Yıl: 2021 Cilt: 6 Sayı: 16 Sayfa Aralığı: 255 - 256 Metin Dili: Türkçe DOI: 10.29399/npa.28019 İndeks Tarihi: 30-12-2021

Klinik İzole Sendrom ve Multipl Sklerozda Fosforile Nörofilament Ağır Zinciri (pNFH)

Öz:
-
Anahtar Kelime:

Makroekonomik Faktörlerin Sorunlu Krediler Üzerindeki Etkisi: Türkiye İçin Bir Zaman Serisi Analizi

Öz:
2008 Küresel Krizi ile takipteki krediler hem gelişmiş hem de gelişmekte olan ülkelerde önemli ölçüde artmıştır. Sorunlu kredilerdeki aşırı ve kontrolsüz artış, bankacılık sisteminde ciddi bir bozulmaya neden olmuştur. Bankacılık siteminin önemli olduğu Türkiye gibi ülkelerde sistemdeki bozulma sadece finansal piyasaları değil, ekonomiyi bir bütün olarak olumsuz yönde etkilemektedir. Bu çalışmada, literatürde dışsal faktörler olarak ifade edilen makroekonomik değişkenlerden döviz kuru, faiz oranı, toplam kredi hacmi ve üretim ile sorunlu krediler arasındaki ilişki 2008:01-2017:12 dönemi Türkiye için incelenmiştir. Analiz yöntemi olarak Pesaran vd. tarafından geliştirilen ARDL analizi kapsamında sınırsız hata düzeltme modeli (UECM) ve sınır testi yaklaşımı (2001) uygulanmıştır. Analiz sonuçları değerlendirildiğinde, ele alınan makroekonomik değişkenlerin ve sorunlu kredilerin eşbütünleşik olduğu bulunmuştur. Ayrıca, faiz oranı ile toplam kredi hacmi ve sorunlu krediler arasında hem uzun hem de kısa vadede ekonomik ve istatistiksel olarak anlamlı bir ilişki olduğu sonucuna ulaşılmıştır. Yani faiz oranı ve toplam kredi hacmi artarsa sorunlu kredilerin de aynı yönde hareket ettiği tespit edilmiştir.
Anahtar Kelime:

The Effect of Macroeconomic Factors on Non-Performing Loans: A Time Series Analysis for Turkey

Öz:
With the 2008 Global Crisis, Non-performing loans (NPLs) has dramatically increased in both developed and developing countries. The excessive and uncontrolled increase in NPLs caused serious deterioration in the banking system. Particularly, in the countries, such as Turkey, where the banking system has a quite significant place in financial system, the deterioration in the banking system affects not only financial markets but also the economy in a negative way. In this research paper, the association between exchange rate, interest rate, total loan volume and production (output), which are macroeconomic variables expressed as external factors in the literature, and NPLs is investigated for 2008:01-2017:12 period in Turkey. Unrestricted error correction model (UECM) and boundary test approach with the scope of ARDL analysis developed by Pesaran et al. (2001) is applied as an analysis method. Based on the analysis results, it is found that these macroeconomic variables and NPLs are cointegrated. Moreover, there is an economical and statistically significant relationship between interest rate and total loan volume and NPLs in both long and short term. In other words, it is determined that if interest rate and total loan volume increases, NPLs also move in the same direction.
Anahtar Kelime:

Phosphorylated Neurofilament Heavy Chain (pNFH) in Clinically Isolated Syndrome and Multiple Sclerosis

Öz:
-
Anahtar Kelime:

