 and 2018. 2009 2018 I II II IV V I II III IV V q development 0.32 0.26 0.24 0.21 0.19 0.37 0.30 0.27 0.24 0.21 Number of communes 102 116 76 98 92 97 127 90 112 58 Determinants of the socio-economic situation Population per km 87 53 50 43 44 96 57 45 40 38 Migration balance per 1000 people 2.4 0.5 1.9 2.9 3.4 2.6 1.9 2.9 4.7 4.5 Unemployed persons registered in 70 71 61 56 58 37 38 41 38 44 communes per 1000 inhabitants Employed persons per 107 80 66 59 54 117 94 80 61 59 1000 inhabitants Entities entered into the REGON 57 51 47 42 40 76 65 57 52 50 register per 1000 inhabitants Natural persons conducting economic activity per 48 41 36 33 31 62 51 43 40 38 1000 inhabitants Determinants of the ﬁnancial situation q ﬁnancial situation 0.18 0.16 0.17 0.16 0.15 0.21 0.19 0.20 0.19 0.18 Personal income/total income 0.34 0.27 0.26 0.24 0.23 0.35 0.29 0.28 0.25 0.24 Investment 0.21 0.18 0.21 0.20 0.18 0.22 0.21 0.20 0.20 0.20 expenditure/total expenditure Transfer income/total income 0.63 0.69 0.69 0.73 0.75 0.58 0.64 0.65 0.68 0.68 Source: own research. Figure 2 shows the distribution model for the synthetic measure of development and ﬁnancial situation. In the case of the development measure, we observed a right-hand distribution of 0.29 > 0.28 in 2018 and 0.25 > 0.24 in 2009. In the case of the ﬁnancial standing measure, we observed a right-hand distribution of 0.17 > 0.16 in 2009 and a symmetrical distribution of 0.19 = 0.19 in 2018. The right-hand skewness indicates that a greater number of communes have values of these variables that are lower than their average value. The largest range in 2018 for the development measure was 0.25–0.30 (155, 32%), and the largest range in 2018 for the ﬁnancial standing measure was 0.15–0.20 (327, 68%). There was a predominance in the indicated ranges. The statistical characteristics of the synthetic measure of the ﬁnancial situation, as well as the income from local taxes of rural communes in eastern Poland in 2018 compared to 2009, do not indicate the stability of this phenomenon in the analyzed area. The analysis of the dispersion of the measure of economic security in rural communes in eastern Poland in 2009 and 2018 shows a slight increase in differentiation. This is indicated by the range of 0.31–0.35 for development and 0.30–0.37 for the ﬁnancial situation; the quarterly range of 0.07–0.08 for development and 0.04–0.04 for the ﬁnancial situation; and the standard deviation of 0.05–0.06 for development and 0.04–0.04 for the ﬁnancial situation. The stability of the phenomenon is indicated by the coefﬁcient of variation of 0.20– 0.20 for development and 0.22–0.20 for the ﬁnancial situation; and the quarter deviation of 0.04–0.04 for development and 0.02–0.02 for the ﬁnancial situation. Additionally, it should be noted that almost all variables (except for transfer income/total income—the state’s ﬁnancial interference rate) show a positive asymmetry, which is not a favorable situation for stimulants. This means that a larger number of communes have values of these variables that are lower than their average, indicating the weakness of the analyzed region in the indicated area (see Table 4). Risks 2021, 9, x FOR PEER REVIEW 12 of 22 greater number of communes have values of these variables that are lower than their average value. The largest range in 2018 for the development measure was 0.25–0.30 (155, Risks 2021, 9, 145 12 of 22 32%), and the largest range in 2018 for the financial standing measure was 0.15–0.20 (327, 68%). There was a predominance in the indicated ranges. qi measure of development qi measure of development 208; 43% 155; 32% 152; 31% 118; 24% 95; 20% 90; 19% 51; 11% 48; 10% 17; 4% 18; 4% 2; 0% 1; 0% 12; 2% 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 1; 0% 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 qi measure of financial situation qi measure of financial situation 350 240 327; 68% 220 216; 45% 216; 45% 101; 21% 40 35; 7% 32; 7% 12; 2% 12; 2% 8; 2% 3; 1% 2; 0% 2; 0% 1; 0% 1; 0% 0 0 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 2018 2009 Figure 2. The synthetic measure of the financial situation of rural communes in eastern Poland in 2009 and 2018. Source: Figure 2. The synthetic measure of the ﬁnancial situation of rural communes in eastern Poland in 2009 and 2018. Source: own research. own research. The statistical characteristics of the synthetic measure of the financial situation, as Table 4. Statistical characteristics of the synthetic measure of the ﬁnancial situation of rural communes in eastern Poland in well as the income from local taxes of rural communes in eastern Poland in 2018 compared 2009 and 2018. to 2009, do not indicate the stability of this phenomenon in the analyzed area. Financial Investment The analysis of the dispersion of the measure of economic security in rural communes q Financial State Financial q Development Independence Attractiveness in eastern Poland in 2009 and 2018 shows a slight increase in differentiation. This is Situation Interference Index Indicator Index indicated by the range of 0.31–0.35 for development and 0.30–0.37 for the financial 2009 2018 2009 2018 2009 2018 2009 2018 2009 2018 situation; the quarterly range of 0.07–0.08 for development and 0.04–0.04 for the financial situation; and the standard deviation of 0.05–0.06 for development and 0.04–0.04 for the Min 0.15 0.16 0.09 0.14 0.09 0.11 0.00 0.01 0.18 0.20 Max 0.46 financial 0.51 situation. 