The Relationship between Economic Growth and Banking Sector

Development in Ukraine

SVITLANA KACHULA

Department of Finance, Banking and Insurance

Dnipro State Agrarian and Economic University

Serhiy Yefremov street 25, Dnipro 49000

UKRAINE

MAKSYM ZHYTAR

Vice-rector for scientific and pedagogical work

Private institution of higher education "International European University"

Akademika Glushkova Avenue building 42 V Kyiv 03187

UKRAINE

LARYSA SIDELNYKOVA

Department of Finance, Accounting and Taxation

Kherson National Technical University

Berislavske shosse 24 Kherson 73008

UKRAINE

OKSANA PERCHUK

Department of Finance, Accounting and Taxation

Hryhorii Skovoroda University in Pereiaslav

Sukhomlyns’koho street 30 Pereiaslav 08401

UKRAINE

OLENA NOVOSOLOVA

Department of Finance, Accounting and Taxation

Kherson National Technical University

Berislavske shosse 24 Kherson 73008

UKRAINE

Abstract: The paper examines the relationship between economic growth and banking sector indicators in

Ukraine. The constructed empirical model revealed a positive impact of bank deposits on real GDP growth. The

causal relationships between economic growth in Ukraine and the performance of the banking sector are

analyzed using the Granger Causality Test. It is established that banking deposits Granger-cause GDP, while

banking credits do not, but GDP has an effect on banking credits. It is noted that the banking sector of Ukraine

does not play a significant role in the redistribution of capital in the intersectoral and spatial dimensions. It is

defined limiting factors of lending to the private sector and ways to increase the deposit base of banks.

Key-Words: economic growth, GDP, banking sector, banking credits, banking deposits, banking investments.

Received: April 25, 2021. Revised: December 5, 2021. Accepted: January 12, 2022. Published: January 14, 2022.

1 Introduction

Economic growth is a necessary condition for

solving socio-economic problems, such as raising

the population's living standards, ensuring the

welfare of the nation. As it is noted by Bil and

Mulska (2020) [1]: “Limited access to material,

socio-economic, and financial benefits leads to the

processes of marginalization of households,

communities, and regions of the country".

Welfare as a social measuring factor is a strategic

dominant of economic growth. Thus, economic

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growth is the crucial aspect of any country's

macroeconomic strategy.

The impact of the financial sector on economic

growth has remained the subject of scientific debate

for decades. The financial sector is an integral part

of the economic system of the state. It plays a

significant role in the redistribution of financial

resources between economic agents.

The financial sector of Ukraine has remained

bank-centric for many years, as of the end of 2020

the share of banking assets in total assets of the

financial sector was 89.6% (Table 1). As for the

level of the financial sector development in Ukraine,

it still remains rather weak. Fig. 1 shows the ratio of

total assets of relevant financial institutions to GDP

in Ukraine.

To compare, at the end of 2019 the Polish

financial landscape was made up of 30 commercial

banks, 538 cooperative banks, and 32 branches of

credit institutions. The size of the banking sector in

terms of GDP (gross domestic product) was 88.3%

[2].

Table 1. Assets structure of the Ukrainian financial sector, %

Financial institution

2015

2016

2017

2018

2021

2020

Banks

88.5

88.8

91.5

90.7

89.4

89.6

Insurance companies

4.3

3.9

2.8

3.0

2.9

2.6

Private pension funds

0.1

Financial companies

6.8

5.3

5.9

7.3

7.4

Pawnshops

0.2

Credit unions

0.1

Source: National Bank of Ukraine [3]

Fig. 1: Assets of financial institutions in Ukraine, % of GDP

Source: National Bank of Ukraine [3]

Fig. 2: Number of banking institutions in Ukraine, units

Source: National Bank of Ukraine [3]

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Fig. 3: Financial intermediation of the Ukrainian banking sector, %

Source: National Bank of Ukraine [3]

It should be noted that the banking sector of

Ukraine has undergone a difficult period of

formation and development. Fig. 2 shows the

number of functioning banking institutions in

Ukraine in 2002-2020. As of January 1, 2021, 74

institutions were operating in the country. Since

2013, more than 100 banks have been declared

insolvent and withdrawn from the market. The

reasons for this were not only military and political

instability and changes in the economic priorities of

the state but also the problems that existed in the

banking system since 2008-2009. Significant

quantitative changes were accompanied by the

restructuring of the banking sector, increasing

requirements for compliance with activity

standards, addressing institutional and functional

problems accumulated in all previous years.

