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ScienceDirect Procedia Economics and Finance 20 (2015) 571 – 579

7th International Conference on Globalization and Higher Education in Economics and Business Administration, GEBA 2013

The impact of bank-specific factors on the commercial banks liquidity: empirical evidence from CEE countries Angela Romana,*, Alina Camelia Sargub a,b

„Alexandru Ioan Cuza” University of Iasi, Bd. Carol I, no. 11, Iasi 700505, Romania

Abstract The recent economic and financial crisis has had a tremendous impact on the banking system, raising key questions about liquidity risk. Its management is seen to be of paramount importance, receiving great attention from policymakers, researchers and practitioners, taking into consideration that a liquidity shortage at a single so called “too big to fail” financial institution can lead to systemic contagion and instability. In this context, the aim of the paper is to analyse a significant issue that needs to be tackled when promoting financial stability, more exactly the determinants of the liquidity risk of a sample of banks operating in a series of CEE countries (Bulgaria, the Czech Republic, Hungary, Latvia, Lithuania, Poland, Romania), reviewing at the same time the progresses made in certain key areas and the remaining challenges. We considered bank specific factors over the period 2004-2011 and examined them employing an OLS regression analysis. The results of our research highlighted the negative impact that the depreciation of the loans portfolio had on the overall liquidity of the analysed banks. © 2015 2014 The TheAuthors. Authors.Published PublishedbybyElsevier Elsevier B.V. © B.V. This is an open access article under the CC BY-NC-ND license Selection and peer-review under responsibility of the Faculty of Economics and Business Administration, Alexandru Ioan Cuza (http://creativecommons.org/licenses/by-nc-nd/4.0/). University of Iasi.responsibility of the Faculty of Economics and Business Administration, Alexandru Ioan Cuza University of Iasi. under Peer-review Keywords: CEE commercial banks; liquidity; regression analysis; financial crisis

1. Introduction The 2007–08 financial crises raised the issue of better understanding the challenges posed by bank liquidity risk management and highlighted the importance of liquidity for the adequate functioning of the financial markets and the banking sector in particular (Bank for International Settlements, 2010; Bank for International Settlements, 2013).

* Corresponding author. Tel.: +40-741-244-481. E-mail address: [email protected]

2212-5671 © 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Peer-review under responsibility of the Faculty of Economics and Business Administration, Alexandru Ioan Cuza University of Iasi. doi:10.1016/S2212-5671(15)00110-0

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Angela Roman and Alina Camelia Sargu / Procedia Economics and Finance 20 (2015) 571 – 579