0.39 The st0.51 ability of0.81 the phen 0.70 omenon0.71 is indicate 0.48d by the co 0.88 efficient 0.85 of Mean 0.25 0.29 0.17 0.19 0.27 0.28 0.20 0.21 0.70 0.65 variation of 0.20–0.20 for development and 0.22–0.20 for the financial situation; and the Median 0.24 0.28 0.16 0.19 0.24 0.26 0.19 0.20 0.73 0.66 quarter deviation of 0.04–0.04 for development and 0.02–0.02 for the financial situation. Standard deviation 0.05 0.06 0.04 0.04 0.11 0.10 0.11 0.09 0.11 0.10 Additionally, it should be noted that almost all variables (except for transfer income/total Quarter deviation 0.04 0.04 0.02 0.02 0.06 0.05 0.07 0.07 0.07 0.06 income—the state’s financial interference rate) show a positive asymmetry, which is not a Coefﬁcient of variation 0.20 0.20 0.22 0.20 0.40 0.34 0.54 0.45 0.16 0.15 favorable situation for stimulants. This means that a larger number of communes have Positional coefﬁcient 0.15 0.15 0.13 0.11 0.25 0.19 0.37 0.33 0.09 0.09 of variation values of these variables that are lower than their average, indicating the weakness of the Range 0.31 0.35 0.30 0.37 0.72 0.59 0.71 0.47 0.70 0.65 analyzed region in the indicated area (see Table 4). Quartile range 0.07 0.08 0.04 0.04 0.12 0.10 0.14 0.13 0.13 0.12 Skewness (asymmetry) 0.80 0.61 1.80 2.63 1.58 1.56 0.85 0.41 1.38 1.06 Table 4. Statistical characteristics of the synthetic measure of the financial situation of rural communes in eastern Poland Kurtosis (measure of in 2009 and 2018. 0.66 0.01 5.81 12.49 3.34 3.12 1.21 0.19 2.36 1.70 concentration) Financial Financial independence indicator = personal income/total income; investment attractiveness index = investment expenditure/total q Financial Investment State Financial expenditure; state ﬁnancial interference index = transfer income/total income. Source: own research. q Development Independence Situation Attractiveness Index Interference Index Indicator Financial independence is an important factor in socio-economic development 2009 2018 2009 2018 2009 2018 2009 2018 2009 2018 (Przybytniowski 2019), especially in rural municipalities. These units are characterized by a lower income potential (lower ﬁnancial independence). As a result, it may constitute a barrier to multifunctional development (Mölders 2014). At the same time, there is a signiﬁcant diversiﬁcation in the socio-economic development of rural communes. Rural number of observations number of observations number of observations number of observations Risks 2021, 9, x FOR PEER REVIEW 13 of 22 Min 0.15 0.16 0.09 0.14 0.09 0.11 0.00 0.01 0.18 0.20 Max 0.46 0.51 0.39 0.51 0.81 0.70 0.71 0.48 0.88 0.85 Mean 0.25 0.29 0.17 0.19 0.27 0.28 0.20 0.21 0.70 0.65 Median 0.24 0.28 0.16 0.19 0.24 0.26 0.19 0.20 0.73 0.66 Standard deviation 0.05 0.06 0.04 0.04 0.11 0.10 0.11 0.09 0.11 0.10 Quarter deviation 0.04 0.04 0.02 0.02 0.06 0.05 0.07 0.07 0.07 0.06 Coefficient of variation 0.20 0.20 0.22 0.20 0.40 0.34 0.54 0.45 0.16 0.15 Positional coefficient of 0.15 0.15 0.13 0.11 0.25 0.19 0.37 0.33 0.09 0.09 variation Range 0.31 0.35 0.30 0.37 0.72 0.59 0.71 0.47 0.70 0.65 Quartile range 0.07 0.08 0.04 0.04 0.12 0.10 0.14 0.13 0.13 0.12 Skewness (asymmetry) 0.80 0.61 1.80 2.63 1.58 1.56 0.85 0.41 −1.38 −1.06 Kurtosis (measure of 0.66 0.01 5.81 12.49 3.34 3.12 1.21 −0.19 2.36 1.70 concentration) Financial independence indicator = personal income/total income; investment attractiveness index = investment expenditure/total expenditure; state financial interference index = transfer income/total income. Source: own research. Financial independence is an important factor in socio-economic development (Przybytniowski 2019), especially in rural municipalities. These units are characterized by a lower income potential (lower financial independence). As a result, it may constitute a barrier to multifunctional development (Mölders 2014). At the same time, there is a significant diversification in the socio-economic development of rural communes. Rural Risks 2021, 9, 145 13 of 22 communes with the highest personal incomes are characterized by a much higher level of development. They determine the degree of financial independence of municipalities, and an increase or decrease in them affects the planning and implementation of investment activities. The impact on the level of financial independence of communes is also communes with the highest personal incomes are characterized by a much higher level of determined by the scope of the rights to freely spend the generated income (Heller and development. They determine the degree of ﬁnancial independence of municipalities, and Fa an rel incr nik 2 ease 013) or. decrease in them affects the planning and implementation of investment ac- tivities. At the sa The impact me time, l on the oca level l governments a of ﬁnancial independence re powered b ofy communes income transf is also erred to them, determined by the scope of the rights to freely spend the generated income (Heller and Farelnik 2013). often for a specific purpose (thus limiting the expenditure independence of local At the same time, local governments are powered by income transferred to them, often government units). The transfer income includes grants and subsidies. These funds are for a speciﬁc purpose (thus limiting the expenditure independence of local government characterized by the fact that they are transferred to a specific unit and constitute its source units). The transfer income includes grants and subsidies. These funds are characterized of income (Oates 2008). They are used to equip local government units with additional by the fact that they are transferred to a speciﬁc unit and constitute its source of income resources and constitute an instrument of state interference in the activities of this unit. (Oates 2008). They are used to equip local government units with additional resources and By employing this transfer income, the state ensures that it has an influence on the constitute an instrument of state interference in the activities of this unit. By employing directions of the implementation of the local financial economy. According to the measure this transfer income, the state ensures that it has an inﬂuence on the directions of the shown in Figure 3, a negative correlation (−0.438, in both analyzed years) was observed Risks 2021, 9, 0 14 of 24 implementation of the local ﬁnancial economy. According to the measure shown in Figure 3, between the measure of development and the financial index of interference in rural a negative correlation (0.438, in both analyzed years) was observed between the measure communes in eastern Poland. of development and the ﬁnancial index of interference in rural communes in eastern Poland. 