**3. Data**

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

studies conducted on credit expansion in Turkey were examined. Orhangazi explored the relation between capital inflows and credit expansion by using logit model. According to the findings, net private capital flows effect positively credit expansion by controlling other determinants [4]. Kara et al. made a cross-country comparison of credit growth by calculating a ratio of net credit use with respect to national income. They suggested a stable ratio of net credit relative to GDP that decreases slowly credit growth in the long-term period [5]. Kılıç examined relation between consumer credits and current account deficit. Time series methodology was adopted in order to find long-run dynamics. The study's results indicate one way Granger causality between consumer credits and current account deficit [6]. Karahan and Uslu analyzed relationship between credits extended by deposit banks to the private sector and current accounts deficit by using ARDL approach within time series framework. They found long-term relationship between variables [7]. Güneş and Yıldırım analyzed long-run relationship between credit expansion and current account deficit by using Johansen cointegration test. The results indicate existence of cointegration relation between vehicle and corporate loans and current account deficit [8]. Kılıç and Torun studied causality relation between consumer credits and inflation by using Granger causality test. The findings of the study gave evidence on two-way Granger causality relation between individual credit cards and inflation [9]. Köroğlu analyzed relation between credit expansion and current account deficit by using Granger causality test. He found one-way causality relation that credit expansion causes current account deficit [10]. Varlık investigated the effect of net and gross capital inflows and their components on credit boom by using logit model. The findings addressed that net and gross foreign direct invest-

Credits can have positive and negative effects on the economy. For this purpose,

econometric method used, and the last section concludes.

*Linear and Non-Linear Financial Econometrics - Theory and Practice*

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

ment inflows are negatively correlated with credit boom [11].

**2. Literature on credit expansion**

**Figure 1.**

**206**

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

In this study, the ratio of the difference of loans and receivables from deposits to total assets was used as a measure of liquidity risk (*LR*) [12].

$$LR = \frac{\text{Loans and Recivables} - \text{Deposits}}{\text{Total Assets}} \tag{1}$$

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].

$$\text{CE} = \frac{\text{Loans and Receivables}}{\text{Total Assets}} \tag{2}$$
