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Modelling of the Weighted Average Funding Cost of the CBRT: LNV-ARMA Approach

Year 2022, Volume: 30 Issue: 54, 243 - 256, 25.10.2022
https://doi.org/10.17233/sosyoekonomi.2022.04.13

Abstract

In this study, we model the monthly time series of the Central Bank of the Republic of Turkey’s Weighted Average Funding Cost (Interest Rate) for the period between 2011:01-2020:12. In this framework, we establish and compare the linear and the nonlinear based various autoregressive (integrated) moving average models in two separate groups and investigate the most suitable model for the series. After all, we reveal that the relevant interest rate series can be modelled best with the LNV-ARMA(2,1) model for the related period. The first novelty of this study is that we model the relevant interest rate itself instead of investigating the relationship of this interest rate with the other macroeconomic variables. The second novelty of this study is that we circumvent the unit root problem and establish a more explanatory time series model by applying the LNV methodology.

References

  • Becker, R. et al. (2006), “A Stationarity Test in the Presence of an Unknown Number of Smooth Breaks”, Journal of Time Series Analysis, 27(3), 381-409.
  • Bierens, H.J. (1997), “Testing the Unit Root with Drift Hypothesis against Nonlinear Trend Stationarity, with an Application to the US Price Level and Interest Rate”, Journal of Econometrics, 81, 29-64.
  • Binici, M. et al. (2019), “Monetary Transmission with Multiple Policy Rates: Evidence from Turkey”, Applied Economics, 51(17), 1869-1893.
  • Box, G.E.P. & G.M. Jenkins (1976), Time Series Analysis Forecasting and Control, Revised Edition, Oakland, California: Holden-Day.
  • Büberkökü, Ö. & C. Kızılder (2019), “Geleneksel Olmayan Para Politikası Uygulamaları Döneminde Faiz Oranı Geçişkenliğinin İncelenmesi”, Van YYÜ İİBF Dergisi, 4(8), 216-244.
  • Dickey, D.A. & W.A. Fuller (1979), “Distribution of the Estimators for Autoregressive Time Series with a Unit Root”, Journal of the American Statistical Association, 74(366), 427-431.
  • Ekinci, R. vd. (2016), “TCMB Ağırlıklı Ortalama Fonlama Maliyeti’nin BİST100 Üzerindeki Etkisi”, Journal of Yaşar University, 11/44, 263-277.
  • Elliott, G. et al. (1996), “Efficient Tests for an Autoregressive Unit Root”, Econometrica, 64(4), 813-836.
  • Enders, W. & C.W.J. Granger (1998), “Unit-Root Tests and Asymmetric Adjustment with an Example Using the Term Structure of Interest Rates”, Journal of Business & Economic Statistics, 16(3), 304-311.
  • Felek, Ş. & R. Ceylan (2021), “Enflasyon-Faiz Etkileşimi: Türkiye için Neo-Fisher Yaklaşım”, International Conference on Economics Turkish Economic Association, 09-11 Nisan.
  • Güler, S. & M. Özçalık (2018), “Hisse Getirisi, Faiz Oranı ve Dolar Kuru İlişkisi: BIST’te Bir Uygulama”, Manisa Celal Bayar Üniversitesi Sosyal Bilimler Dergisi, 16(4), 291-305.
  • Im, K.S. et al. (2003), “Testing for Unit Roots in Heterogeneous Panels”, Journal of Econometrics, 115, 53-74.
  • Kapetanios, G. et al. (2003), “Testing for a Unit Root in the Nonlinear STAR Framework”, Journal of Econometrics, 112, 359-379.
  • Kara, H. (2015), “Faiz Koridoru ve Para Politikası Duruşu”, TCMB Ekonomi Notları, 2015-13, 1-12.
  • Kartal, M.T. (2020), “Kovid-19 Pandemisinde Türkiye’de Alınan Para Politikası Tedbirlerinin Temel Finansal Göstergelere Etkileri”, Bankacılar Dergisi, 115, 88-106.
  • Küçük, H. et al. (2016), “Interest Rate Corridor, Liquidity Management, and the Overnight Spread”, Contemporary Economic Policy, 34(4), 746-761.
