Yem Fiyatlarındaki Değişim Et Fiyatlarını Nasıl Etkiler? Türkiye Örneği

Yıl 2023, Cilt: 54 Sayı: 2, 68 - 74, 23.05.2023

Veli Anıl Çakan , Tolga Tipi

https://doi.org/10.5152/AUAF.2023.22054

Öz

Bu çalışma, et ve et ürünleri fiyatları ile yem fiyatları arasındaki ilişkiyi anlamayı amaçlamaktadır. Bu amaçla değişkenler arasındaki nedensellik ve uzun dönem ilişkileri Granger nedensellik testi ve ARDL modeli yaklaşımları kullanılarak incelenmiştir. Çalışmanın verileri, Türkiye İstatistik Kurumu tarafından paylaşılan Et Tüketici Fiyat Endeksi (MCPI) ve Yem Fiyat Endeksi'nden (FPI) oluşturulmuştur. Veri seti, Ocak 2016 ile Ekim 2021 arasındaki dönemi kapsayan 70 gözlemden oluşmaktadır. Granger nedensellik testi sonuçları, FPI'nin MCPI'nin Granger nedeni olduğunu göstermektedir. Otoregresif Dağıtılmış Gecikme (ARDL) modelinin uzun dönemli tahmin sonuçlarına göre, FPI'deki %1'lik bir artış MCPI'yi %0,97 artırmaktadır. Yaklaşık 4 ayda kısa dönemdeki sapmaların düzeleceği ve sistemin uzun dönem dengesine yakınsayacağı tahmin edilmektedir. Et ve et ürünleri fiyatlarının yem fiyatlarından önemli ölçüde etkilendiğini gösteren çalışmanın sonuçları dikkate alındığında, yem bitkileri ve yem sanayine yönelik teşviklerin et fiyatlarını olumlu yönde etkileme potansiyeline sahip olduğu ifade edilebilir.

Anahtar Kelimeler

ARDL modeli, Tüketici Fiyat Endeksi, yem fiyatları, Granger nedensellik testi, et fiyatları

How Does the Change in Feed Prices Affect Meat Prices? A Case Study of Turkey

Öz

This study aims to understand the relationship between meat and meat product prices and feed prices. For this purpose, causality and long-run relationship between variables are examined using the Granger causality test and autoregressive distributed lag model approaches. The data of the study is formed from the Meat Consumer Price Index and Feed Price Index shared by the Turkish Statistical Institute. The data set is composed of 70 observations covering the period from January 2016 to October 2021. The results of the Granger causality test show that the Feed Price Index is the Granger cause of the Meat Consumer Price Index. According to the long-run estimation results of the autoregressive distributed lag model, a 1% increase in the Feed Price Index increases the Meat Consumer Price Index by 0.97%. It is estimated that the deviations from the long-run equilibrium will be adjusted in approximately 4 months. Considering the results of the study showing that the prices of meat and meat products are significantly affected by feed prices, it can be concluded that the subsidies to the feed crops and feed industry has the potential to impact meat prices positively

Anahtar Kelimeler

ARDL model, Consumer Price Index, feed prices, Granger causality test, meat prices

