Examining the financial development channels affecting economic growth in Turkey

Demirhan, Banu Article Examining the financial development channels affecting economic growth in Turkey Ekonomika Provided in Cooperation with: Vilnius University Press Suggested Citation: Demirhan, Banu (2025) : Examining the financial development channels affecting economic growth in Turkey, Ekonomika, ISSN 2424-6166, Vilnius University Press, Vilnius, Vol. 104, Iss. 1, pp. 48-69, https://doi.org/10.15388/Ekon.2025.104.1.3 This Version is available at: https://hdl.handle.net/10419/323171 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ 48 Ekonomika ISSN 1392-1258 eISSN 2424-6166 2025, vol. 104(1), pp. 48–69 DOI: https://doi.org/10.15388/Ekon.2025.104.1.3 Examining the Financial Development Channels Affecting Economic Growth in Turkey Banu Demirhan Afyon Kocatepe University, Afyon, Turkey E-mail: [email protected] ORCID: https://orcid.org/0000-0002-0902-4629 Abstract. In the early 1980s, Turkey took steps towards financial liberalization. Accordingly, policymakers have implemented policies for the development of the financial system. Since then, developments in the banking sector have driven economic growth and met the private sector’s demand for funds. The research problem involves analyzing the relationship between financial development and economic growth in Turkey, which is crucial in determining the effectiveness of policies implemented for financial development. Determining the source through which financial development is vital for economic growth is also critical in designing these policies. This research examines the channels through which financial development impacts economic growth in Turkey. By using data from 1974 to 2023 for Turkey, this study conducted a Granger causality test based on VECM and the Toda Yamamoto method to analyze the causal relationship between economic growth and financial development. The analysis also included impulse response functions. Our study reveals that financial development contributes to economic growth. Policymakers should implement policies that prioritize the development of the financial system. Keywords: Financial development, economic growth, VECM, Toda-Yamamoto, impulse response function, Turkey. 1. Introduction Have Turkey’s financial development efforts over the years contributed to economic growth? If so, which components of the financial system play a role in this contribution? In 1980, the financial system began to advance in Turkey. The early 1980s witnessed significant measures implemented, including the development of the capital and interbank money markets. Furthermore, the Government implemented measures to liberalize foreign exchange legislation. These developments enhanced the efficiency of the financial system and had a positive effect on the real economy. Turkey adopted an open economy approach and liberalized its financial sector by implementing significant reforms since the 1980s. The process aimed to target the liberalization of capital flows on a domestic and international level and the expansion of trade volumes and foreign investment (Pamuk, 2019; Fırat, 2009). Received: 11/08/2024. Revised: 09/09/2024. Accepted: 05/01/2025 Copyright © 2025 Erdal Demirhan. Published by Vilnius University Press This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Contents lists available at Vilnius University Press Banu Demirhan. Examining the Financial Development Channels Affecting Economic Growth in Turkey 49 Many studies on the relationship between financial development and economic growth use Turkish data. Studies analyzing the relationship between financial development and economic growth have mainly used time series methods. Examples of these studies are Kuzucu (2022), Coşkun and Kuloğlu (2022), Aşık (2023), Kılıç et al. (2019), and Eroğlu and Yeter (2021). These studies used loans to the private sector as an indicator of financial development. On the other hand, they did not analyze the development of the capital market. In addition, although the studies conducted by using quarterly data cover the data for 2023, the studies conducted using annual data include the latest data for 2019 only. Finally, the studies that used annual data did not incorporate significant structural changes in the Turkish economy into their models. Our study differs from recent studies in that it considers the development of the capital market, covers a more extended period, and examines structural changes in the Turkish economy. Therefore, the research problem in this study is whether the financial development policies implemented in Turkey for a long time contribute to economic growth. Another research problem is to determine the channels through which these policies contribute to economic growth. In other words, we aim to assess the contribution of the components of the financial system. This study set out to answer the following questions: (1) Has financial development in Turkey since the 1980s impacted economic growth? (2) If so, what is the source of this impact? We expect the development of the Turkish banking system and capital