  • Kwiatkowski, D. et al. (1992), “Testing the Null Hypothesis of Stationarity against the Alternative of a Unit Root”, Journal of Econometrics, 54, 159-178.
  • Leybourne, S. et al. (1998), “Unit Roots and Smooth Transitions”, Journal of Time Series Analysis, 19(1), 83-97.
  • Lumsdaine, R.L. & D.H. Papell (1997), “Multiple Trend Breaks and the Unit-Root Hypothesis”, The Review of Economics and Statistics, 79(2), 212-218.
  • Omay, T. & D. Yıldırım (2013), “Nonlinearity and Smooth Breaks in Unit Root Testing”, Munich Personal RePEc Archive (MPRA) Paper, 62334.
  • Omay, T. (2012), “The Comparison of Optimization Algorithms on Unit Root Testing with Smooth Transition”, Munich Personel RePEc Archive (MPRA) Paper, 42129.
  • Perron, P. & S. Ng (1996), “Useful Modifications to Some Unit Root Tests with Dependent Errors and Their Local Asymptotic Properties”, Review of Economic Studies, 63, 435-463.
  • Perron, P. (1989), “The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis”, Econometrica, 57(6), 1361-1401.
  • Perron, P. (1990), “Testing for a Unit Root in a Time Series with a Changing Mean”, Journal of Business & Economic Statistics, 8(2), 153-162.
  • Perron, P. (1997), “Further Evidence on Breaking Trend Functions in Macroeconomic Variables”, Journal of Econometrics, 80, 355-385.
  • Phillips, P.C.B. & P. Perron (1988), “Testing for a Unit Root in Time Series Regression”, Biometrika, 75(2), 335-346.
  • Phillips, P.C.B. & W. Ploberger (1994), “Posterior Odds Testing for a Unit Root with Data-Based Model Selection”, Econometric Theory, 10(3/4), 774-808.
  • Rappoport, P. & L. Reichlin (1989), “Segmented Trends and Non-Stationary Time Series”, The Economic Journal, 99(395), 168-177.
  • Sevüktekin, M. & M. Çınar (2014), Ekonometrik Zaman Serileri Analizi EViews Uygulamalı, Genişletilmiş 4. Baskı, Bursa: Dora Yayıncılık.
  • Sollis, R. (2009), “A Simple Unit Root Test against Asymmetric STAR Nonlinearity with an Application to Real Exchange Rates in Nordic Countries”, Economic Modelling, 26, 118-125.
  • Sollis, R. et al. (1999), “Unit Roots and Asymmetric Smooth Transitions”, Journal of Time Series Analysis, 20(6), 671-677.
  • Sollis, R. et al. (2002), “Tests for Symmetric and Asymmetric Nonlinear Mean Reversion in Real Exchange Rates”, Journal of Money, Credit and Banking, 34(3), 686-700.
  • Sümer, A.L. (2019), “Geleneksel Olmayan Para Politikası Şoklarının Hedefi Aşma (Overshooting) Etkisi: Türkiye Örneği”, Maliye Dergisi, 177, 177-202.
  • TCMB (2021), TCMB Ortalama Fonlama Faizi ve Toplam Fonlama Miktarı, <https://evds2.tcmb.gov.tr/index.php?/evds/dashboard/1441>, 06.06.2021.
  • Tunalı, H. & Y. Yalçınkaya (2017), “Dolar Kuru, Enflasyon ve TCMB Ağırlıklı Ortalama Fonlama Maliyeti Arasında Granger Nedensellik Analizi”, Uluslararası Ekonomik Araştırmalar Dergisi, 3(3), 461-466.
  • Varlık, S. & M.H. Berument (2017), “Multiple Policy Interest Rates and Economic Performance in a Multiple Monetary-Policy-Tool Environment”, International Review of Economics and Finance, 52, 107-126.
  • Vougas, D.V. (2006), “On Unit Root Testing with Smooth Transitions”, Computational Statistics & Data Analysis, 51, 797-800.
  • Yüksel, S. vd. (2019), “Merkez Bankalarının Faiz Politikalarının Döviz Kuru Üzerindeki Etkisinin Belirlenmesi: Türkiye Üzerine Bir Eşbütünleşme ve Nedensellik Analizi”, Ekonomi, İşletme ve Maliye Araştırmaları Dergisi, 1(4), 335-346.
  • Zivot, E. & D.W.K. Andrews (1992), “Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis”, Journal of Business & Economic Statistics, 10(3), 251-270.

