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Dinamik Sermaye Yapısı Belirleyicileri ve Optimal Kaldıraç Oranı Uyarlama Hızı: Türkiye’de Finans Şirketleri Üzerine Bir Çalışma

Year 2022, , 137 - 155, 30.06.2022
https://doi.org/10.26650/ISTJECON2021-1083801

Abstract

Bu çalışma Türkiye’de faaliyet gösteren finansal şirketlerin sermaye yapılarını oluştururken bir hedef doğrultusunda hareket edip etmedikleri ve uyarlama maliyetlerinin olduğu bir ortamda uyarlama hızlarının ne olduğunun tespit edilmesi amacıyla yapılmıştır. Finansal şirketlerin borç uyarlama hızlarını analiz etmek üzere gerekli olan veri Amerikan “Standard and Poor’s” firmasının küresel şirket verilerini tuttuğu S&P Compustat Fundementals veri tabanından derlenmiştir. Veri setinde 114 finansal şirkete (mevduat bankaları, katılım bankaları, menkul ve gayrimenkul yatırım ortaklıkları ve sigorta şirketleri) ait 1996-2018 yıllarını kapsayan toplam 1570 firma-yılı gözlem bulunmaktadır. Dinamik panel veri analiz yöntemlerinden GMM-SYS kullanılarak yapılan analizler sonucu, finansal şirketlerin cari borçlarını optimal borç oranına uyarlama hızı 26% olarak tespit edilmiştir. Ancak bu hızın finansal şirketlerin toplam borçlanma oranlarının art arda düştüğü 2008 yılını da içine alan küresel finans krizi sürecinde (2007-2010) 19%’a gerilediği görülmüştür. Modellerden elde edilen bulgular yorumlandığında, finansal şirketlerin sermayelerini yapılandırırken alternatif finansman tercihleri arasında hiyerarşik bir sıralama yapmak yerine, borç ve özsermaye oranlarını belli bir seviyede tutmak amacıyla hedef bir borç oranı etrafında dengeleme davranışı sergilediklerini söylemek yanlış olmayacaktır. Araştırma keşfedici nitelikte bir çalışma olduğundan, uyarlama hızını etkileyen faktörler ve bu faktörlerin farklı dönemlerde uyarlama hızını ne ölçüde arttırdığı veya azalttığı çalışmanın kapsamı dışındadır. Firma yönetimlerine optimal sermaye yapısı kararlarında yardımcı olunabilmesi için gelecekteki çalışmaların uyarlama hızına etki eden kurumsal ve makroekonomik bazı değişkenler üzerine yoğunlaşması uygun olacaktır.