This topic has been a focus of regulatory and supervision institutions such as the European Systemic Risk Board at the European Union level and different national and international financial stability institutions at the global level, key aspects of recent regulatory reform being provided by the Basel III framework. Therefore, Basel III intended to address the vulnerabilities that triggered the financial crisis - among which the large exposure of banks to liquidity risk - through strengthening bank capital and liquidity standards and promoting thus a more resilient banking sector (De Waal et al., 2013; Petersen et al., 2013). In the case of the Central and Eastern European - CEE - countries, the banking sector has registered tremendous transformations over the last years on the background of the financial integration and innovation process. On the one hand, there were transformations with a positive impact, especially before 2008, the banks operating in the CEE countries recording an expansion of their business, sophistication and diversification of their products and services and an increase of their territorial network (Buch and Heinrich, 2003). Notwithstanding, in the context of the global financial crisis, liquidity risk problems emerged due to extreme loan-to-deposit ratios, excessive credits denominated in foreign currency granted to households based on deposits attracted in domestic currency or to a continue funding need from their parent banks (Lehmann et al., 2011). The decrease in funding liquidity then caused an important distress and the frozen of the interbank market. In order to restore the financial stability, successive liquidity support was granted by ECB and FED, mainly through bank deposit guarantees and short-term loans to banks (Orlowski, 2008) and when these measures started to be inefficient unprecedented actions needed to be taken, such as unconventional monetary policy measures. Hence, the global financial and economic crisis highlighted once more the importance of proper liquidity risk management. In this context, the aim of our research is therefore to analyse the relationship between different bank features, more exactly the impact of a series of financial indicators like the capital adequacy, assets quality, management quality and profitability on the liquidity risk of a sample of banks operating in a series of CEE countries (Bulgaria, the Czech Republic, Hungary, Latvia, Lithuania, Poland, Romania), over the period 2004-2011. The research contributes thus to the literature on the topic thorough reviewing the progresses made in certain key areas of liquidity risk management by the seven analysed CEE banking sectors and the remaining challenges. Nevertheless, our research addresses an up-to-date topic which is of concern to regulators, researchers and practitioners, being of paramount importance especially in a crisis environment. The remainder of the paper is organized as follows: the second section is dedicated to a review of the relevant literature regarding the determinants of liquidity, the third section presents the data and methodology employed in order to carry out the empirical analysis, the forth section is focused on the empirical findings while the fifth section presents the concluding remarks. 2. Literature review Taking into account the serious implication for the overall macroeconomic and financial stability, the topic regarding bank liquidity risk management has always been significant in the academic literature, many authors (Diamond and Dybvig, 1983; Molyneux and Thornton, 1992; Bangia et al., 1999; Diamond and Rajan, 2001; Allen and Gale, 2004; Kosmidou, 2008; Drehmann and Nikolaou, 2009; Bissoondoyal-Bheenick and Treepongkaruna, 2011) addressing this subject in their papers. As the financial crisis of 2007 unfolded, scholars, professionals and policy makers, such as the Basel Committee, BIS, the national central banks, have granted an increasingly interest to this theme. The literature on the determinants of liquidity risk is relatively scarce, in general, the empirical researches being focused mostly on the case of the advanced economies. For example, the research of Bonfim and Kim (2012) highlights how a sample of European and North American banks manage liquidity risk, over the period 2002-2009. In particular, the research investigates whether banks tend to take more risks in a crisis period and if they follow similar strategies. The results provide important insights for regulators, suggesting that banks have a collective behaviour in the pre-crisis period, reflected in a global deterioration of liquidity indicators and that collective risk taking incentives are focused mainly among the largest banks worldwide. A more recent example is the research of Cucinelli (2013), undertaken on the banking system from the Euro area countries and investigating the interconnection between liquidity risk and a series of bank structure variables, in the attempt of determining which are the variables that impact the two new indicators recommended by the Basel Committee, more exactly the

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liquidity coverage ratio and the net stable funding ratio. The results emphasis that the selected variables can have an impact on liquidity risk management, because even if the specific bank structure variables (size, capitalization, assets quality and specialization) do not highlight always a relationship with both liquidity indicators, the relationship is present at least in one case. In the case of the Central and Eastern European Union member countries the literature centred on this subject is less developed, existing however a series of recent studies that are trying to address this issue in various ways. For instance, Vodovà (2012), using a panel data regression analysis, attempts to identify the liquidity determinants of commercial banks in Poland. The results pinpoint that liquidity tends to decrease with the size of the bank, more exactly large banks tend to hold less liquid assets, relying on a liquidity assistance of the lender of last resort in case of distress, while small and medium sized banks hold more liquid assets. On the other hand, the research demonstrates that the inflation, increases in capital adequacy, share of non-performing loans have a positive impact on bank liquidity. The research of Horvàt et al. (2012), on Czech banks examines the relation between capital and liquidity creation, by carrying out a series of Granger-causality tests, over the period 2000-2010. The conclusions of the paper support the idea that the requirements of Basel III can lead to the decrease of liquidity creation, but on the other hand that greater liquidity creation can reduce banks’ solvency, leading thus to a trade-off between the benefits of financial stability generated by stronger capital requirements and the benefits of greater liquidity creation. Taking all this into account, we can conclude that the exposure to risk liquidity is lower for the banking institutions that create less liquidity on the market. Considering all this issues, our research contributes to the existing literature on the topic of liquidity risk and its determinants by analysing the relationship between different bank features, more exactly the impact of a series of financial indicators like the capital adequacy, assets quality, management quality and profitability on the liquidity risk of a sample of banks operating in a series of CEE countries (Bulgaria, the Czech Republic, Hungary, Latvia, Lithuania, Poland, Romania). 3. Data and methodology In order to calculate the liquidity of the analysed banks we have employed a very common indicator represented by the ratio of loans to total assets. Taking into account the cross-border component of our research, we have considered that this indicator answers better to our needs, the ratio of loans to total assets being very easy to be calculated for all the banks from our sample (equation 1).