TCMB Ağırlıklı Ortalama Fonlama Maliyetinin Modellenmesi: LNV-ARMA Yaklaşımı

Year 2022, Volume: 30 Issue: 54, 243 - 256, 25.10.2022
https://doi.org/10.17233/sosyoekonomi.2022.04.13

Abstract

Bu çalışmada, 2011:01-2020:12 dönemine ait Türkiye Cumhuriyet Merkez Bankası Ağırlıklı Ortalama Fonlama Maliyeti (Faiz Oranı) aylık zaman serisi modellenmiştir. Bu çerçevede, iki ayrı grupta doğrusal ve doğrusal olmayan temelli çeşitli otoregresif (bütünleşik) hareketli ortalama modelleri kurularak karşılaştırılmış ve seriye en uygun model araştırılmıştır. Sonuç olarak, ilgili faiz oranı serisinin bahsi geçen dönem için en iyi LNV-ARMA(2,1) modeli ile modellenebileceği ortaya konmuştur. Bu çalışmanın ilk yeniliği, bu faiz oranının diğer makroekonomik değişkenlerle ilişkisini araştırmak yerine ilgili faiz oranının kendisini modellememizdir. Bu çalışmanın ikinci yeniliği, LNV metodolojisini uygulayarak birim kök sorununu aşmamız ve daha açıklayıcı bir zaman serisi modeli oluşturmamızdır.

