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TCMB Para Politikası İçin Reel Faiz Oranı Mı? Bayesçi TVP-VAR Model

Yıl 2025, Cilt: 3 Sayı: 2, 23 - 34, 31.12.2025

Öz

Taylor kuralına dayalı olarak geliştirilen örtük reel faiz oranı kuralı, enflasyon açığı ve çıktı açığının yanında parasal olmayan faktörlerin de uzun vadede merkez bankası faiz kararlarının belirleyicilerinden olduğunu varsaymaktadır. Buna göre, makroekonomik değişkenlerin karşılaştığı yüksek frekanslı şoklar politika faiz oranının yönünün belirlenmesinde etkili olmaktadır. Diğer taraftan ampirik bir bakış açısıyla değerlendirme yapıldığında para politikasının bu zamanla olası değişen yapısına ilişkin belirsizlikleri tespit etmek için aşırı parametrelendirmeyi kısıtlayan Bayesçi zamanla değişen parametre vektör otoregresif (TVP-VAR) modeli öne çıkmaktadır. Bayesçi TVP-VAR modelinde kısa vadeli trendin belirlediği hem parametreler hem de bu parametrelere gelen şoklar belirli bir zaman ufkunda etki-tepki fonksiyonları ile yorumlanarak incelenmektedir. Bu amaçla, örtük reel faiz oranı kuralına dayalı olarak seçilmiş makroekonomik değişkenlerdeki şoklara TCMB politika faiz oranının verdiği tepkiler küresel ekonomideki ve Türkiye ekonomisindeki gelişmeler doğrultusunda belirlenen 2003:q1-2024:q4 döneminde Bayesçi TVP-VAR yöntemi ile analiz edilmiştir. Elde edilen bulgular, küresel deflasyonist eğilimin, döviz kuru kırılganlıklarının ve TCMB para politikalarındaki belirsizliğin yaşandığı 2015q3, 2020q1 ve 2024q4 proaktif tepkilerin ortaya çıktığını göstermiştir. Böylece, durağan olmayan makroekonomik zaman serilerinde gözlemlenemeyen ve zamanla değişen katsayılar para politikası otoriteleri tarafından Bayesçi TVP-VAR modelleri ile kademeli bir değişimi öngören nicel sonuçlar olarak algılanmaktadır. Bu sayede, para politikalarına ilişkin rejim dönemlerinde alternatif politika araçlarının belirlenmesine katkıda bulunacağı düşünülmektedir.