2018, y = 0.1507 + 0.1501*x; r = 0.2136; p = 0.00000; r2 = 0.0456 2009, y = 0.1129 + 0.2118*x; r = 0.2950; p = 0.0000; r2 = 0.0870 0.55 0.45 0.50 0.40 0.45 0.35 0.40 0.30 0.35 0.25 0.30 0.20 0.25 0.15 0.20 0.10 0.15 Risks 2021, 9, x FOR PEER REVIEW 14 of 22 0.10 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 qi measure of development qi measure of development 2009, y = 0.0376 + 0.9291*x; r = 0.4348; p = 0.0000; r2 = 0.1890 2018, y = 0.0655 + 0.7591*x; r = 0.4365; p = 0.0000; r2 = 0.1905 0.9 0.8 0.8 0.7 0.7 0.6 0.6 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0.0 0.0 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 qi measure of development qi measure of development 2009, y = 0.1403 + 0.2285*x; r = 0.1070; p = 0.0186; r2 = 0.0114 2018, y = 0.15 + 0.1951*x; r = 0.1165; p = 0.0103; r2 = 0.0136 0.5 0.8 0.7 0.4 0.6 0.5 0.3 0.4 0.2 0.3 0.2 0.1 0.1 0.0 0.0 -0.1 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 -0.1 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 qi measure of development qi measure of development 2018, y = 0.8676 - 0.7781*x; r = - 0.4385; p = 0.0000; r2 = 0.1923 2009, y = 0.947 - 1.0095*x; r = - 0.4386; p = 0.0000; r2 = 0.1923 0.9 1.0 Figure 3. Cont. 0.9 0.8 0.8 0.7 0.7 0.6 0.6 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 qi measure of development qi measure of development Figure 3. Dispersion of the synthetic measure of the financial situation of rural communes in eastern Poland in 2009 and Figure 3. Dispersion of the synthetic measure of the ﬁnancial situation of rural communes in eastern Poland in 2009 and 2018. Source: own research. 2018. Source: own research. As shown in Table As shown in Table 5 5,, the the development development measur measure e w was as most c most closely losely corre correlated lated in in the the f ﬁnancial inancial s situation ituation w withith th the ﬁnancial e finanindependence cial independ ratio enceand rati the o an state d th ﬁnancial e state f interfer inanence cial interferen ratio. Personal ce ratio. income Person shows al income the economic shows the activity economi of inhabitants c activity ofand inha the bita state nts a of nd their the state of their possessions. possess They depend ions. They depend on the economic on the econo development mic deve of an lopindividual, ment of an in expanding dividual, expanding the economic base and increasing the income of local governments. A high value of the correlation with the share of transfers may indicate the dependence of a commune on revenues from the state budget. This stiffens the financial economy of the commune, making it relatively insensitive to the influence of other factors. According to Rosner’s (2012) research, there is a close relationship between the processes regarding a population and the level of socio-economic development. The age structure of the population shapes the situation of the labor market and has an impact on local finances and development (Antony et al. 2017; Banwo et al. 2017). Rural communes in eastern Poland are characterized by a low correlation measure (below 0.5) of development with the natural increase in and balance of migration. The number of economic entities proves the level of entrepreneurship in the region, which is confirmed by the correlation measure being above 0.5. There is a clear disproportion between the own income / total income transfer income / total income inv es tm ent expenditure / total ex pens es qi measure of financial situation investment expenditure / total expenses transfer income / total income own income / total income qi measure of financial situation Risks 2021, 9, x FOR PEER REVIEW 13 of 22 Min 0.15 0.16 0.09 0.14 0.09 0.11 0.00 0.01 0.18 0.20 Max 0.46 0.51 0.39 0.51 0.81 0.70 0.71 0.48 0.88 0.85 Mean 0.25 0.29 0.17 0.19 0.27 0.28 0.20 0.21 0.70 0.65 Median 0.24 0.28 0.16 0.19 0.24 0.26 0.19 0.20 0.73 0.66 Standard deviation 0.05 0.06 0.04 0.04 0.11 0.10 0.11 0.09 0.11 0.10 Quarter deviation 0.04 0.04 0.02 0.02 0.06 0.05 0.07 0.07 0.07 0.06 Coefficient of variation 0.20 0.20 0.22 0.20 0.40 0.34 0.54 0.45 0.16 0.15 Positional coefficient of 0.15 0.15 0.13 0.11 0.25 0.19 0.37 0.33 0.09 0.09 variation Range 0.31 0.35 0.30 0.37 0.72 0.59 0.71 0.47 0.70 0.65 Quartile range 0.07 0.08 0.04 0.04 0.12 0.10 0.14 0.13 0.13 0.12 Skewness (asymmetry) 0.80 0.61 1.80 2.63 1.58 1.56 0.85 0.41 −1.38 −1.06 Kurtosis (measure of 0.66 0.01 5.81 12.49 3.34 3.12 1.21 −0.19 2.36 1.70 concentration) Financial independence indicator = personal income/total income; investment attractiveness index = investment expenditure/total expenditure; state financial interference index = transfer income/total income. Source: own research. Financial independence is an important factor in socio-economic development (Przybytniowski 2019), especially in rural municipalities. These units are characterized by a lower income potential (lower financial independence). As a result, it may constitute a barrier to multifunctional development (Mölders 2014). At the same time, there is a significant diversification in the socio-economic development of rural communes. Rural communes with the highest personal incomes are characterized by a much higher level of development. They determine the degree of financial independence of municipalities, and an increase or decrease in them affects the planning and implementation of investment activities. The impact on the level of financial independence of communes is also determined