References

  • Becker, R. et al. (2006), “A Stationarity Test in the Presence of an Unknown Number of Smooth Breaks”, Journal of Time Series Analysis, 27(3), 381-409.
  • Bierens, H.J. (1997), “Testing the Unit Root with Drift Hypothesis against Nonlinear Trend Stationarity, with an Application to the US Price Level and Interest Rate”, Journal of Econometrics, 81, 29-64.
  • Binici, M. et al. (2019), “Monetary Transmission with Multiple Policy Rates: Evidence from Turkey”, Applied Economics, 51(17), 1869-1893.
  • Box, G.E.P. & G.M. Jenkins (1976), Time Series Analysis Forecasting and Control, Revised Edition, Oakland, California: Holden-Day.
  • Büberkökü, Ö. & C. Kızılder (2019), “Geleneksel Olmayan Para Politikası Uygulamaları Döneminde Faiz Oranı Geçişkenliğinin İncelenmesi”, Van YYÜ İİBF Dergisi, 4(8), 216-244.
  • Dickey, D.A. & W.A. Fuller (1979), “Distribution of the Estimators for Autoregressive Time Series with a Unit Root”, Journal of the American Statistical Association, 74(366), 427-431.
  • Ekinci, R. vd. (2016), “TCMB Ağırlıklı Ortalama Fonlama Maliyeti’nin BİST100 Üzerindeki Etkisi”, Journal of Yaşar University, 11/44, 263-277.
  • Elliott, G. et al. (1996), “Efficient Tests for an Autoregressive Unit Root”, Econometrica, 64(4), 813-836.
  • Enders, W. & C.W.J. Granger (1998), “Unit-Root Tests and Asymmetric Adjustment with an Example Using the Term Structure of Interest Rates”, Journal of Business & Economic Statistics, 16(3), 304-311.
  • Felek, Ş. & R. Ceylan (2021), “Enflasyon-Faiz Etkileşimi: Türkiye için Neo-Fisher Yaklaşım”, International Conference on Economics Turkish Economic Association, 09-11 Nisan.
  • Güler, S. & M. Özçalık (2018), “Hisse Getirisi, Faiz Oranı ve Dolar Kuru İlişkisi: BIST’te Bir Uygulama”, Manisa Celal Bayar Üniversitesi Sosyal Bilimler Dergisi, 16(4), 291-305.
  • Im, K.S. et al. (2003), “Testing for Unit Roots in Heterogeneous Panels”, Journal of Econometrics, 115, 53-74.
  • Kapetanios, G. et al. (2003), “Testing for a Unit Root in the Nonlinear STAR Framework”, Journal of Econometrics, 112, 359-379.
  • Kara, H. (2015), “Faiz Koridoru ve Para Politikası Duruşu”, TCMB Ekonomi Notları, 2015-13, 1-12.
  • Kartal, M.T. (2020), “Kovid-19 Pandemisinde Türkiye’de Alınan Para Politikası Tedbirlerinin Temel Finansal Göstergelere Etkileri”, Bankacılar Dergisi, 115, 88-106.
  • Küçük, H. et al. (2016), “Interest Rate Corridor, Liquidity Management, and the Overnight Spread”, Contemporary Economic Policy, 34(4), 746-761.
  • Kwiatkowski, D. et al. (1992), “Testing the Null Hypothesis of Stationarity against the Alternative of a Unit Root”, Journal of Econometrics, 54, 159-178.
  • Leybourne, S. et al. (1998), “Unit Roots and Smooth Transitions”, Journal of Time Series Analysis, 19(1), 83-97.
  • Lumsdaine, R.L. & D.H. Papell (1997), “Multiple Trend Breaks and the Unit-Root Hypothesis”, The Review of Economics and Statistics, 79(2), 212-218.
  • Omay, T. & D. Yıldırım (2013), “Nonlinearity and Smooth Breaks in Unit Root Testing”, Munich Personal RePEc Archive (MPRA) Paper, 62334.
  • Omay, T. (2012), “The Comparison of Optimization Algorithms on Unit Root Testing with Smooth Transition”, Munich Personel RePEc Archive (MPRA) Paper, 42129.
  • Perron, P. & S. Ng (1996), “Useful Modifications to Some Unit Root Tests with Dependent Errors and Their Local Asymptotic Properties”, Review of Economic Studies, 63, 435-463.
  • Perron, P. (1989), “The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis”, Econometrica, 57(6), 1361-1401.
  • Perron, P. (1990), “Testing for a Unit Root in a Time Series with a Changing Mean”, Journal of Business & Economic Statistics, 8(2), 153-162.
  • Perron, P. (1997), “Further Evidence on Breaking Trend Functions in Macroeconomic Variables”, Journal of Econometrics, 80, 355-385.
  • Phillips, P.C.B. & P. Perron (1988), “Testing for a Unit Root in Time Series Regression”, Biometrika, 75(2), 335-346.
  • Phillips, P.C.B. & W. Ploberger (1994), “Posterior Odds Testing for a Unit Root with Data-Based Model Selection”, Econometric Theory, 10(3/4), 774-808.
  • Rappoport, P. & L. Reichlin (1989), “Segmented Trends and Non-Stationary Time Series”, The Economic Journal, 99(395), 168-177.
  • Sevüktekin, M. & M. Çınar (2014), Ekonometrik Zaman Serileri Analizi EViews Uygulamalı, Genişletilmiş 4. Baskı, Bursa: Dora Yayıncılık.
  • Sollis, R. (2009), “A Simple Unit Root Test against Asymmetric STAR Nonlinearity with an Application to Real Exchange Rates in Nordic Countries”, Economic Modelling, 26, 118-125.
  • Sollis, R. et al. (1999), “Unit Roots and Asymmetric Smooth Transitions”, Journal of Time Series Analysis, 20(6), 671-677.
  • Sollis, R. et al. (2002), “Tests for Symmetric and Asymmetric Nonlinear Mean Reversion in Real Exchange Rates”, Journal of Money, Credit and Banking, 34(3), 686-700.
  • Sümer, A.L. (2019), “Geleneksel Olmayan Para Politikası Şoklarının Hedefi Aşma (Overshooting) Etkisi: Türkiye Örneği”, Maliye Dergisi, 177, 177-202.
  • TCMB (2021), TCMB Ortalama Fonlama Faizi ve Toplam Fonlama Miktarı, <https://evds2.tcmb.gov.tr/index.php?/evds/dashboard/1441>, 06.06.2021.
  • Tunalı, H. & Y. Yalçınkaya (2017), “Dolar Kuru, Enflasyon ve TCMB Ağırlıklı Ortalama Fonlama Maliyeti Arasında Granger Nedensellik Analizi”, Uluslararası Ekonomik Araştırmalar Dergisi, 3(3), 461-466.
  • Varlık, S. & M.H. Berument (2017), “Multiple Policy Interest Rates and Economic Performance in a Multiple Monetary-Policy-Tool Environment”, International Review of Economics and Finance, 52, 107-126.
  • Vougas, D.V. (2006), “On Unit Root Testing with Smooth Transitions”, Computational Statistics & Data Analysis, 51, 797-800.
  • Yüksel, S. vd. (2019), “Merkez Bankalarının Faiz Politikalarının Döviz Kuru Üzerindeki Etkisinin Belirlenmesi: Türkiye Üzerine Bir Eşbütünleşme ve Nedensellik Analizi”, Ekonomi, İşletme ve Maliye Araştırmaları Dergisi, 1(4), 335-346.
  • Zivot, E. & D.W.K. Andrews (1992), “Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis”, Journal of Business & Economic Statistics, 10(3), 251-270.
There are 39 citations in total.