Belge Türü: Makale Makale Türü: Editoryal Erişim Türü: Erişime Açık
  • Akbalık, M. (2009). Bankalarda stres testi. İstanbul: Avcıol Basım Yayın.
  • 1. Fuchs E, Cleveland DW. A structural scaffolding of intermediate filaments in health and disease. Science 1998;279:514–519.
  • Akel, V. and Gazel, S. (2014). Döviz kurları ile BIST sanayi endeksi arasındaki eşbütünleşme ilişkisi: Bir ARDL sınır testi yaklaşımı. Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 44, 23-41
  • 2. Khalil M, Teunissen CE, Otto M, Piehl F, Sormani MP, Gattringer T, Barro C, Kappos L, Comabella M, Fazekas F, Petzold A, Blennow K, Zetterberg H, Kuhle J. Neurofilaments as biomarkers in neurological disorders. Nat Rev Neurol 2018;14:577–589.
  • Bayraktar, Y. and Karaoğlu, E. (2016). Reel konjonktür teorisi, getirdiği yenilikler ve diğer konjonktür teorileri ile karşılaştırılması. Yalova Sosyal Bilimler Dergisi, 6(12), 140-162
  • 3. Gordon BA. Neurofilaments in disease: what do we know? Curr Opin Neurobiol 2020;61:105–115.
  • Beaton, K., Myrvoda, A. and Thompson S. (2016). Non-performing loans in the ECCU: Determinants and macroeconomic impact. IMF Working Paper, 16/229
  • 4. Kuhle J, Barro C, Andreasson U, Derfuss T, Lindberg R, Sandelius Å, Liman V, Norgren N, Blennow K, Zetterberg H. Comparison of three analytical platforms for quantification of the neurofilament light chain in blood samples: ELISA, electrochemiluminescence immunoassay and Simoa. Clin Chem Lab Med 2016;54:1655–1661.
  • Beck, R., Jakubík, P. and Piloiu, A. (2013). Non-performing loans: What matters in addition to the economic cycle?. European Central Bank Working Paper, 1515, 1-34
  • 5. Teunissen CE, Iacobaeus E, Khademi M, Brundin L, Norgren N, KoelSimmelink MJ, Schepens M, Bouwman F, Twaalfhoven HA, Blom HJ, Jakobs C, Dijkstra CD. Combination of CSF N-acetylaspartate and neurofilaments in multiple sclerosis. Neurology 2009;72:1322–1329.
  • Belgrave, A., G. Kester and M. Jackman. (2012). Industry specific shocks and 33 non-performing loans in Barbados. The Review of Finance and Banking, 4(2), 123-133
  • 6. Arrambide G, Espejo C, Eixarch H, Villar LM, Alvarez-Cermeño JC, Picón C, Kuhle J, Disanto G, Kappos L, Sastre-Garriga J, Pareto D, Simon E, Comabella M, Río J, Nos C, Tur C, Castilló J, Vidal-Jordana A, Galán I, Arévalo MJ, Auger C, Rovira A, Montalban X, Tintore M. Neurofilament light chain level is a weak risk factor for the development of MS. Neurology 2016;87:1076–1084.
  • Bofondi, M. and Ropele, T. (2011). Macroeconomic determinants of bad loans: Evidence from Italian banks. Occasional Papers, 89, 1-42
  • 7. Siller N, Kuhle J, Muthuraman M, Barro C, Uphaus T, Groppa S, Kappos L, Zipp F, Bittner S. Serum neurofilament light chain is a biomarker of acute and chronic neuronal damage in early multiple sclerosis. Mult Scler 2019;25:678– 686.
  • Brown, R. L. Durbin, J. and Evans, J.M. (1975). Techniques for testing the consistency of regression relations over time. Journal of Royal Statistical Society, 37, 149–192