The sharp decline in lending since 2015 is the

result of negative expectations of economic entities

due to economic and military-political events that

led to the outflow of deposits in the banking sector,

reduced solvency of borrowers and a significant

increase in the risk of non-repayment of borrowed

funds.

However, the policy of 'cleansing' the banking

sector resulted in a significant reduction in banking

assets, which became quite noticeable in 2017-2020

Accordingly, it limited opportunities for lending to

the economy. Fig. 3 shows the ratio of bank

deposits to GDP, bank lance to GDP and bank

credits to bank deposits in Ukraine. The withdrawal

of troubled banks from the market increased the

burden on the Deposit Guarantee Fund, which was

forced to borrow funds in the financial market to

make payments.

Another feature of the development of the

banking sector of Ukraine in 2019-2020 was a

significant reduction in the ratio of loans/deposits.

The reason for this was a considerable increase in

banking investments in government bonds of

Ukraine due to fairly high interest rates.

This paper empirically examines the relationship

between the development of the banking sector and

economic growth. The algorithm of our study is

structured as follows: Section II is focused on a

review of the literature on the relationship between

the development of the banking sector and

economic growth. Section III describes the data

sources and methodology for studying the

relationship between the development of the

banking sector and economic growth in Ukraine.

Section IV presents the results of the empirical

model. Section V represents the findings of the

study.

2 Literature Review

The relationship between the banking sector

indicators and economic growth has been studied

by many Ukrainian and foreign scholars. In the

early 20th century, Schumpeter (1911) [4] proved

the positive influence of banks on the growth of

national income through directing funds to the

implementation of the most effective projects.

In the late 1960s, Goldsmith (1969) [5] studied

the relationship between financial and economic

development of 35 countries within the period from

1860 to 1963. He derived the Financial Interrelation

Ratio defined as the value of all financial assets

over GNP. Goldsmith was the first to empirically

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establish a unidirectionality of the economic growth

pace and financial development.

McKinnon (1973) [6], studying the relationship

between the level of economic development and the

financial sector in the post-World War II period for

countries such as Argentina, Brazil, Chile,

Germany, Indonesia, Korea, and Taiwan, concluded

that the countries where financial the sector is

functioning better provide higher economic growth

rates as well. As the main reason for this

phenomenon, the scientist considered financial

liberalization, which allows intensifying the

activities of financial intermediaries and, thus, more

effectively redistribute investment to productive

areas.

Levine, Zervos (1998) [7] analyzed the

indicators of the banking sector, stock market, and

economic development in 47 countries from 1976

to 1993. They found that the growth of stock

market liquidity and the development of the

banking sector are positively correlated with

economic growth, capital accumulation, and

productivity growth. Scientists have determined

that one standard-deviation increase in initial stock

market liquidity and the estimated coefficient on

Bank Credit would have increased real GDP per

capita by 31 percent in 18 years, the capital stock

per person would have been 29 percent higher, and

productivity would have been 24 percent greater.

Liang, Reichert (2006) [8], assessing the

relationship between financial development and

economic growth in 70 Emerging and Developing

Countries and 20 Advanced Countries in the period

between 1960 and 2000, found that Granger

causality results showed a stronger relationship in

Emerging and Developing Countries. This confirms

the hypothesis of the "demand-following"

relationship. Herewith, the globalization of

financial markets and the development of

international trade help to balance the tightness of

the relationships between the studied variables in

Emerging / Developing Countries and Advanced

Countries. The authors also state that the direction

of the relationships may change depending on the

stage of the economic cycle.

However, scientific thought provides other

views on the role of the financial sector in ensuring

economic growth. Thus, Robinson (1952) [9]

believed that the development of financial markets

is only a consequence of general economic growth.

It is economic growth that creates the demand for

financial services; thus, the financial sector

responds more to the needs of the real sector of the

economy rather than causing it to grow.

Lucas (1988) [10] noted that the impact of the

financial sector on economic growth is somewhat

exaggerated. The researcher considered increasing

investment in scientific development and human

capital to be the main determinants of economic

growth.