References

  • 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. google scholar
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  • Baltagi, B. H. (2008). Econometric analysis of panel data (Vol. 4). Chichester: John Wiley & Sons. google scholar
  • Basu, S. (1977). Investment performance of common stocks in relation to their price-earnings ratios: A test of the efficient market hypothesis. The Journal of Finance, 32(3), 663-682. google scholar
  • Baxter, N. D. (1967). Leverage, risk of ruin and the cost of capital. The Journal of Finance, 22(3), 395-403. google scholar
  • Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87(1), 115-143. google scholar
  • Booth, L. Aivazian, V. Demirguc-Kunt, A. & Maksimovic, V. (2001). Capital structures in developing countries. The Journal of Finance, 56(1), 87-130. google scholar
  • Bradley, M. Jarrell, G. & Kim, E.H. (1984). On the existence of an optimal capital structure: Theory and evidence. The Journal of Finance, 39(3), 857-878. google scholar
  • De Miguel, A. and Pindado, J. 2001. Determinants of capital structure: New evidence from spanish panel data. Journal or Corporate Finance, 7: 77-99. google scholar
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  • Frank, M. Z. & Goyal, V. K. (2009). Capital structure decisions: Which factors are reliably important? Financial Management, 38(1), 1-37. google scholar
  • Hansen, L. P. (1982). Large sample properties of generalized method of moments estimators. Econometrica: Journal of the econometric society, 1029-1054. google scholar
  • Hirshleifer, J. (1966). Investment decision under uncertainty: Applications of the state-preference approach. Quarterly Journal of Economics, 80(2), 252-277. google scholar
  • Huang, R., & Ritter, J. R. (2009). Testing theories of capital structure and estimating the speed of adjustment. Journal of Financial and Quantitative analysis, 44(2), 237-271. google scholar
  • Hovakimian, A., Opler, T. & Titman, S. (2001). The debt equity choice. Journal of Financial and Quantitative Analysis, 36(1), 1-24. google scholar
  • Jalilvand, A., & Harris, R. S. (1984). Corporate behavior in adjusting to capital structure and dividend targets: An econometric study. The Journal of Finance, 39(1), 127-145. google scholar
  • Kraus, A.,& Litzenberger, R. H. (1973). A state-preference model of optimal financial leverage. The Journal of Finance, 28(4), 911-922. google scholar
  • Lemmon, M. L., Roberts, M. R., & Zender, J. F. (2008). Back to the beginning: Persistence and the cross-section of corporate capital structure. The journal of finance, 63(4), 1575-1608. google scholar Myers, S.C. (1984). Capital structure puzzle. The Journal of Finance, 39(3), 261-274. google scholar
  • Myers, S. C. & Majluf, N. S. (1984). Corporate financing and investment decisions when firms have information that investors do not have. Journal of Financial Economics, 13(2), 187-221. google scholar
  • Öztekin, Ö., & Flannery, M. J. (2012). Institutional determinants of capital structure adjustment speeds. Journal of financial economics, 103(1), 88-112. google scholar
  • Rajan, R. G. & Zingales, L. (1995). What do we know about capital structure? Some evidence from international data. The journal of Finance, 50(5), 1421-1460. google scholar
  • Scott Jr, J. H. (1976). A theory of optimal capital structure. The Bell Journal of Economics, 7(1), 33-54. google scholar
  • Stiglitz, J. E. (1972). Some aspects of the pure theory of corporate finance: Bankruptcies and takeovers. Bell Journal of Economics, 3(2), 458-482. google scholar
  • Titman, S. & Wessels, R. (1988). The determinants of capital structure choice. The Journal of Finance, 43(1), 1-19. google scholar
  • Yıldız, Y. (2018). Adjustment to target capital structure and global financial crisis: Evidence from Turkey. Business and Economics Research Journal, 9(3), 543-557. google scholar

Determinants of Dynamic Capital Structure and the Speed of Adjustment to Optimal Leverage: A Study on Financial Institutions in Turkiye

Year 2022, , 137 - 155, 30.06.2022
https://doi.org/10.26650/ISTJECON2021-1083801

Abstract

This study examines whether financial institutions in Turkiye revise target debt ratios when determining capital structures, in addition to investigating the speed of adjustment to optimal capital structure in the presence of adjustment costs. The data were obtained from the COMPUSTAT Fundamentals database, which is maintained by Standard & Poor’s. The dataset covers 1,570 firm-year observations from 114 financial institutions (deposit banks, Islamic banks, securities, real estate investment trusts, and insurance companies) between 1996 and 2018. Using the dynamic panel data analysis method GMM-SYS, the speed of adjustment to optimal capital structure is determined to be 26%; however, during the global financial crisis (2007–2010), when financial institutions’ total debt ratios declined, this speed plummeted to 19%. Based on the results of the analysis, it is reasonable to conclude that financial firms conduct balancing behavior around a target debt ratio to maintain optimal debt ratios when structuring capital, rather than making a hierarchical selection among alternative financing options. As the study is an exploratory endeavor to determine the speed of adjustment, the factors affecting the adjustment speed and the extent to which these factors increase or decrease adjustment speeds in different periods are beyond the scope of the study. Future research should consider institutional and macroeconomic determinants of adjustment speed to help advise firm executives about the optimal capital structures of their respective firms.