Kaynakça

• Akın, A. C., Arıkan, M. S., Çevrimli, M. B., & Tekindal, M. A. (2020). Assessment of the effect of beef and mutton meat prices on chicken meat prices in Turkey using different regression models and the decision tree algorithm. Kafkas Universitesi Veteriner Fakultesi Dergisi, 26(1), 47–52. [CrossRef]
• Albez, A. (2018). Red meat sector profitability and cost analysis in Erzurum scale. Atatürk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 22(Special Issue 3), 2969–2986 (in Turkish with an abstract in English).
• Arıkan, M. S., Çevrimli, M. B., Polat, M., Mat, B., Akın, A. C., Özel, Z., & Tekindal, M. A. (2022). Analyzing the factors affecting the price of broiler chicken in Turkey using the boosting regression method. Brazilian Journal of Poultry Science, 24(4). [CrossRef]
• Bölük, G., & Mert, M. (2015). The renewable energy, growth and environmental Kuznets curve in Turkey: An ARDL approach. Renewable and Sustainable Energy Reviews, 52, 587–595. [CrossRef] Çevrimli, M. B., Akın, A. C., Mat, B., Tekindal, M. A., & Arıkan, M. S. (2019). Cointegration analysis of broiler meat and broiler feed prices in Turkey. Eurasian Journal of Veterinary Sciences, 35(4), 210–216. [CrossRef]
• Çoban, A., Çoban, O., & Coşkun, Ö. (2019). The effects on the red meats prices of feed price: The case of Turkey. In P. S. Sandhu, L. M. Cordoso & D. C. Bueno (Eds.), 16th ITALY International Conference on Economics, Education, Humanities and Social Sciences Studies (E2HS3-19) (pp. 14–17). Milan, Italy.
• Erdoğdu, H., & Çiçek, H. (2017). Modelling beef consumption in Turkey: The ARDL/bounds test approach. Turkish Journal of Veterinary and Animal Sciences, 41(2), 255–264. [CrossRef] Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3), 424–438. [CrossRef]
• Granger, C. W. J. (1980). Testing for causality. Journal of Economic Dynamics and Control, 2, 329–352. [CrossRef]
• Işık, S., & Özbuğday, F. C. (2021). The impact of agricultural input costs on food prices in Turkey: A case study. Agricultural Economics, 67(3), 101–110. [CrossRef]
• Kripfganz, S., & Schneider, D. C. (2018). ardl: Estimating autoregressive distributed lag and equilibrium correction models. In Proceedings of the 2018 London Stata conference (Vol. 9). London, UK.
• Mat, B., Arıkan, M. S., Çevrimli, M. B., Akın, A. C., & Tekindal, M. A. (2020). Causality analysis of the factors affecting the consumer price of veal: The case of Turkey. Sustainability, 12(15), 6257. [CrossRef]
• Mert, M., & Çağlar, A. E. (2019). Eviews ve Gauss uygulamalı zaman serileri analizi. Detay Yayıncılık. Musunuru, N. M. (2017). Causal relationships between grain, meat prices and exchange rates. International Journal of Food and Agricultural Economics (IJFAEC), 5(4), 1–10. [CrossRef]
• Narayan, P. K. (2004). Fiji's tourism demand: The ARDL approach to cointegration. Tourism Economics, 10(2), 193–206. [CrossRef]
• Narayan, P. K. (2005). The saving and investment nexus for China: Evidence from cointegration tests. Applied Economics, 37(17), 1979–1990. [CrossRef]
• Organization for Economic Co-operation and Development. (2021). Meat consumption. https://data.oecd.org/agroutput/meat-consumption.htm.
• Özen, D. (2019). Modeling and forecasting meat consumption per capita in Turkey. Erciyes Üniversitesi Veteriner Fakültesi Dergisi, 16(2), 122–129. [CrossRef]
• Özer, O. O. (2013). Modeling the relationship between the beef producer price and the oil prices in Turkey. Journal of Food, Agriculture and Environment, 11(3–4), 769–772.
• Özkan, U., & Şahin Demirbağ, N. (2016). Status quo of quality roughage resources in Turkey. Türkiye Bilimsel Derlemeler Dergisi, 9(1), 23–27.
• 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. [CrossRef]
• Pozo, V. F., & Schroeder, T. C. (2012). Price and volatility spillover between livestock and related commodity markets. Selected Paper prepared for presentation at the Agricultural & Applied Economics Association’s 2012 AAEA Annual Meeting, Seattle, WA.
• Tandoğan, M., & Çiçek, H. (2016). Technical performance and cost analysis of broiler production in Turkey. Brazilian Journal of Poultry Science, 18(1), 169–174. [CrossRef]
• Türkiye Yem Sanayicileri Birliği (TÜRKİYEM-BİR). (2019). Karma yem Sanayii raporu. Poyraz Ofset Matbaacılık (in Turkish). TURKSTAT. (2022). Inflation and price. https://data.tuik.gov.tr/Kategori/GetKategori?p=enflasyon-ve-fiyat-106&dil=2
• Yalçınkaya, S., & Aktaş, M. A. (2019). Yem üzerindeki Kdv Oran İndirimlerinin et Ve Süt Fiyatlarina etkisi. Öneri Dergisi, 14(51), 38–60 (in Turkish with an abstract in English).