markets to facilitate the transfer of savings to investments and boost consumption expenditures. Therefore, the study hypothesizes that financial development positively affects economic growth. Furthermore, given the high level of development in Turkey’s banking system, the study also hypothesizes that the source of financial development comes mainly from the banking system. This study aims to investigate the channels through which financial development affects economic growth in Turkey. In this context, we will determine whether the banking system or the capital market is more effective for economic growth. For this purpose, we will frequently use time series methods, as used in the literature. First, we will apply VECM and impulse-response functions for our analyses. Next, we will conduct Toda-Yamamoto analysis to provide methodological support. We will also determine short-term and longterm effects by using these methods. This study examines the causal relationship between financial development and economic growth in Turkey from 1974 to 2023. This study makes various contributions to the existing literature. First, this research analyzes the relationship between financial development and economic growth over a very long period, considering the structural breaks in the Turkish economy. The financial system in Turkey has undergone significant development since the 1980s; therefore, this study provides a long-term perspective on the consequences of the combinations of financial development. Secondly, the study uses components of financial development in Turkey in econometric models. In this framework, we will determine the effects of the banking system and the capital market on economic growth separately. ISSN 1392-1258 eISSN 2424-6166 Ekonomika. 2025, vol. 104(1) 50 We organize the rest of the article as follows: Section 2 presents the theoretical and empirical literature. Section 3 describes the model specification and data. Section 4 includes the empirical estimations. Section 5 presents the robustness check. Section 6 presents a discussion, and the final section comprises the concluding remarks. 2. Theoretical and Empirical Literature Review The financial system transfers surplus funds from economic units to those in need. This leads to an increased investment and economic growth. Current developments in the financial system enhance its positive impact on economies. The fact that the total value of all financial assets and liabilities exceeds that of the entire economy demonstrates the financial system’s critical role in the modern world. The significance of financial tools to economic growth is evident during the economy’s up and down cycles (Rutkauskas, 2015). King and Levine (1993) found a strong correlation between financial development, real per capita GDP growth, physical capital accumulation, and improvements in physical capital efficiency. Schumpeter (1911) conducted the first study of the correlation between financial development and economic growth, thereby marking the beginning of theoretical explanations on this subject. According to the prevailing viewpoint, supported by Schumpeter’s seminal study in 1911, the stock market’s growth benefits the economy by providing liquidity and a method for distributing while minimizing risks. Furthermore, it facilitates the effective distribution of resources toward profitable projects, minimizes expenses related to information and transactions, and eventually empowers organizations to pursue successful ventures (Ibrahim, 2011). According to the Schumpeter’s model, the financial sector’s growth is one of the main factors that trigger economic growth. Many economists have recognized the crucial role of financial markets in economic development. Schumpeter (1934) noted the role of financial intermediaries in directing resources toward more productive investments, while Bagehot (1873) and Hicks (1969) emphasized the significance of financial development for the economy. The authors believed that the presence of financial markets and institutions played a crucial role in facilitating the industrial revolution. This was achieved by enabling enterprises to borrow and lend, encouraging the adoption of new technologies, and pursuing riskier yet potentially more profitable investments (Capasso, 2004). Moreover, McKinnon (1973) and Shaw (1973) describe financial liberalization as establishing higher interest rates that equalize the demand and supply of savings. According to the two authors, higher interest rates will enhance savings and financial intermediation while improving savings efficiency (Balassa, 1990). Patrick (1966) provided two definitions of the connection between financial development and economic growth. Economic growth closely correlates with the increasing demand for financial services. Financial development enables the effective transformation of savings into investments, which supports economic growth. Moreover, according to Robinson (1952), there is a correlation between the growth of the financial system and Banu Demirhan. Examining the Financial Development Channels Affecting Economic Growth