Details

Primary Language English
Subjects Economics
Journal Section Articles
Authors

Şiyar Canpolat 0000-0002-6022-2882

Publication Date October 25, 2022
Submission Date October 1, 2021
Published in Issue Year 2022 Volume: 30 Issue: 54

Cite

APA Canpolat, Ş. (2022). Modelling of the Weighted Average Funding Cost of the CBRT: LNV-ARMA Approach. Sosyoekonomi, 30(54), 243-256. https://doi.org/10.17233/sosyoekonomi.2022.04.13
AMA Canpolat Ş. Modelling of the Weighted Average Funding Cost of the CBRT: LNV-ARMA Approach. Sosyoekonomi. October 2022;30(54):243-256. doi:10.17233/sosyoekonomi.2022.04.13
Chicago Canpolat, Şiyar. “Modelling of the Weighted Average Funding Cost of the CBRT: LNV-ARMA Approach”. Sosyoekonomi 30, no. 54 (October 2022): 243-56. https://doi.org/10.17233/sosyoekonomi.2022.04.13.
EndNote Canpolat Ş (October 1, 2022) Modelling of the Weighted Average Funding Cost of the CBRT: LNV-ARMA Approach. Sosyoekonomi 30 54 243–256.
IEEE Ş. Canpolat, “Modelling of the Weighted Average Funding Cost of the CBRT: LNV-ARMA Approach”, Sosyoekonomi, vol. 30, no. 54, pp. 243–256, 2022, doi: 10.17233/sosyoekonomi.2022.04.13.
ISNAD Canpolat, Şiyar. “Modelling of the Weighted Average Funding Cost of the CBRT: LNV-ARMA Approach”. Sosyoekonomi 30/54 (October 2022), 243-256. https://doi.org/10.17233/sosyoekonomi.2022.04.13.
JAMA Canpolat Ş. Modelling of the Weighted Average Funding Cost of the CBRT: LNV-ARMA Approach. Sosyoekonomi. 2022;30:243–256.
MLA Canpolat, Şiyar. “Modelling of the Weighted Average Funding Cost of the CBRT: LNV-ARMA Approach”. Sosyoekonomi, vol. 30, no. 54, 2022, pp. 243-56, doi:10.17233/sosyoekonomi.2022.04.13.
Vancouver Canpolat Ş. Modelling of the Weighted Average Funding Cost of the CBRT: LNV-ARMA Approach. Sosyoekonomi. 2022;30(54):243-56.