Liquidity indicator

total loans total banking assets

(1)

The academic literature on this subject (e.g. Vodovà, 2012) considers alongside this ratio also the ratio of liquid assets to total assets as the most popular indicator for bank liquidity. In order to determine the evolution of the analysed banks liquidity, we have chosen six internal indicators (one capital adequacy indicator, one assets quality indicator, one management quality indicator, two profitability indicators and total assets / total sector assets for the bank size). We have chosen these six indicators as they can be influenced through the business strategy adopted by the banks, thus being under the direct control of the management team. Thus, we are able to underline also how business decisions influence the overall liquidity of a bank. In order to ensure the comparability of the obtained results, we have chosen for our sample only the commercial banks located in the analysed countries. The data used have been obtained from the Bureau Van Dijk Bankscope database and the unconsolidated financial statements of the banks from our sample. The comprehensiveness of our study is twofold. Thus on the one hand, the analysed period is 2004-2011, covering the pre and post EU ascension period and also the impact and aftermath of the global financial and economic crisis and the first stages of the EU

574


sovereign debt crisis. This will allow us to have a very comprehensive look on the evolution of the analysed banks liquidity and also on the impact that the chosen six factors had on it, in a crisis environment. On the other hand, the banks from our sample own together over 2/3 of the total banking assets of the analysed countries making our sample one of the largest to be used in such a type of analysis. The chosen sample of banks is composed from: 11 banks from Bulgaria, 14 banks from Czech Republic, 8 banks from Hungary, 7 banks from Lithuania, 16 banks from Latvia, 15 banks from Romania and 15 from Poland. The summary statistics for the liquidity indicator and the chosen six internal indicators are presented in table 1. Table 1. Descriptive statistics of the variables used in our research Liquid

TCR

ILTL

average

25.59

19.75

4.47

median

20.13

14.37

std.dev.

21.47

17.11

IED

ROAE

ROAA

TATSA

5.95

16.06

1.52

4.42

2.75

3.31

16.84

1.43

1.09

4.82

12.52

10.35

1.12

7.23

2005

min

2.15

8.28

0.02

0.14

-19.13

-4.08

0.00

max

137.59

121.16

28.88

110.53

54.32

4.31

33.69

2007 average

22.10

15.11

3.62

4.69

17.31

1.57

5.27

median

18.58

13.06

2.40

3.46

17.14

1.41

2.13

std.dev.

16.50

9.40

3.43

3.79

10.47

1.03

7.40

min

1.92

8.31

0.07

0.53

-8.58

-0.98

0.00

max

113.70

84.55

20.82

22.32

62.22

5.80

31.45

average

23.87

16.33

10.55

4.30

-5.28

-0.26

4.65

median

20.28

13.92

7.22

3.83

4.52

0.34

1.18

2009

std.dev.

17.71

10.04

11.25

2.67

31.64

2.35

7.59

min

0.76

6.80

0.10

0.01

-131.68

-8.72

0.00

max

91.12

90.37

79.10

12.82

29.44

2.92

34.28

2011 average

28.26

16.85

14.79

2.80

-4.87

0.02

4.23

median

25.57

14.58

12.34

2.70

6.19

0.66

1.38

std.dev.

