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CROSS-BORDER LOAN LIABILITY, THE EXCHANGE RATE AND PROFITABILITY IN THE TURKISH BANKING SECTOR

Year 2018, Volume: 40 Issue: 1, 51 - 68, 27.06.2018

Gökhan Övenç Resul Aydemir

https://doi.org/10.14780/muiibd.434951

Abstract

We examine how the cross border banking loan liabilities (syndication and securitization loans) and

the exchange rate affect the Turkish banking industry profitability using a balanced panel data for the

period 2003Q1-2016Q3. We study with different subsamples and model specifications. Overall, we find

that the banking sector financial inflows are positively associated with bank profitability. Specifically, the

results show that the banking sector cross border inflows have significant and positive impact on return

on assets (ROA), return on equity (ROE) and on net interest margin (NIM). The long-term inflows

play a more important role than the short-term inflows in explaining profitability in all specifications

while short-term inflows have no any significant effect on these profitability indicators. Moreover, we

show that the exchange rate has significant and negative impact on ROA and ROE and has insignificant

effect on NIM. Our findings are more notable in private banks compared to the whole sample. Given

the fact that the existing studies examine the banking profitability through aggregate capital inflows

and maturity mismatch, this study will fill a meaningful gap in emerging market literature.

Keywords

Cross Border Banking Liability Long-term Liability Short-term Liability The Exchange Rate Bank Profitability Net Interest Margin Return on Asset

