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- Publisher
- de Gruyter
- Copyright
- © 2022 Iryna Tkachuk et al., published by Sciendo
- eISSN
- 2345-0355
- DOI
- 10.15544/mts.2022.46
- Publisher site
- See Article on Publisher Site
Abstract
In the conditions of a changing economic environment, it is important not only to analyze the main indi cators of the banking system, but also to clearly define the main factors that determine them. The aim of the article is to study the mutual influence of the main performance indicators of the banking system of Ukraine and macroeconomic indicators of Ukraine at the present stage of its operation to outline the main factors that will promote the formation of a methodology for studying the essence of the basic processes in the functioning of banks, identifying obstacles to their development and developing effective mechanisms to improve their further activities. As a result of the study, the authors developed a multifactor model of the influence of factors on the performance of banks and used the method of canonical correlations to find the maximum correlations between groups of variables. There is a close correlation between the performance of banks and macroeconomic indicators of the country. The results of the canonical analysis confirmed that the relationship between the selected performance indicators and the selected determinants should be studied in terms of individual performance indicators of banks to form a system of scenarios for the development of these indicators depending on selected factors using the scenario method. The possibility of achieving positive changes in the banking system of Ukraine by influencing the resulting indicators of each of the significant equations through the management of specific significant factor variables is analyzed. Correlation-regression and scenario analysis makes it possible to state that the state policy should be pursued to manage a given set of factors that have a positive impact on banks' performance, promote bank capital growth, number of legal entities, average monthly salary, stability of the National Bank of Ukraine discount rate, etc. Keywords: bank, performance indicators of banks, macroeconomic indicators, factors influencing banking activity. JEL Codes: G 21; O 11. Introduction The banking system is a basic and economy depends on the reliable and extremely important component of the efficient work of banks. financial system of any country. Banks in the Banks in Ukraine are dynamically process of their operation actively influence changing and developing, which is reflected the socio-economic relations that take place in the fluctuations of indicators that in the country. The development of banks in characterize their activities. Banks' Ukraine has become a stimulus for the performance indicators are closely formation of new market relations, a basic interrelated with the country's element of the movement of financial macroeconomic indicators, reflecting both resources, without which the functioning of a internal and external causal links between market economy is impossible. The economic processes. Outlining the main efficiency of all branches of the country's factors influencing the activities of banks is very important in terms of forming a Copyright © 2022 Author(s), published by Vytautas Magnus University. This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial 4.0 (CC BY-NC 4.0) license, which permits unrestricted use, distribution, and reproduction in any medium provided the original author and source are credited. The material cannot be used for commercial purposes. Iryna Tkachuk, Olha Hladchuk, Olena Vinnychuk methodology for their research, and the main LEV, and Beta are controlled at optimal - understanding the essence of the basic levels (Nguyen Phu Ha, 2021). The results of processes of their operation, to form effective the study by Salamat W., Momani M., mechanisms for their further development. Batayneh K. “Firm-specific, macroeconomic The structuring of the most influential factors factors and stock price risk for Jordanian can serve as a basis for identifying obstacles banks” show, that trading volume (TV), to the development of banks and the dividend yield (DY), and Gross Domestic formation of sound forecasts of their future Product (GDP) have a positive effect on operation. stock price volatility, while stock price A large number of researchers studied volatility is statistically negatively affected the activities of banking institutions, who by return on assets (ROA), dividend payout studied both the peculiarities of their ratio (DPR), and price-earnings ratio (PE). functioning in a changing economic On the other hand, money supply (MS) does environment and directly the results of banks. not affect stock price volatility. Paying more For example, Wahyudi S., T., Nabella R. S., dividends can reduce stock risk and, in turn, and Sari K. conducted a study of the reduce stock price volatility (Wasfi Al relationship between competition and the Salamat, Mohammad Q. M. Momani and efficiency of the banking sector in Indonesia, Khaled Batayneh, 2021). We also conducted which led to the conclusion that bank some research, the aim of which was to competition that leads to a monopolistic characterize the real stage of realization of market structure stimulated banks to achieve asset operations of the Ukrainian banks. For higher profits and put bank projects and this aim, an analysis of the Ukrainian banks’ financing at high risk. Competition has had a activities from 2011 through 2016 was made negative correlation with bank efficiency (Tkachuk, 2017). because competition encourages banks to Despite the significant amount of focus on profit rather than efficiency, engage research on the state and problems of bank in risky financing/projects, and undertake development, issues related to the study of high lending activities (Setyo Tri Wahyudi, the mutual influence of key performance Rihana Sofie Nabella and Kartika Sari, indicators of Ukrainian banks and 2021). Nguhen Phu Ha in his article “Impact macroeconomic indicators of Ukraine's of macroeconomic factors and interaction development at the present stage of its with institutional performance on development remain unexplored. Thus, this Vietnamese bank share prices''. A new study is relevant and has theoretical and contribution of this study is the application of practical value. interactive factors between macroeconomics The aim of the article is to study the and bank performance (i.e., Equity Capital mutual influence of the main performance (E), Deposit Аmounts (D), Loan Amounts indicators of the banking system of Ukraine (L), Non-performing Loans (NPLs), and macroeconomic indicators of Ukraine at Leverage (LEV), Capital Adequacy Ratio the present stage of its operation to outline (CAR), Return on Assets (ROA), and Stock the main factors that will promote the Beta (Beta)) in evaluating their impact on formation of a methodology for studying the bank share prices. Applying the econometric essence of the basic processes in the method of Two-Stage Least Square (2SLS) functioning of banks, identifying obstacles to and the quarterly financial data of 13 listed their development and developing effective banks from Q1/2009 to Q3/2020, the mechanisms to improve their further regression results show that GDP activities. improvements can foster an increase in bank In the process of research, the methods share prices, and this impact is strengthened of economic-mathematical analysis were if banks have good performance of ROA, used: the method of canonical correlations, CAR, and with strict control of NPLs. The R correlation-regression analysis, as well as the also has a positive impact on bank share scenario method. For correlation-regression prices, and the price level increases if NPLs, analysis it is important that the phenomena Management Theory and Studies for Rural Business and Infrastructure Development eISSN 2345-0355. 