Stiglitz (2000) [11], examining the impact of the

financial sector on economic growth, concludes that

the liberalization of capital markets does not

promote economic growth, but produces instability,

which negatively affects it. The scientist sees the

cause of financial instability in short-term capital

movements, resulting in a discrepancy between

private and social returns and risks. Stiglitz notes

that capital flows are markedly procyclical,

exacerbating economic fluctuations when they do

not actually cause them.

Cameron (1967) [12] believed that financial

systems may be both growth-inducing and growth-

induced, with the key being the quality of financial

services and the efficiency of their provision.

Effective financial intermediaries are able to better

redistribute resources in the economy and

accelerate innovation development.

Empirical studies of the relationship between

financial development and economic growth in

Ukraine include the research by Paranytsya (2013)

[13], who studied the impact of the financial sector

on the industrial sector during 2000-2011. In

general, the scientist concluded that the indicator of

financial depth has a negative impact on the growth

of industrial production in Ukraine.

Ukrainian scientist Korneyev (2014) [14]

assessed the relationship between financial

development and economic growth during 1991-

2021 based on the data from 15 countries close to

Ukraine in terms of economic development, in

particular: Moldova, Romania, Latvia, Lithuania,

Estonia, Hungary, Slovakia, Czech Republic,

Bulgaria, Armenia, Azerbaijan, Poland,

Kazakhstan, and Georgia. According to his

findings, in the long run, there is a weak negative

connection between the financial development

index and economic growth, i.e. the growth of the

financial development index slows down GDP

growth per capita.

Ukrainian scientists Zveryakov and Zherdets'ka

(2017) [15] studying causal links between Ukraine's

economic growth and the development of the

banking system found that the results of empirical

research are sensitive to the stage of the economic

cycle: if the period 2008-2009 was studied, the

results showed the impact of economic

development on the banking sector, and in the

period 2006-2008, the direction of causation was

opposite.

Thus, empirical studies of the relationship

between indicators of the banking sector and

economic growth are divided into the following

main areas:

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- the development of the banking sector

determines economic growth;

- economic growth determines the level of the

banking sector development;

- lack of relationship between the banking sector

and economic growth.

3 Methodology

3.1 The Research Model

According to the endogenous model of economic

growth of Barro, and Sala-i-Martin (2004) [16]

GDP growth rate depends on the influence of

certain institutional factors.

The main indicator that measures economic

growth is the change in real GDP.

In our research of the relationship between

economic growth (EG) and banking sector

development, we estimate the standard growth

equation:

EG = f(BC, BD, BI)

EGt = α + β1×BCt-1 + β2×BD t-1 + β3×BI t-1 + β4×

BC_BD t-1 + εt, (1)

where EGt is economic growth measured as the

annual growth rate of the real GDP;

BCt-1 - banking credits provided to

economic sectors;

BD t-1 - banking deposits;

BI t-1 - banking investments;

BC_BD t-1 – the ratio of bank credits to

deposits;

α – intercept or constant;

β1, β2, β3 – coefficients;

εt - residual errors.

The least squares method was used to construct

the regression equation.

3.2 Source of Data

The study used the data from the State Statistics

Service of Ukraine and the National Bank of

Ukraine. Real GDP growth was used as an indicator

of GDP. BC is the amount of bank credits to

residents,% of GDP. BD is the amount of bank

deposits of residents and non-residents,% of GDP.

BI is the amount of bank investments (except for

the National Bank of Ukraine) in securities of

residents, including shares,% of GDP. BC_BD is

the ratio of bank credits to deposits,%.

In our research, we estimate the standard growth

equation using a panel data set over the period of

2002-2020. Calculations of model parameters were

performed using Eviews 9.0.

4 Research Findings and Discussion

Table 2 shows the input data for the construction of

the regression model.