  • 8. Oeckl P, Jardel C, Salachas F, Lamari F, Andersen PM, Bowser R, de Carvalho M, Costa J, van Damme P, Gray E, Grosskreutz J, Hernández-Barral M, Herukka SK, Huss A, Jeromin A, Kirby J, Kuzma-Kozakiewicz M, Amador Mdel M, Mora JS, Morelli C, Muckova P, Petri S, Poesen K, Rhode H, Rikardsson AK, Robberecht W, Rodríguez Mahillo AI, Shaw P, Silani V, Steinacker P, Turner MR, Tüzün E, Yetimler B, Ludolph AC, Otto M. Multicenter validation of CSF neurofilaments as diagnostic biomarkers for ALS. Amyotroph Lateral Scler Frontotemporal Degener 2016;17:404–413.
  • Carlos A. O. B. (2012). Macroecononic determinants of the NPLs in Spain and Italy. (Unpublished Dissertation). Submitted to The University of Leicester
  • 9. Uzunköprü C, Yüceyar N, Güven Yılmaz S, Afrashi F, Ekmekçi Ö, Taşkıran D. Retinal Nerve Fiber Layer Thickness Correlates with Serum and Cerebrospinal Fluid Neurofilament Levels and is Associated with Current Disability in Multiple Sclerosis. Arch Neuropsychiatr 2021;58:34–40.
  • Castro, V. (2013). Macroeconomic determinants of the credit risk in the banking system: The case of the GIPSI. Economic Modelling, 31, 672-683
  • 10. Won JH, Ahn KH, Back MJ, Ha HC, Jang JM, Kim HH, Choi SZ, Son M, Kim DK. DA-9801 promotes neurite outgrowth via ERK1/2-CREB pathway in PC12 cells. Biol Pharm Bull 2015;38:169–178.
  • CBRT. (2010). Financial Stability Report. Ankara: CBRT Publication
  • 11. Silber E, Semra YK, Gregson NA, Sharief MK. Patients with progressive multiple sclerosis have elevated antibodies to neurofilament subunit. Neurology 2002;58:1372–1381.
  • Dickey, D. A. and Fuller, W.A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica Journal of the Econometric Society, 49(4), 1057-1072
  • Engle, R. F. and Granger, C.W.J. (1987). Cointegration and error correction: Representation, estimation and testing. Econometrica, 55, 251–76
  • Espinoza, R. and A. Prasad. (2010). Nonperforming Loans in the GCC Banking Systems and Their Macroeconomic Effects. IMF Working Paper No. 10/224
  • Gabeshi, K. (2017). The impact of macroeconomic and bank specific factors on Albanian NPLs. European Journal of Sustainable Development Research, 2(1), 95-102
  • Garanti Bank. (2005). Krediler ve dış ticaret, İstanbul: Eğitim Merkezi Dökümanları
  • Hada, T., Bărbut,ă-Mişu, N., Iuga, I. C. and Wainberg, D. (2020). Macroeconomic Determinants of Nonperforming Loans of Romanian Banks. Sustainability, 12, 1-19
  • Hess, K., Grimes, A. and Holmes, V. (2009). Credit losses in Australasian banking. The Economic Record, 85(270), 331–343
  • Inaba, N., Kozu, T., Sekine, T. and Nagahata, T. (2005). NPLs and the real economy: Japan’s experience. BIS Papers, 22, 106-127
  • Jakubik, P. (2007). Macroeconomic environment and credit risk. Czech Journal of Economics and Finance, 57(1-2), 60-78
  • Jakubik, P. and Reininger, T. (2013). Determinants of nonperforming loans in Central, Eastern and Southeastern Europe. Oesterreichische Nationalbank Focus on European Economic Integration, 3, 48-66
  • Johansen, S. (1988). Statistical analysis of cointegration vectors. Journal of Economics Dynamic and Control, 12(2-3), 231–254
  • Jordan, A. and Tucker, C. (2013). Assessing the impact of nonperforming loans on economic growth in the Bahamas. Monetaria, 371-400
