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Dergiler / Gazi University Journal of Science / 2026 / Volume: 29 Issue: 2

DETERMINING RELATIVE WEIGHTS OF INFLATION UNCERTAINTY IN TURKEY VIA CPI AND ITS COMPONENTS

Pınar Göktaş
Ali Çımat
Sayfa
—
Yayın Tarihi
2016-06-20
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Contrary to expectations, it was revealed that the expenditure group having the greatest impact on inflation uncertainty is not “food, beverage and tobacco” expenditure group but “transportation”.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:This study aims to investigate the interaction of main expenditures groups of CPI with the fluctuations taking place at the level of general prices and calculate the relative weights of theirs uncertainties within inflation uncertainty.
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Temel Bulgular & Veri:Since there might be structural breaks in the investigated variables, Bai-Perron test, GARCH-type models are constructed by including the breaks in the fluctuation measurement and ARDL approach has been used to determine the long-term relationship between the variables.
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Sonuç & Katkı:Contrary to expectations, it was revealed that the expenditure group having the greatest impact on inflation uncertainty is not “food, beverage and tobacco” expenditure group but “transportation”.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:GARCH-type models with multiple structural breaks · Bai-Perron method · Inflation uncertainty

Abstract

This study aims to investigate the interaction of main expenditures groups of CPI with the fluctuations taking place at the level of general prices and calculate the relative weights of theirs uncertainties within inflation uncertainty. Since there might be structural breaks in the investigated variables, Bai-Perron test, GARCH-type models are constructed by including the breaks in the fluctuation measurement and ARDL approach has been used to determine the long-term relationship between the variables. Contrary to expectations, it was revealed that the expenditure group having the greatest impact on inflation uncertainty is not “food, beverage and tobacco” expenditure group but “transportation”.

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Bu Makaleye Atıf Yap

Göktaş, P., Çımat, A. (2016). DETERMINING RELATIVE WEIGHTS OF INFLATION UNCERTAINTY IN TURKEY VIA CPI AND ITS COMPONENTS. Gazi University Journal of Science, Volume: 29 Issue: 2. https://ajindex.com/articles/1269501

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Kaynakça (51)