Table 2. Input data

GDP

BC_BD

01.01.2003

5,3

18,7

17,8

1,8

104,9

01.01.2004

9,5

25,4

24,1

2,4

105,5

01.01.2005

11,8

25,7

25,2

2,3

101,9

01.01.2006

3,1

32,5

32,0

2,6

101,6

01.01.2007

7,6

45,1

35,7

2,5

126,2

01.01.2008

8,2

59,2

41,7

3,0

142,2

01.01.2009

2,2

77,4

42,7

3,7

181,3

01.01.2010

-15,1

79,2

41,1

3,8

192,6

01.01.2011

4,1

67,7

40,9

6,9

165,6

01.01.2012

5,5

60,9

39,9

6,2

152,7

01.01.2013

0,2

57,9

42,8

6,8

135,2

01.01.2014

0,0

62,6

48,2

9,3

129,8

01.01.2015

-6,6

65,1

45,3

9,6

143,8

01.01.2016

-9,8

49,6

38,2

5,7

129,7

01.01.2017

2,4

41,9

35,8

11,2

117,1

01.01.2018

2,5

34,1

31,2

12,1

109,3

01.01.2019

3,4

30,2

26,9

11,8

112,3

01.01.2020

3,2

24,5

27,5

9,5

89,0

01.01.2021

-4,2

22,6

32,7

14,6

69,2

Table 3 shows the result of unit root test for

selected variables.

Table 3. Augmented Dickey Fuller Test

Variables

ADF values

Test

critical

values

5% level

Sig. level

2st

difference

GDP

0.0018

-4.979623

-3.098896

0.0045

-4.624554

-3.144920

0.0288

-3.413150

-3.098896

0.0001

-6.843625

-3.081002

BC_BD

0.0058

-4.256288

-3.081002

The result indicates that all variables are

stationary at the second difference.

Table 4 presents the descriptive statistics of the

research model. Thus, the average value of GDP

growth is 1.56%. The average ratio of bank credits

to deposits is 130.04%, and the maximum is

192.59%. The Jarque-Bera statistics are all

statistically significant at the 1% level, indicating

that the variables follow a normal distribution.

Table 5 shows the correlation matrix of the

selected variables used in the study.

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Table 4. Descriptive statistics

GDP

BC_BD

Mean

1.555556

47.64183

35.38176

6.173938

130.0382

Median

2.800000

47.32853

37.01389

5.975665

127.9789

Maximum

11.80000

79.19187

48.22394

12.10203

192.5875

Minimum

-15.10000

18.70068

17.82251

1.837828

89.03309

Std. Dev.

6.823594

19.31811

8.426874

3.605987

28.82843

Skewness

-0.883852

0.081506

-0.458370

0.343005

0.704603

Kurtosis

3.381554

1.696085

2.205337

1.654234

2.643620

Jarque-Bera

2.452769

1.295076

1.103925

1.711271

1.584653

Probability

0.293351

0.523333

0.575819

0.425013

0.452790

Sum

28.00000

857.5529

636.8717

111.1309

2340.688

Sum Sq. Dev.

791.5444

6344.221

1207.207

221.0534

14128.34

Observations

Table 5. Correlation Matrix

GDP

BC_BD

GDP

1.000000

-0.539221

-0.592834

-0.355003

-0.381463

-0.539221

1.000000

0.906904

0.012896

0.939420

-0.592834

0.906904

1.000000

0.198303

0.711317

-0.355003

0.012896

0.198303

1.000000

-0.133817

BC_BD

-0.381463

0.939420

0.711317

-0.133817

1.000000

Four independent variables exhibit a negative

correlation with GDP, with the correlation between

bank deposits and GDP reporting the largest value

(0.593). The results indicate that there is a close

relationship between bank credits and bank deposits

as well as between bank credits and the ratio of bank

credits to bank deposits. It shows the existence of

multicollinearity between variables.

Fig. 4: Correlation Matrix

Table 6 presents The Regression Model Results.

Table 6. Multivariate Regression Model

Variable

Coefficient

Std. Error

t-Statistic

Prob.

-4.306045

1.086432

-3.963475

0.0016

4.393384

1.222695

3.593196

0.0033

-0.594807

0.302199

-1.968260

0.0707

BC_BD

1.696958

0.435317

3.898209

0.0018

-165.7393

47.34508

-3.500667

0.0039

R-squared

0.733738

Mean dependent var

1.555556

Adjusted R-

squared

0.651811

S.D. dependent var

6.823594

S.E. of

regression

4.026437

Akaike info criterion

5.853774

Sum squared

resid

210.7585

Schwarz criterion

6.101100

Log

likelihood

-47.68397

Hannan-Quinn criter.

5.887877

F-statistic

8.956003

Durbin-Watson stat

2.519168

Prob(F-

statistic)

0.001061

The structural parameter estimate obtained

implies that 73,37% of GDP is explained by selected

variables. F test is 8.956 and the probability of F test

value 0.001 is less than the significant level of 5%.