References

  • AGENOR, P. R., McDermott, C. J., & Üçer, M. (1997). Fiscal imbalances, capital inflows, and the real exchange rate: the case of Turkey. European Economic Review, 41(3), 819-825.
  • AKCELİK, Y., Basci, E., Ermisoglu, E., & Oduncu, A. (2013). The Turkish approach to capital flow volatility. Central Bank of the Republic of Turkey Working Paper, (13/06).
  • ALPER, K., Kara, H., & Yörükoğlu, M. (2013). Alternative tools to manage capital flow volatility. BIS Paper, (73z).
  • ARELLANO, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The review of economic studies, 58(2), 277-297.
  • ARELLANO, M., & Bover, O. (1995). Another look at the instrumental variable estimation of errorcomponents models. Journal of econometrics, 68(1), 29-51.
  • AYDIN, B., & Igan, D. (2012). Bank lending in Turkey: Effects of monetary and fiscal policies. Emerging Markets Finance and Trade, 48(5), 78-104.
  • AYSAN, A. F., Fendoglu, S., & Kilinc, M. (2014). Managing short-term capital flows in new central banking: unconventional monetary policy framework in Turkey. Eurasian Economic Review, 4(1), 45-69.
  • AYSUN, U. (2012). Capital flows, maturity mismatches, and profitability in emerging markets: evidence from bank level data. The Journal of Developing Areas, 46(1), 211-239.
  • BALTAGI, B. H. (2008). Forecasting with Panel Data. Journal of Forecasting, 27, p. 153- 173.
  • BIKKER, J. A., & Haaf, K. (2002). Competition, concentration and their relationship: An empirical analysis of the banking industry. Journal of Banking & Finance, 26(11), 2191-2214.
  • BLUNDELL, R.W. and Bond, S.R. (1998). Initial Conditions and Moment Restrictions in Dynamic Panel Data Models. Journal of Econometrics, 87: 115-143.
  • BRONER, F., Didier, T., Erce, A., & Schmukler, S. L. (2013). Gross capital flows: Dynamics and crises. Journal of Monetary Economics, 60(1), 113-133.
  • BRUNO, V., & Shin, H. S. (2014). Cross-Border Banking and Global Liquidity*.The Review of Economic Studies, rdu042.
  • CABALLERO, J. A. (2014). Do surges in international capital inflows influence the likelihood of banking crises?. The Economic Journal. October 2014, p.281-290.
  • CALVO, G. A., Leiderman, L., & Reinhart, C. M. (1994). The capital inflows problem: Concepts and issues. Contemporary Economic Policy, 12(3), 54-66.
  • CALVO, G. A., Leiderman, L., & Reinhart, C. M. (1996). Inflows of Capital to Developing Countries in the 1990s. The Journal of Economic Perspectives, 123-139.
  • CBRT, Financial Stability Report, November 2015.
  • CRAGG, J. G., and Donald, S.G. (1993). Testing identifiability and Specification in Instrumental Variables Models. Econometric Theory, 9: 222–240.
  • DAVIDSON, R. and MacKinnon, J.G. (1993). Estimation and Inference in Econometrics. Oxford:Oxford University Press.
  • GREENE, W. H. (2008). Econometric Analysis. Granite Hill Publishers.
  • HANSEN, L. P. (1982). Large sample properties of generalized method of moments estimators. Econometrica: Journal of the Econometric Society, 1029-1054.
  • HERRMANN, S., & Mihaljek, D. (2010). The determinants of cross-border bank flows to emerging markets: new empirical evidence on the spread of financial crises.
  • KLEIBERGEN, F., & Paap, R. (2006). Generalized reduced rank tests using the singular value decomposition. Journal of econometrics, 133(1), 97-126.
  • MENDOZA, E. G., & Terrones, M. E. (2008). An anatomy of credit booms: evidence from macro aggregates and micro data (No. w14049). National Bureau of Economic Research.
  • MERCAN, M., Reisman, A., Yolalan, R., & Emel, A. B. (2003). The effect of scale and mode of ownership on the financial performance of the Turkish banking sector: results of a DEA-based analysis. Socio-Economic Planning Sciences, 37(3), 185-202.
  • MISHKIN, F. S. (2009). Why we shouldn’t turn our backs on financial globalization. IMF Staff Papers, 139-170.
  • OZSUCA, E. A., & Akbostanci, E. (2015). An Empirical Analysis of the Risk Taking Channel of Monetary Policy in Turkey. Emerging Markets Finance and Trade, ,1-21.
  • SCHAFFER, M. E. (2012). xtivreg2: Stata module to perform extended IV/2SLS, GMM and AC/HAC, LIML and k-class regression for panel data models.Statistical Software Components.
  • STOCK, J. H., & Yogo, M. (2002). Testıng For Weak Instruments In Linear Iv Regression. National Bureau Of Economic Research, Working Paper No: 284.
  • REINHART, C. M., & Rogoff, K. (2009). This time is different: eight centuries of financial folly. Princeton University Press.
  • REINHART, C., & Calvo, G. (2000). When capital inflows come to a sudden stop: Consequences and policy options. , Munich Personal RePEc Archive, 2000, No: 6982.
  • YENTÜRK, N. (1999). SHORT‐TERM CAPITAL INFLOWS AND THEIR IMPACT ON MACROECONOMIC STRUCTURE: TURKEY IN THE 1990s.The Developing Economies, 37(1), 89-113.
  • WOOLDRIDGE, J. M. (2010). Econometric analysis of cross section and panel data. MIT press.