in Turkey 51 economic development. Certain viewpoints argue that financial development does not impact economic growth. The pioneer of these investigations, Lucas (1988), highlighted that physical and human capital and technological advancements drive economic progress. Several analyses in the literature on the relationship between financial development and economic growth employ time series techniques for a specific country, while others rely on estimating panel data models that combine data from many countries. Some studies in the literature on financial development and economic growth employ time series techniques that focus on a particular country, while others combine data from multiple countries to construct panel data models. While several of these models focus on the influence of financial development on economic growth, others examine the causal relationship between these two variables. Recent studies that conduct causality analyses based on panel data models demonstrate the relationship between economic growth and financial development. Mtar and Belazreg (2021) can be given as an example of these studies. Once more, recent studies (e.g., Nguyen et al., 2022; Pradhan et al., 2013; Çınar et al., 2024) have proven a two-way causality relationship between economic growth and financial development. The relationship between financial development and economic growth in countries may also depend on their income levels. Canbaloğlu and Gürgün (2019) conducted a study where they found that there was no relationship between financial development and economic growth in countries in the upper-middle and high-income categories. Despite this, they discovered a unidirectional causality, indicating that financial development drives economic growth in countries classified as lowand lower-middle income. Several studies have examined the relationship between financial development and economic growth by employing panel data techniques and combining data for country groups. For instance, the studies conducted by Ibrahim and Alagidede (2018) and Asante and Takyi (2023) have determined that the development of financial systems supports economic growth in sub-Saharan countries. Ahmed (2016) conducted another study on countries in sub-Saharan Africa, which found that international financial integration positively impacts economic growth by enhancing financial development. Bist (2018) demonstrates that financial development in low-income countries positively influences economic growth. In their study, Ekanayake and Thaver (2021) employed a large dataset to determine various panel relationships that exhibit differences across various country groups within developing countries. According to Abbas et al. (2022), financial development in middle-income countries contributes to economic growth, with a particularly significant impact in upper-middle-income countries. While most of the literature indicates that financial development has a positive effect on economic growth, some studies suggest that financial development has a negative impact on economic growth, as shown by Wen et al. (2022). In addition to the impact of financial development on economic growth, some studies examine the consequences of financial reforms. For instance, Boikos et al. (2022) determined that financial reforms have a greater impact on economic growth than financial development in developed and developing countries. Furthermore, researchers have ex- ISSN 1392-1258 eISSN 2424-6166 Ekonomika. 2025, vol. 104(1) 52 amined the relationship between financial development and economic growth on a sectoral basis. Ustarz et al. (2021) conducted a study that demonstrated the positive influence of financial development on the growth of the agriculture and service sectors. After a certain point, financial development begins to influence the industry sector. Furthermore, researchers have conducted studies in the literature by using the panel data technique, employing data from industrialized countries. Swamy and Dharani (2019) found a long-term inverted U-shaped relationship between financial development and economic growth. Financial development facilitates firms’ financing of private investment, thereby supporting economic growth. Castro et al. (2015) used firm-level data to demonstrate how financial development in Brazil influences investments of firms. Many studies have been conducted in Turkey to investigate the causal relationship between economic growth and financial development. Studies examining the causal connection between financial development and economic growth in Turkey have produced different findings. While some studies, such as Aşık (2023), Acaravcı et al. (2007), Eroğlu and Yeter (2021), and Şeyranlıoğlu (2024), indicate that financial development leads to economic growth, other studies, such as Aslan and Küçükaksoy (2006), Kandır et al. (2007), Taşseven and Yılmaz (2022), Atay (2020), and Özcan and Arı (2011), suggest that economic growth leads to financial development. Some studies (Demirhan et al., 2011; Kuzucu, 2022; Coşkun and Kuloğlu, 2022; Kılıç et al., 2019) have found a bidirectional causal