2022. Vol. 44. No. 4: 461-481 Article DOI: https://doi.org/10.15544/mts.2022.46 and processes studied have a mathematical essence of all processes, intending to form expression, so to study the peculiarities of the effective mechanisms of its development. banking system of Ukraine and the formation The structuring of such factors can of its results we use basic macroeconomic serve as a program to identify obstacles to indicators (GDP in actual prices; Average the development of the banking system in the monthly wages per employee; prices; NBU state and a separate subject of banking discount rate; Population; Number of activity in particular. business entities; Number of legal entities) The development of a multifactorial and data on the performance of Ukrainian model of the influence of factors on the banks (Number of banks; Number of banks performance indicators of the banking system with foreign capital; Number of banks with requires further development in this 100% foreign capital; Bank assets; Loans to direction. customers; Loans to entities; Loans to Determining and monitoring factors individuals; Bank capital; Bank liabilities; affecting the results of the banking system Funds of entities; Funds of individuals; Net provide a toolkit for analysis, but usually it is profit/loss). carried out with the help of an economic and The study period is 10 years and covers mathematical modeling apparatus. As a rule, the period from January 1, 2011 to December correlation-regression analysis is used to 31, 2020, divided quarterly. All data is taken build multifactorial models of the influence from open sources. of factors on performance indicators. The Scientific knowledge obtained as a specified method makes it possible to result of studying the impact of changes in determine the strength and influence of the macroeconomic indicators on the system of factors on one effective indicator performance of the banking system of of the banking system. However, the primary Ukraine will expand the methodology of task of building a system of factors, in our research in the banking sector in Ukraine, as opinion, is to assess the influence of factors well as provide significant practical benefits: not on one effective indicator of the banking the results of the study will make it possible system (for example, the capital of banks), to direct the state policy of macroeconomic but on several, which ensures greater realism factors management to increase the and validity of the obtained research results. efficiency of the banking system in Ukraine. Conducting such research is carried out using canonical correlations analysis. Results The method of canonical correlation analysis was first published by the American Factors influencing the activity of the economist H. Hotelling (1936) (Hotelling H., banking sector reflect both internal and 1936). Canonical correlation analysis finds external processes in the economy of the linear relationships between two sets of state and significantly determine the results variables, it is a generalized version of of banking activity. pairwise correlation (Yarovy A., Strakhov E., In practical activity, the outline of the 2015). At the same time, it is not required main factors that determine the results of the that there is no correlation both in the group banking sphere is important in the aspect of of performance indicators Y and in the group forming the methodology of its research, and of factor characteristics X (Fig. 1). most importantly - in understanding the Iryna Tkachuk, Olha Hladchuk, Olena Vinnychuk Figure 1. Illustrative representation of relationships between factor and dependent variables in canonical analysis *Source: Compiled by the authors. The calculation algorithm of the provided to individuals; Capital of banks; method of canonical correlations is built in Liabilities of banks; Funds of economic such a way that the initial variables are entities; Funds of individuals; Net profit/loss) replaced by their linear independent and are defined as Y1, Y2, ..., Y12, combinations. The main purpose of using this respectively. The indicators of the second method is to find maximum correlations group are factorial, independent (GDP in between groups of variables. In addition, the actual prices; Average monthly wage per method of canonical correlations makes it employee; Consumer price index; possible to reduce the volume of initial data Accounting Rate of the NBU; Population; due to the elimination of insignificant factors. Number of business entities; Number of legal Let's consider the possibilities of the entities) are defined as X1, X2, ... X7 method of canonical correlations in relation respectively. to the construction of a system of factors and The mathematical formalization of the performance indicators of the banking system method of canonical correlations in our case of Ukraine. consists in finding such linear combinations The analysis of the dynamics of the Uy = ii specified indicators to determine the i=1 of canonical variables та direction of cause-and-effect relationships Vx = jj leads to the conclusion that the variables of j=1 , so that the correlation between U the first group, which characterize the criteria and V is maximal. The dependence between for changing the performance indicators of canonical variables is measured by the the banking activity of Ukraine, are canonical correlation coefficient R. dependent variables (Number of banks; Using the method of canonical Number of banks with foreign capital; correlation (Fig. 2), we will check the Number of banks with 100% foreign capital; relationships between two sets of variables Assets of banks; Loans provided to clients; (vectors) Y and X. Loans provided to economic entities; Loans Management Theory and Studies for Rural Business and Infrastructure Development eISSN 2345-0355. 2022. Vol. 44. No. 4: 461-481 Article DOI: https://doi.org/10.15544/mts.2022.46 Figure 2. Canonical Analysis Summary for factor and resulting variables in the banking system of Ukraine *Source: own calculations depicted in Statistica 12. Analysis of the results in Fig. 2 has We obtained seven roots with a showed that as a result of the canonical canonical value of the correlation coefficient analysis, the total redundancy for the R = 0.9977. This coefficient is significant variables of the first set (Y1-Y12) is (because p <0.001) and shows the closeness 83.1932%, and the total redundancy for the between the canonical variables in the first variables of the second set (X1 - X7) is and second sets. These roots describe 86.6132%. This means that 83.1932% of the 90.2278% of the variance of the set of variations in the main performance indicators indicators of the banking system and 100% of the banking system are determined by the of the variance of the set of factors. These change in factors (X1 - X7). At the same results indicate a fairly strong relationship time, the main performance indicators of the between the variables of the two sets. banking system describe 86.6132% of the The significance of the canonical roots variation of their main factors. is checked using the Chi-Square test (Fig. 3). Figure 3. Significance of canonical roots (Chi-Square Tests) performance indicators of the banking system *Source: Compiled by the authors using the Statistica 12 toolkit. The value of the canonical correlation canonical root is greater than the value for coefficient R=0.997717 for the first other canonical roots (see Fig. 