References

  • 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. google scholar
  • Arıoglu, E., & Tuan, K. (2014). Speed of adjustment: Evidence from borsa Istanbul. Borsa Istanbul Review, 14(2), 126-131. google scholar
  • Baltagi, B. H. (2008). Econometric analysis of panel data (Vol. 4). Chichester: John Wiley & Sons. google scholar
  • Basu, S. (1977). Investment performance of common stocks in relation to their price-earnings ratios: A test of the efficient market hypothesis. The Journal of Finance, 32(3), 663-682. google scholar
  • Baxter, N. D. (1967). Leverage, risk of ruin and the cost of capital. The Journal of Finance, 22(3), 395-403. google scholar
  • Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87(1), 115-143. google scholar
  • Booth, L. Aivazian, V. Demirguc-Kunt, A. & Maksimovic, V. (2001). Capital structures in developing countries. The Journal of Finance, 56(1), 87-130. google scholar
  • Bradley, M. Jarrell, G. & Kim, E.H. (1984). On the existence of an optimal capital structure: Theory and evidence. The Journal of Finance, 39(3), 857-878. google scholar
  • De Miguel, A. and Pindado, J. 2001. Determinants of capital structure: New evidence from spanish panel data. Journal or Corporate Finance, 7: 77-99. google scholar
  • Demir, N. (2019). Dynamics of capital structure: An empirical analysis of Turkish banking sector (Doctoral Dissertation), retrieved from https://research.sabanciuniv.edu/39461/1/10219245_ NazanDemir.pdf. google scholar
  • Fama, E. F. & French, K. R. (2002). Testing trade-off and pecking order predictions about dividends and debt. Review of Financial Studies, 15(1), 1-33. google scholar
  • Fischer, E. O., Heinkel, R. & Zechner, J. (1989). Dynamic capital structure choice: Theory and tests. The Journal of Finance, 44(1), 19-40. google scholar
  • Frank, M. Z. & Goyal, V. K. (2009). Capital structure decisions: Which factors are reliably important? Financial Management, 38(1), 1-37. google scholar
  • Hansen, L. P. (1982). Large sample properties of generalized method of moments estimators. Econometrica: Journal of the econometric society, 1029-1054. google scholar
  • Hirshleifer, J. (1966). Investment decision under uncertainty: Applications of the state-preference approach. Quarterly Journal of Economics, 80(2), 252-277. google scholar
  • Huang, R., & Ritter, J. R. (2009). Testing theories of capital structure and estimating the speed of adjustment. Journal of Financial and Quantitative analysis, 44(2), 237-271. google scholar
  • Hovakimian, A., Opler, T. & Titman, S. (2001). The debt equity choice. Journal of Financial and Quantitative Analysis, 36(1), 1-24. google scholar
  • Jalilvand, A., & Harris, R. S. (1984). Corporate behavior in adjusting to capital structure and dividend targets: An econometric study. The Journal of Finance, 39(1), 127-145. google scholar
  • Kraus, A.,& Litzenberger, R. H. (1973). A state-preference model of optimal financial leverage. The Journal of Finance, 28(4), 911-922. google scholar
  • Lemmon, M. L., Roberts, M. R., & Zender, J. F. (2008). Back to the beginning: Persistence and the cross-section of corporate capital structure. The journal of finance, 63(4), 1575-1608. google scholar Myers, S.C. (1984). Capital structure puzzle. The Journal of Finance, 39(3), 261-274. google scholar
  • Myers, S. C. & Majluf, N. S. (1984). Corporate financing and investment decisions when firms have information that investors do not have. Journal of Financial Economics, 13(2), 187-221. google scholar
  • Öztekin, Ö., & Flannery, M. J. (2012). Institutional determinants of capital structure adjustment speeds. Journal of financial economics, 103(1), 88-112. google scholar
  • Rajan, R. G. & Zingales, L. (1995). What do we know about capital structure? Some evidence from international data. The journal of Finance, 50(5), 1421-1460. google scholar
  • Scott Jr, J. H. (1976). A theory of optimal capital structure. The Bell Journal of Economics, 7(1), 33-54. google scholar
  • Stiglitz, J. E. (1972). Some aspects of the pure theory of corporate finance: Bankruptcies and takeovers. Bell Journal of Economics, 3(2), 458-482. google scholar
  • Titman, S. & Wessels, R. (1988). The determinants of capital structure choice. The Journal of Finance, 43(1), 1-19. google scholar
  • Yıldız, Y. (2018). Adjustment to target capital structure and global financial crisis: Evidence from Turkey. Business and Economics Research Journal, 9(3), 543-557. google scholar
There are 27 citations in total.