by the scope of the rights to freely spend the generated income (Heller and Farelnik 2013). At the same time, local governments are powered by income transferred to them, often for a specific purpose (thus limiting the expenditure independence of local government units). The transfer income includes grants and subsidies. These funds are characterized by the fact that they are transferred to a specific unit and constitute its source of income (Oates 2008). They are used to equip local government units with additional resources and constitute an instrument of state interference in the activities of this unit. By employing this transfer income, the state ensures that it has an influence on the directions of the implementation of the local financial economy. According to the measure shown in Figure 3, a negative correlation (−0.438, in both analyzed years) was observed Risks 2021, 9, 0 14 of 24 between the measure of development and the financial index of interference in rural communes in eastern Poland. 2018, y = 0.1507 + 0.1501*x; r = 0.2136; p = 0.00000; r2 = 0.0456 2009, y = 0.1129 + 0.2118*x; r = 0.2950; p = 0.0000; r2 = 0.0870 0.55 0.45 0.50 0.40 0.45 0.35 0.40 0.30 0.35 0.25 0.30 0.20 0.25 0.15 0.20 0.10 0.15 Risks 2021, 9, x FOR PEER REVIEW 14 of 22 0.05 0.10 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 qi measure of development qi measure of development 2009, y = 0.0376 + 0.9291*x; r = 0.4348; p = 0.0000; r2 = 0.1890 2018, y = 0.0655 + 0.7591*x; r = 0.4365; p = 0.0000; r2 = 0.1905 0.9 0.8 0.8 0.7 0.7 0.6 0.6 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0.0 0.0 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 qi measure of development qi measure of development 2009, y = 0.1403 + 0.2285*x; r = 0.1070; p = 0.0186; r2 = 0.0114 2018, y = 0.15 + 0.1951*x; r = 0.1165; p = 0.0103; r2 = 0.0136 0.8 0.5 0.7 0.4 0.6 0.5 0.3 0.4 0.2 0.3 0.2 0.1 0.1 0.0 Risks 2021, 9, 145 14 of 22 0.0 -0.1 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 -0.1 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 qi measure of development qi measure of development 2018, y = 0.8676 - 0.7781*x; r = - 0.4385; p = 0.0000; r2 = 0.1923 2009, y = 0.947 - 1.0095*x; r = - 0.4386; p = 0.0000; r2 = 0.1923 0.9 1.0 0.9 0.8 0.8 0.7 0.7 0.6 0.6 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 qi measure of development qi measure of development Figure 3. Figure 3. Di Dispersion spersion ofof the the synthetic measur synthetic measur e of e of the the financial ﬁnancial situation situation of of rural communes rural communes in in ea eastern stern PPoland in oland in 2009 2009 and and Figure 3. Dispersion of the synthetic measure of the ﬁnancial situation of rural communes in eastern Poland in 2009 and 2018. Source: own research. 2018. Source: own research. 2018. Source: own research. As shown in Table 5, the development measure was most closely correlated in the As shown in Table As shown in Table 5 5,, the the development development measur measure e w was as most c most closely losely corre correlated lated in in the the ﬁnancial situation with the ﬁnancial independence ratio and the state ﬁnancial interference f ﬁnancial inancial s situation ituation w withith th the ﬁnancial e finanindependence cial independ ratio enceand rati the o an state d th ﬁnancial e state f interfer inanence cial ratio. Personal income shows the economic activity of inhabitants and the state of their interferen ratio. Personal ce ratio. income Person shows al income the economic shows the activity economi of inhabitants c activity ofand inha the bita state nts a of nd their the possessions. They depend on the economic development of an individual, expanding state of their possessions. possess They depend ions. They depend on the economic on the econo development mic deve of an lopindividual, ment of an in expanding dividual, the economic base and increasing the income of local governments. A high value of the expanding the economic base and increasing the income of local governments. A high correlation with the share of transfers may indicate the dependence of a commune on value of the correlation with the share of transfers may indicate the dependence of a revenues from the state budget. This stiffens the ﬁnancial economy of the commune, commune on revenues from the state budget. This stiffens the financial economy of the making it relatively insensitive to the inﬂuence of other factors. commune, making it relatively insensitive to the influence of other factors. Table 5. Correlation between the ﬁnancial situation and development measures and socio-economic variables in rural According to Rosner’s (2012) research, there is a close relationship between the communes of eastern Poland (co. Pearson; 2009–2018). processes regarding a population and the level of socio-economic development. The age structure of the population shapes the situation of the labor market and has an impact on Speciﬁcation q Development local finances and development (Antony et al. 2017; Banwo et al. 2017). Rural communes Financial independence indicator 0.4077 in eastern Poland are characterized by a low correlation measure (below 0.5) of State ﬁnancial interference index 0.359 development with the natural increase in and balance of migration. The number of Entities entered in the REGON register per 1000 inhabitants 0.580 Units newly registered in the REGON register per 1000 inhabitants 0.5206 economic entities proves the level of entrepreneurship in the region, which is confirmed Natural persons conducting economic activity per 1000 inhabitants 0,5759 by the correlation measure being above 0.5. There is a clear disproportion between the % of the population using the sewage network 0.8514 % of the population using the water supply system 0.3698 % of the population using the gas network 0.4957 Population growth per 1000 inhabitants 0.4354 