Considering that the probability of all variables is

less than 5%, we can reject the null hypothesis and

accept the alternative hypothesis:

- H0: indicator equals zero (reject);

- H1: indicator does not equal zero (accept).

Table 5 reveals a significant positive relationship

between banking deposits and GDP. Thus, an

increase in banking deposits by 1 deviation will

increase GDP by 4.39:

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EG = α – 4,306045×BC + 4,393384×BD –

– 0,594807×BI + 1,696958 × BC_BD –

– 165,7393, (2)

Lending to the private sector in Ukraine is carried

out in two main areas - lending to the non-financial

sector (business entities) and lending to households.

The lack of a positive impact of bank lending on real

GDP growth can be explained by the fact that banks

in Ukraine, wanting to reduce credit risks, prefer

short-term lending to economic entities. Such credits

are normally used to cover current needs, rather than

to finance investment projects and economic

expansion. For many years, Ukrainian banks have

experienced a shortage of long-term resources

resulting in an imbalance between the terms of

attracting liabilities and placing them in assets. The

opportunities for economic development are

threatened by low level of credit activity. Lack of

own funds and limited lending lead to a reduction in

business activity, loss of markets. As a result, there

are problems with employment and job creation,

which ultimately leads to social tensions. The low

efficiency of economic entities directly affects the

amount of budget resources of the state.

At the same time, the credit portfolio of Ukrainian

banks contains a significant share of non-performing

loans, which significantly affects the financial

performance of the banking sector. Thus, the

Ukrainian banking sector is unable to perform its key

task of ensuring effective redistribution of capital in

cross-sectoral and spatial dimensions.

Breusch-Godfrey Serial Correlation LM Test

showed the absence of autocorrelation (Table 7).

Table 7. Breusch-Godfrey Serial Correlation LM

Test

F-statistic

1.199150

Prob. F(2,11)

0.3380

Obs*R-

squared

3.222006

Prob. Chi-Square(2)

0.1997

Variable

Coefficient

Std. Error

t-Statistic

Prob.

-0.161749

1.077586

-0.150103

0.8834

0.258983

1.217170

0.212775

0.8354

-0.124073

0.312777

-0.396682

0.6992

BC_BD

0.037755

0.431005

0.087598

0.9318

-5.573573

46.91334

-0.118806

0.9076

RESID(-1)

-0.373060

0.289849

-1.287084

0.2245

RESID(-2)

-0.376022

0.311061

-1.208835

0.2521

R-squared

0.179000

Mean dependent var

2.98E-14

Adjusted R-

squared

-0.268818

S.D. dependent var

3.521017

S.E. of

regression

3.966137

Akaike info criterion

5.878764

Sum

squared

resid

173.0327

Schwarz criterion

6.225019

Log

likelihood

-45.90887

Hannan-Quinn criter.

5.926508

F-statistic

0.399717

Durbin-Watson stat

1.931873

Prob(F-

statistic)

0.864286

The null hypothesis of the model is that there is

no serial correlation. The alternative hypothesis is

that exists autocorrelation. In Table 7, it failed to

reject the null hypothesis because the p-value is more

than 0.05 up to the specified lag of 2 (0,2521). The

Breusch-Godfrey Correlation LM test exhibits

probability values of 0.3380 for F-statistics and

0.1997 for R-Squared that are significant to accept

the null hypothesis implying that there is no

autocorrelation in the residuals generated from the

regression model. Therefore, the model is valid as it

is not victimized by sequential correlation throughout

the series.

At the next stage, we will perform a Granger

Causality test for estimating the relationship between

economic growth and banking sector development in

Ukraine (Table 8).

Н1: H0 hypothesis implies that banking sector

development does not Granger-cause GDP. If Prob.

is greater than 0.05 we accept H0. It means the lack

of causality. If Prob. is less than 0.05 we reject H0. It

means that there is Granger causality running from

banking sector development to economic growth

(Supply-leading relationship).

Н2: H0 hypothesis implies that GDP does not

Granger-cause banking sector development. If Prob.

is greater than 0.05 we accept H0. It means the lack

of causality. If Prob. is less than 0.05 we reject H0. It

means that there is Granger causality running from

economic growth to banking sector development

(Demand-following relationship).