Kaynakça

  • Arestis, P. & Chortareas, G.E. (2007). Natural equilibrium real interest rate estimates and monetary policy design. Taylor and Francis, 29 (4): 521-643. https://www.jstor.org/stable/4539036
  • Arratibel, O. & Michaelis, H. (2013). The impact of monetary policy and exchange rate shocks in Poland: evidence from a time-varying VAR. Munich Discussion Paper, 2013 (36): 1-37. https://doi.org/10.5282/ubm/epub.21088
  • Aunsri, N. & Taveeapiradeecharoen, P. (2020). A time-varying Bayesian compressed vector autoregression for macroeconomic forecasting. In IEEE Access, 8: 192777-192786. https://doi.org/10.1109/ACCESS.2020.3033203
  • Bekiros, S. (2014). Forecasting with a state space time-varying parameter VAR model: Evidence from the Euro area. Economic Modelling, 38 (2014): 619–626. https://doi.org/10.1016/j.econmod.2014.02.015
  • Bernanke, B.S. & Woodford, M. (1997). Inflation forecastand monetary policy. NBER Working Paper, 6157: 1-66. https://doi.org/10.3386/w6157 Boehm, C.E. & House, C.L. (2014). Optimal Taylor rules in New Keynesian models. NBER Working Paper, 20237: 1-39. https://doi.org/10.3386/w20237
  • Central Bank of the Republic of Türkiye (CBRT). (2025). Statistics. https://www.tcmb.gov.tr/wps/wcm/connect/ TR/TCMB+TR/Main+Menu/Istatistikler
  • Chan, J. C. C. & Eisenstat, E. (2015). Bayesian model comparison for time-varying parameter VARs with stochastic volatility. Journol of Applied Econometrics, 2018(33): 509-532. https://doi.org/10.1002/jae.2617
  • Clarida, R., Gali, J. & Gertler, M. (2000). Monetary policy rules and macroeconomic stability: evidence and some theory. The Quarterly Journal of Economics, 115: 147-180. http://www.jstor.org/stable/2586937
  • Ciccarelli, M. & Rebucci, A. (2003). Measuring contagion with a Bayesian, time-varying coefficient model. IMF Working Paper, 03(171): 1-41.http://dx.doi.org/10.2139/ssrn.457531
  • Cogley, T. & Sargent, T. J. (2005). Drifts and volatilities: monetary policies and outcomes in the post WWII US. Review of Economic Dynamics, 8: 262– 302. https://doi.org/10.1016/j.red.2004.10.009
  • D’Agostino, A., Gambetti, L. & Giannone, D. (2013). Macroeconomic forecasting and structural change. Journal of Applied Econometrics, 28, 82–101. https://doi.org/10.1002/jae.1257
  • Drossidis, T. (2024). The time-varying effect of monetary policy onincome inequality in the Us. https://ssrn.com/abstract=5110038.
  • Eisenstat, E., Chan, J. C. C. & Strachan, R. (2014). Stochastic model specification search for time-varying parameter VARs. Working Paper series Rimini Centre for Economic Analysis, 44(14): 1-34. http://www.rcea.org/RePEc/pdf/wp44_14.pdf
  • Fisher, I. (1930). The theory of interest as determined by impatience to spend income and opportunity to invest it. The Macmillan Company.
  • Fischer, M. N., Hauzenberger, N., Huber, F. & Pfarrhofer, M. (2022). General Bayesian time-varying parameter VARs for modeling government bond yields. WU Vienna University of Economics and Business. Working Papers in Regional Science, 2021(01): 1-48. https://doi.org/10.57938/10106af8-e12a-422e-be86-c465799823aa
  • Gayaker, S.& Yalcin, Y. (2025). Examining the impact of monetary policy in Turkey: TVP-VAR with stochastic volatility. Panoeconomicus, 1-30. https://doi.org/10.2298/PAN230325007G
  • Giraitis, L., Kapetanios, G. & Yates, T. (2014). Inference on stochastic time-varying coefficient models. Journal of Econometrics, 179 (2014): 46–65. http://dx.doi.org/10.1016/j.jeconom.2013.10.009
  • Goodfriend, M. and King, R. (1997). The new neoclassical synthesis and the role of monetary policy. NBER Macroeconomics Annual, 12: 231–83. https://www.jstor.org/stable/i284975
  • Hauzenberger, N., Huber, F., Koop, G. & Onorante, L. (2022). Fast and flexible Bayesian inference in time-varying parameter regression models. Journal of Business & Economic Statistics, 40(4): 1904-1918. https://doi.org/10.1080/07350015.2021.1990772
  • Hauzenberger, N., Huber, F., Koop, G. & Mitchell, J. (2023). Bayesian modeling of time-varying parameters using regression trees. Federal Reserve Bank of Cleveland Working Paper Series, 23(05): 1-47. https://doi.org/10.26509/frbc-wp-202305
  • Hofmann, B. & Bogdanova, B. (2012). Taylor rules and monetary policy: A global 'Great Deviation'?. BIS Quarterly Review, 9: 37-49. https://www.researchgate.net/publication/254953879
  • Kerr, W. & Robert, G.K. (1996). Limits on interest rate rules in the IS model. Federal Reserve Bank of Richmond Economic Quarterly, 82: 47–75. https://ssrn.com/abstract=1230144
  • Koop, G. & Korobilis, D. (2013). Large time-varying parameter VARs. Journal of Econometrics, 177(2): 185-198. https://doi.org/10.1016/j.jeconom.2013.04.007
  • Kumawat, L. (2024). Time-variation in response of inflation to monetary policy shocks in India: evidence from TVP-VAR models. Indian Economic Review, 59(1): 233-248. http://dx.doi.org/10.2139/ssrn.4629732
  • Matějů, J. (2019). What drives the strength of monetary policy transmission? International Journal of Central Banking, 15(3): 59-87.
  • Melzer, C., Hoeppner, F. & Neumann, T. (2008). Changing effects of monetary policy in the U.S.- evidence from a time-varying coefficient VAR. Applied Economics, 40(18): 2353-2360. https://doi.org/10.1080/00036840600970112
  • Nakajima, J., Kasuya, M. & Watanabe, T. (2009). Bayesian analysis of time-varying parameter vector autoregressive model for the Japanese economy and monetary policy. Journal of the Japanese and International Economies, 2009(13): 1-28. https://doi.org/10.1016/j.jjie.2011.07.004
  • Paul, P. (2018). The time-varying effect of monetary policy on asset prices. Federal Reserve Bank of San Francisco Working Paper, 2017(09): 1-52. https://doi.org/10.24148/wp2017-09
  • Perron, P. (1997). Further evidence on breaking trend functions in macroeconomic variables. Journal of Econometrics, 80: 355-385. https://doi.org/10.1016/S0304-4076(97)00049-3 Perron, P. (Eds.) (2006). Dealing with structural breaks palgrave handbook of econometrics. Palgrave.
  • Prado, R., Herta, G. & West, M. (2000). Bayesian time-varying autoregressions: theory, methods and applications, Resenhas do Instituto de Matemática e Estatística da Universidade de São Paulo, 4: 405-422.
  • Primiceri, G. E. (2005). Time varying structural vector autoregressions and monetary policy. The Review of Economic Studies, 72: 821-852. https://doi.org/10.1111/j.1467-937X.2005.00353.x
  • Prüser, J. (2021). The horseshoe prior for time-varying parameter VARs and monetary policy. Journal of Economic Dynamics and Control, 129: 104–188. https://doi.org/10.1016/j.jedc.2021.104188 Roşoiu, A. (2015). Monetary policy and time varying parameter vector autoregression model. Procedia Economics and Finance, 32(2015):496 – 502. https://doi.org/ 10.1016/S2212-5671(15)01423-9
  • Sihvonen, J. & Vähämaa, S. (2012). Forward-looking monetary policy rules and option-implied interest rate expectations. Journal of Futures Markets, 34(4), , 27(1): 2-30. http://dx.doi.org/10.2139/ssrn.1574746
  • Simionescu, M., Schneider, N. & Gavurova, B. (2024). A Bayesian vector-autoregressive application with time-varying parameters on the monetary shocks–production network Nexus. Journal of Applied Economics, 27(1): 2-30. https://doi.org/10.1080/15140326.2024.2395114
  • Trabelsi, E. (2025). Monetary policy under global and spillover uncertainty shocks: what do the Bayesian time-varying coefficient VAR, local projections, and vector error correction model tell us in Tunisia?, Risk Financial Management, 18(3): 1-74. https://doi.org/10.3390/jrfm18030129
  • Yıldız, S.N. & Aydın, Ü. (2025). Empirical analysis of the relationship between monetary policy and asset prices in the Turkish economy, International Journal of Social and Economic Studies, 6(1): 282-298. https://doi.org/ 10.62001/gsijses.1711037