Migration rate per 1000 inhabitants 0.3948 Wastewater treated during the year treated together 0.7098 % of the population using sewage treatment plants 0.8292 Financial independence indicator = personal income/total income; state ﬁnancial interference index = transfer income/total income. Key: Linear correlation coefﬁcients for observations from sample 1 to 4840; critical value (with a two-sided 5% critical area) = 0.0282 for n = 4840. Source: own research. According to Rosner’s (2012) research, there is a close relationship between the pro- cesses regarding a population and the level of socio-economic development. The age structure of the population shapes the situation of the labor market and has an impact on local ﬁnances and development (Antony et al. 2017; Banwo et al. 2017). Rural communes in eastern Poland are characterized by a low correlation measure (below 0.5) of development with the natural increase in and balance of migration. The number of economic entities proves the level of entrepreneurship in the region, which is conﬁrmed by the correla- tion measure being above 0.5. There is a clear disproportion between the density of the distribution of economic entities in urban centers as compared with rural communes. Pearson’s correlation coefﬁcient between the value of the synthetic measure of devel- opment and the measure of ﬁnancial standing in 2018 was 0.213 (0.295 in 2009), while the ﬁnancial independence index was 0.436 and 0.434 in 2018 and 2009, respectively. A low level of the indicated relation was observed in the case of the investment attractiveness own income / total income transfer income / total income inv es tm ent expenditure / total ex pens es qi measure of financial situation investment expenditure / total expenses transfer income / total income own income / total income qi measure of financial situation Risks 2021, 9, 145 15 of 22 index (0.116; 0.107). Other correlation values are shown in Table 5. This may conﬁrm that the spatial differentiation of the studied area was quite stable, and the units reacted similarly to changes taking place in the economy. In order to assess the impact of the variables of the ﬁnancial situation of rural com- munes in eastern Poland on the differentiation of development measures (taking into account the values of correlation measures between the selected variables), a regression model was estimated (see Table 6). The ﬁt of the model was measured using the indi- cators: coefﬁcient of determination R-squared value: 0.359698; and corrected R-squared value: 0.358106. This means that 35% of the variation in the model was explained by the variability of the independent variables. No collinearity was found in the explanatory variables (non-redundancy was assessed by the correlation coefﬁcient). The coefﬁcient of determination measures how much of the overall variability in the dependent variable is explained by the linear regression. One must therefore be careful in its interpretation, because the ﬁt of the model does not increase with the number of variables. There is an essential impact on the dependent variable. Further increasing the multidimensionality of the model would cause the R2 value to increase slightly (the bigger the better). For the model, this could lead to the inclusion of statistically insigniﬁcant variables. We can add a large number of irrelevant variables and the actual process will show that the model does not correctly describe the modeled phenomenon. The adjusted coefﬁcient of determination did not reach 60%. This may indicate the need to extend the range of variables with socio-economic elements to characterize the economic security in a multidimensional way. The F statistic (12, 4827) of 225.9688 is statistically signiﬁcant (the p-value for the F test was 0.000000), meaning that the construction of the linear model is correct. Table 6. Results of the regression analysis between the ﬁnancial situation (q) and the variables of development of rural communes in eastern Poland. Description Coefﬁcient Standard Error Student’s t Test p-Value Constant 0.382410 0.00639275 59.82 <0.0001 State ﬁnancial interference index 0.128171 0.00704407 18.20 <0.0001 Index of ﬁscal wealth per capita 0.136306 0.0247880 5.499 <0.0001 Agricultural tax 0.214572 0.00791490 27.11 <0.0001 Forest tax 0.203985 0.0263104 7.753 <0.0001 Vehicle tax 0.158478 0.0411964 3.847 0.0001 Investment expenditure 0.0525267 0.00804685 6.528 <0.0001 Expenditures on education and upbringing/number 5 6 2.84325 10 2.83874 10 10.02 <0.0001 of inhabitants 5 6 Apartments per 1000 inhabitants 6.986 <0.0001 5.07479 10 7.26467 10 Expenditures on the municipal economy and 6 6 5.38541 10 2.39585 10 2.248 0.0246 environmental protection/population Public safety and ﬁre protection 5 5 2.53834 10 1.15646 10 2.195 0.0282 expenditure/population Public administration expenditure/number 5 6 7.61551 10 6.97651 10 10.92 <0.0001 of inhabitants 5 6 Expenditure on agriculture and hunting/population 1.93975 10 2.85645 10 6.791 <0.0001 Arithmetic mean of Standard deviation of the dependent 0.266829 0.054140 dependent variable variable Sum of residual squares 9.081804 Residual standard error 0.043376 Coefﬁcient of determination 0.359698 Corrected R-square 0.358106 R-square F (12, 4827) 225.9688 P-value for the F test 0.000000 Logarithm of credibility 8326.059 Akaike Information criterion 16,626.12 Bayesian information 16,541.82 Crit. Hannana–Quinna 16,596.52 criterion Schwarza State ﬁnancial interference index = transfer income/total income; index of ﬁscal wealth per capita = share in taxes constituting state budget revenues/number of inhabitants; observations from sample 1 to 4840 used; dependent variable (Y): TOPSIS development; linear correlation coefﬁcients for observations from sample 1 to 4840; critical value (with a two-sided 5% critical area) = 0.0282 for n = 