The results of Granger Causality models reveal

that banking deposits Granger-cause GDP in the 1-

lag model, herewith, in the 2-lag model banking

deposits also have an impact on GDP, although

therelationship is weak. Thus, the growth of GDP in

Ukraine is facilitated by an increase in savings in the

economy.

However, banking credits provided to economic

sectors do not Granger-Cause GDP but GDP affects

banking credits in the 1-lag model. This indicates

that in Ukraine there are no effective mechanisms for

transforming the savings of the population into an

investment resource for economic development,

which means that the functioning of the banking

sector as a financial intermediary still remains

inefficient.

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5 Conclusion

The main purpose of this work is to study the impact

of the banking sector on the economic growth in

Ukraine. A standard growth equation using a panel

data-set over the period of 2002-2020 was used for

the empirical study. We used four variables to

measure the banking sector level: BC is the amount

of bank loans to residents, % of GDP, BD is the

amount of bank deposits of residents and non-

residents, % of GDP, BI is the amount of bank

investments (except for the National Bank of

Ukraine) in residents' securities, including shares, %

of GDP, BC_BD is the ratio of bank credits to

deposits, %. The obtained equation reveals a

significant positive relationship between banking

deposits and GDP. Thus, an increase in banking

deposits by 1 deviation will increase GDP by 4.39.

At the same time, there is a negative impact of

banking credits on GDP.

The assessment of the causal links between GDP

dynamics and indicators of the banking sector

development using the Granger Causality Test

established that banking deposits Granger-cause

GDP. Accordingly, the increase in savings

contributes to economic growth in Ukraine.

Important areas of increasing deposits by the

banking sector of Ukraine are: launching new types

of deposit services, exemption passive income from

personal income tax and military collection,

increasing the minimum amount of deposit guarantee

for individuals, which will strengthen public

confidence in banking institutions, increase reliability

of banking sector by bringing the standards of

banking in line with the requirements of Basel III.

Granger Causality Test shows that banking credits

do not Granger Cause GDP but GDP has an effect on

banking credits in the 1-lag model. This confirms the

conclusion that in Ukraine the development of the

economy affects the amount of bank lending and not

vice versa. Therefore, limiting factors of lending to

the private sector in Ukraine are significant

devaluation risks, inflation expectations, low level of

confidence in the banking system, unsatisfactory

quality of bank management in the field of loan

portfolio management, reduction of real incomes,

high probability of default crisis.

Future work concerns analysis of the relationship

between indicators of the real sector and economic

growth in Ukraine.

Table 8. Granger Causality Test

Null Hypothesis:

Lag 1

Lag 2

Lag 3

Obs

F-Statistic

Prob.

Obs

F-Statistic

Prob.

Obs

F-Statistic

Prob.

BC does not Granger Cause GDP

4.36852

0.0541

1.45292

0.2722

0.96517

0.4504

GDP does not Granger Cause BC

8.65521

0.0101*

2.38232

0.1345

2.14663

0.1644

BD does not Granger Cause GDP

6.18349

0.0252*

4.57628

0.0333*

1.79824

0.2175

GDP does not Granger Cause BD

1.96007

0.1818

0.53438

0.5994

0.11786

0.9473

BI does not Granger Cause GDP

1.56844

0.2296

0.93767

0.4184

0.27365

0.8430

GDP does not Granger Cause BI

1.96849

0.1810

0.91129

0.4281

0.65148

0.6017

BC_BD does not Granger Cause

GDP

1.33136

0.2666

0.56009

0.5854

0.67912

0.5866

GDP does not Granger Cause

BC_BD

3.77504

0.0710

1.27693

0.3142

0.98205

0.4435

* If Prob. is greater than 0.05 we accept H0

WSEAS TRANSACTIONS on BUSINESS and ECONOMICS

DOI: 10.37394/23207.2022.19.21

Svitlana Kachula, Maksym Zhytar,

Larysa Sidelnykova, Oksana Perchuk,

Olena Novosolova

E-ISSN: 2224-2899

229

Volume 19, 2022

References:

[1]. Bil, M. M., Mulska, O. P. (2020). Dobrobut

yak dominanta ekonomichnoho zrostannia:

kontseptualno-metodychnyi bazys. Modern

Economic, 23, 6-12. [in Ukrainian].

[2]. Banking in Europe: EBF Facts & Figures

(2020). European Banking Federation.

https://www.ebf.eu/wp-

content/uploads/2020/11/EBF_043537-

Banking-in-Europe-EBF-Facts-and-Figures-

2020.pdf.