2). Further Iryna Tkachuk, Olha Hladchuk, Olena Vinnychuk consistent application of the criterion gives with the canonical factor Y10 (Funds of reason to consider only the first canonical economic entities, value: 0.946921), Y1 root with R = 0.997717. (Number of banks, value: -0.937803). We will describe the correlation Similarly, the factor structure of the right set between the variables of each set, taking into (Fig. 5) allows us to identify factors with account their factor structures according to higher loadings relative to the first canonical the first canonical root. The structure of the root. These are X1 (GDP in actual prices), factors of the left set shows (Fig. 4) that the X2 (Average monthly wage per employee), variables of the left set are highly correlated X5 (Population). Figure 4. Factor Structure, left set *Source: Compiled by the authors using the Statistica 12 toolkit. Figure 5 . Factor Structure, right set *Source: Compiled by the authors using the Statistica 12 toolkit. Based on the Canonical Weights of of the canonical models for the variables and the left (Fig. 4) and right (Fig. 5) sets, for the first canonical root (R = 0.997717): respectively, we will construct the equations Figure 6. Canonical Weights, left set *Source: Compiled by the authors using the Statistica 12 toolkit. Management Theory and Studies for Rural Business and Infrastructure Development eISSN 2345-0355. 2022. Vol. 44. No. 4: 461-481 Article DOI: https://doi.org/10.15544/mts.2022.46 Figure 7 . Canonical Weights, right set *Source: Compiled by the authors using the Statistica 12 toolkit. U =−0, 559874Y − 0, 267365Y + 0,166297Y + 1 2 3 + 0, 324147Y + 0,111637Y − 0, 206232Y + 4 5 6 + 0, 003970Y − 0,115512Y − 0, 444590Y − 7 8 9 − 0, 044340Y + 0, 427787Y + 0, 090214Y 10 11 12 V = 0, 067224 X + 1, 006036 X − 0, 061062 X + 0, 030408 X + 1 2 3 4 + 0, 080493X − 0, 022171X − 0,163265 X 5 6 7 On the basis of the constructed with several, which increases the objectivity equations, it is possible to analyze the of analytical conclusions as a basis for influence of each variable. The canonical making management decisions. correlation method also allows you to link a The relationship between the values of set of factor indicators not with one indicator canonical variables from the right and left of the banking system's performance, but sets is shown in fig. 8. Figure 8. Scatterplot of canonical correlations for the first canonical root *Source: Compiled by the authors using the Statistica 12 toolkit. There are no sharp outliers on the characteristic bends (for example, being obtained graph. In addition, the deviations located in the form of U or S curves around from the regression line do not form any the regression line). Therefore, it can be Iryna Tkachuk, Olha Hladchuk, Olena Vinnychuk concluded that there are no noticeable matrices characterizing the relationship violations of the main assumptions of the between variables. The matrix of the canonical analysis. relationship between the variables of bank Correlations within and between sets efficiency (Y) and factors (X) is presented make it possible to analyze correlation (Fig. 9). Figure 9. Correlations within and between sets* *Source: own calculations depicted in Statistica 12. Marked correlations are significant at p < ,05000. N=41 (Casewise deletion of missing data). Analysis of the matrix shows that and X6 (number of business entities) do not factor X1 (GDP at actual prices) affects such have a significant impact on the performance performance indicators of the banking system of the banking system of Ukraine. as Y1 (number of banks), Y2 (number of The results of the canonical analysis banks with foreign capital), Y4 (bank assets), confirmed that the relationship between the Y5 (loans to customers), Y6 (loans to selected performance indicators and selected economic entities), Y9 (liabilities of banks), determinants should be studied in terms of Y10 (funds of economic entities), and Y11 individual indicators of the banking system (funds of individuals); of Ukraine to form a system of scenarios for X2 (average monthly salary per employee) - the development of these indicators Y1 (number of banks), Y2 (number of banks depending on selected factors. Therefore, we with foreign capital), Y4 (bank assets), Y5 turn to the correlation-regression analysis and (loans to customers), Y6 (loans to investigate the dependencies of performance businesses), Y9 (liabilities of banks), Y10 indicators on selected factors. (funds of economic entities), and Y11 (funds Let us construct linear models of of individuals); multiple regression of the dependence of the X4 (NBU discount rate) - Y5 (loans to performance indicators of the banking system customers), and Y6 (loans to businesses); of Ukraine on the main macroeconomic X5 (Population) - Y1 (number of banks), Y2 factors that affect them: (number of banks with foreign capital), Y4 YX = + + jj (bank assets), Y5 (loans to customers), Y6 j=1 (loans to businesses), Y9 (liabilities of where is the corresponding performance banks), Y10 (funds of economic entities), indicator of the banking system of Ukraine, Y11 (funds of individuals); X7 (number of legal entities) - Y3 (Number is the appropriate selected factor that of banks with 100% foreign capital); Y8 hypothetically should affect the development (capital of banks); Y12 (net profit / loss); and dynamics of the banking system of Also, the analysis of the matrix (Fig. Ukraine, , ( , is the number 9) shows that factors X3 (consumer price of independent factors) are unknown index as a percentage of the previous month) Management Theory and Studies for Rural Business and Infrastructure Development eISSN 2345-0355. 2022. Vol. 44. No. 4: 461-481 Article DOI: https://doi.org/10.15544/mts.2022.46 Analyzing the dependence of the theoretical regression parameters, and is performance of the banking system of random theoretical deviation. Ukraine on the selected factors, it can be Using the least squares method, the theoretical parameters of regressions are argued that the selected set of factors to some estimated and the sample equations of linear extent affect the resulting indicators. All constructed regression equations are multiple regression of the dependence of the significant at a significance level of 0.05, the performance of the banking system on the corresponding coefficients of determination selected set of factors are constructed. Models of linear multiple regression in are more than 0.61. standardized form are also constructed, as The insignificance of some regression parameters is explained by the presence of a standardized regression parameters relationship between the included jm = 1, explanatory factors, i.e. the existence of the ( ) are dimensionless quantities and in phenomenon of multicollinearity (Table 1). contrast to the usual parameters of multiple In this case, the regression parameter b , j = 1, m regression , they can be compared estimates found using the method of least with each other. The larger the value of the squares become shifted (the property of the j Gauss-Markov theorem is violated), the parameter , the greater the influence on the variances of the parameter estimates dependent variable Y has factor. This (respectively, and standard parameter errors) content of standardized regression increase (leading to widening confidence parameters allows to use them when intervals and deteriorating accuracy), and eliminating insignificant factors, namely, the decrease t-statistics of regression parameters factors with the lowest value will be (which in turn generates incorrect j conclusions about the existence of the excluded from the model. (Grygorkiv, V., influence of the corresponding explanatory 