Year 2018, Volume: 40 Issue: 1, 51 - 68, 27.06.2018

Gökhan Övenç Resul Aydemir

https://doi.org/10.14780/muiibd.434951

Abstract

References

  • AGENOR, P. R., McDermott, C. J., & Üçer, M. (1997). Fiscal imbalances, capital inflows, and the real exchange rate: the case of Turkey. European Economic Review, 41(3), 819-825.
  • AKCELİK, Y., Basci, E., Ermisoglu, E., & Oduncu, A. (2013). The Turkish approach to capital flow volatility. Central Bank of the Republic of Turkey Working Paper, (13/06).
  • ALPER, K., Kara, H., & Yörükoğlu, M. (2013). Alternative tools to manage capital flow volatility. BIS Paper, (73z).
  • ARELLANO, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The review of economic studies, 58(2), 277-297.
  • ARELLANO, M., & Bover, O. (1995). Another look at the instrumental variable estimation of errorcomponents models. Journal of econometrics, 68(1), 29-51.
  • AYDIN, B., & Igan, D. (2012). Bank lending in Turkey: Effects of monetary and fiscal policies. Emerging Markets Finance and Trade, 48(5), 78-104.
  • AYSAN, A. F., Fendoglu, S., & Kilinc, M. (2014). Managing short-term capital flows in new central banking: unconventional monetary policy framework in Turkey. Eurasian Economic Review, 4(1), 45-69.
  • AYSUN, U. (2012). Capital flows, maturity mismatches, and profitability in emerging markets: evidence from bank level data. The Journal of Developing Areas, 46(1), 211-239.
  • BALTAGI, B. H. (2008). Forecasting with Panel Data. Journal of Forecasting, 27, p. 153- 173.
  • BIKKER, J. A., & Haaf, K. (2002). Competition, concentration and their relationship: An empirical analysis of the banking industry. Journal of Banking & Finance, 26(11), 2191-2214.
  • BLUNDELL, R.W. and Bond, S.R. (1998). Initial Conditions and Moment Restrictions in Dynamic Panel Data Models. Journal of Econometrics, 87: 115-143.
  • BRONER, F., Didier, T., Erce, A., & Schmukler, S. L. (2013). Gross capital flows: Dynamics and crises. Journal of Monetary Economics, 60(1), 113-133.
  • BRUNO, V., & Shin, H. S. (2014). Cross-Border Banking and Global Liquidity*.The Review of Economic Studies, rdu042.
  • CABALLERO, J. A. (2014). Do surges in international capital inflows influence the likelihood of banking crises?. The Economic Journal. October 2014, p.281-290.
  • CALVO, G. A., Leiderman, L., & Reinhart, C. M. (1994). The capital inflows problem: Concepts and issues. Contemporary Economic Policy, 12(3), 54-66.
  • CALVO, G. A., Leiderman, L., & Reinhart, C. M. (1996). Inflows of Capital to Developing Countries in the 1990s. The Journal of Economic Perspectives, 123-139.
  • CBRT, Financial Stability Report, November 2015.
  • CRAGG, J. G., and Donald, S.G. (1993). Testing identifiability and Specification in Instrumental Variables Models. Econometric Theory, 9: 222–240.
  • DAVIDSON, R. and MacKinnon, J.G. (1993). Estimation and Inference in Econometrics. Oxford:Oxford University Press.
  • GREENE, W. H. (2008). Econometric Analysis. Granite Hill Publishers.
  • HANSEN, L. P. (1982). Large sample properties of generalized method of moments estimators. Econometrica: Journal of the Econometric Society, 1029-1054.
  • HERRMANN, S., & Mihaljek, D. (2010). The determinants of cross-border bank flows to emerging markets: new empirical evidence on the spread of financial crises.
  • KLEIBERGEN, F., & Paap, R. (2006). Generalized reduced rank tests using the singular value decomposition. Journal of econometrics, 133(1), 97-126.
  • MENDOZA, E. G., & Terrones, M. E. (2008). An anatomy of credit booms: evidence from macro aggregates and micro data (No. w14049). National Bureau of Economic Research.
  • MERCAN, M., Reisman, A., Yolalan, R., & Emel, A. B. (2003). The effect of scale and mode of ownership on the financial performance of the Turkish banking sector: results of a DEA-based analysis. Socio-Economic Planning Sciences, 37(3), 185-202.
  • MISHKIN, F. S. (2009). Why we shouldn’t turn our backs on financial globalization. IMF Staff Papers, 139-170.
  • OZSUCA, E. A., & Akbostanci, E. (2015). An Empirical Analysis of the Risk Taking Channel of Monetary Policy in Turkey. Emerging Markets Finance and Trade, ,1-21.
  • SCHAFFER, M. E. (2012). xtivreg2: Stata module to perform extended IV/2SLS, GMM and AC/HAC, LIML and k-class regression for panel data models.Statistical Software Components.
  • STOCK, J. H., & Yogo, M. (2002). Testıng For Weak Instruments In Linear Iv Regression. National Bureau Of Economic Research, Working Paper No: 284.
  • REINHART, C. M., & Rogoff, K. (2009). This time is different: eight centuries of financial folly. Princeton University Press.
  • REINHART, C., & Calvo, G. (2000). When capital inflows come to a sudden stop: Consequences and policy options. , Munich Personal RePEc Archive, 2000, No: 6982.
  • YENTÜRK, N. (1999). SHORT‐TERM CAPITAL INFLOWS AND THEIR IMPACT ON MACROECONOMIC STRUCTURE: TURKEY IN THE 1990s.The Developing Economies, 37(1), 89-113.
  • WOOLDRIDGE, J. M. (2010). Econometric analysis of cross section and panel data. MIT press.
There are 33 citations in total.