relationship. Moreover, Atgür (2019) demonstrates that financial development does not significantly impact economic growth. Furthermore, several studies in the literature indicate that there is no causal relationship between financial development and economic growth. Such studies include Nur (2021) and Tekin et al. (2024), Shahzadi et al. (2023), Çetin et al. (2023), Alhassan et al. (2022), and Li et al. (2021) have all recently conducted studies which undertook to estimate the relationship between financial development and variables such as energy consumption and air pollution. Moreover, Sghaier (2023), Asteriou et al. (2024), and Emara and Said (2021) have conducted research indicating that the influence of financial development on economic growth is dependent on trade openness, fiscal policy, and governance. Studies such as those performed by Younsi and Bechtini (2020) have investigated the influence of financial development on income inequality. 3. Data and Model Specification 3.1. Data Econometric estimations cover the years 1974 to 2023. The reason for selecting this period was the availability of data. The models use annual time series data. The data used for the models is a yearly time series dataset. Financial development indicators were based on two variables. The first variable is the total bank credit to the private sector, expressed as a percentage of GDP (cre); the second is the share of the broadly defined money supply in GDP (m2). We depicted that previous studies frequently used these indicators. Since our research covered an extended period, we were able to obtain these indicators consistently. Banu Demirhan. Examining the Financial Development Channels Affecting Economic Growth in Turkey 53 The dependent variable, economic growth, is defined as the natural logarithm of the real GDP (gdp). The control variable, trade openness, is the sum of exports and imports of goods and services expressed as a percentage of GDP (open). We sourced all variables from the World Bank (2024). After 1980, outward-oriented policies were implemented in the Turkish economy, and financial liberalization began. This situation made significant contributions to financial development. In addition, the Turkish economy faced two major crises in 1994 and 2001, independent of the global crises. In this context, we included dummy variables in the econometric models for the period after 1980 and the 1994 and 2001 crises. The Appendix displays summary statistics and correlation matrix in Tables A1 and A2. 3.2. Econometric Model The first step in analyzing the relationship between financial development and economic growth is to determine if the series has unit roots. This study employs the Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root tests to determine whether the series in question has a unit root (Dickey and Fuller, 1979 and 1981; Phillips, 1987; Phillips and Perron, 1988). We will proceed with our investigation by applying cointegration tests if we find a unit root, or I(1), in the series. This study employs the Johansen multivariate cointegration technique, as Johansen (1988) and Johansen and Juselius (1990) suggested. This method offers two likelihood ratio tests, employing trace and maximum eigenvalue statistics. In the trace and maximum eigenvalue tests, the null hypothesis is that the number of cointegrating vectors is less than or equal to r, where r is 0, 1, or 2. In the λtrace and λmax tests, the null hypothesis is tested against at least r + 1 cointegrating vector and r + 1 cointegrating vector, respectively. We will perform the causality test after the cointegration test. According to Engle and Granger (1987) and Granger (1988), the cointegration of two time series variables results in at least a unidirectional Granger causality. Granger (1988) asserts that when cointegration exists between I(1) variables, the Granger causality test necessitates the incorporation of the error correction term derived from the cointegration equation. When there is a long-term relationship between the variables, we apply the causality analysis using VECM, as shown below. 1 1 1 1 11 1 1 11 p pp t i ti i ti i ti t t i ii gdp gdp cre open z αβ φ λ ψε − − −− = = = ∆=+ ∆ + ∆ + ∆ + + ∑ ∑∑ (1) 2 2 2 2 21 2 1 11 p pp t i ti i ti i ti t t i ii cre gdp cre open z αβ φ λ ψε − − −− = = = ∆=+ ∆ + ∆ + ∆ + + ∑ ∑∑ (2) 2 3 3 3 31 3 1 11 p pp t i ti i ti i ti t t i ii open gdp cre open z αβ φ λ ψε − − −− = = = ∆ =+ ∆ +∆+ ∆ + + ∑ ∑∑ (3) where ∆ is the difference operator, εt is zero mean, serially uncorrelated random error terms, p represents the number of lags, and zt-1 is the error correction term, the lagged values of the error term derived from the estimated long-term cointegration relationship. ISSN 1392-1258 eISSN 2424-6166 Ekonomika. 