20.49

9.62

12.95

1.87

47.75

2.49

6.75

min

0.02

2.37

0.10

0.01

-298.10

-10.94

0.00

max

109.32

61.02

79.10

12.38

35.26

3.12

33.74

Note: Liquid - the calculated liquidity indicator; TCR - total capital ratio; ILTL – the ratio of impaired loans to total loans; IED - the ratio of interest expenses to total deposits; ROAE - return on average equity; ROAA - return on average assets; TATSA the share of the total banking system assets. Source: authors’ calculations

After analysing the data displayed in table 1 a few quick conclusions can be drawn. Regarding the liquidity indicator we can observe that until the start of the global crisis its values are registering a decreasing trend, while after the start of the crisis and on a background of a depressed macroeconomic environment the analysed banks increased their overall liquidity. This can be attributed especially to the tightening of the banking regulation both at national and European level. In the case of total capital ratio, the values registered have decreased since the start of the analysed period, although as a result of the tightening of the banks regulations, since 2008 a small amelioration has been registered.


575

Unfortunately the existing of a depressed macroeconomic environment in most of the analysed countries and the deepening of the sovereign debt crisis has led to a new decrease of the total capital ratio toward the end of the analysed period. The ratio of impaired loans to total loans has registered a very steep increase as a result of the international financial crisis start and especially of the macroeconomic environment depreciation of the analysed countries. The sharpest increase of the impaired loans to total loans ratio has been registered by Romania, Bulgaria and the two Baltic states. The ratio of interest expenses to total deposits has registered a continuous decrease since the start of the analysed period, with the exception of the year 2008. The decrease of this ratio has been determined by two different reasons. Thus, on the one hand, before 2008, the credit expansion period registered in the analysed countries droved loans interest rate down, implicitly decreasing the deposits interest rates. After 2008, the aggressive policies implemented by the national governments in order to stimulate the loaning process and the relaxed monetary policy adopted by the national banks of the analysed countries have pushed the interest rates of the deposits even lower. The exception registered in 2008, is determined by the implementation of the new prudential measures by the regulatory and supervision authorities of the banking sectors, which determined banks to attract more deposits from the market in order to improve their overall liquidity. Regarding the evolution of the profitability indicators, it underlines very well the depreciation of the national macroeconomic environment as the international financial crisis deepened and the EU sovereign debt crisis started. The depreciation of the profitability indicators has been extremely deep, their average value becoming negative for the period 2009 - 2011. Nevertheless, the size of the analysed banks has slightly decreased during the analysed period of time, except for 2007. During this year in most of the analysed countries a consolidation phase took place, large banks acquiring more new clients in the dawn of the international financial crisis. After the start of the international financial turbulences and the downturn of the national economies, banks clients tried to find the safest bank for their savings, larger banks losing market share in favour of the smaller more clients orientated banks. This explains the downward trend in the size of the analysed banks after 2007. In order to underline the impact of the business strategy adopted by the analysed banks on their liquidity we have chosen six internal indicators. Thus we have employed an ordinary least squares regression analysis (OLS), the model used being expressed as follows:

Liquid

it

Į TCR

it

ILTL IED ROAE ROAA TATSA İ it it it it it it

(2)

where: Liquidit is the calculated liquidity indicator for bank i in period t, Į is the constant, TCRit is the total capital ratio for bank i in period t, ILTLit represents the ratio of impaired loans to total loans for bank i in period t, IEDit is the ratio of interest expenses to total deposits in the case of bank i for period t, ROAEit is the return on average equity for bank i in period t, ROAAit is the return on average assets in the case of bank i for the period t, TATSAit represents the share of the total banking system assets owned by bank i in period t and İit is the error. A high total capital ratio will impact negatively the bank, as shareholders will pressure the management of the bank to make more profitable investments or to grant more loans with high interest rates. A reasonable value of the total capital ratio, not to high above the legal limit will ensure that the management does not face additional pressure from the shareholder in order to increase the average returns of the banks and will also ensure the existence of an adequate liquidity level. An increase of the impaired loans to total loans ratio is expected to impact negatively the overall liquidity of a bank, as liquid assets turn illiquid. Implicitly, a decrease of the impaired loans to total loans ratio will tend to increase the overall liquidity of a banking institution. Especially in our case, as more loans become impaired, the bank will tend to decrease its loaning operations until it can change the negative trend, this leading to a decrease of the ratio of loans to total assets.