Details

Primary Language English
Subjects Economics
Journal Section Makaleler
Authors

Gökhan Övenç

Resul Aydemir This is me

Publication Date June 27, 2018
Submission Date April 1, 2018
Published in Issue Year 2018 Volume: 40 Issue: 1

Cite

APA Övenç, G., & Aydemir, R. (2018). CROSS-BORDER LOAN LIABILITY, THE EXCHANGE RATE AND PROFITABILITY IN THE TURKISH BANKING SECTOR. Marmara Üniversitesi İktisadi Ve İdari Bilimler Dergisi, 40(1), 51-68. https://doi.org/10.14780/muiibd.434951
AMA Övenç G, Aydemir R. CROSS-BORDER LOAN LIABILITY, THE EXCHANGE RATE AND PROFITABILITY IN THE TURKISH BANKING SECTOR. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi. June 2018;40(1):51-68. doi:10.14780/muiibd.434951
Chicago Övenç, Gökhan, and Resul Aydemir. “CROSS-BORDER LOAN LIABILITY, THE EXCHANGE RATE AND PROFITABILITY IN THE TURKISH BANKING SECTOR”. Marmara Üniversitesi İktisadi Ve İdari Bilimler Dergisi 40, no. 1 (June 2018): 51-68. https://doi.org/10.14780/muiibd.434951.
EndNote Övenç G, Aydemir R (June 1, 2018) CROSS-BORDER LOAN LIABILITY, THE EXCHANGE RATE AND PROFITABILITY IN THE TURKISH BANKING SECTOR. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi 40 1 51–68.
IEEE G. Övenç and R. Aydemir, “CROSS-BORDER LOAN LIABILITY, THE EXCHANGE RATE AND PROFITABILITY IN THE TURKISH BANKING SECTOR”, Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi, vol. 40, no. 1, pp. 51–68, 2018, doi: 10.14780/muiibd.434951.
ISNAD Övenç, Gökhan - Aydemir, Resul. “CROSS-BORDER LOAN LIABILITY, THE EXCHANGE RATE AND PROFITABILITY IN THE TURKISH BANKING SECTOR”. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi 40/1 (June 2018), 51-68. https://doi.org/10.14780/muiibd.434951.
JAMA Övenç G, Aydemir R. CROSS-BORDER LOAN LIABILITY, THE EXCHANGE RATE AND PROFITABILITY IN THE TURKISH BANKING SECTOR. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi. 2018;40:51–68.
MLA Övenç, Gökhan and Resul Aydemir. “CROSS-BORDER LOAN LIABILITY, THE EXCHANGE RATE AND PROFITABILITY IN THE TURKISH BANKING SECTOR”. Marmara Üniversitesi İktisadi Ve İdari Bilimler Dergisi, vol. 40, no. 1, 2018, pp. 51-68, doi:10.14780/muiibd.434951.
Vancouver Övenç G, Aydemir R. CROSS-BORDER LOAN LIABILITY, THE EXCHANGE RATE AND PROFITABILITY IN THE TURKISH BANKING SECTOR. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi. 2018;40(1):51-68.
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