Türkiye gıda enflasyonunun dönemselliklerinin alt gruplar dikkate alınarak incelenmesi

Year 2022, Volume: 24 Issue: 1, 232 - 250, 05.01.2022

Kamil Demirberk Ünlü , Yılmaz Akdi , Cem Baş , Yunus Emre Karamanoğlu

https://doi.org/10.25092/baunfbed.913206

Abstract

Bu makale, Ocak 2004 - Haziran 2020 dönemleri için Türkiye aylık gıda enflasyonu zaman serilerindeki gizli periyodiklikleri alt grupları ile ampirik olarak tanımlamaktadır. Dönemsellik, mevsimselliğin ötesinde olan zaman serilerinin gizli döngüleridir. Bu gizli döngülerle başa çıkmak için periodogram tabanlı zaman serisi analizi kullanılır. Ayrıca, gelecekteki enflasyon oranları harmonik regresyon ile tahmin edilmektedir. Bu çalışmanın sonuçları, Türkiye gıda enflasyonunun yaklaşık 2 yıllık döngülere sahip olduğunu ve bunun çoğunlukla gıda ve alkolsüz içecek enflasyonundan kaynaklandığını ortaya koymaktadır.

Keywords

Harmonik regresyon, periodogram, gıda enflasyonu, enflasyonun alt grupları, Türkiye.

Investigating the periodicities of the Turkish food inflation with considering the subgroups

Abstract

This paper empirically identifies the hidden periodicities in the time series of monthly food inflation of Turkey with its subgroups for the periods from January, 2004 to June, 2020. Periodicity is the hidden cycles of the time series which is beyond the seasonality. In order to deal with this hidden cycles periodogram based time series analysis is used. Also, future inflation ratios are forecasted by Harmonic regression. The results of this study reveal that food inflation of Turkey has cycles of approximately 2 years which is mostly derived by food and non-alcoholic beverage inflation.

Keywords

Harmonic regression, periodogram, food inflation, subgroups of inflation, Turkey

References

• Adam, C., Kwimbere, D., Mbowe, W., O'Connell, S., Food Prices and Inflation in Tanzania. Journal of African Development, 18(2), 19-40, (2016).
• Akdi, Y., & Dickey, D. A., Periodograms of unit root time series: distributions and tests. Communications in Statistics-Theory and Methods, 27(1), 69-87, (1998).
• Akdi, Y., Okkaoğlu, Y., Gölveren, E., & Yücel, M. E., Estimation and forecasting of PM 10 air pollution in Ankara via time series and harmonic regressions. International Journal of Environmental Science and Technology, 1-14, (2020a).
• Akdi, Y., Gölveren, E., & Okkaoğlu, Y., Daily electrical energy consumption: Periodicity, harmonic regression method and forecasting. Energy, 191, 116524, (2020b).
• Akdi, Y., Varlik, S., & Berument, M. H., Duration of Global Financial Cycles. Physica A: Statistical Mechanics and its Applications, 124331, (2020c).
• Agrawal, P., Kumarasamy, D., Food Price Inflation in India: Causes and Cures. Indian Economic Review, 49(1), 57-84, (2014).
• Altissimo, F., Ehrmann, M., Smets, F., Inflation Persistence and Price-Setting Behavior in the Euro Area, European Central Bank, Occasional Paper Series, No. 46, (2006).
• Bronnenberg, B., Mela, C., Boulding, W. The Periodicity of Pricing, Journal of Marketing Research, 43(3), 477-493. (2006).
• Durevalla, D., Loening, J.L, Birru, Y.A., Inflation dynamics and food prices in Ethiopia, Journal of Development Economics, 104, 89-106, (2013).
• Franses, P.H., Ooms, M., A periodic long-memory model for quarterly UK inflation. International Journal of Forecasting, 13(1), March, 117-126, (1997).
• Fuller, W. A., Introduction to statistical time series, Wiley, NewYork, (1996).
• Gómez, M.I., González, E., Melo, L., Torres, J.L., Forecasting Food Price Inflation in Developing Countries with Inflation Targeting Regimes: The Colombian Case, American Agricultural Economics Association Annual Meeting, (2006).
• Hafer, R., Hein, S., On the Accuracy of Time-Series, Interest Rate, and Survey Forecasts of Inflation, The Journal of Business, 58(4), 377-398, (1985).
• Hanif, M.N., A Note on Food Inflation in Pakistan, Pakistan Economic and Social Review, 50, No. 2, 183-206, (2012).
• Hasanov, M. Effects of Inflation Uncertainty on Output: The Case of Turkey, Journal of Doğuş University, (In Turkish), 2, (2008).
• Gil-Alana, L.A., Trani, T., The cyclical structure of the UK inflation rate: 1210–2016, Economics Letters, Elsevier, 181(C), 182-185, (2019).
• Ida, D., Sectoral inflation persistence and optimal monetary policy, Journal of Macroeconomics, 65, (2020).
• Joiya, S.A., Shahzad, A.A., Determinants of High Food Prices: The Case of Pakistan, Pakistan Economic and Social Review, Department of Economics, University of the Punjab, 51, No. 1 (Summer 2013), 93-107, (2013).
• Kang, S.H., Lahmiri, S., Uddin, G.S, Hernandez, J.A., Yoon, S.M., Inflation cycle synchronization in ASEAN countries, Physica A: Statistical Mechanics and its Applications, 545, (2020).
• Lamm, R. M., Dynamics of Food Price Inflation, Western Journal of Agricultural Economics, 4, No. 2 (December 1979), 119-132, (1979).
• Okkaoğlu, Y., Akdi, Y., Ünlü, K. D., Daily PM10, periodicity and harmonic regression model: The case of London, Atmospheric Environment, 117755, (2020).
• Safouane, M., Aïssaab, B., Musyc, O., Pereaud, J.C., Modelling inflation persistence with periodicity changes in fixed and predetermined prices models, Economic Modelling, 24, Issue 5, September 2007, 823-838, (2007).
• Salisu, A.A., Kazeem, O.I., Predicting US inflation: Evidence from a new approach. Economic Modelling, 71, 134-158, (2018).
• Schnepf, R., Richardson, J., Consumers and food price inflation, Congressional Research Service, Library of Congress, (2012).
• Van D.C., Food Prices, Expectations, and Inflation, American Journal of Agricultural Economics, 64(3), 419-430, (1982).
• Wei, W. W.S., Time Series Analysis: Univariate and Multivariate Methods, Second Edition, Pearson Addision Wesley, Boston, (2006).