**1. Introduction**

Liquidity risk, which is an important measure of the bank's success in the long run, is the ability to pay liabilities and swap debts when needed. Banks should keep optimal liquid assets to meet their loan activities, investments, and depositors' demands on time and adequately. In this respect, banks try to balance this situation. As a result, the bank is exposed to liquidity risk. Thanks to the liquidity risk management, it is ensured that banks continue their effectiveness against new risks that may arise due to changes in the operating environment or increases in the current risk level [1]. On the other hand, credit is the debt given to real persons and corporations within the framework of contracts. It is one of the important financial instruments that cause economic growth by gaining investors'savings to the economy and increasing private consumption expenditures [2].

Total amount of credits given by the Turkish banking sector have been increasing rapidly in the last decade. This situation was shown in **Figure 1**. However, there is a risk that the bank loan client is not able to meet the obligations of the agreement. In this case, it is expected that there will be a decrease in the income and capital of banks and an increase in expenses and losses [3].

Banks should have liquid funds in their hands in order to meet their credit activities on time and adequately. If they do not hold this fund, the liquidity risk will increase. Increasing liquidity risk will increase financial vulnerability and economic instability. Therefore, in this study, the long-term relationship between credit expansion and liquidity risk is investigated with a panel cointegration

There is an extensive literature in Turkey examining the impact of credit expansion on macroeconomic factors. However, there is no study investigating the effect of credit expansion on liquidity risk by directly considering banks. The aim of this study is to fill this gap in the literature by using the panel data approach.

*More Credits, Less Cash: A Panel Cointegration Approach*

*DOI: http://dx.doi.org/10.5772/intechopen.93778*

This study examines long-run relation among liquidity risk and credit expansion. For this purpose, quarterly panel data was used in order to conduct analysis. Selected variables of 20 Turkish banks from 2014.Q1 to 2017.Q4 were obtained from the database of The Banks Association of Turkey in order to calculate liquidity risk and credit expansion from banks' balance sheet. The banks used in the study can be analyzed in three different groups. These are state-owned deposit banks, privateowned deposit banks, and foreign banks. Halkbank, Ziraat Bank, and Vakıf Bank were taken as state-owned deposit banks. Akbank, Fibabank, Şekerbank, Turkish Bank, Turkish Economy Bank, İş Bank, and Yapı Kredi Bank were used as privateowned deposit banks. Alternatif Bank, Arab Turkish Bank, Burgan Bank, Denizbank, ICBC Turkey Bank, ING Bank, QNB Finansbank, and Garanti BBVA Bank were taken

In this study, the ratio of the difference of loans and receivables from deposits to

*LR* <sup>¼</sup> *Loans and Receivables* � *Deposits*

The increase in credits, which causes an increase in production, income, exports, and profits of the financial sector, is expressed as credit expansion. Credit expansion (*CE*) which is the other variable of interest was created using equation below [13].

*CE* <sup>¼</sup> *Loans and Receivables*

The main purpose of this study is to explore long-run relationship among liquidity risk and credit expansion in the Turkish banking sector. This study adopts dynamic panel econometric methodology. It consists of four steps. First, the crosssectional dependence of the units (banks) is investigated with the Pesaran CDLM test developed by Pesaran [14]. Second, Delta tests are applied to analyze whether the parameters change according to the units. Third, CIPS panel unit root test developed by Pesaran [15] is used to determine order of the integration of the variables. Finally, panel cointegration test developed by Westerlund [16] is

conducted in order to explore the existence of the long-run relationship among the variables. In this section, theoretical background of methodology is explained.

One of the important concepts that affects the choice of method to be used in dynamic panel data analysis is inter-units correlation. The inter-units correlation, in other words, cross-sectional dependence is the simultaneous correlation of series that may occur due to excluded, observed common factors, spatial spillover effects,

**4.1 Investigation of cross-sectional dependence**

and all common effects observed or not observed [17].

*Total Assets* (1)

*Total Assets* (2)

as foreign banks. These banks constitute the units of the panel data set.

total assets was used as a measure of liquidity risk (*LR*) [12].

**3. Data**

**4. Methodology**

**207**

**Figure 1.** *Total amount of credits in the Turkish banking sector (million TL).*

analysis. The rest of this study is organized as follows. In the second section, literature on credit expansion is given. The third section introduces the data set and variables used in this study. The fourth section examines the results of the econometric method used, and the last section concludes.