[3]. Supervisory statistics. National Bank of

Ukraine.

https://bank.gov.ua/ua/statistic/supervision -

statist.

[4]. Schumpeter, J. (1911). The Theory of

Economic Development. (3nd ed.). Oxford

University.

[5]. Goldsmith, R. W. (1969). Financial

Structure and Economic Development. Yale

University Press.

[6]. McKinnon, R. (1973). Money and Capital in

Economic Development. Brookings

Institution.

[7]. Levine, R., Zervos, S. (1998). Stock Markets,

Banks, and Economic Growth. The American

Economic Review, Vol. 88, No. 3, 537–558.

[8]. Liang, H.-Y., Reichert, A. (2006). The

Relationship Between Economic Growth and

Banking Sector Development. Banks and

Bank Systems, Vol. 1, Issue 2, 20-35.

[9]. Robinson, J. (1952). The Generalisation of

the General Theory, in the Rate of Interest,

and Other Essays. (2nd Ed.). Macmillan.

[10]. Lucas, R. (1988). On the Mechanics of

Economic Development. Journal of

Monetary Economics, Vol. 22, 3-42.

[11]. Stiglitz, J. E. (2000). Capital Market

Liberalization, Economic Growth, and

Instability. World Development, Vol. 28, No.

6, 1075-1086.

[12]. Cameron, R., Crisp, O., Patrick, H. T.,

Tilly, R. (1967). Banking in the Early Stages

of Industrialization. Oxford University Press.

[13]. Paranytsya, N. (2013). Vplyv variatsii

koniunktury finansovoho rynku na

promyslovyi sektor Ukrainy. Ekonomika ta

derzhava, 10, 90-92. [in Ukrainian].

[14]. Korneyev, M. (2014). Zasady

vzaiemozviazku mizh rivnem finansovoho

rozvytku ta ekonomichnym zrostanniam.

Investytsii: praktyka ta dosvid, 17, 37-41. [in

Ukrainian].

[15]. Zveryakov, M., Zherdets’ka, L. (2017).

Bankivskyi ta realnyi sektory ekonomiky

Ukrainy: otsinka vzaiemozviazkiv i

determinant rozvytku. Ekonomika Ukrainy,

10 (671), 31-48. [in Ukrainian].

[16]. Barro, R. J., Sala-i-Martin, X. (1995).

Economic Growth. McGraw Hill.

[17]. Cinaj, V., Meçe M., Ribaj, A., Kadrimi, I.

(2020) The Need for Improvement of

External Audit Reports of Banks (The Case

of Banks in Albania which Mainly belong to

EU Banks). WSEAS Transactions on

Environment and Development, Vol. 16,

539-54.

[18]. Chima, M., Babajide, A., Omankhanlen,

A., Adejumo, B. (2020) Development:

Unconventional Monetary Policy on Bank

Performance in Nigeria. WSEAS

Transactions on Environment and

Development, Vol. 16, 844-860.

Contribution of Individual Authors to the

Creation of a Scientific Article

(Ghostwriting Policy)

- Conceptualization: Svitlana Kachula, Maksym

Zhytar, Larysa Sidelnykova, Oksana Perchuk,

Olena Novosolova.

- Formal analysis: Maksym Zhytar.

- Methodology: Larysa Sidelnykova, Olena

Novosolova.

- Project administration: Svitlana Kachula,

Maksym Zhytar, Larysa Sidelnykova, Oksana

Perchuk, Olena Novosolova.

- Supervision: Svitlana Kachula.

- Validation: Svitlana Kachula.

- Visualization: Oksana Perchuk.

- Writing – original draft: Svitlana Kachula,

Maksym Zhytar, Larysa Sidelnykova, Oksana

Perchuk, Olena Novosolova.

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(Attribution 4.0 International, CC BY 4.0)

This article is published under the terms of the

Creative Commons Attribution License 4.0

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n_US

WSEAS TRANSACTIONS on BUSINESS and ECONOMICS

DOI: 10.37394/23207.2022.19.21

Svitlana Kachula, Maksym Zhytar,

Larysa Sidelnykova, Oksana Perchuk,

Olena Novosolova

E-ISSN: 2224-2899

230

Volume 19, 2022