2009). variable on the dependent variable). Table 1. Correlation matrix between selected factors Average Accounting GDP in actual Consumer price Number of monthly Rate of the Number prices, separately index, in % of business wage per NBU, or of legal by quarter (UAH the previous entities, employee, refinancing entities million) month units UAH rate,, % GDP in actual prices, separately by quarter (UAH 1 million) X1 Average monthly wage per employee, 0,94 1 UAH Consumer price index, in % of the -0,01 -0,08 1 previous month Accounting Rate of the NBU, or 0,24 0,14 0,27 1 refinancing rate,, % Population -0,81 -0,79 -0,25 -0,56 1 Number of business 0,10 0,10 0,08 0,19 -0,18 1 entities, units Number of legal 0,03 0,15 -0,31 -0,80 0,38 -0,23 1 entities *Source: Compiled by the authors in MS Excel. Population Iryna Tkachuk, Olha Hladchuk, Olena Vinnychuk Therefore, the values of correlation also explained by the general shortage of coefficients in Table 1 indicate the presence personnel and increased competition for an of direct relationships between such factors individual employee. After all, the population as “GDP in actual prices” and “Average of Ukraine is rapidly decreasing during the monthly wage per employee”; as well as entire period of independence [], while the inverse relations between such pairs of need for workers in the conditions of the factors as “GDP in actual prices” and development of the market economy is “Population”; “Population” and “Average constantly increasing. monthly wage per employee”; “Accounting The pair of factors “Accounting Rate of Rate of the NBU” and “Number of legal the NBU” and “Number of legal entities” are entities”. Let's consider the connections of also characterized by inverse relationships, each pair of factors in more detail. which is related to the nature of the “GDP in actual prices” and “Average accounting rate as an instrument of the monthly wage per employee”. These factors monetary policy of the NBU. Thus, its characterize direct relationships that are easy reduction leads to an increase in the amount to explain in theory: an increase in the of money supply, which creates additional average monthly salary per employee leads opportunities for attracting financial to an increase in the purchasing power of the resources (in particular, credit) for the population in general, and therefore to an creation and development of legal entities of increase in demand for goods, work, and all forms of ownership. services, which, in turn, stimulates the We believe that there is no real production of goods inland. At the same relationship between the pair of factors time, the development of production leads to “GDP in actual prices” and “Population”, the an increase in the wages of workers, as a tool revealed mathematical relationship is of the competitive struggle for workers in explained by the existence of two parallel conditions of total personnel shortage in processes, and not by regularity. Ukraine and an element of universal We will carry out correlation and motivation of workers. regression analyzes of the dependence of The inverse nature of the relationship performance indicators on a selected set of between the factors “Population” and macroeconomic factors. The results are “Average monthly wage per employee” is presented in Table 2. Table 2. Correlation coefficients between the resulting indicators and factors influencing the results of the banking system in Ukraine Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y8 Y9 Y10 Y11 Y12 -0,91 -0,87 0,30 0,76 0,74 0,73 0,27 0,36 0,75 0,90 0,84 0,38 X1 -0,89 -0,87 0,40 0,83 0,73 0,69 0,37 0,47 0,81 0,95 0,92 0,49 X2 -0,04 -0,07 -0,39 0,14 0,25 0,28 -0,19 -0,31 0,22 0,03 0,01 -0,36 X3 -0,44 -0,46 -0,34 0,07 0,55 0,64 -0,24 -0,66 0,15 0,16 0,05 -0,39 X4 0,91 0,92 0,11 -0,75 -0,87 -0,90 -0,02 -0,01 -0,80 -0,84 -0,75 -0,05 X5 -0,21 -0,19 -0,15 -0,03 0,00 0,08 0,39 -0,31 0,02 0,14 -0,06 -0,11 X6 0,26 0,31 0,72 0,09 -0,29 -0,44 0,53 0,79 -0,01 0,00 0,16 0,62 X7 *Source: Compiled by the authors using the Statistica 12 toolkit. The analysis of the results of the correlation coefficients) allows to exclude correlation and regression analysis of the individual macroeconomic factors from the relationships between the resulting indicators study. Table 3 contains data on the initial of the banking system of Ukraine and inclusion of factors in the model and on the selected macroeconomic factors (constructed inclusion of factors in new models. regressions and standardized parameters, Management Theory and Studies for Rural Business and Infrastructure Development eISSN 2345-0355. 2022. Vol. 44. No. 4: 461-481 Article DOI: https://doi.org/10.15544/mts.2022.46 Table 3. Factors included in the studied model before and after exclusion Initial inclusion of factors in the model New model after exclusion Y1 Number of banks, X1, X2, X3, X4, X5, X6, X7 X1, X2, X4, X5, X7 units Y4 Assets of banks, X1, X2, X4, X5, X6, X7 X2, X4, X5, X7 UAH million Y5 Loans provided to X1, X2, X4, X5, X6, X7 X4, X5, X6 clients, UAH million Y8 Capital of banks, X1, X2, X4, X5, X6, X7 X4, X7 UAH million Y9 Liabilities of banks, X1, X2, X4, X5, X6, X7 X4, X5, X7 UAH million Y 12 Net profit/loss, X1, X2, X3, X4, X5, X6, X7, Y1, Y4, Y8 X1, Y1, Y2, Y3 UAH million *Source: Compiled by the authors. So, after the transformation, the models part of such a performance variable as Y1 became significantly simpler. At the same (Number of banks) . time, it is worth noting that some factors A similar situation with regard to showing weak relationships with the performance indicators Y6 (Loans provided corresponding Y were left in the model, to business entities), Y7 (Loans provided to because the theory indicates that there should individuals), which are components of the be real relationships between them, which, performance variable Y5 (Loans provided to however, the analysis did not show, probably clients), as well as Y10 (Funds of business due to the existence of phenomena of entities) and Y11 (Funds of individuals), multicollinearity. which are components of the resulting Also, we consider it inappropriate to variable Y9 (Liabilities of banks). continue the analysis for such performance We will construct the relationship indicators as Y2 (Number of banks with equation between the performance indicators foreign capital) and Y3 (Number of banks and the selected factors of the new models with 100% foreign capital), since they are (Table 3), the results will be placed in Tables 4-9. Table 4. Equation of the relationship between Y1 (Number of banks) and selected macroeconomic factors Y1 (R=0,9815, R^2=0,9634, F(5,35)=184,18, p<0,0000) Y1 b* sb* b sb t p-value -88,7658 107,3714 -0,8267 0,4140 -0,2548 0,1041 0,0000 0,0000 -2,4483 0,0195 X1 -0,7098 0,1253 -0,0103 0,0018 -5,6650 0,0000 X2 0,0708 0,0615 0,5452 0,4731 1,1524 0,2570 X4 0,0203 0,0923 0,0000 0,0000 0,2205 0,8268 X5 0,4245 0,0706 0,0002 0,0000 6,0132 0,0000 X7 The model is adequate, the parameters at Х1, Х2, and Х7 are significant *Source: Compiled by the authors using the Statistica 12 toolkit. Iryna Tkachuk, Olha Hladchuk, Olena Vinnychuk Table 5. Equation of the relationship between Y4 (Assets of banks) and selected macroeconomic factors Y4 (R=0,8775, R^2=0,7699, F(4,36)=30,118, p<0,00000) Y4 b* sb* b sb t p-value 4748591,5624 1027537,6046 4,6213 0,0000 0,2902 0,2093 16,3877 11,8187 1,3866 0,1741 X2 -0,3528 0,1511 -10580,9611 4530,3292 -2,3356 0,0252 X4 -0,7341 0,2275 -0,0815 0,0253 -3,2275 0,0027 X5 0,0403 0,1743 0,0768 0,3321 0,2313 0,8184 X7 The model is adequate, the parameters at Х4 and Х5 are significant *Source: Compiled by the authors using the Statistica 12 toolkit. Table 6. Equation of the relationship between Y5 (Loans provided to clients) and