Real Interest Rate for CBRT Monetary Policy? Bayesian TVP-VAR Model

Yıl 2025, Cilt: 3 Sayı: 2, 23 - 34, 31.12.2025

Öz

The implied real interest rate rule, developed based on the Taylor rule, assumes that non-monetary factors, in addition to the inflation gap and output gap, are among the determinants of central bank interest rate decisions in the long-run. Accordingly, high-frequency shocks to macroeconomic variables influence the direction of the policy interest rate. Furthermore, from an empirical perspective, the Bayesian time varying parameter vector autoregressive (TVP-VAR) model, which restricts overparameterization, stands out for its ability to identify uncertainties related to the potentially changing structure of monetary policy over time. In the Bayesian TVP-VAR model, both the parameters determined by the short-run trend and the shocks to these parameters are analyzed by interpreting them with impulse-response functions over a specific time horizon. For this purpose, the responses of the CBRT policy interest rate to shocks in selected macroeconomic variables based on the implicit real interest rate rule were analyzed using the Bayesian TVP-VAR method over the period 2003:q1-2024:q4, determined in line with developments in the global economy and the Turkish economy. The findings indicate that proactive responses emerged in 2015q3, 2020q1 and 2024q4, a period characterized by global deflationary trends, exchange rate vulnerabilities, and uncertainty surrounding the CBRT monetary policies. Thus, unobservable and time-varying coefficients in non-stationary macroeconomic time series are perceived by monetary policy authorities as quantitative results predicting a gradual change through Bayesian TVP-VAR models. This is believed to contribute to the identification of alternative policy instruments during regime periods related to monetary policy.