576


As the bank is able to attract deposits at a lower rate, implicitly it will be able to engage in extensive loaning operations, thus the ratio of total loans to total assets increasing (the liquidity level as well). As banks will need to pay additionally in order to attract deposits, their loaning operations will be negatively impacted, thus their overall liquidity will suffer. The profitability of the banks impacts directly its overall liquidity, as banks with high returns will tend to be more liquid than their peers that are registering lesser results. Additional returns, tend not to be distributed in the first year after they are made, thus increasing the retained earnings of the bank, implicitly its liquidity level. Contrary, lower returns or losses will negatively impact the retained earnings, thus leading to a decrease of the overall liquidity of the bank. Regarding the size of the banking institution, its effects on the overall liquidity are mixed. Thus, a large bank will tend to attract additional clients through the crowding-in effect, therefore increasing the overall liquidity of the bank. Still in prolonged boom periods, larger banking institutions will tend to provide more average products (higher interest rates for loans and lower interest rates for deposits), this determining a part of their clientele to relocate toward more smaller banking institutions which are more costumer friendly, in this case the overall liquidity of the smaller banks being increased. 4. Empirical results As mentioned previous in order to underline the impact of a series of banks characteristics on the liquidity indicator calculated for the banks from our sample we have employed an OLS regression analysis. In order to avoid any multicollinearity problems we have performed a Pearson correlation analysis. The obtained results underline that there are no multicollinearity problems between the chosen independent variables. Taking into account the paper size restriction the results are available upon request. The obtained results for the regression analysis are displayed in table 2 and table 3. Table 2. Regression analysis results for the banks from Bulgaria, Czech Republic and Hungary Bulgaria

Czech Republic

Hungary

Beta

Sig.

Beta

Sig.

Beta

constant

26.4773

0.0000

2.9637

0.1716

-1.4322

Sig. 0.7084

TCR

-0.2642

0.0129

-0.1170

0.1743

0.0819

0.4364

ILTL

-0.1769

0.1002

0.3213

0.0000

0.0803

0.4617

IED

0.2090

0.0513

-0.0309

0.6882

0.5875

0.0000

ROAE

0.0437

0.6974

1.0474

0.0000

-0.3580

0.0010

ROAA

-0.0746

0.4774

-0.6856

0.0000

-0.1756

0.4560

-0.1218

0.2538

0.0898

0.2373

0.3364

0.0010

TATSA Adjusted R

2

0.0590

0.4579

0.4069

Durbin-Watson sta.

2.4141

1.8410

1.4662

No. of observations

88

112

64

Note: 5% significance level Source: authors’ calculations

Analysing the results presented in table 2, we can observe that Bulgaria has not been hit directly by the international financial crisis (as the banking institutions from this country have not been directly exposed to the US subprime mortgage crisis), still the banks operating in this country have registered a decrease of their activity as the macroeconomic environment has depreciated. The regression analysis results underline a negative and statistically significant link between the liquidity indicator and the total capital ratio. This can be explained by the pressure that shareholders put on the management of banks to enhance the profitability if they are required to increase their participation. In order to meet the shareholders requirements the management of the bank is forced to transform