selected macroeconomic factors Y5 (R=0,8868, R^2=0,77868, F(3,37)=45,42, p<0,00000) Y5 b* sb* b Sb t p-value 3542470,2930 300292,3307 11,7967 0,0000 0,1127 0,0924 2012,5771 1650,5885 1,2193 0,2304 X4 -0,8360 0,0922 -0,0553 0,0061 -9,0669 0,0000 X5 -0,1739 0,0778 -0,1149 0,0514 -2,2356 0,0315 X6 The model is adequate, the parameters at Х5 and Х6 are significant *Source: Compiled by the authors using the Statistica 12 toolkit. Table 7. Equation of the relationship between Y8 (Capital of banks) and selected macroeconomic factors Y8 (R=0,929, R^2=0,6286, F(2,38)=32,161, p<,00000) Y8 b* sb* b sb t p-value -133495,2897 74894,0688 -1,7825 0,0827 -0,0721 0,1650 -355,0923 813,1273 -0,4367 0,6648 X4 0,7340 0,1650 0,2297 0,0516 4,4476 0,0001 X7 The model is adequate, the parameters at X7 are significant *Source: Compiled by the authors using the Statistica 12 toolkit. Table 8. Equation of the relationship between Y9 (Liabilities of banks) and selected macroeconomic factors Y9 (R=0,8762, R^2=0,7678, F(3,37)=40,78, p<0,00000) Y9 b* sb* b sb t p-value 5711400,0686 609347,8712 9,3730 0,0000 -0,3715 0,1497 -10385,9788 4184,7575 -2,4819 0,0177 X4 -1,0341 0,0968 -0,1071 0,0100 0,0000 X5 10,6845 0,0779 0,1337 0,1383 0,2374 0,5826 0,5637 X7 The model is adequate, the parameters at X4 and X5 are significant *Source: Compiled by the authors using the Statistica 12 toolkit. Management Theory and Studies for Rural Business and Infrastructure Development eISSN 2345-0355. 2022. Vol. 44. No. 4: 461-481 Article DOI: https://doi.org/10.15544/mts.2022.46 Table 9. Equation of relationships between Y12 (net profit / loss) and selected macroeconomic factors Y12 (R=0,8200, R^2=0,6725, F(4,36)=40,78, p<0,00000) Y12 b* sb* b sb t p-value -107486,8426 49000,8056 -2,1936 0,0348 1,0737 0,3907 13,1703 4,7926 2,7480 0,0093 X2 0,4765 0,3149 403,3107 266,5721 1,5130 0,1390 Y1 -0,4962 0,1728 -0,1078 0,0375 -2,8714 0,0068 Y4 0,5386 0,1596 0,7123 0,2110 3,3749 0,0018 Y8 The model is adequate, the parameters at X2, Y4, and Y8 are significant *Source: Compiled by the authors using the Statistica 12 toolkit. Tables 4-9 demonstrate that at a Table 10 shows an idealistic version of significance level of 0.05, all constructed the events, according to which we regression equations are significant, so let's simultaneously manage all significant construct point and interval forecasts of factors, changing them by 5% in the direction individual values of the dependent variable. that ensures the achievement of a positive Construction of interval estimates was effect on the resulting indicator. Accordingly, performed at a significance level of 0.05. a simultaneous decrease by 5% of factor Taking into account the significance of indicators X1 (GDP) and X2 (Average the constructed regression equations, using monthly wage) and an increase of factor the scenario method, we will analyze the indicator X7 (number of legal entities) by 5% possibility of achieving positive changes in (the direction of change is determined by the the banking system of Ukraine by direction of the relationship between factor influencing the resulting indicators of each of and resulting indicators) can lead to growth the significant equations through the of the resulting indicator Y1 (Number of management of significant factor variables banks) to the indicator of 85 units. (16.5%) in (Tables 10-14). the confidence interval [75:95] units. Table 10. Point and interval estimates of the values of the performance indicator Y (Number of banks, units) with a simultaneous decrease by 5% of factors X1 and X2 and an increase of factor X7 by 5% The left The right boundary of boundary of GDP Average Accounting Population Number of Predicted the interval the interval monthly wage Rate of the legal entities estimate estimate NBU -95,0%CL +95,0%CL -5% -5% 6 41588354 +5% 85 75 95 +16,5% +3% +30% 952937,516 11455,19142 1465220 *Source: Compiled by the authors using the Statistica 12 toolkit. Table 11 shows an idealistic version of and X5 (Population) (the direction of change the events, according to which we is determined by the direction of the simultaneously manage all significant relationship between factor and resulting factors, changing them by 5% in the direction indicators) may lead to a decrease in the that ensures the achievement of a positive resulting indicator Y4 (Assets of banks, UAH effect on the resulting indicator. Accordingly, million ) to the figure of UAH 1,771,344.51 a simultaneous decrease by 5% of factor million. (-0.6%) in the confidence interval indicators X4 (Accounting Rate of the NBU) [1631145.5:1911543.6] UAH million. Iryna Tkachuk, Olha Hladchuk, Olena Vinnychuk Table 11. Point and interval estimates of the values of the performance indicator Y4 (Assets of banks, UAH million) with a simultaneous decrease of 5% of factors Х4 and Х5 The left The right boundary of boundary of Average monthly Accounting Population Number of Predicted the interval the interval wage Rate of the legal entities estimate estimate NBU -95,0%CL +95,0%CL 1771344,51 1631145,5 1911543,6 -5% -5% 12058,1 1395448 5,7 39508936,3 -0,6% -8,4% +7,3% *Source: Compiled by the authors using the Statistica 12 toolkit. Table 12 shows an idealistic version of is determined by the direction of the the events, according to which we relationship between factor and resulting simultaneously manage all significant indicators) may lead to an increase in the factors, changing them by 5% in the direction resulting indicator Y5 (Loans provided to that ensures the achievement of a positive clients, UAH million) to the figure of UAH effect on the resulting indicator. Accordingly, 1157212.8 million. (+22.9%) in the a simultaneous decrease by 5% of factor confidence interval [1091484.7:1222940.8] indicators X5 (Population) and X6 (Number UAH million. of business entities) (the direction of change Table 12. Point and interval estimates of the values of the performance indicator Y5 (Loans provided to clients, UAH million) with a simultaneous decrease of 5% of factors X5 and X6 The left The right boundary of boundary of Accounting Population Number of Predicted the interval the interval Rate of the business entities estimate estimate NBU -95,0%CL +95,0%CL -5% -5% 6 1157212,8 1091484,7 1222940,8 39508936,3 1844615,95 +22,9% +15,9% +29,8% *Source: Compiled by the authors using the Statistica 12 toolkit. Table 13 shows an idealistic version of is determined by the direction of the the events, according to which we relationship between factor and resulting simultaneously manage all significant indicators) may lead to an increase in the factors, changing them by 5% in the direction resulting indicator Y9 (Liabilities of banks, that ensures the achievement of a positive UAH million) to the figure of UAH effect on the resulting indicator. Accordingly, 1,614,165.5 million. (+2.44%) in the a simultaneous decrease by 5% of factor confidence interval [1505753.4:1722577.5] indicators X4 (Accounting Rate of the NBU) UAH million. and X5 (Population) (the direction of change Table 13. Point and interval estimates of the values of the performance indicator Y9 (Liabilities of banks, UAH million) with a simultaneous decrease of 5% of factors X4 and X5 The left The right boundary of boundary of Accounting Population Number of Predicted the interval the interval Rate of the legal entities estimate estimate NBU -95,0%CL +95,0%CL -5% -5% 1395448 1614165,5 1505753,4 1722577,5 5,7 39508936, +2,44% -4,44% +9,32% *Source: Compiled by the authors using the Statistica 12 toolkit. Management Theory and Studies for Rural Business and Infrastructure Development eISSN 2345-0355. 