Kaynakça

  • Arestis, P. & Chortareas, G.E. (2007). Natural equilibrium real interest rate estimates and monetary policy design. Taylor and Francis, 29 (4): 521-643. https://www.jstor.org/stable/4539036
  • Arratibel, O. & Michaelis, H. (2013). The impact of monetary policy and exchange rate shocks in Poland: evidence from a time-varying VAR. Munich Discussion Paper, 2013 (36): 1-37. https://doi.org/10.5282/ubm/epub.21088
  • Aunsri, N. & Taveeapiradeecharoen, P. (2020). A time-varying Bayesian compressed vector autoregression for macroeconomic forecasting. In IEEE Access, 8: 192777-192786. https://doi.org/10.1109/ACCESS.2020.3033203
  • Bekiros, S. (2014). Forecasting with a state space time-varying parameter VAR model: Evidence from the Euro area. Economic Modelling, 38 (2014): 619–626. https://doi.org/10.1016/j.econmod.2014.02.015
  • Bernanke, B.S. & Woodford, M. (1997). Inflation forecastand monetary policy. NBER Working Paper, 6157: 1-66. https://doi.org/10.3386/w6157 Boehm, C.E. & House, C.L. (2014). Optimal Taylor rules in New Keynesian models. NBER Working Paper, 20237: 1-39. https://doi.org/10.3386/w20237
  • Central Bank of the Republic of Türkiye (CBRT). (2025). Statistics. https://www.tcmb.gov.tr/wps/wcm/connect/ TR/TCMB+TR/Main+Menu/Istatistikler
  • Chan, J. C. C. & Eisenstat, E. (2015). Bayesian model comparison for time-varying parameter VARs with stochastic volatility. Journol of Applied Econometrics, 2018(33): 509-532. https://doi.org/10.1002/jae.2617
  • Clarida, R., Gali, J. & Gertler, M. (2000). Monetary policy rules and macroeconomic stability: evidence and some theory. The Quarterly Journal of Economics, 115: 147-180. http://www.jstor.org/stable/2586937
  • Ciccarelli, M. & Rebucci, A. (2003). Measuring contagion with a Bayesian, time-varying coefficient model. IMF Working Paper, 03(171): 1-41.http://dx.doi.org/10.2139/ssrn.457531
  • Cogley, T. & Sargent, T. J. (2005). Drifts and volatilities: monetary policies and outcomes in the post WWII US. Review of Economic Dynamics, 8: 262– 302. https://doi.org/10.1016/j.red.2004.10.009
  • D’Agostino, A., Gambetti, L. & Giannone, D. (2013). Macroeconomic forecasting and structural change. Journal of Applied Econometrics, 28, 82–101. https://doi.org/10.1002/jae.1257
  • Drossidis, T. (2024). The time-varying effect of monetary policy onincome inequality in the Us. https://ssrn.com/abstract=5110038.
  • Eisenstat, E., Chan, J. C. C. & Strachan, R. (2014). Stochastic model specification search for time-varying parameter VARs. Working Paper series Rimini Centre for Economic Analysis, 44(14): 1-34. http://www.rcea.org/RePEc/pdf/wp44_14.pdf
  • Fisher, I. (1930). The theory of interest as determined by impatience to spend income and opportunity to invest it. The Macmillan Company.
  • Fischer, M. N., Hauzenberger, N., Huber, F. & Pfarrhofer, M. (2022). General Bayesian time-varying parameter VARs for modeling government bond yields. WU Vienna University of Economics and Business. Working Papers in Regional Science, 2021(01): 1-48. https://doi.org/10.57938/10106af8-e12a-422e-be86-c465799823aa
  • Gayaker, S.& Yalcin, Y. (2025). Examining the impact of monetary policy in Turkey: TVP-VAR with stochastic volatility. Panoeconomicus, 1-30. https://doi.org/10.2298/PAN230325007G
  • Giraitis, L., Kapetanios, G. & Yates, T. (2014). Inference on stochastic time-varying coefficient models. Journal of Econometrics, 179 (2014): 46–65. http://dx.doi.org/10.1016/j.jeconom.2013.10.009
  • Goodfriend, M. and King, R. (1997). The new neoclassical synthesis and the role of monetary policy. NBER Macroeconomics Annual, 12: 231–83. https://www.jstor.org/stable/i284975
  • Hauzenberger, N., Huber, F., Koop, G. & Onorante, L. (2022). Fast and flexible Bayesian inference in time-varying parameter regression models. Journal of Business & Economic Statistics, 40(4): 1904-1918. https://doi.org/10.1080/07350015.2021.1990772
