Parasal Değişkenler ve Çıktı İlişkisinin Türkiye İçin Tarihsel Ayrıştırma Yöntemi İle Analizi

Abstract

Parasal değişkenler ve çıktı arasındaki dinamik ilişki makroekonomide en çok çalışılan konulardan biridir. Türkiye Ekonomisine ilişkin olarak yapılan çalışmaların önemli bir kısmının çıkmazı bu çalışmaların birçoğu Granger Nedensellik Testi ve Etki-Tepki fonksiyonu analizi gibi tam örneklem tahmin yöntemlerinin sonuçlarının, göz önünde bulundurduğu örneklem dönemine göre duyarlı görünmesidir. Bu zorluğun üstesinden gelmenin bir yolu olarak, bu çalışmada, Türkiye Ekonomisi için parasal değişkenler ile çıktı değişkeni arasındaki dinamik ilişkiyi vektör otoregresif bir modele dayanan Tarihsel Ayrışma yöntemi kullanılarak incelenmiştir. Çalışmada 1987-2019 dönemi için M1, M2 ve iskonto oranı ile çıktı arasındaki ilişki VAR modeli ile incelenmiş olup enflasyon değişkeninin gecikmeleri bu oluşturulan VAR modeline dışsal değişken olarak eklenmiştir. Tarihsel Ayrıştırma yönteminin avantajlarından faydalanarak değişkenler arasındaki zamanla değişen şoklar uygulanarak daha doğru sonuçlar elde edilmiştir. Bu çalışmadan elde edilen temel sonuç ise çalışmada kullanılan parasal değişkenlerin 1994 ve 2001 Krizlerinde gelir değişkenini negatif olarak güçlü bir şekilde açıkladığı, diğer dönemlerde çoğunlukla güçlü olmamakla beraber pozitif etkilediği şeklindedir.

Keywords

• Tarihsel Ayrıştırma
• Parasal Değişkenler
• M1
• M2
• Çıktı
• Türkiye

Analysis of Monetary Variables and Output Relationship with Historical Decomposition Method for Turkey

Abstract

The dynamic links between monetary variables and output is one of the most studied issues in macroeconomics. One puzzle from the significant portion of the literature is that the results of full estimation methods such as Granger Causality Test and Impulse-Response Function analysis appear to be sensitive with respect to the sample period that one considers. As a way of overcoming this difficulty, this study investigates the dynamic links between monetary variables and output for Turkey using the method Historical Decomposition which is based on a vector autoregressive model. In the study, the relationship between M1, M2 and discount rate and output for the period of 1987-2019 was examined with the VAR model, and the lags of the inflation variable were added to this created VAR model as an external variable. By taking advantage of the historical decomposition method, more accurate results were obtained by applying time-varying shocks between the variables. The main conclusion obtained from this study is that the monetary variables used in the study while explains the income negatively in 1994 and 2001 Crises it affects positively although it was not strong in other periods.

Keywords

• Historical Decomposition
• Monetary Variables
• M1
• M2
• Output
• Turkey

References

1. Bernanke, B. S. (1986). Alternative explanations of the money–income correlation. Carnegie-Rochester Conference Series on Public Policy, 25, 49–99. https://doi.org/10.1016/0167-2231(86)90037-0
2. Berüment, H. and Doğan, B. (2003). Openness and the effectiveness of monetary policy: Empirical evidence from Turkey. Applied Economics Letters, 10(4), 217-221. https://doi.org/10.1080/1350485022 000015842
3. Bozkurt, C. (2014). Money, inflation and growth relationship: The Turkish case. International Journal of Economics and Financial Issues, 4(2), 309-322. Retrieved from https://www.econjournals.com/
4. Bozoklu, Ş. (2013). Money, income, and causality: An examination for the Turkish economy. Economic Research-Ekonomska Istraživanja, 26(1), 171-182. https://doi.org/10.1080/1331677X.2013.11517596
5. Christiano, L. J. and Ljungqvist, L. (1988). Money does Granger-cause output in the bivariate money–output relation. Journal of Monetary Economics, 22(2), 217–235. https://doi.org/10.1016/0304-3932(88)90020-7
6. Cömert, H. ve Türel, O. (2016). Finansal küreselleşme sürecinde Türkiye’de para politikalarının evrimi, 1980-2014 (ERC-Economic Research Center, Middle East Technical University Working Paper Series 1613). Erişim adresi: http://erc.metu.edu.tr/en/system/files/menu/series16/1613.pdf/
7. Efron, B. (1982). The jackknife, the bootstrap, and other resampling plans (1. Ed.). Philadelphia: SIAM.
8. Eichenbaum, M. and Singleton, K. J. (1986). Do equilibrium real business cycle theories explain postwar US business cycles? NBER Macroeconomics Annual, 1, 91-135. https://doi.org/10.2307/3585163