4840. Source: own research. Risks 2021, 9, 145 16 of 22 5. Discussion The socio-economic diversity of municipalities should be analyzed frequently. Re- search in this area is often focused on the search for and identiﬁcation of factors shaping the development process (analyses covering one area, e.g., ﬁnance, the economy, infras- tructure, human capital). The analyses carried out also concern a synthetic measure, e.g., of development or ﬁnancial situation. Spatial differentiation in the level of development results in different conditions for running a business and a different quality of life and living conditions for inhabitants (Capello 2014). Socio-economic development is associated with the economic, demographic, and natural aspects as well as with the geographical location (Saviotti et al. 2020). The develop- mental potential of communes is built by ﬁnancial resources, the professional activities of inhabitants, the local labor market, entrepreneurship, infrastructure, and the condition of the natural environment (Vermeulen and Pyka 2018). Financial resources are the basis for an individual’s activities. They are a prerequisite for the successful implementation of local tasks (related to the needs of residents). Endogenous resources are becoming more and more important in the development of communes. The progressive decentralization of power, competence, and management makes it possible to speak about the growing importance of local, material, and intangible resources. The endogenous potential of a region, which results from a combination of local conditions, determines its possibilities and directions of development (Churski and Kołsut 2017). As in- dicated by Milczarek (2005), it is the sum of, among other things, geographic, demographic, economic, and social elements. Kiniorska (2014) distinguishes three types: demographic, economic, and infrastructural elements. The analyses conducted by Churski et al. (2013), Stanny and Strzelczyk (2015), and Dziekan ´ ski and Prus (2020) show that an important en- dogenous element influencing development opportunities is financial potential. The ﬁnancial potential of communes is conditioned by many factors, including legal and spatial conditions, the level of urbanization of the area, and the potential demographic and economic conditions of a given local government unit. Most rural communes that still exist perform a function typical of rural areas—agriculture (forestry), which translates into a low level of ﬁnancial potential. Under the conditions of European integration, however, the functions performed by rural communes have changed from typically agricultural to residential, service, tourist, and recreational, which strengthens the role of units in a dynamically changing environment and determines the level and structure of income (Rosner and Stanny 2016). Filipiak (2009) also points to the importance of the spatial development of an area as a factor inﬂuencing the ﬁnancial condition of municipalities through creating favorable conditions for the development of economic activity and thus encouraging settlement and increasing the potential of human capital. Local authorities should take care of the condition of the infrastructure. This may increase the attractiveness of the area and attract new entrepreneurs or improve the quality of life of the inhabitants. Infrastructure contributes to the economic activation of the region. Knowledge of the social potential, the labor market, and changes in it is of importance to the determinants of a development policy. Human capital is one of the key elements of development (Quaranta et al. 2016; Jutengren et al. 2020). The quality of the natural environment is an important element that enables the proper functioning of economic processes. For economic reasons, it constitutes one of the sources of raw materials and energy and provides geographical space, a place for economic activity, and a place to live or rest. The ﬁnancial situation of communes determines the possibilities for the fulﬁllment of ﬁnancial obligations, ensuring continuity in the provision of services. Finance allows for a multi-element assessment of the commune’s activities, its development possibilities, and the implementation of public tasks. According to Stanny and Strzelczyk (2018), the ﬁnancial situation is an assessment of the commune’s ﬁnances, i.e., the possibilities to ensure ﬁnancial security. This security includes the ability to perform tasks and reliability in terms of the ability to pay off liabilities. Risks 2021, 9, 145 17 of 22 Hendrick (2004) relates the ﬁnancial situation to the ability to raise a sufﬁcient amount of funds, deliver public services, and manage debt. Financial standing relates to the overall level of economic development (Przybytniowski 2016; Drozdowski 2017; Dobrowolski 2020b). It indicates a commune’s ability to meet its own administrative and investment needs, which means maintaining and developing its own assets in line with the current and future demand for public services (Aleksandrova-Zlatanska 2019). The ﬁnancial situation, according to Cabaleiro et al. (2013), is a complex phenomenon and is inﬂuenced by many factors. Knowledge of the state of ﬁnances allows local authorities to make comparisons with other entities and helps them make ﬁnancial decisions. Standar (2019) analyzed the relationship between the location of communes in rural areas in relation to cities with county status and the ﬁnancial results achieved by them. As a result of the research, it was proved that the smaller the distance from an urban center, the greater the ﬁnancial independence, ﬁnancial liquidity, and investment execution becomes, albeit at a higher level of debt. Dziekanski ´ and Wyszkowski (2018), in their research on the diversiﬁcation of the ﬁnancial situation of communes in rural areas of the Swietokrzyskie ˛ province, used a synthetic measure based on a deliberately selected set of diagnostic variables. The synthetic measure conﬁrmed the diversiﬁcation of the ﬁnancial situation of the analyzed rural communes. Data analysis showed that the ﬁnancial situation was inﬂuenced by the level of income from taxes and local fees as well as income from participation in PITs and CITs. The low share of personal income in the total income of the Swietokrzyskie ˛ communes proves their low income independence. Dziekanski ´ (2014) undertook the construction of a synthetic measure allowing for the measurement of a multidimensional phenomenon and the linear ordering of the studied units. In this way, the author assessed the level of local development by assessing the ﬁnancial situation, infrastructure, and natural environment of rural communes in the Swietokrzyskie ˛ province. Dziekanski ´ and Prus (2020) indicate in their research the growing role and importance of communes in the local economy. The analysis showed that rural communes of eastern Poland are characterized by signiﬁcant disproportions in their ﬁnancial situation. Rural communes that are in the best ﬁnancial situation are characterized by a higher share of personal income in total income and a higher level of income from premises and the taxes obtained from the share in the tax on natural and legal persons. The analyses carried out by Głowicka-Wołoszyn and Wysocki (2016) showed that there are signiﬁcant differences in the level and structure of municipalities’ income. Rural communes of good ﬁnancial standing were characterized by a higher share of personal income in total income, a higher level of income from taxes on real estate, and income obtained from participation in the tax on natural persons. The revenues of communes with the best ﬁnancial situation played the greatest role in supplying their budgets, ensuring the independence of local self-governments in decision-making on spending directions. Stanny and Strzelczyk (2018) presented a number of empirical indicators (covering ﬁscal solvency, liabilities, dependence on transfers from the state budget, and the degree of ﬁnancing of public services) used in the assessment of the ﬁnancial situation. It was proved that communes characterized by a relatively good ﬁnancial situation were mainly concentrated in suburban zones of large province centers (on the center-periphery line). It was also indicated that the level of socio-economic development and the ﬁnancial condition are interdependent. Wang et al. (2017) indicate that the socio-economic environment is a factor that should be taken into account when analyzing the ﬁnancial situation. Berne and Schramm (1986) include among the main determinants of the ﬁnancial situation the needs of the local community, the directions of the distribution of local public goods and services, and the society’s afﬂuence. Ladd (1992) emphasizes the impact of demographic conditions on the condition of local government ﬁnances. Rodríguez Bolívar et al. (2016) identiﬁed the main factors shaping the ﬁnancial situation, including the state of and changes in the size of the Risks 2021, 9, 145 18 of 22 population, the local labor market conditions, increases in local government spending, and public ﬁnance management. 6. Conclusions The activities of municipalities are a multidimensional process implemented in a set of elements, including demographic, economic, ﬁnancial, and environmental elements, and the links between these elements. Each spatial decision and each process for formulating conditions and directions of development is based on speciﬁc premises and information. Having information is a fundamental condition for making correct spatial decisions (in- cluding risk minimization). An evaluation of a commune’s activities, due to the variety of undertakings, may be performed with the use of a synthetic measure. It should also provide local authorities with information on the use of public resources or the possibility of making operational or investment decisions. The distribution of the evaluation of the development and ﬁnancial situation of rural communes in eastern Poland was spatially polarized. The results show that the development of the surveyed communes is related to a better ﬁnancial situation. Local authorities should ﬁrst of all take care to improve the economic potential, which would increase the attractiveness of the area and attract new entrepreneurs. The synthetic measure of development (qi) ranged from 0.15 to 0.46 in 2009, while in 2018 it ranged from 0.16 to 0.51. The ﬁnancial standing measure ranged from 0.09 to 0.39 in 2009 and from 0.14 to 0.51 in 2018. Taking into account the increase in the range of the measure, these results indicate an increase in the differentiation of units in terms of development from 0.31 to 0.35 and in terms of the ﬁnancial situation measure from 0.30 to 0.37. The correlation coefﬁcient between the values of the synthetic measure indicates the stability of spatial differentiation in terms of development. A similar situation can be seen in the reaction of communes to changes in the economy. Pearson’s correlation coefﬁcient between the value of the synthetic measure of development and the measure of ﬁnancial standing in 2018 was 0.213 (0.295 in 2009), and the ﬁnancial independence index was 0436 and 0.434 in 2018 and 2009, respectively. A low level of the indicated relation was observed in the case of the investment attractiveness index: 0.116 and 0.107, respectively. Between the measure of development and the rate of state ﬁnancial interference, a negative correlation coefﬁcient (0.438) was observed in both 2009 and 2018. The surveyed communes are characterized by a low measure of the correlation be- tween development and the natural increase in the population, and a migration balance of less than 