  • Hauzenberger, N., Huber, F., Koop, G. & Mitchell, J. (2023). Bayesian modeling of time-varying parameters using regression trees. Federal Reserve Bank of Cleveland Working Paper Series, 23(05): 1-47. https://doi.org/10.26509/frbc-wp-202305
  • Hofmann, B. & Bogdanova, B. (2012). Taylor rules and monetary policy: A global 'Great Deviation'?. BIS Quarterly Review, 9: 37-49. https://www.researchgate.net/publication/254953879
  • Kerr, W. & Robert, G.K. (1996). Limits on interest rate rules in the IS model. Federal Reserve Bank of Richmond Economic Quarterly, 82: 47–75. https://ssrn.com/abstract=1230144
  • Koop, G. & Korobilis, D. (2013). Large time-varying parameter VARs. Journal of Econometrics, 177(2): 185-198. https://doi.org/10.1016/j.jeconom.2013.04.007
  • Kumawat, L. (2024). Time-variation in response of inflation to monetary policy shocks in India: evidence from TVP-VAR models. Indian Economic Review, 59(1): 233-248. http://dx.doi.org/10.2139/ssrn.4629732
  • Matějů, J. (2019). What drives the strength of monetary policy transmission? International Journal of Central Banking, 15(3): 59-87.
  • Melzer, C., Hoeppner, F. & Neumann, T. (2008). Changing effects of monetary policy in the U.S.- evidence from a time-varying coefficient VAR. Applied Economics, 40(18): 2353-2360. https://doi.org/10.1080/00036840600970112
  • Nakajima, J., Kasuya, M. & Watanabe, T. (2009). Bayesian analysis of time-varying parameter vector autoregressive model for the Japanese economy and monetary policy. Journal of the Japanese and International Economies, 2009(13): 1-28. https://doi.org/10.1016/j.jjie.2011.07.004
  • Paul, P. (2018). The time-varying effect of monetary policy on asset prices. Federal Reserve Bank of San Francisco Working Paper, 2017(09): 1-52. https://doi.org/10.24148/wp2017-09
  • Perron, P. (1997). Further evidence on breaking trend functions in macroeconomic variables. Journal of Econometrics, 80: 355-385. https://doi.org/10.1016/S0304-4076(97)00049-3 Perron, P. (Eds.) (2006). Dealing with structural breaks palgrave handbook of econometrics. Palgrave.
  • Prado, R., Herta, G. & West, M. (2000). Bayesian time-varying autoregressions: theory, methods and applications, Resenhas do Instituto de Matemática e Estatística da Universidade de São Paulo, 4: 405-422.
  • Primiceri, G. E. (2005). Time varying structural vector autoregressions and monetary policy. The Review of Economic Studies, 72: 821-852. https://doi.org/10.1111/j.1467-937X.2005.00353.x
  • Prüser, J. (2021). The horseshoe prior for time-varying parameter VARs and monetary policy. Journal of Economic Dynamics and Control, 129: 104–188. https://doi.org/10.1016/j.jedc.2021.104188 Roşoiu, A. (2015). Monetary policy and time varying parameter vector autoregression model. Procedia Economics and Finance, 32(2015):496 – 502. https://doi.org/ 10.1016/S2212-5671(15)01423-9
  • Sihvonen, J. & Vähämaa, S. (2012). Forward-looking monetary policy rules and option-implied interest rate expectations. Journal of Futures Markets, 34(4), , 27(1): 2-30. http://dx.doi.org/10.2139/ssrn.1574746
  • Simionescu, M., Schneider, N. & Gavurova, B. (2024). A Bayesian vector-autoregressive application with time-varying parameters on the monetary shocks–production network Nexus. Journal of Applied Economics, 27(1): 2-30. https://doi.org/10.1080/15140326.2024.2395114
  • Trabelsi, E. (2025). Monetary policy under global and spillover uncertainty shocks: what do the Bayesian time-varying coefficient VAR, local projections, and vector error correction model tell us in Tunisia?, Risk Financial Management, 18(3): 1-74. https://doi.org/10.3390/jrfm18030129
  • Yıldız, S.N. & Aydın, Ü. (2025). Empirical analysis of the relationship between monetary policy and asset prices in the Turkish economy, International Journal of Social and Economic Studies, 6(1): 282-298. https://doi.org/ 10.62001/gsijses.1711037
Toplam 36 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Zaman Serileri Analizi, Para Politikası
Bölüm Araştırma Makalesi
Yazarlar

