Türkiye Ekonomisi Bağlamında Fisher Etkisinin Birim Kök Testleri ve ARDL Sınır Testiyle Sınanması

Abstract

The positive relationship between the interest rate and the inflation rate is known as the Fisher effect in economics. The validity of the Fisher effect in the Turkish economy between 1971 and 2021 was tested using the ARDL bounds test and unit root tests within the scope of this study. In this context, it was concluded that the variables that are not stationary at the level move together in the long run. In the long run, a 1% increase in the inflation rate increases the interest rates by 1.05%. The Toda-Yamamoto causality test revealed a one-way Granger causality relationship between the related variables, ranging from the inflation rate to the interest rate. The stationarity of the real interest rate was tested with ADF, Lee- Strazicich and Fourier KPSS unit root tests. The findings indicate that the real interest rate variable is stationary and that the Fisher hypothesis holds in the Turkish economy.

Keywords

• Fisher Hipotezi
• ARDL sınır testi
• Toda-Yamamoto Nedensellik Testi
• DOLS

Testing The Fisher Effect in The Context Of Turkish Economy With Unit Root Tests and ARDL Bounds Testing Approach

Abstract

Ekonomi yazınında faiz oranı ile enflasyon oranı arasındaki pozitif yönlü ilişki Fisher etkisi olarak bilinmektedir. Bu çalışma kapsamında, Türkiye ekonomisinde 1971-2021 arası Fisher etkisinin geçerliliği ARDL sınır testi ve birim kök testleriyle sınanmıştır. Bu bağlamda, düzeyde durağan olmayan değişkenlerin uzun dönemde birlikte hareket ettikleri sonucuna ulaşılmıştır. Uzun dönemde enflasyon oranında meydana gelen %1lik artış faiz oranlarını % 1.05 oranında artırmaktadır. Toda-Yamamoto nedensellik test sonucuna göre ilgili değişkenler arasında enflasyon oranından faiz oranına doğru olmak üzere tek yönlü Granger nedensellik ilişkisi tespit edilmiştir. Reel faiz oranının durağanlık durumu ise ADF, Lee- Strazicich ve Fourier KPSS birim kök testleriyle sınanmıştır. Sonuçlar reel faiz oranı değişkeninin durağan olduğunu göstererek Fisher hipotezinin Türkiye ekonomisinde geçerli olduğunu göstermiştir.

Keywords

• Fisher Hypothesis
• ARDL bounds test
• Toda-Yamamoto Causality Test
• DOLS

References

1. Akinci, M., & Yilmaz, Ö. (2016). Enflasyon-faiz oranı takası: Fisher hipotezi bağlamında Türkiye ekonomisi için dinamik en küçük kareler yöntemi. Sosyoekonomi, 24(27), 33-56.
2. Alimi, R. S. (2014). ARDL bounds testing approach to Cointegration: A re-examination of augmented fisher hypothesis in an open economy. Asian Journal of Economic Modelling, 2(2), 103-114.
3. Amiri, A., & Ventelou, B. (2012). Granger causality between total expenditure on health and GDP in OECD: Evidence from the Toda–Yamamoto approach. Economics Letters, 116(3), 541-544.
4. Atkins, F. J., & Coe, P. J. (2002). An ARDL bounds test of the long-run Fisher effect in the United States and Canada. Journal of Macroeconomics, 24(2), 255-266.
5. Bayat, T. (2012). Türkiye’de fisher etkisinin geçerliliği: doğrusal olmayan eşbütünleşme yaklaşimi. Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, (38), 47-60.
6. Becker, R., Enders, W., & Lee, J. (2006). A stationarity test in the presence of an unknown number of smooth breaks. Journal of Time Series Analysis, 27(3), 381-409.
7. Berument, H., & Jelassi, M. M. (2002). The Fisher hypothesis: a multi-country analysis. Applied Economics, 34(13), 1645-1655.
8. Camba Jr, A. C., & Camba, A. L. (2021). An Engle-Granger and Johansen Cointegration Approach in Testing the Validity of Fisher Hypothesis in the Philippines. The Journal of Asian Finance, Economics and Business, 8(12), 31-38.