0.5. On the other hand, the number of economic entities proves the appropriate level of entrepreneurship in the region (over 0.5). It seems that the main reason for the relatively low impact of ﬁnancial conditions on the development of rural communes in eastern Poland is their strong dependence on income transferred from the state budget. This stiffens and at the same time stabilizes the ﬁnancial economy, making it relatively insensitive to the inﬂuence of other factors. Low independence may be a signiﬁcant barrier to future local development. The results of this study allow local governments to compare their development with the situation of neighboring communes. Conclusions drawn on this basis may allow local authorities to deﬁne potential directions for the optimization of the development process. The obtained results conﬁrm the usefulness of synthetic measures for the assessment of the endogenous potential of the examined communes. They can be an important source of information for local government authorities on disproportions between units, and their effect may be the use of these analyses as a source of knowledge for more effective management of local government units. One should look for regularities explaining the spatial differentiation of the development of communes, as well as their structures and local conditions. At the same time, the obtained results indicate the directions of future research, which include, among other things, comparison of the results of the linear ordering based on a larger number of empirical data sets, comparison of the results of the linear ordering based on the simulation of data sets with speciﬁc statistical distributions, conducting a Risks 2021, 9, 145 19 of 22 dynamic analysis in a speciﬁed period of time in order to learn about the trend of changes, and comparing the results of rankings based on other methods of linear ordering. A commune’s self-government is the subject of economic development. Its course is inﬂuenced by many factors (including infrastructural, economic, demographic, and ﬁnancial factors) both dependent on and independent of the commune itself. Between development and endogenous resources there is a feedback loop (Hall 2015). An inﬂux of new residents, investors, and enterprises will occur where an area is economically developed. This entails further budget revenues in the form of, e.g., a real estate tax, shares in personal taxes (PIT), and legal revenue (CIT), which enable the undertaking of further pro-development projects (Standar 2017). Parysek (1997) points out that certain factors are common, while others may be present and interact only in certain places and at certain moments in time. Development is related directly to meeting the growing needs of society. In a diversiﬁed economic structure, individuals create a speciﬁc development climate in which the conditions for taking up business are created by new entities and the conditions for cooperation with others shape these entities. The issue of the development of rural communes in eastern Poland is very speciﬁc, and the villages have undergone a process of intense transformation since Poland’s accession to the EU. The research results (for 2008–2019) show that inequality has stabilized the development and ﬁnancial situation in the rural areas of the surveyed provinces. In the presented studies, particular attention was paid to the relationship between the ﬁnancial situation and socio-economic diagnostic variables of the development process in 484 rural communes in eastern Poland (in the research carried out so far, they most often included single communes of provinces in eastern Poland; i.e., communes of a speciﬁc county). This approach allows us to assess in a wider area the inﬂuence of ﬁnancial variables on the development process. The wider range of ﬁnancial variables (X1–X15, Table 1) indicate that the main reason for the relatively low impact of these conditions on ﬁnancial resources for the development of rural communes in eastern Poland is their strong dependence on income transferred from the state budget. This stiffens and at the same time stabilizes the ﬁnancial economy, making it relatively insensitive to the inﬂuence of other factors. Low ﬁnancial independence may be a signiﬁcant barrier to future local development. The important development problem of rural communes is to recognize the worsening demographic situation, which is shaping the ﬁnancial situation in a negative way. Author Contributions: Conceptualization, A.P., P.D. and J.W.P.; methodology, A.P. and P.D.; software, A.P., P.D. and J.W.P.; validation, A.P., P.D. and J.W.P.; formal analysis, A.P. and P.D.; investigation, A.P., P.D. and J.W.P.; resources, A.P., P.D. and J.W.P.; data curation, A.P., P.D. and J.W.P.; writing— original draft preparation, A.P., P.D. and J.W.P.; writing—review and editing, A.P., P.D. and J.W.P.; visualization, A.P., P.D. and J.W.P.; supervision, A.P., P.D. and J.W.P.; project administration, A.P., P.D. and J.W.P.; funding acquisition, A.P., P.D. and J.W.P. 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Risks – Multidisciplinary Digital Publishing Institute

Published: Aug 12, 2021

Keywords: synthetic measure; rural municipalities; competitiveness; financial security; TOPSIS method; public sector

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Influence of Financial Variables on the Development of Rural Communes of Eastern Poland in 2009–2018

Influence of Financial Variables on the Development of Rural Communes of Eastern Poland in 2009–2018

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Influence of Financial Variables on the Development of Rural Communes of Eastern Poland in 2009–2018

Influence of Financial Variables on the Development of Rural Communes of Eastern Poland in 2009–2018

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