  1. Antoshin, S. Berg, A. & Souto, M. (2008). Testing For Structural Breaks In Small Samples. International Monetary Fund (IMF) Working Paper African Department, 75
  2. Bai, J. (1997). Estimating Multiple Breaks One At A Time. Econometric Theory, 13 (3), 315-352
  3. Bai, J., Perron, P. (1998). Estimating and Testing Lineer Models With Multiple Structural Change. Econometrica, 66 (1), 47-78
  4. Bai, J., Perron, P. (2003a). Computation and Analysis of Multiple Structural Change Models, Journal of Applied Econometrics, 18, 1-22.
  5. Bai, J., Perron, P. (2003b). Critical Values For Multiple Structural Change Tests. Econometrics Journal, 6, 72–78
  6. Bai, J., Perron, P. (2004). Multiple Structural Change Models: A Simulation Analysis. http://www.columbia.edu/~jb3064/papers/2006_Multiple_structural_changes_models_a_simulation_analysis.pdf.
  7. Ball, L. (1992). Why Does Higher Inflation Raise Inflation Uncertainty? Journal of Monetary Economics, 29(3), 371-388
  8. Banerjee, S. (2013). Essays on inflation volatility (Doctoral dissertation, University of Durham)
  9. Banerjee, P. & A., Rahman, M. (2012). Carbon Emissions and Environment: Evidences from Three Selected SAARC Countries. Southwest Business and Economics, 1-13.
  10. Bollerslev, T. (2007). Glossary to ARCH (GARCH). Center for Research in Econometrics Analysis of Time Series Research Paper
  11. Carare, A., Schaechter, A., Stone, M.ve Zelmer, M.(2002). Establishing Initial Conditions in Support of Inflation Targeting. IMF Working Paper, 102
  12. Cukierman A. & Meltzer A.H. (1986). A Theory of Ambiguity, Credibility and Inflation Under Discretion and Asymmetric Information. Econometrica, 54( 5), 1099-1128
  13. Dickey, D. A. & W. A. Fuller (1981). Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root. Econometrica, 49 (4), 1057-1072
  14. Drakos, A.A., Kouretas, G.P. & Zarangas, L.P. (2010). Forecasting financial volatility of the Athens stock exchange daily returns: An application of the Asymmetric normal mixture GARCH model. International Journal of Finance and Economics, 15, 331–350
  15. Endresz, M. V. (2004). Structural Breaks And Financial Risk Management. Magyar Nemzeti Bank, MNB Working Paper, 11, 1-56
  16. Enders, W.& Sandler, T. (2005). After 9/11: Is It All Different Now?. Journal of Conflict Resolution, 49 (2), 259-277
  17. Engle, R. F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica, 50 (4), 987-1007
  18. Engle, R.F. & Granger, C.W.J. (1987). Co-integration and Error Correction: Reprenetationi Estimation, And Testing. Econometrica, 55(2), 251-276
  19. Friedman, M. (1977). Nobel Lecture: Inflation and Unemployment. Journal of Political Economy, 85(3), 451-472
  20. Frimpong, J.M.& Oteng-Abayie, E.F. (2006). Bounds Testing Approach: An Examination of Foreign Direct Investment, Trade, and Growth Relationships. Munich Personel RePEc Archive (MPRA), 352
  21. Greene, J. & D’Olivera, M. (2005), Learning to use statistical tests in psychology, New York: Open University Press, McGraw-Hill Education.
  22. Grier K.B. & Perry M.J. (1998). On Inflation and Inflation Uncertainty in the G7 Countries. Journal of International Money and Finance, 17, 671-689
  23. Gujarati, D. N. (2004). Temel Ekonometri. (Ü. Şenesen ve G. Günlük Şenesen, Çev.). İstanbul: Literatür Yayınları.
  24. Hentschel, L. (1995). All In The Family Nesting Symmetric And Asymmetric GARCH Models. Journal of Financial Economics, 39, 71-104
  25. Holland, A.S. (1995). Inflation and Uncertainty: Tests for Temporal Ordering. Journal of Money, Credit and Banking, 27(3), 827-837
  26. Johansen, S. (1988). Statistical Analysis of Cointegration Vectors. Journal of Economic Dynamics and Control, 12(2–3), 231–254
  27. Johansen, S. (1991). Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models. Econometrica, 59(6), 1551-1580
  28. Johansen, S. (1995). Identifying Restrictions of Linear Equations With Applications To Simultaneous Equations and Cointegration. Journal of Econometrics, 69(1), 111–132
  29. Johansen, S. & Juselius, K. (1990). Maximum Likelihood Estimation And Inference On Cointegration – With Applcations To The Demand For Money. Oxford Bulletin Of Economics and Statistics, 52(2), 169-210
  30. Kwiatkowski, D., Phillips, P.C.B., Schmidt,P. & Shin, Y. (1992): Testing the Null Hypothesis of Stationarity against the Alternative of a Unit Root. Journal of Econometrics, 54, 159-178.
  31. Larsen, E.R. (2004). Does the CPI Mirror Costs-ofLiving? Engel's Law Suggests Not in Norway. Statistics Norway, Research Department, Discussion Papers, 368
  32. Laurenceson J. & Chai J. (2003). Financial reform and economic development in China. Advance in Chinese Economic Studies Series, Cheltenham, UK: Edward Elgar Publishing Limited
  33. Mankiw, N.G. (2006). Principles of macroeconomics, Sixth Edition. United States of America: Worth Publishers.
  34. Narayan, P.K.& Narayan, S. (2005). Estimating Income And Price Elasticities of Imports for Fiji in A Cointegration Framework. Economic Modelling 22, 423– 438
  35. Norman, D. & Richards, A. (2012). The Forecasting Performance of Single Equation Models of Inflation. Economic Record, 88(280), 64-78
  36. Omotosho, B.S. & Doguwa, S.I. (2013). Understanding the Dynamics of Inflation Volatility in Nigeria: A GARCH Perspective. CBN Journal of Applied Statistics, 3(2), 51-74
  37. Pelipas, I. (2012). Multiple Structural Breaks And Inflation Persıstence in Belarus. Belarusian Economic Research and Outreach Center, Working Paper Series, BEROC WP, 021
  38. Pesaran, M.H.& Shin, Y. (1998). An autoregressive distributed lag modelling approach to cointegration analysis. S. Strom (Ed.), Econometrics and Economic Theory in the 20th Century: The Ragnar Frisch Centennial Symposium (pp. 371-413). UK: Cambridge University Press.
  39. Pesaran, H.M.; Shin Y. & Smith R. (1999). Bounds Testing Approaches to the Analysis of Level Relationships. Journal Of Applied Econometrics, 16, 289-326
  40. 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
  41. Petursson, T.G. (2000). Exchange rate or inflation targeting in monetary policy? Monetary Bulletin, 1, 36-45
  42. Phillips, P.C.B. & Hansen, B.E. (1990). Statistical Inference in Instrumental Variables Regression with I(1) Processes. Review of Economic Studies, 57, 99-125
  43. Phillips, P.C.B., Perron, (1988). Testing For A in time Series Reggression. Biometrica, 75(2), 335-346
  44. Pourgerami, A. & Maskus, K.E. (1987). The Effects of Inflation on the Predictability of Price Changes in Latin America: Some Estimates and Policy Implications. World Development, 15(2), 287-290
  45. Shahbaz, M., Adnan, H. Q. M. & Kumar, T.A. (2012). Economic Growth, Energy Consumption, Financial Development, International Trade and CO2 Emissions in Indonesia. Munich Personel RePEc Archive (MPRA), 43294
  46. Tsyplakov, A. (2010). The Links Between Inflation And Inflation Uncertainty At The Longer Horizon. Economics Education and Research Consortium: Russia and CIS, Working Paper No10/09E
  47. Türkiye Cumhuriyet Merkez Bankası (2001). Türkiye’nin Güçlü Ekonomiye Geçiş Programı.
  48. Türkiye Cumhuriyet Merkez Bankası, (2006). Enflasyon Hedeflemesi Rejimi
  49. Zapodeanu, D., Cociuba, M.I. and Petris, S. (2014), The Inflation- Inflation Uncertainty Nexus In Romania. International Conference “Monetary, Banking and Financial Issues in Central and Eastern EU Member Countries: How Can Central and Eastern EU Members Overcome the Current Economic Crisis?. Iaşi, Romania, 10-12 April 2014
  50. Carare, A., Schaechter, A., Stone, M.ve Zelmer, M.(2002). Establishing Initial Conditions in Support of Inflation Targeting. IMF Working Paper, 102
  51. Phillips, P.C.B., Perron, (1988). Testing For A in time Series Reggression. Biometrica, 75(2), 335-346