9. Caporale, G. M., & Gil-Alana, L. (2019). Testing the Fisher hypothesis in the G-7 countries Using i (d) Techniques. International Economics, 159, 140-150.
10. Christopoulos, D. K., & León‐Ledesma, M. A. (2007). A long‐run non‐linear approach to the fisher effect. Journal of Money, Credit and Banking, 39(2‐3), 543-559.
11. Dogan, I., Orun, E., Aydın, B., & Afsal, M. S. (2020). Non-parametric analysis of the relationship between inflation and interest rate in the context of Fisher effect for Turkish economy. International Review of Applied Economics, 34(6), 758-768.
12. Dritsaki, C. (2017). Toda-Yamamoto causality test between inflation and nominal interest rates: evidence from three countries of Europe. International Journal of Economics and Financial Issues, 7(6), 120.
13. Dutt, S. D., & Ghosh, D. (1995). The Fisher hypothesis: examining the Canadian experience. Applied Economics, 27(11), 1025-1030.
14. Enders, W. (2015). Applied econometric time series fourth edition. New York (US): University of Alabama.
15. Engle, R. F., & Granger, C. W. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica: journal of the Econometric Society, 251-276.
16. Gocer, I., & Ongan, S. (2020). The relationship between inflation and interest rates in the UK: The nonlinear ARDL approach. Journal of Central Banking Theory and Practice, 9(3), 77-86.
17. Granville, B., & Mallick, S. (2004). Fisher hypothesis: UK evidence over a century. Applied Economics Letters, 11(2), 87-90.
18. Gujarati, D., & Porter, D. (2009). Essentials of Econometrics 4e. McGraw Hill.
19. Gul, E., & Acikalin, S. (2008). An examination of the Fisher hypothesis: The case of Turkey. Applied Economics, 40(24), 3227-3231.
20. Güriş, B., & Yaşgül, Y. S. (2014). Does the Fisher hypothesis hold for the G7 countries? Evidence from ADL threshold cointegration test. Quality & Quantity, 49(6), 2549-2557.
21. İncekara, A., Demez, S., & Ustaoğlu, M. (2012). Validity of Fisher effect for Turkish economy: Cointegration analysis. Procedia-social and behavioral sciences, 58, 396-405.
22. Junttila, J. (2001). Testing an augmented fisher hypothesis for a small open economy: The case of Finland. Journal of Macroeconomics, 23(4), 577-599.
23. Lee, J., & Strazicich, M. C. (2003). Minimum Lagrange multiplier unit root test with two structural breaks. Review of economics and statistics, 85(4), 1082-1089.
24. MacDonald, R., & Murphy, P. D. (1989). Testing for the long run relationship between nominal interest rates and inflation using cointegration techniques. Applied Economics, 21(4), 439-447.
25. Mankiw, N. G. (2016). Macroeconomics,(9th edition). Cengage learning. New York: Worth Publishers.
26. Menegaki, A. N. (2019). The ARDL method in the energy-growth nexus field; best implementation strategies. Economies, 7(4), 105.
27. Mishkin, F. S. (2012). Macroeconomics-Policy and Practice (Global ed.). Essex, England: Pearson Education Limited.
28. Mishkin, F. S., & Simon, J. (1995). An empirical examination of the Fisher effect in Australia. Economic Record, 71(3), 217-229.
29. Odhiambo, N. M. (2009). Energy consumption and economic growth nexus in Tanzania: An ARDL bounds testing approach. Energy policy, 37(2), 617-622.
30. Özcan, B., & Ari, A. (2015). Does the Fisher hypothesis hold for the G7? Evidence from the panel cointegration test. Economic research-Ekonomska istraživanja, 28(1), 259-270.
31. Peláez, R. F. (1995). The Fisher effect: reprise. Journal of Macroeconomics, 17(2), 333-346.
32. Pesaran, M. H. (2015). Time series and panel data econometrics. Oxford University Press.
33. Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of applied econometrics, 16(3), 289-326.
34. Phylaktis, K., & Blake, D. (1993). The Fisher hypothesis: Evidence from three high inflation economies. Weltwirtschaftliches Archiv, 129(3), 591-599.
35. Sjölander, P., Månsson, K., & Shukur, G. (2017). Testing for panel cointegration in an error-correction framework with an application to the Fisher hypothesis. Communications in Statistics-Simulation and Computation, 46(3), 1735-1745.
36. Srinivasan, P., Kumar, P. S., & Ganesh, L. (2012). Tourism and economic growth in Sri Lanka: An ARDL bounds testing approach. Environment and Urbanization Asia, 3(2), 397-405.
37. Stierle, M. H., & Rocher, S. (2015). Household saving rates in the EU: Why do they differ so much? (No. 005). Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
38. Stock, J. H., & Watson, M. W. (1993). A simple estimator of cointegrating vectors in higher order integrated systems. Econometrica: journal of the Econometric Society, 783-820.
39. Stock, J. H., ve Watson, M. W. (2020). Introduction to econometrics. Harlow: Pearson Education.
40. Sugözü, İ. H., & Yaşar, S. (2020). Enflasyon ve Faiz İlişkisi: OECD Ülkeleri Üzerine Panel Regresyon ve Nedensellik Analizleri. Maliye Dergisi,179,85-105.
41. Sun, Y., & Phillips, P. C. (2004). Understanding the Fisher equation. Journal of Applied Econometrics, 19(7), 869-886.
42. Şimşek, M., & Kadılar, C. (2006). Fisher etkisinin Türkiye verileri ile testi. Doğuş Üniversitesi Dergisi, 7(1), 99-111.
43. Tinoco-Zermeno, M. A., Venegas-Martínez, F., & Torres-Preciado, V. H. (2014). Growth, bank credit, and inflation in Mexico: evidence from an ARDL-bounds testing approach. Latin American Economic Review, 23(1), 1-22.
44. Toda, H.Y., & Yamamoto, T. (1995). Statistical inference in vector auto regressions with possibly integrated processes. Journal of Econometrics, 66, 225-250.
45. Tsong, C. C., ve Lee, C. F. (2013). Quantile cointegration analysis of the Fisher hypothesis. Journal of macroeconomics, 35, 186-198.
46. Verma, R. (2007). Savings, investment and growth in India: An application of the ARDL bounds testing approach. South Asia Economic Journal, 8(1), 87-98.
47. Westerlund, J. (2008). Panel cointegration tests of the Fisher effect. Journal of Applied Econometrics, 23(2), 193-233.
48. Wooldridge, J. M. (2018). Introduction to econometrics: A modern approach. Michigan State University. USA.
49. Yilanci, V. (2009). Fisher Hipotezinin Türkiye İçin Sınanması: Doğrusal Olmayan Eşbütünleşme Analizi. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 23(4), 205-213.