Details

Primary Language Turkish
Subjects Business Administration
Journal Section Research Article
Authors

Hülya Yılmaz 0000-0002-1735-445X

Publication Date June 30, 2022
Submission Date March 7, 2022
Published in Issue Year 2022

Cite

APA Yılmaz, H. (2022). Dinamik Sermaye Yapısı Belirleyicileri ve Optimal Kaldıraç Oranı Uyarlama Hızı: Türkiye’de Finans Şirketleri Üzerine Bir Çalışma. İstanbul İktisat Dergisi, 72(1), 137-155. https://doi.org/10.26650/ISTJECON2021-1083801
AMA Yılmaz H. Dinamik Sermaye Yapısı Belirleyicileri ve Optimal Kaldıraç Oranı Uyarlama Hızı: Türkiye’de Finans Şirketleri Üzerine Bir Çalışma. İstanbul İktisat Dergisi. June 2022;72(1):137-155. doi:10.26650/ISTJECON2021-1083801
Chicago Yılmaz, Hülya. “Dinamik Sermaye Yapısı Belirleyicileri Ve Optimal Kaldıraç Oranı Uyarlama Hızı: Türkiye’de Finans Şirketleri Üzerine Bir Çalışma”. İstanbul İktisat Dergisi 72, no. 1 (June 2022): 137-55. https://doi.org/10.26650/ISTJECON2021-1083801.
EndNote Yılmaz H (June 1, 2022) Dinamik Sermaye Yapısı Belirleyicileri ve Optimal Kaldıraç Oranı Uyarlama Hızı: Türkiye’de Finans Şirketleri Üzerine Bir Çalışma. İstanbul İktisat Dergisi 72 1 137–155.
IEEE H. Yılmaz, “Dinamik Sermaye Yapısı Belirleyicileri ve Optimal Kaldıraç Oranı Uyarlama Hızı: Türkiye’de Finans Şirketleri Üzerine Bir Çalışma”, İstanbul İktisat Dergisi, vol. 72, no. 1, pp. 137–155, 2022, doi: 10.26650/ISTJECON2021-1083801.
ISNAD Yılmaz, Hülya. “Dinamik Sermaye Yapısı Belirleyicileri Ve Optimal Kaldıraç Oranı Uyarlama Hızı: Türkiye’de Finans Şirketleri Üzerine Bir Çalışma”. İstanbul İktisat Dergisi 72/1 (June 2022), 137-155. https://doi.org/10.26650/ISTJECON2021-1083801.
JAMA Yılmaz H. Dinamik Sermaye Yapısı Belirleyicileri ve Optimal Kaldıraç Oranı Uyarlama Hızı: Türkiye’de Finans Şirketleri Üzerine Bir Çalışma. İstanbul İktisat Dergisi. 2022;72:137–155.
MLA Yılmaz, Hülya. “Dinamik Sermaye Yapısı Belirleyicileri Ve Optimal Kaldıraç Oranı Uyarlama Hızı: Türkiye’de Finans Şirketleri Üzerine Bir Çalışma”. İstanbul İktisat Dergisi, vol. 72, no. 1, 2022, pp. 137-55, doi:10.26650/ISTJECON2021-1083801.
Vancouver Yılmaz H. Dinamik Sermaye Yapısı Belirleyicileri ve Optimal Kaldıraç Oranı Uyarlama Hızı: Türkiye’de Finans Şirketleri Üzerine Bir Çalışma. İstanbul İktisat Dergisi. 2022;72(1):137-55.