9. Erdal, B. (2018). The nexus between monetary variables and economic growth under inflation targeting regime: Empirical evidence from Turkey. International Research Journal of Applied Finance, 9(10), 435-444. Retrieved from www.irjaf.com
10. Friedman, B. M. and Kuttner, K. N. (1992). Money, income, prices, and interest rates. American Economic Review, 82, 472–492. Retrieved from https://www.aeaweb.org/journals/aer
11. Friedman, B. M. and Kuttner, K. N. (1993). Another look at the evidence on money–income causality. Journal of Econometrics, 57, 189–203. https://doi.org/10.1016/0304-4076(93)90064-C
12. Hansen, B. E. (1999). The grid bootstrap and the autoregressive model. Review of Economics and Statistics, 81, 594–607. https://doi.org/10.1162/003465399558463
13. Korap, H. L. (2007). Multirank cointegration analysis of Turkish M1 money demand (1987Q1-2006Q3). Istanbul University Econometrics and Statistics E-Journal, 6, 1-28. Retrieved from https://dergipark.org.tr/tr/pub/ekoist
14. Krol, R. and Ohanian, L. E. (1990). The impact of stochastic and deterministic trends on money–output causality: A multi-country investigation. Journal of Econometrics, 45, 291–308. https://doi.org/10.1016/0304-4076(90)90001-A
15. Litterman, R. B. and Weiss L. (1985). Money, real-interest rates, and output: A reinterpretation of postwar U.S. data. Econometrica, 53, 128–156. https://doi.org/10.2307/1911728
16. Lütkepohl, H. (2005). New introduction to multiple time series analysis (1. Ed.). Berlin: Springer.
17. Ng, S. and Perron, P. (1995). Unit root tests in ARMA models with data-dependent methods for the selection of the truncation lag. Journal of the American Statistical Association, 90, 268–281. https://doi.org/10.2307/2291151
18. Özatay, F. (2009). Türkiye’de 2000-2008 döneminde para politikası. İktisat, İşletme ve Finans Dergisi, 24(275), 37-65. Erişim adresi www.iif.com.tr
19. Psaradakis, Z., Ravn, M. O. and Sola, M. (2005). Markov switching causality and the money output relationship. Journal of Applied Econometrics, 20, 665-683. https://doi.org/10.1002/jae.819
20. Romano, J. P. and Wolf, M. (2001). Subsampling intervals in autoregressive models with linear time trend. Econometrica, 69, 1283–1314. https://doi.org/10.1111/1468-0262.00242
21. Saatçioğlu, C. and Korap, L. (2008). Long-run relations between money, prices and output: The case of Turkey. Uluslararası Yönetim İktisat ve İşletme Dergisi, 4(7), 33-54. Erişim adresi https://dergipark.org.tr/en/pub/ijmeb
22. Shi, S., Hurn, S. and Phillips, P. C. (2016). Causal change detection in possibly integrated systems: Revisiting the money–income relationship. Journal of Financial Econometrics, 18(1), 158-180. https://doi.org/10.1093/jjfinec/nbz004
23. Sims, C. A. (1972). Money, income and causality. American Economic Review, 62, 540–552. Retrieved from https://www.aeaweb.org/journals/aer
24. Sims, C. A. (1980). Macroeconomics and reality. Econometrica, 48, 1–48. https://doi.org/10.2307/1912017
25. Stock, J. H and Watson, M. W. (1989). Interpreting the evidence on money–income causality. Journal of Econometrics, 40, 161–181. https://doi.org/10.1016/0304-4076(89)90035-3
26. Taştan, H. and Şahin, S. (2020). Low-frequency relationship between money growth and inflation in Turkey. Quantitative Finance and Economics, 4(1), 91. https://doi.org/10.3934/QFE.2020005
27. Thoma, M. A. (1994). Subsample instability and asymmetries in money–income causality. Journal of Econometrics, 64, 279–306. https://doi.org/10.1016/0304-4076(94)90066-3