2022. Vol. 44. No. 4: 461-481 Article DOI: https://doi.org/10.15544/mts.2022.46 Table 14 shows an idealistic version of indicator Y4 (Assets of banks) by 5% (the events, according to which we direction of change is determined by the simultaneously manage all significant direction of the relationship between factor factors, changing them by 5% in the direction and resulting indicators) can lead to to the that ensures the achievement of a positive increase of the resulting indicator Y12 (Net effect on the resulting indicator. Accordingly, profit/loss, UAH million) to the indicator of a simultaneous increase by 5% of factor UAH 60,227.2 million. (+49.22%) in the indicators X2 (Average monthly wage) Y8 confidence interval [37058:83397.4] UAH (Capital of banks) and a decrease of factor million. Table 14. Point and interval estimates of the values of the performance indicator Y12 (Net profit/loss, UAH million) with a simultaneous 5% increase in the X2 and Y8 factors and a 5% decrease in the Y4 factor The left boundary The right of the interval boundary of the Average monthly Number of Predicted Assets of Capital of estimate interval estimate wage banks banks banks -95,0%CL +95,0%CL +5% 73 -5% +5% 60227,2 37058 83397,4 12661,0 1692525,2 216171,9 +49,22% -8,19% +106,62% *Source: Compiled by the authors using the Statistica 12 toolkit. However, such a variant of the scenario alternate management of significant factors analysis presented in Tables 10-14 is not only with other factors unchanged. Accordingly, idealistic, but also impossible, since the state- we can see that changes in such factors as X1 wide conjuncture forms certain internal “GDP” and X2 “Average monthly wage” do relationships between factor indicators, and, not lead to an increase in the number of therefore, achieving “pure” simultaneous banks in the banking system (the last value of changes in all significant factor indicators in the indicator of the number of banks as of practice is impossible. January 1, 2021 was 73 in total). At the same Therefore, scenario analysis is more time, an increase in factor variable X7 realistic and useful from a practical point of “Number of legal entities” by 5% leads to a view under the condition of managing significant increase in the indicator of the specific values of significant factor variables number of banks in the banking system (with other factors unchanged) (increase and (+5.17%). Such growth is quite logical and decrease by 5% from the last sample indicates that the increase in business activity observation). Let's consider in detail the within the state, the consequence of which is results of constructed estimates (tables 15- the increase in the number of legal entities 20). that are necessarily bank clients, leads to an Table 15 contains information about increase in the number of banks in the the expected value of the resulting indicator banking system, i.e. the load on the banking “Number of banks” under the condition of system remains unchanged. Iryna Tkachuk, Olha Hladchuk, Olena Vinnychuk Table 15. Point and interval estimates of the values of the performance indicator Y (Number of banks, units) The left The right boundary of boundary of GDP Average monthly Accounting Population Number of Predicted the interval the interval wage Rate of the legal entities estimate estimate NBU -95,0%CL +95,0%CL -5% 12058,1 6 41588354 1395448 64 55 74 952937,516 -11,8% -24,74% +1,14% +5% 12058,1 6 41588354 1395448 60 52 68 1053246,728 -17,53% -28,84% -6,22% 1003092,124 -5% 6 41588354 1395448 69 60 77 11455,19 -6,17% -17,17% +4,84% 1003092,124 +5% 6 41588354 1395448 56 46 66 12661,00 -23,16% -36,63% -9,69% 1003092,124 12058,1 6 41588354 -5% 48 37 58 1325675,6 -34,5% -48,85% -20,15% 1003092,124 12058,1 6 41588354 +5% 77 67 86 1325675,6 +5,17% -7,79% +18,13% *Source: Compiled by the authors using the Statistica 12 toolkit. Table 16 contains information about of bank assets as of January 1, 2021 was the expected value of the resulting indicator UAH 1,781,605.47 million). Such results “Assets of banks” under the condition of indicate that for the normal development of managing a significant factor with other the banking system of Ukraine, other factors unchanged. Accordingly, we can see parameters remaining unchanged, stability is that the management of factor X4 important, and a change in the discount rate “Accounting Rate of the NBU” in any is stressful for it and in any case leads to a direction leads to a decrease in bank assets reduction in bank assets (at least in the short (the last value of the indicator of the amount term). Table 16. Point and interval estimates of the values of the performance indicator Y4 (Assets of banks, UAH million) The left The right boundary of boundary of Average Accounting Population Number of Predicted the interval the interval monthly wage Rate of the legal entities estimate estimate NBU -95,0%CL +95,0%CL -5% 1601778,94 1522039,2 1681518,68 12058,1 41588354 1395448 5,7 -10,09% -14,57% -5,62% +5% 1595430,36 1518237,35 1672623,37 12058,1 41588354 1395448 6,3 -10,45% -14,78% -6,12% 1768170,28 1629109,45 1907231,11 -5% 12058,1 6 1395448 39508936,3 -0,75% -8,56% +7,05% +5% 1429039,01 1303854,54 1554223,48 12058,1 6 1395448 43667771,7 -19,79% -26,82% -12,76% *Source: Compiled by the authors using the Statistica 12 toolkit. Table 17 contains information on the increase in the resulting indicator by 21.68%. expected value of the resulting indicator Such a result can be explained by the fact “Loans provided to clients” under the that, since the reduction of the population condition of alternate management of means at the same time a decrease in the significant factors, with other factors number of bank customers (which means a unchanged. Accordingly, we can see that an decrease in the ability to dispose of their increase in factor X5 “Population” by 5% resources), banks choose the easiest option leads to a reduction of the resulting indicator for them to increase earnings - providing by 2.75%, and a decrease in the factor loans. indicator by 5% leads to a significant Management Theory and Studies for Rural Business and Infrastructure Development eISSN 2345-0355. 2022. Vol. 44. No. 4: 461-481 Article DOI: https://doi.org/10.15544/mts.2022.46 As a result of the management of factor business entities by 5% leads to an increase indicator X6 “Number of economic entities” in the volume of Loans provided to clients by there is an increase in the volume of loans 10.65%, as and in the case of a decrease in provided. Thus, an increase in the number of the “Population’ indicator, it means a business entities leads to additional demand decrease in the client base of banks, and from them for the credit product of banks, therefore forces them to use the issuance of a that is, to an increase in the volume of loans credit product as a means of generating granted, and a reduction in the number of income. Table 17. Point and interval estimates of the values of the performance indicator Y5 (Loans provided to clients, UAH million) The left The right boundary of boundary of Accounting Population Number of legal Predicted the interval the interval Rate of the entities estimate estimate NBU -95,0%CL +95,0%CL -5% 1146058,69 1080091,72 1212025,67 6 1941701 39508936,3 21,68% +14,67% +28,68% +5% 916016,06 887645,04 944387,07 6 1941701 43667771,7 -2,75% -5,76% +0,27% 916016,06 887645,04 944387,07 -5% 41588354 1844615,95 +10,65% +6,1% +15,2% 1019883,27 972965,85 1066800,69 +5% 2038786,05 +8,28% +3,3% +13,26% *Source: Compiled by the authors using the Statistica 12 toolkit. Table 18 contains information about in the capital of banks - by 2.41%. Thus, it the expected value of the resulting indicator can be assumed that the capital formation of of “Capital or banks” under the condition of banks is affected by other indicators, which, controlling a significant