2025, vol. 104(1) 54 The error correction term shows the short-run deviations from the long-run equilibrium, reflecting the speed of adjustment of any disequilibrium to the long-run equilibrium. If there is no cointegration relationship, we estimate Equations (1–3) without using error correction terms. The choice of the model in this study relies on the existing cointegration relationship. We employ dummy variables in VECM to explore the effects of the 1994 and 2001 crises and the period of financial liberalization following 1980. We assign the dummy variable to one during periods of crisis and financial liberalization, and to zero otherwise. To examine causality from financial development to economic growth, we computed the Wald test statistics under the null hypothesis that all coefficients of φ1i=0 as a group. Similarly, when performing the Wald test to determine causation from economic growth to financial development, the null hypothesis being tested is that all coefficients of β2i=0 as a group. After estimating Equations (1–3), if the null hypothesis of all coefficients of φ1i=0 or the coefficient of ψ1i=0 is rejected, then it is concluded that there is a causality from financial development to economic growth. On the other hand, if the null hypothesis of all coefficients of β2i=0 or the coefficient of ψ1i=0 is rejected, then the causality relationship is from economic growth to financial development. We will also conduct causality analyses using the m2 variable, a different financial development indicator, instead of the cre variable in Equations (1–3). Rejecting the null hypothesis that the explanatory variables as a group are different from zero indicates a short-run causality from the explanatory variables to the dependent variables. The statistical significance of the coefficient ψ1i indicates long-term causality from explanatory variables to dependent variables. 4. Empirical Results Table A1 in the Appendix presents the descriptive statistics for the variables used in the econometric model. The Jarque-Bera test reveals a normal distribution of all variables at the 5% level. The standard deviation indicates the extent of dispersion in the data from the mean value. The data show the highest variation in cre. Table A2 in the Appendix displays the correlation between the variables. Table A2 shows a strong correlation between gdp, cre, m2, and open. Table 1 represents the ADF and PP test results for the levels and first differences of all variables used in the econometric models. According to the ADF and PP tests, all variables are integrated in order one in first differences; thus, all variables are I(1) or non-stationary. We determine the optimal lag by minimizing Akaike’s FPE criterion. Since the unit root test results show that all variables are I(1), we can use the Johansen cointegration technique. We will, therefore, perform both short-term and long-term analyses. Table 2 presents the results of the Johansen cointegration test for the cre and m2 variables, which represent financial development indicators. Table 2 indicates that there is a statistically significant cointegration relationship between the variables. Therefore, we conclude that gdp, cre, and open have a long-run relationship. This relationship is also valid when m2 is considered the financial development variable. Table 2 displays the normalized cointegrating coefficients at the bottom. Banu Demirhan. Examining the Financial Development Channels Affecting Economic Growth in Turkey 55 Table 1. Unit root tests Series ADF PP gdp 0.40 (0) 0.68 (5) ∆gdp -6.80 (0)*** -6.87 (4)*** cre -2.19 (0) -0.94 (3) ∆cre -2.06 (2) -4.71(1)*** m2 1.80 (10) -0.79 (17) ∆m2 -5.35 (3)*** -16.03 (47)*** open -0.74 (2) -0.71 (7) ∆open -6.71(1)*** -7.06 (12)*** Source: the author’s computation PP is the Phillips-Perron, and ADF is the Augmented Dickey-Fuller test. *** signifies the rejection of the non-stationary null hypothesis at the 1% level. The optimal lag order for the ADF test is chosen by considering the Akaike Information Criteria, represented in parentheses. The bandwidth is chosen for PP tests using the Newey-West method, and spectral estimation uses the Bartlett kernel, represented in parentheses. The 1%, 5%, and 10% critical values for the ADF and PP tests are -3.57, -2.92, and -2.60, respectively. Table 2. Cointegration test results (gdp, cre, open) (gdp, m2, open) Hypothesized No. of CE(s) Trace Statistic 0.05 Critical Value Prob. Hypothesized No. of CE(s) Trace Statistic 0.05 Critical Value Prob. r = 0* 45.74 29.79 0.0009 r = 0* 39.15 29.79 0.0305 r ≤ 1 12.60 15.49 0.3312 r ≤ 1 11.02 15.49 0.7438 r ≤ 2 1.29 3.84 0.5184 r ≤ 2 1.62 3.84 0.2215 gdp= 24.95 + 0.01 cre + 0.04 open (0.001) (0.002) gdp= 24.87 + 0.02 m2 + 0.03open (0.005) (0.005) Source: the author’s computation * denotes rejection of the hypothesis at the 5% level. The optimal lag order for the cointegration test is determined as 3, chosen by considering the Akaike Information Criteria. Standard errors of the coefficients in the cointegration equations are shown in parentheses. Below Table 2, we display the results of the cointegration equation showing the longterm effect of financial development indicators on economic growth. The first equation shows that the effect of credit to the private sector on economic growth is positive. The second equation shows that the broadly defined money supply contributes positively to economic growth. According to the cointegration equation, both financial development indicators positively affect economic growth in the long run. The Granger causality test based on VECM investigated the causal relationship between financial development and economic growth. The test results indicate that the credit ISSN 1392-1258 eISSN 2424-6166 Ekonomika. 