577

some of their liquid assets, which generate zero to low returns, into illiquid assets, like long term loans and other long term investments which have a higher return. The Bulgarian banking supervision authorities have required higher than average own capital ratios for the Bulgarian banks during the financial and economic turbulences that manifested during the analysed period. Despite shareholders pressure and the increase of the TCR indicator, Bulgarian banks have been reluctant to engage in new loaning activities, hence the negative impact that the TCR indicator has on the liquidity indicator (loans / total assets) of the analysed Bulgarian banks. The banks operating in the Czech Republic haven’t been hit either directly by the international financial crisis, but were affected by the depreciation of the Czech economic environment which is export oriented and was negatively affected by the European downturn. Thus, the banks operating in the Czech Republic registered an increase of their impaired loans ratio during the analysed period of time. The new regulations adopted by the Czech Republic National Bank demanded an increase of the overall banks liquidity level for the banks that registered a deterioration of their loans portfolio, this determining also the positive and statistically significant link between the liquidity indicator and the ILTL indicator. An interesting situation is between the liquidity indicator and ROAA and ROAE respectively. This can be attributed partly to the new supervision regulations adopted as a result of the financial crisis and in part because of the bank’s shareholders business strategies. Thus, if a bank becomes more and more profitable the liquidity requirements are less stringent thus a negative and statistically significant link. On the other hand as banks shareholders must contribute with more capital as a result of new prudential requirements they expect an increase of their returns. Thus the positive relationship between ROAE and the liquidity indicator can be explained. The Hungarian government has avoided artificially the increasing of the impaired loans ratio to gross loans by freezing the exchange rate between the Hungarian forint and the Swiss franc until 2015, thus allowing most of the mortgage owners to still be able to pay their monthly interest rates. Moreover banks had to attract additional deposits in order to comply with the new regulatory framework regarding liquidity standards, this leading to an increase of the interest expenses for deposits, hence the positive and statistically significant link between IED indicator and the liquidity indicator. As the larger banks operating in Hungary have been heavily involved in the loaning process, these banks had to create additional liquidity buffers in order to comply with the new guidelines of the Magyar Central Bank, thus the positive and statistically significant link between the ratio of total bank assets to total banking sector assets and the liquidity indicator. Also, banks registering losses had to increase their liquidity under the new guidelines, but as the loan market was almost saturated, banks were unable to increase their revenues by granting additional loans, thus being unable to satisfy the demands of their shareholders, hence the negative and statistically significant link between ROAE and the liquidity indicator. In the case of the Lithuanian banks, the increase of the impaired loans ratio had a tremendous impact on their overall liquidity. In order to avoid the collapse of the banking system the Lithuanian National Banks has undertaken a series of reforms, among which an increase of the minimum liquidity level that banks must maintain. As banks registered an increase of their impaired loans ratios the Central Bank required an even higher level of liquidity, thus the positive and statistically significant link between the liquidity indicator and the impaired loans ratio. In the case of the other Baltic country, namely Latvia, the regression results underline a positive and statistically significant link between the total capital ratio and the liquidity indicator. As mentioned earlier, the shareholders pressure on management for additional returns is the main cause for the existence of this outcome, the difference being that Latvian banks were not reluctant to engage in loaning activities as their TCR indicator increased, thus the positive and statistically significant link. In the case of the Polish banks the evolution of the liquidity indicator was influenced by the IED and ROAE indicators. Thus, as Poland has been one of the best performing economies in the analysed period of time, managing to avoid the negative impact of the international and European financial turbulences, the Polish banks did not need additional liquidity reserves, thus the regression analysis underling a negative relationship between the liquidity indicator and the IED indicator. As interest rates to deposits dropped on the background of a stable macroeconomic environment, banks were able to increase their liquidity level at a lower cost. As mentioned earlier, the shareholders of the banks demanded higher returns for their additional participations to the bank capital, this explaining the positive link between the ROAE indicator and the liquidity indicator, the Polish banks being able to carry out a normal loaning activity during the analysed period of time.

578

Angela Roman and Alina Camelia Sargu / Procedia Economics and Finance 20 (2015) 571 – 579 Table 3. Regression analysis results for the banks from Lithuania, Latvia, Poland and Romania Lithuania Beta

Latvia Sig.

Beta

Poland Sig.

Beta

Romania Sig.