Ayşegül Ladin Sümer 0000-0001-6507-3954

Gönderilme Tarihi 7 Ağustos 2025
Kabul Tarihi 19 Kasım 2025
Yayımlanma Tarihi 31 Aralık 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 3 Sayı: 2

Kaynak Göster

APA Sümer, A. L. (2025). Real Interest Rate for CBRT Monetary Policy? Bayesian TVP-VAR Model. Uluslararası İktisadi ve İdari Çalışmalar Dergisi, 3(2), 23-34.
AMA Sümer AL. Real Interest Rate for CBRT Monetary Policy? Bayesian TVP-VAR Model. Uluslararası İktisadi ve İdari Çalışmalar Dergisi. Aralık 2025;3(2):23-34.
Chicago Sümer, Ayşegül Ladin. “Real Interest Rate for CBRT Monetary Policy? Bayesian TVP-VAR Model”. Uluslararası İktisadi ve İdari Çalışmalar Dergisi 3, sy. 2 (Aralık 2025): 23-34.
EndNote Sümer AL (01 Aralık 2025) Real Interest Rate for CBRT Monetary Policy? Bayesian TVP-VAR Model. Uluslararası İktisadi ve İdari Çalışmalar Dergisi 3 2 23–34.
IEEE A. L. Sümer, “Real Interest Rate for CBRT Monetary Policy? Bayesian TVP-VAR Model”, Uluslararası İktisadi ve İdari Çalışmalar Dergisi, c. 3, sy. 2, ss. 23–34, 2025.
ISNAD Sümer, Ayşegül Ladin. “Real Interest Rate for CBRT Monetary Policy? Bayesian TVP-VAR Model”. Uluslararası İktisadi ve İdari Çalışmalar Dergisi 3/2 (Aralık2025), 23-34.
JAMA Sümer AL. Real Interest Rate for CBRT Monetary Policy? Bayesian TVP-VAR Model. Uluslararası İktisadi ve İdari Çalışmalar Dergisi. 2025;3:23–34.
MLA Sümer, Ayşegül Ladin. “Real Interest Rate for CBRT Monetary Policy? Bayesian TVP-VAR Model”. Uluslararası İktisadi ve İdari Çalışmalar Dergisi, c. 3, sy. 2, 2025, ss. 23-34.
Vancouver Sümer AL. Real Interest Rate for CBRT Monetary Policy? Bayesian TVP-VAR Model. Uluslararası İktisadi ve İdari Çalışmalar Dergisi. 2025;3(2):23-34.

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