factor with other however, were not taken as a basis for our factors unchanged. Accordingly, we can see research. However, based on the calculations, that the change in factor X7 “Number of it is obvious that under the conditions of legal entities” without changes in another management of the selected macroeconomic significant factor “Accounting rate of the indicators and unchanged all other indicators, National Bank of Ukraine” does not give the it is possible to direct the state policy to desired result - the growth of banks' capital. increase the number of legal entities, because A reduction in the factor indicator by 5% the right interval limit of the confidence leads to a reduction in banks' capital by as interval still shows an increase in the capital much as 17.98%. However, the growth of the of banks by 4.04%. factor indicator is accompanied by a decrease Table 18. Point and interval estimates of the values of the performance indicator Y8 (Capital of banks, UAH million) The left The right boundary of boundary of Accounting Number of the interval the interval Predicted Rate of the legal estimate estimate NBU entities -95,0%CL +95,0%CL -5% 168868,38 159140,73 178596,04 1325675,6 -17,98% -22,7% -13,25% 200920,41 187642,79 214198,02 +5% 1465220,4 -2,41% -8,86% +4,04% *Source: Compiled by the authors using the Statistica 12 toolkit. Iryna Tkachuk, Olha Hladchuk, Olena Vinnychuk Table 19 contains information on the liabilities. As the population grows, current expected value of the resulting indicator consumption and household expenses will “Liabilities of banks” under the condition of increase, which may lead to a decrease in alternate management of significant factors, savings, which are transformed into bank with other factors unchanged. When factor deposits and their liabilities. Important X5 “Population” is changed while the other characteristics of the current state of significant factor “Number of legal entities” development of the Ukrainian economy are remains unchanged, there is no desired result its high level of shadowing and labor — an increase in bank liabilities. A reduction migration of the population, which can also of the factor indicator by 5% leads to an significantly distort statistical indicators and increase in the liabilities of banks by 2.24%. the results of their economic and However, the growth of the factor indicator mathematical analysis. In order to reduce the is accompanied by a reduction in the probability of exposing income obtained liabilities of banks — by 26.02%. As we illegally, the population tries to bypass the noted above, we discovered the inverse services of banks (in particular, opening nature of the relationship between the factors deposits with them), since banks are one of “Population” and “Average monthly wage the most important subjects of primary per employee”, therefore, even with a financial monitoring. It can also be assumed decrease in the population of Ukraine, the that the formation of banks' liabilities is amount of income received by Ukrainians influenced by other indicators, which, increased, which became an impetus for however, were not taken as a basis for this increasing citizens' investments in banks. study. which are an important component of banks' Table 19. Point and interval estimates of the values of the performance indicator Y9 (Liabilities of banks, UAH million) The left The right boundary of boundary of Accounting Population Number of Predicted the interval the interval Rate of the legal entries estimate estimate NBU -95,0%CL +95,0%CL -5% 41588354 1395448 1391478,05 1320160,84 1462795,25 5,7 -11,69% -16,22% -7,17% +5% 41588354 1395448 1385246,46 1316338,02 1454154,9 6,3 -12,09% -16,46% -7,72% 6 -5% 1395448 1611049,66 1503917,99 1718181,33 +2,24% -4,56% +9,04% 6 +5% 1395448 1165674,85 1121958,43 1209391,27 43667772 -26,02% -28,80% -23,25% *Source: Compiled by the authors using the Statistica 12 toolkit. Table 20 contains information about reduction in the net profit of banks. There is the expected value of the resulting indicator a direct and close relationship between the “Net profit/loss” under the condition of factor indicator “Bank capital” and the alternate management of significant factors effective indicator “Net profit”: a decrease in with other factors unchanged. So we can see the capital of banks by 5% results in a that an increase in the factor X2 “Average decrease in profit by 30.58%, while an monthly wage” by 5% leads to an increase in increase in the capital of banks by 5% leads net profit by 7.26%. Management of bank to an increase and banks' profits by 5.75%. assets does not give a positive result, because Thus, it can be concluded that the reduction the reduction of assets leads to an increase in of the total capital of banks is a significant profit, and their growth leads to a significant stress for the banking system. Management Theory and Studies for Rural Business and Infrastructure Development eISSN 2345-0355. 2022. Vol. 44. No. 4: 461-481 Article DOI: https://doi.org/10.15544/mts.2022.46 Table 20. Point and interval estimates of the values of the performance indicator Y12 (Net profit/loss, UAH million) The left boundary The right of the interval boundary of the Average monthly Number of Predicted Bank assets Bank capital estimate interval estimate wage banks -95,0%CL +95,0%CL -5% 73 1781605,47 205878,04 27411,98 2822,41 52001,56 11455,19 -32,09% -93,01% +28,84% +5% 73 1781605,47 205878,04 43292,87 16866,01 69719,72 12661,00 +7,26% -58,21% +72,73% 12058,10 73 -5% 205878,04 44954,89 23469,19 66440,58 1692525 +11,38% -41,85% +64,61% 12058,10 73 +5% 205878,04 25749,98 -3655,94 55155,92 1870685,74 -36,20% -109,06% +36,65% 12058,10 73 1781605,47 -5% 28020,55 2277,13 53763,96 195584,14 -30,58% -94,36% +33,20% 12058,10 73 1781605,47 +5% 42684,30 17977,13 67391,47 216171,94 +5,75% -55,46% +66,97% *Source: Compiled by the authors using the Statistica 12 toolkit. Conclusions Correlation and regression analysis and As a result of the conducted research, research on the dependence of the the main macroeconomic factors affecting performance indicators on the selected the results of the banking system of Ukraine factors demonstrated that the selected set of were determined, which is crucial for the factors affects the resulting indicators to one formation of a methodology for researching degree or another, as all constructed the banking system in general, identifying regression equations are significant. The obstacles to its development and developing presence of direct relationships between such effective mechanisms for improving its factors as “GDP in actual prices” and functioning. “Average monthly wage per employee” has A multifactorial model of the influence been revealed (since the increase in the of factors on the performance indicators of average monthly wage per employee leads to the banking system has been developed, and an increase in the purchasing power of the the method of canonical correlations has population in general); as well as inverse relationships between such pairs of factors as “Population” and “Average monthly wage been used to find the maximum correlations per employee” (which is explained by the between groups of variables. As a result, we general staffing deficit and increased found a close correlation between the change competition for an individual employee); in the macroeconomic indicators of Ukraine's “Accounting rate of the National Bank of development and the performance indicators Ukraine” and “Number of legal entities” of the banking system of Ukraine. The results (since the reduction of the accounting rate of of the canonical analysis have confirmed that the National Bank of Ukraine leads to an the relationship