  • Kara, M. and Afsal, M. S. (2018). The effectiveness of monetary policy instruments applied for financial stability in Turkey. Journal of the Human and Social Science Researches, 7(3), 1822- 1847
  • Karahanoğlu, İ. and Ercan, H. (2015). The effect of macroeconomic variables on non-performing loans in Turkish banking sector. The Journal of International Social Research, 8(39), 883-892
  • Kjosevski, J. and Petkovski, M. (2016). Non-performing loans in the Baltic states: Determinants and macroeconomic effects. Baltic Journal of Economics, 17(2), 25-44
  • Klein, N. (2013). NPLs in CESEE: Determinants and impact on macroeconomic performance. IMF Working Paper, 13(72), 1-27.
  • Köksel, B. and Yöntem, T. (2014). Türk bankacılık sektöründe kredi tayınlaması: 2002-2013 dönemi üzerine bir uygulama. Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 43, 107- 131.
  • Kuutol, P.K. (2016). Exchange rate, non-performing loans and economic growth in Africa. (Unpublished Master’s Thesis). Kwame Nkrumah University of Science and Technology (Knust) Institute of Social Sciences, Ghana
  • Louzis, D. P., Vouldis, A.T. and Metaxas, V.L. (2012). Macroeconomic and bank-specific determinants of NPLs in Greece: A comparative study of mortgage, business and consumer loan portfolios. Journal of Banking and Finance, 36, 1012–1027
  • Love, I. and R.T. Ariss. (2014). Macro-financial linkages in Egypt: a panel analysis of economic shocks and loan portfolio quality. Journal of International Financial Markets, Institutions and Money, 28, 158-181
  • Mancka A. (2012). The impact of national currency ınstability and the world financial crisis in the credit risk: The case of Albania. Journal of Knowledge Management, Economics and Information Technology, 8, 1-18
  • Narayan S. and Narayan P.K. (2004). Determinants of demand of Fiji’s exports: An empirical investigation. The Developing Economics, 17(1), 95-112
  • Nkusu, M. (2011). Nonperforming loans and macrofinancial vulnerabilities in advanced economies. IMF Working Paper, 11(161), 1-28
  • Pesaran M.H., Shin, Y. and Smith, R.J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289–326
  • Rahman, F. and Hamid Md. K. (2019). Impact of macroeconomic variables on non-performing loan in banking sector of Bangladesh. The Jahangirnagar Journal of Business Studies, 8(1), 157- 168
  • Reinhart, C. and Rogoff, K. (2009). This time is different. Princeton: Princeton University Press. Roy, S. G. (2014). Determinants of non-performıng assets in India - panel regression. Eurasian Journal of Economics and Finance, 2(3), 69-78
  • Seval, B. (1990). Kredilendirme süreci ve kredi yönetimi. İstanbul: İstanbul Üniversitesi İşletme Fakültesi Yayınları
  • Shingjergji, A. (2013). The impact of macroeconomic variables on the non-performing loans in the Albanian banking system during 2005 – 2012. Academic Journal of Interdisciplinary Studies, 2(9), 335-339
  • Skarica, B. (2014). Determinants of non-performing loans in Central and Eastern European Countries. Financial Theory and Practice, 38(1), 37-59