2025, vol. 104(1) 62 financial development, obtained by using the TY method, confirms the studies of Özcan and Arı (2011) and Atay (2020). Policymakers can benefit from the significant policy recommendations provided by the empirical findings. The research findings indicate that the financial system’s growth in Turkey since the 1970s contributed to economic growth. Implementing policies to enhance the financial system is crucial to sustaining an average growth rate of 4.5 percent. The empirical results suggest that the financial system is vital for economic growth in Turkey, which is an economy with a robust banking system. Policymakers must prioritize policies designed to eliminate constraints on the financial system’s development and ensure financial stability. High inflation has been an ongoing problem in Turkey for a long time. To prevent inflation, policymakers limit the credit possibilities of the financial system, which, in turn, restricts the financial system’s influence on economic growth. In this context, it is favorable to implement fiscal and monetary policies rationally so that to ensure that the financial system can perform its functions to the highest level. Further studies are needed to investigate whether the impact of financial development on economic growth is sensitive to monetary and fiscal policies. Monetary and fiscal policies can play a role in the effect of financial development on economic growth. Implementing monetary policies that effectively reduce inflation will decrease uncertainty and stimulate the private sector’s demand for credit, thereby fostering economic growth. Furthermore, the establishment of fiscal discipline will be the foundation for allocating additional resources to the private sector, thereby supporting economic growth. Considering the current implementation of economic policies in Turkey which prioritize price stability and financial stability, further study is necessary to investigate the relationship between the financial system and monetary policies. Moreover, further studies will provide more detailed information on the effects of financial development on sectoral growth rates. Certain limitations of this study could be addressed in future research. Firstly, we performed analyses with limited data, as we only obtained the annual data. Second, significant economic and political developments affected the Turkish economy during the period examined. Our models incorporate structural changes and crises but do not include economic policies implemented since 2021. This is due to the unavailability of time data necessary to measure the impact of these policies. Despite all these limitations, the study findings provide important information about the relationships between financial development and economic growth. 7. Conclusions Analyzing the relationship between financial development and economic growth, as well as determining the source of financial development in Turkey, is crucial for assessing the effectiveness of policies implemented for financial development. This study analyzed Turkey’s data of 1974–2023 with various time series methods. The results show that financial development contributed to economic growth during the discussed period. This Banu Demirhan. Examining the Financial Development Channels Affecting Economic Growth in Turkey 63 contribution comes mainly from the banking system. The results show a unidirectional causal relationship from financial development to economic growth in Turkey in the short and long term. Although economic growth affects financial development, methodological differences are observed. The results confirm the validity of the Schumpeterian theory that financial development is a trigger factor in economic growth. The results also support Patrick’s (1966) supply-leading approach. Policymakers in Turkey have long encouraged financial market development and stability. Evidence suggests that Turkey’s financial development and stability measures are working. In this context, the development of the financial system in Turkey will significantly impact economic growth in the future. In particular, the development of the banking system will increase this impact. Empirical evidence supports the argument that policies aimed at enhancing financial development in Turkey yield gains by stimulating economic growth. In this context, it is beneficial to continue implementing policies to develop the financial system and ensure financial stability. 