between the selected increase in the volume of the money supply, performance indicators of the banking system which creates additional opportunities for of Ukraine and macroeconomic indicators attracting financial resources for the creation should be investigated in terms of individual and development of legal entities of all forms indicators of the banking system of Ukraine of ownership); “GDP in actual prices” and in order to form a system of scenarios that “Population” (which can be explained by the will make it possible to predict their change existence of two parallel processes, and not depending on the selected factors. by real connections between these factors). Iryna Tkachuk, Olha Hladchuk, Olena Vinnychuk Using the scenario method, the limit of the confidence interval still shows an possibility of achieving positive changes in increase in the capital of banks by 4.04%. the banking system of Ukraine by Changes in the “Population” factor, influencing the resulting indicators of each of with the other significant factor “Number of the significant equations through the legal entities” unchanged, have no desired management of specific significant factor result — an increase in the resulting variables has been analyzed. “Liabilities of banks” indicator. Important A change in such factors as “GDP” and characteristics of the current state of “Average monthly salary” does not lead to an development of the Ukrainian economy are increase in the number of banks, at the same its high level of shadowing and labor time, an increase in the “Number of legal migration of the population, which can also entities” by 5% leads to a significant increase significantly distort statistical indicators and in the indicator of the number of banks the results of their economic and (+5.17%), since the increase in business mathematical analysis. activity within the state, an increase in the The resulting indicator “Net number of legal entities that are necessarily profit/loss” under the condition of increasing bank clients leads to an increase in the the factor “Average monthly salary” by 5% number of banks. leads to an increase in net profit by 7.26%. A change in the “Accounting Rate of Management of bank assets does not give a the NBU” in any direction leads to a decrease positive result, because the reduction of in “Bank Assets” (at least in the short term), assets leads to an increase in profit, and their since the stability of the regulator's policy is growth leads to a significant reduction in the important for the activity of banks. net profit of banks. Not all assets of banks An increase in the factor “Population” bring them profit, as they can be “non- by 5% leads to a reduction of the resulting working”, but expenses for them arise indicator "Loans provided to clients" by constantly (the need to pay interest on 2.75%, and a decrease in the factor indicator borrowed deposits, interbank loans, etc.), and by 5% leads to a significant increase in the also carry a certain level of risk, which resulting indicator by 21.68%. When the affects the amount of profit received by population decreases, the number of bank banks. A direct and close connection was clients also decreases (which means a found between the factor indicator “Capital decrease in the ability to dispose of their of banks” and the effective indicator “Net resources), so banks choose the easiest option profit”, therefore, the reduction of the for them to increase earnings, that is aggregate capital of banks is a significant providing loans. As a result of the stress for the banking system, and it is management of the factor indicator “Number necessary to direct the regulatory policy to a of business entities” there was an increase in stable and gradual growth of the capital of the indicator “Loans provided to clients”. banking institutions. The resulting indicator “Bank capital” The carried out correlation-regression under the condition of managing the and scenario analysis of the impact of significant factor “Number of legal entities” macroeconomic indicators on the does not provide the desired result - the performance of banks makes it possible to growth of the capital of banks. The capital state that it is worth conducting a state policy formation of banks is influenced by other to manage these factors in order to achieve indicators that we have not taken as a basis the desired result in the country's banking for this study. However, under the conditions system. It is necessary to manage a given set of management of the selected of factors that have been found to have a macroeconomic indicators and the invariance positive effect on the performance of banks, of all other indicators, it is possible to direct to promote the growth of banks' capital, the the state policy to the growth of the number number of legal entities, the average monthly of legal entities, because the right interval salary, the stability of the NBU discount rate, etc. Management Theory and Studies for Rural Business and Infrastructure Development eISSN 2345-0355. 2022. Vol. 44. No. 4: 461-481 Article DOI: https://doi.org/10.15544/mts.2022.46 It is also worth noting that this analysis significant volumes of labor migration of the has been carried out on the basis of official population, in which the actual number of the statistics, which may not take into account population may decrease, but the incomes many significant factors influencing the received by them entering Ukraine pass functioning of Ukrainian banks. In particular, through the banking system. the high level of shadowing of the Ukrainian The results of this study will serve as a economy and the reluctance to cooperate basis for further studies devoted to the with banks that are subjects of primary development of the banking system of financial monitoring, that is, they are obliged Ukraine, in order to find opportunities to to be the first to expose suspicious improve the conditions of functioning of transactions (based on the sources of origin Ukrainian banks, which are a powerful of funds and their volumes). As well as source of development of the entire economy. References Grygorkiv, V. S. (2009). Ekonometrika: Liniini modeli parnoyi ta mnozhynnoyi regresiyi [Econometrics: Linear models and multiple regression pair], Chernivtsi, Ukraine, 224p. Hotelling, H. (1936), Relations between two sets of variates. Biometrika, Vol. 28, no. 3/4, pp. 321–377. https://doi.org/10.2307/2333955 Nguyen Phu Ha (2021). Impact of macroeconomic factors and interaction with institutional performance on Vietnamese bank share prices. Banks and Bank Systems, 16 (1), 127-137. doi:10.21511/bbs.16(1).2021.12 Setyo Tri Wahyudi, Rihana Sofie Nabella and Kartika Sari (2021). Measuring the competition and banking efficiency level: a study at four commercial banks in Indonesia. Banks and Bank Systems, 16 (1), 17-26. doi:10.21511/bbs.16(1).2021.02 State Statistics Service of Ukraine. Statistic materials. Retrieved from: http://www.lv.ukrstat.gov.ua/dem/piramid/all.php Tkachuk I. (2017). Asset operations of Ukrainian banks on the current stage of banking system d evelopment. Banks and Bank Systems, 12(1-1), 119-127. doi:10.21511/bbs.12(1-1).2017.04 Wasfi Al Salamat, Mohammad Q. M. Momani and Khaled Batayneh (2021). Firm-specific, macroeconomic factors and stock price risk for Jordanian banks. Banks and Bank Systems, 16(3), 166-172. doi:10.21511/bbs.16(3).2021.15 Yarovy A., Strakhov E. (2015). 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Journal
Management Theory and Studies for Rural Business and Infrastructure Development – de Gruyter
Published: Dec 1, 2022
Keywords: bank; performance indicators of banks; macroeconomic indicators; factors influencing banking activity; G 21; O 11