Euro Bölgesi Enflasyon Oranında Şokların Kalıcılığı Üzerine Bir İnceleme

Bu çalışmada 2001M1-2022M11 yılları arasında aylık veriler kullanılarak Euro bölgesinde seçilmiş ülkelerin enflasyon oranları üzerinden fiyat değişkenliğinin yapısı analiz edilmektedir. Yapı analizi enflasyon oranlarının farklı dönemler arasındaki durağanlıktan durağan olmayana veya tersine geçiş yapan bir sürecin tahmini yapılarak analiz edilmiştir. Ayrıca, söz konusu analizde incelenen bütün ülkelere ait enflasyon oranlarının değişim noktalarının tespitine yönelik tahminler de yapılmıştır. Bulgularımız covid19 döneminden önce enflasyon oranlarında ortalamaya dönme eğiliminin devam ettiği bulgusuna ulaşılmıştır. Bu fiyat istikrarı ve enflasyon hedeflemesi için öngörülen %2 enflasyon oranına karşı bir kalıcılık ve direnç olduğu biçiminde yorumlanabilir. Ancak bu yapı analiz sonuçlarımıza göre covid19 salgın döneminde enflasyon oranının ortalamaya dönme eğilimi yapısında bir değişim olduğu yönündedir.

Anahtar Kelimeler:

Avrupa Birliği, Enflasyon oranı, Yapısal kırılma, Uzun hafıza, Covid19 salgını

An Examination on the Persistence of Shocks in the Eurozone Inflation Rate

In this study, the structure of price variability is analyzed over the inflation rates of selected countries in the Eurozone using monthly data between 2001M1-2022M11. The structure analysis is analyzed by estimating a process by which inflation rates move from stationary to non-stationary or vice versa across different periods. In addition, in this analysis, forecasts were also made to determine the change points of inflation rates for all countries analyzed. Our findings suggest that the tendency for inflation rates to revert to the mean continued before the covid19 period. This can be interpreted as a persistence and resistance to the 2% inflation rate envisaged for price stability and inflation targeting. However, according to our analysis results, there is a change in the structure of the tendency of the inflation rate to return to the average during the covid19 pandemic period.

Keywords:

European Union, Inflation rate, Structural break, Long memory, Covid19 pandemic,

PDF

___

Angeloni, I., Aucremanne, L., Ehrmann, M., Galí, J., Levin, A., & Smets, F. (2006). New evidence on inflation persistence and price stickiness in the Euro area: Implications for macro modeling. Journal of the European Economic Association, 4(2–3), 562–574. https://doi.org/10.1162/jeea.2006.4.2-3.562
Baba, C., Duval, R., Lan, T., & Topalova, P. (2023). The 2020-2022 Inflation Surge Across Europe : A Phillips-Curve-Based Dissection (WP/23/30).
Balcilar, M. (2004). Persistence in inflation: Does aggregation cause long memory? Emerging Markets Finance and Trade, 40(5), 25–56. https://doi.org/10.1080/1540496x.2004.11052583
Bos, C. S., Franses, P. H., & Ooms, M. (1999). Long memory and level shifts: Re-analyzing inflation rates. Empirical Economics, 24(3), 427–449. https://doi.org/10.1007/s001810050065
Busetti, F., & Taylor, A. M. R. (2004). Tests of Stationarity against a Change in Persistence. Journal of Econometrics, 123, 33–66. https://doi.org/10.1016/j.jeconom.2003.10.028
Caporale, G. M., & Gil-Alana, L. A. (2013). Long Memory and Fractional İntegration in High Frequency Data on the US Dollar/British Pound Spot Exchange Rate. International Review of Financial Analysis, 29, 1–9. https://doi.org/10.1016/j.irfa.2013.03.011
Carrière-Swallow, Y., Deb, P., Furceri, D., Jiménez, D., & Ostry, J. D. (2022). Shipping Costs and Inflation (WP/22/61).
Charemza, W. W., Hristova, D., & Burridge, P. (2005). Is inflation stationary? Applied Economics, 37(8), 901–903. https://doi.org/10.1080/00036840500076721
Choueiri, N., Ohnsorge, F., & Elkan, R. van. (2008). Inflation Differentials in the EU: A Common ( Factors ) Approach with Implications for EU8 Euro Adoption Prospects. IMF Working Papers, 08(21), 1. https://doi.org/10.5089/9781451868838.001
Culver, S. E., & Papell, D. H. (1997). Is there a unit root in the inflation rate? Evidence from sequential break and panel data models. Journal of Applied Econometrics, 12(4), 435–444. https://doi.org/10.1002/(SICI)1099-1255(199707)12:4<435::AID-JAE430>3.0.CO;2-1
Dickey, D. A., & Fuller, W. A. (1979). Distribution of the Estimators for Autoregressive Time Series With a Unit Root. Journal of the American Statistical Association, 74(July 2015), 427–431. https://doi.org/10.1080/01621459.1979.10482531
Dickey, D., & Fuller, W. (1981). Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root. Econometrica, 49(4), 1057–1072.
Errit, G., & Uusküla, L. (2014). Euro Area Monetary Policy Transmission in Estonia. Baltic Journal of Economics, 14(1–2), 55–77. https://doi.org/10.1080/1406099X.2014.980113
Henry, Ó. T., & Shields, K. (2004). Is there a unit root in inflation? Journal of Macroeconomics, 26(3), 481–500. https://doi.org/10.1016/j.jmacro.2003.03.003
Hou, J., & Perron, P. (2014). Modified local Whittle estimator for long memory processes in the presence of low frequency (and other) contaminations. Journal of Econometrics, 182(2), 309–328. https://doi.org/10.1016/j.jeconom.2014.05.004
Hurvıch, M., & Chen, W. W. (1998). An Efficient Taper for Potentially Overdıfferenced Long Memory Time Series.
Im, K. S., Pesaran, M. H., & Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115(1), 53–74. https://doi.org/10.1016/S0304-4076(03)00092-7
IMF. (2022). Regional Economic Outlook: Europe. In Regional Economic Outlook: Europe. https://doi.org/10.5089/9798400220586.086
Kabundi, A., Mlachila, M., & Yao, J. (2022). How Persistent are Implications for Monetary Policy (WP/22/207).
Kurozumi, T., & Zandweghe, W. Van. (2019). A Theory of Intrinsic Inflation Persistence. In Journal of Money, Credit and Banking (No. 19–16). https://doi.org/10.1111/jmcb.13066
Lee, H. Y., & Wu, J. L. (2001). Mean reversion of inflation rates: Evidence from 13 OECD countries. Journal of Macroeconomics, 23(3), 477–487. https://doi.org/10.1016/S0164-0704(01)00174-4
Li, D., Robinson, P. M., & Shang, H. L. (2020). Local Whittle Estimation of Long-Range Dependence For Functional Time Series. Journal of Time Series Analysis, 42(5–6), 685–695. https://doi.org/10.1111/jtsa.12577
Malliaropulos, D. (2000). A note on nonstationarity, structural breaks, and the Fisher effect. Journal of Banking and Finance, 24(5), 695–707. https://doi.org/10.1016/S0378-4266(99)00064-3
Martins, L. F., & Rodrigues, P. M. M. (2014). Testing for Persistence Change in Fractionally İntegrated Models: An Application to World İnflation Rates. Computational Statistics and Data Analysis, 76, 502–522. https://doi.org/10.1016/j.csda.2012.07.021
Robalo Marques, C. M. (2004). Inflation Persistence: Facts or Artefacts? In SSRN Electronic Journal (No. 371). https://doi.org/10.2139/ssrn.533131
Robinson, P. M. (2010). Long Memory Models. Macroeconometrics and Time Series Analysis, 163–168. https://doi.org/10.1057/9780230280830_19
Robinson, P.M. (1995). Gaussian Semiparametric Estimation of Long Range Depence. Annals of Statistics, 23(5), 1630–1661.
Robinson, Peter M. (2020). Spatial long memory. Japanese Journal of Statistics and Data Science, 3(1), 243–256. https://doi.org/10.1007/s42081-019-00061-z
Taylor, M. P., & Sarno, L. (1998). The behavior of real exchange rates during the post-Bretton Woods period. Journal of International Economics, 46(2), 281–312. https://doi.org/10.1016/S0022-1996(97)00054-8
Véron, N. (2016). The International Monetary Fund’s Role in the Euro-Area Crisis : Financial Sector Aspects. Bruegel Policy Contribution, 13. https://www.piie.com/system/files/documents/veron201608.pdf
Yaya, O. S., Ogbonna, A., & Atoi, N. V. (2019). Are inflation rates in OECD countries actually stationary during 2011-2018? Evidence based on Fourier Nonlinear Unit root tests with Break. 93937.
Zhou, S. (2013). Nonlinearity and Stationarity of İnflation Rates: Evidence from the Euro-Zone Countries. Applied Economics, 45(7), 849–856. https://doi.org/10.1080/00036846.2011.613774
Zivot, E., & Andrews, D. W. K. (1992). Further evidence on the great crash, the oil-price shock, and the unit-root hypothesis. Journal of Business and Economic Statistics, 10(3), 251–270. https://doi.org/10.1080/07350015.1992.10509904