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Dev. 0.63 18.27 13.73 16.15 Skewness 0.14 1.06 0.55 -0.07 Kurtosis 1.85 2.53 2.25 2.69 Jarque-Bera 2.93 9.82 3.73 0.23 Probability 0.23 0.01 0.15 0.89 Obs. 50 50 50 50 Source: the author’s computation Table A2. Correlation matrix gdp cre m2 open gdp 1 cre 0.81 1 m2 0.94 0.88 1 open 0.93 0.67 0.87 1 Source: the author’s computation -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A1. CUSUM and CUSUMSQ tests (dependent variable: gdp, independent variables: cre and open) -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A2. CUSUM and CUSUMSQ tests (dependent variable: cre, independent variables: gdp and open) -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A1. CUSUM and CUSUMSQ tests (dependent variable: gdp, independent variables: cre and open) -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A2. CUSUM and CUSUMSQ tests (dependent variable: cre, independent variables: gdp and open) -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A1. CUSUM and CUSUMSQ tests (dependent variable: gdp, independent variables: cre and open) ISSN 1392-1258 eISSN 2424-6166 Ekonomika. 2025, vol. 104(1) 68 -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A1. CUSUM and CUSUMSQ tests (dependent variable: gdp, independent variables: cre and open) -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A2. CUSUM and CUSUMSQ tests (dependent variable: cre, independent variables: gdp and open) -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A1. CUSUM and CUSUMSQ tests (dependent variable: gdp, independent variables: cre and open) -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A2. CUSUM and CUSUMSQ tests (dependent variable: cre, independent variables: gdp and open) -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A2. CUSUM and CUSUMSQ tests (dependent variable: cre, independent variables: gdp and open) -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A1. CUSUM and CUSUMSQ tests (dependent variable: gdp, independent variables: cre and open) -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A2. CUSUM and CUSUMSQ tests (dependent variable: cre, independent variables: gdp and open) -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A1. CUSUM and CUSUMSQ tests (dependent variable: gdp, independent variables: cre and open) -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A2. CUSUM and CUSUMSQ tests (dependent variable: cre, independent variables: gdp and open) -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A3. CUSUM and CUSUMSQ tests (dependent variable: open, independent variables: cre and gdp) Source: the author’s computation Source: the author’s computation Figure A3. CUSUM and CUSUMSQ tests (dependent variable: open, independent variables: cre and gdp) -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A4. CUSUM and CUSUMSQ tests (dependent variable: gdp, independent variables: m2 and open) -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A5. CUSUM and CUSUMSQ tests (dependent variable: m2, independent variables: gdp and open) Source: the author’s computation Source: the author’s computation Figure A3. CUSUM and CUSUMSQ tests (dependent variable: open, independent variables: cre and gdp) -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A4. CUSUM and CUSUMSQ tests (dependent variable: gdp, independent variables: m2 and open) -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A5. CUSUM and CUSUMSQ tests (dependent variable: m2, independent variables: gdp and open) Source: the author’s computation Source: the author’s computation Figure A4. CUSUM and CUSUMSQ tests (dependent variable: gdp, independent variables: m2 and open) Banu Demirhan. Examining the Financial Development Channels Affecting Economic Growth in Turkey 69 Source: the author’s computation Source: the author’s computation Figure A3. CUSUM and CUSUMSQ tests (dependent variable: open, independent variables: cre and gdp) -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A4. CUSUM and CUSUMSQ tests (dependent variable: gdp, independent variables: m2 and open) -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A5. CUSUM and CUSUMSQ tests (dependent variable: m2, independent variables: gdp and open) Source: the author’s computation Source: the author’s computation Figure A3. CUSUM and CUSUMSQ tests (dependent variable: open, independent variables: cre and gdp) -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A4. CUSUM and CUSUMSQ tests (dependent variable: gdp, independent variables: m2 and open) -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A5. CUSUM and CUSUMSQ tests (dependent variable: m2, independent variables: gdp and open) Source: the author’s computation Source: the author’s computation Figure A5. CUSUM and CUSUMSQ tests (dependent variable: m2, independent variables: gdp and open) -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A6. CUSUM and CUSUMSQ tests (dependent variable: open, independent variables: m2 and gdp) -15 -10 -5 0 5 10 15 02 04 06 08 10 12 14 16 18 20 22 CUSUM 5% Significance -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 02 04 06 08 10 12 14 16 18 20 22 CUSUM of Squares 5% Significance Source: the author’s computation Source: the author’s computation Figure A6. CUSUM and CUSUMSQ tests (dependent variable: open, independent variables: m2 and gdp) Source: the author’s computation Source: the author’s computation Figure A6. CUSUM and CUSUMSQ tests (dependent variable: open, independent variables: m2 and gdp)