Beta

Sig.

constant

15.1210

0.0000

9.8805

0.0000

24.8704

0.0000

19.0200

0.0000

TCR

-0.0245

0.8622

0.2625

0.0027

-0.0641

0.4708

0.5972

0.0000

ILTL

0.3375

0.0109

0.0745

0.3969

0.0486

0.5864

1.2427

0.0032

IED

-0.0908

0.4840

-0.1476

0.0940

-0.1865

0.0346

-0.1035

0.2184 0.3786

ROAE

0.0511

0.7173

-0.0442

0.6196

0.2833

0.0015

-0.0856

ROAA

-0.0029

0.9832

-0.0848

0.3416

0.1182

0.5131

-0.0746

0.4426

TATSA

-0.1364

0.3037

0.0429

0.6297

-0.0022

0.9799

-0.1305

0.1203

Adjusted R2

0.0975

0.0615

0.0947

0.1774

Durbin-Watson sta.

2.2480

2.4493

1.9243

1.9998

No. of obs.

56

128

120

120

Note: 5% significance level Source: authors’ calculation

As the macroeconomic environment depreciated, more and more debtors were unable to repay their loans, Romanian banks registering the highest increase of impaired loans from all of the sample countries during the analysed period. In order to prevent additional troubles the National Bank of Romania has imposed additional liquidity requirements for the banks with large bad loans portfolios. Thus, overall the banks operating in Romania had to increase their liquidity reserves, this explaining the positive impact that the ILTL indicator has on the liquidity indicator of the Romanian banks. Also, banks were required to increase their capital in order to be better prepared in the event of sudden negative macroeconomic downturns. The banks operating in Romania have continued their loaning process, this leading just like in the case of the Latvian banks, to a statistically significant positive link between the TCR indicator and the liquidity indicator for the banks from our sample. 5. Concluding remarks Summarising the obtained results, we can observe that the internal factors that have the most influence on the overall liquidity of the analysed banks are: the total capital ratio (TCR), the ratio of impaired loans to total loans (ILTL) and the return on average equity (ROAE). Notwithstanding, the impact of these indicators on the overall liquidity of the analysed banks has been positive in some cases and negative in others, depending on the local macroeconomic environment particularities. Taking into account the link between the total capital ratio (TCR) and the overall liquidity of the analysed banks, it becomes obvious that the measures adopted by the regulatory and supervision authorities, both at national and European level, in order to prevent the negative effects of the global financial turmoil and the internal macroeconomic downturn, had a positive impact also on the overall liquidity of the banks, this being of course one of the desired outcomes. The obtained results also underline the negative impact of impair loans raise on the overall liquidity of the banks. Unfortunately this problem requires more comprehensive measures to be adopted, a diminishing of the impaired loans to total loans ratio (ILTL) being possible only on the background of an improvement of the overall macroeconomic environment. Until such an outcome is possible, the regulatory authorities, both at national and European level, must closely supervise the overall liquidity of the CEE banks and take appropriate measure in order to ensure that these banks have an adequate liquidity level despite a possible further depreciation of their loans portfolios. Nevertheless, supervision authorities must find an appropriate balance between their liquidity requirements and the pressure that they put on the shareholders of the banks. As these are required to contribute with additional funds


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to the bank capital, their pressure on the bank management for an enhancement of the bank returns (ROAE) will increase also exponentially, which can determine the enhancement of the possibility for moral hazard to appear. Taking into account the importance of this subject, we consider appropriate the deepening of the analysis as a further research direction. Thus we consider suitable to study the link between the efficiency of the banks operating in CEE countries and their overall liquidity level in a future research. Hence, in order to underline the robustness of the obtained results it is recommended to employ both a parametric and non-parametric analysis to estimate the efficiency of the banks. Also, the usage of several liquidity indicators can enhance the precision of the obtained results. This extensive analysis will allow the underlining of the link between the efficiency of the analysed banks and their liquidity in a crisis environment, helping the regulatory authorities to better develop their monetary and macro-prudential policies.

Acknowledgments With the support of the Lifelong Learning Program of the European Union through the Jean Monnet Module “Euro and the Banking Integration Process in an Enlarged EU - 2012-2911”. This publication reflects the views only of the authors, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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