  • Us, V. (2020). A panel VAR approach on analyzing non-performing loans in the Turkish banking sector. Journal of BRSA Banking and Financial Markets, 14(1), 1-38
  • Zribi, N. and Boujelbene, Y. (2011). The factors ınfluencing bank credit risk: The case of Tunisia. Journal of Accounting and Taxation, 3(4), 70-78
APA Tuzun E, Baş G, Şanlı E, kara m, Akbayır E, Türkoğlu R (2021). Klinik İzole Sendrom ve Multipl Sklerozda Fosforile Nörofilament Ağır Zinciri (pNFH). , 255 - 256. 10.29399/npa.28019
Chicago Tuzun Erdem,Baş Gizem,Şanlı Elif,kara mehmet,Akbayır Ece,Türkoğlu Recai Klinik İzole Sendrom ve Multipl Sklerozda Fosforile Nörofilament Ağır Zinciri (pNFH). (2021): 255 - 256. 10.29399/npa.28019
MLA Tuzun Erdem,Baş Gizem,Şanlı Elif,kara mehmet,Akbayır Ece,Türkoğlu Recai Klinik İzole Sendrom ve Multipl Sklerozda Fosforile Nörofilament Ağır Zinciri (pNFH). , 2021, ss.255 - 256. 10.29399/npa.28019
AMA Tuzun E,Baş G,Şanlı E,kara m,Akbayır E,Türkoğlu R Klinik İzole Sendrom ve Multipl Sklerozda Fosforile Nörofilament Ağır Zinciri (pNFH). . 2021; 255 - 256. 10.29399/npa.28019
Vancouver Tuzun E,Baş G,Şanlı E,kara m,Akbayır E,Türkoğlu R Klinik İzole Sendrom ve Multipl Sklerozda Fosforile Nörofilament Ağır Zinciri (pNFH). . 2021; 255 - 256. 10.29399/npa.28019
IEEE Tuzun E,Baş G,Şanlı E,kara m,Akbayır E,Türkoğlu R "Klinik İzole Sendrom ve Multipl Sklerozda Fosforile Nörofilament Ağır Zinciri (pNFH)." , ss.255 - 256, 2021. 10.29399/npa.28019
ISNAD Tuzun, Erdem vd. "Klinik İzole Sendrom ve Multipl Sklerozda Fosforile Nörofilament Ağır Zinciri (pNFH)". (2021), 255-256. https://doi.org/10.29399/npa.28019
APA Tuzun E, Baş G, Şanlı E, kara m, Akbayır E, Türkoğlu R (2021). Klinik İzole Sendrom ve Multipl Sklerozda Fosforile Nörofilament Ağır Zinciri (pNFH). Nöropsikiyatri Arşivi, 6(16), 255 - 256. 10.29399/npa.28019
Chicago Tuzun Erdem,Baş Gizem,Şanlı Elif,kara mehmet,Akbayır Ece,Türkoğlu Recai Klinik İzole Sendrom ve Multipl Sklerozda Fosforile Nörofilament Ağır Zinciri (pNFH). Nöropsikiyatri Arşivi 6, no.16 (2021): 255 - 256. 10.29399/npa.28019
MLA Tuzun Erdem,Baş Gizem,Şanlı Elif,kara mehmet,Akbayır Ece,Türkoğlu Recai Klinik İzole Sendrom ve Multipl Sklerozda Fosforile Nörofilament Ağır Zinciri (pNFH). Nöropsikiyatri Arşivi, vol.6, no.16, 2021, ss.255 - 256. 10.29399/npa.28019
AMA Tuzun E,Baş G,Şanlı E,kara m,Akbayır E,Türkoğlu R Klinik İzole Sendrom ve Multipl Sklerozda Fosforile Nörofilament Ağır Zinciri (pNFH). Nöropsikiyatri Arşivi. 2021; 6(16): 255 - 256. 10.29399/npa.28019
Vancouver Tuzun E,Baş G,Şanlı E,kara m,Akbayır E,Türkoğlu R Klinik İzole Sendrom ve Multipl Sklerozda Fosforile Nörofilament Ağır Zinciri (pNFH). Nöropsikiyatri Arşivi. 2021; 6(16): 255 - 256. 10.29399/npa.28019
IEEE Tuzun E,Baş G,Şanlı E,kara m,Akbayır E,Türkoğlu R "Klinik İzole Sendrom ve Multipl Sklerozda Fosforile Nörofilament Ağır Zinciri (pNFH)." Nöropsikiyatri Arşivi, 6, ss.255 - 256, 2021. 10.29399/npa.28019
ISNAD Tuzun, Erdem vd. "Klinik İzole Sendrom ve Multipl Sklerozda Fosforile Nörofilament Ağır Zinciri (pNFH)". Nöropsikiyatri Arşivi 6/16 (2021), 255-256. https://doi.org/10.29399/npa.28019