Modeling and Forecasting Meat Consumption per Capita in Turkey

Doğukan Özen

doi:10.32707/ercivet.595626

Research Article

Modeling and Forecasting Meat Consumption per Capita in Turkey

Year 2019, Volume: 16 Issue: 2, 122 - 129, 08.08.2019

Doğukan Özen

https://doi.org/10.32707/ercivet.595626

Cited By: 5

Abstract

The objective of this study is to model the per capita consumption of red meat in Turkey employing various time series methods, evaluate the forecasting capability of the developed models, and address the variables that may affect the per capital consumption of red meat using the cointegration method on a term basis (short/long). The material of the study consists of the per capita consumption of red meat, total annual population, feed prices, gross domestic product and share of agriculture in gross domestic product in Turkey between 1993 and 2017. ARIMA (0,1,0) and Brown's exponential smoothing method were employed to model the time series data for per capita consumption of red meat, and Johansen method was used to address the cointegration relationship between per capita consumption of red meat and the other variables. The results of the modelling work suggest that per capita consumption of red meat has an increasing trend. Additionally, a statistically significant short-term relationship was found between per capita consumption of red meat and the other variables. Given the relationship between consumption of red meat and level of economic development, the projections concerning red meat consumption are important from the viewpoint of the policies that will be formulated.

References

1. Akbay C, Bilgiç A, Miran B. Demand estimation for basic food products in Turkey. Turkish J Agri Econ 2008; 14(2): 55-65.
2. Akın AC, Arıkan MS, Çevrimli MB. Effect of import decisions in Turkey between 2010-2017 on the red meat sector. 1st International Health Sciences and Life Congress. 2-5 May 2018; Burdur, Turkey.
3. Armağan G, Akbay C. An econometric analysis of urban households’ animal products consumption in Turkey. Appl Econ 2008; 40(15): 2029-36.
4. Bilgic A, Yen ST. Demand for meat and dairy products by Turkish households: a bayesian censored system approach. Agr Econ 2014; 45(2): 117-27.
5. Box GEP, Jenkins GM, Reinsel GC, Ljung GM. Time series analysis: forecasting and control. USA: Holden Day Inc, 2015; p:47.
6. Box GEP, Pierce DA. Distribution of residual autocorrelations in autoregrresive integrated moving average time series models. J Am Stat Assoc 1970; 65(332): 1509-26.
7. Brockwell P, Davis R. Introduction to Time Series and Forecasting. 2nd. Ed., Springer, 2002; p:179.
8. Cenan N, Gurcan IS. Türkiye çiftlik hayvan sayılarının ileriye yönelik projeksiyonu: ARIMA modellemesi. Vet Hekim Der Derg 2014; 82(1): 35-42.
9. Dagdemir V, Demir O, Keskin A. Estimation of supply and demand models for chicken meat in Turkey. J Appl Anim Res 2004; 25(1): 45-48.
10. Duy TA, Thoma MA. Modelling and forecasting cointegrated variables: some practical experience. J Bus Econ Stat 1998; 50(3): 291-307.
11. Engle RF, Yoo BS. Forecasting and testing in cointegrated systems. J Econom 1987; 35(1): 143-59.
12. Engle RF, Granger CWJ, Hallman JJ. Merging short and long-run forecasts: an application of seasonal cointegrating to monthly electricity sales foreacasting. J Econom 1989; 40(1): 45-62.
13. Fanchon P, Wendel J. Estimating VAR models under non-stationarity and cointegration: alternative approaches for forecasting cattle prices. Appl Econ 1992; 24(2):107-217.
14. Faostat. Food and Agricultural Organization. http://faostat.fao.org; Access Date: 12.09.2018.
15. Hall DA, Anderson HM, Granger, CWJ. A cointegration analysis of treasury bill yields. Rev Econ Stat 1992; 74(1): 116-26.
16. Hatırlı SA, Öztürk E, Aktaş AR. An analysis of demand of red meat, sheep and chicken using full demand system approach. J Suleyman Demirel Uni Inst Soc Sci 2007; 6(2): 211-21.
17. Hoffman DL, Rasche RH. Assessing forecasting performance in a cointegrated system. J Appl Econom 1996; 11: 495-517.
18. Johansen S, Juselius K. Maximum likelihood estimation and inference on cointegration with applications to the demand for money. Oxford B Econ Stat 1990; 52(2): 169-210.
19. OECD. Meat consumption indicator. https://data.oecd.org/agroutput/meat-consumption.htm; Access Date: 15 December 2018.
20. Pensel NA. The future of red meat in human diet: outlook on agriculture. Int Cent Agricult Biosci 1997; 26: 159-64.
21. Sacli Y, Özer OO. Analysis of factors affecting red meat and chicken meat consumption in Turkey using an ideal demand system model. Pak J Agr Sci 2017; 54: 933-42.
22. Sevükteki̇n M, Nargeleçekenler M. Ekonometrik Zaman Serileri Analizi. Ankara: Nobel Yayınevi, 2007; p.397.
23. TURKSTAT. Turkish Statistical Institute, Agricultural statistics database. http://www.tuik.gov.tr; Access Date: 22.09.2018.
24. Uzunöz M, Karakaş G. Socio-economic determinants of red meat consumption in Turkey: A case study. Çankırı Karatekin Univ J Instit Soc Sci 2014; 5(1): 037-052.
25. Yavuz F, Zulauf RC. Introducing a new approach to estimating red meat production in Turkey. Turk J Vet Anim Sci 2004; 28(4): 641-8.
26. Yavuz F, Bilgic A, Terin M, Guler IO. Policy implications of trends in Turkey’s meat sector with respect to 2023 vision. Meat Sci 2013; 95(4): 798-804.
27. Yaylak E, Taşkın T, Koyunbenbe N, Konca Y. A study on determination of red meat consumption behaviours in Ödemiş, İzmir. Agric Prod 2010; 5(1): 21-30.
28.YEM-BİR. Türkiye Yem Sanayicileri Birliği, Access: http://www.yem.org.tr/, Accessed on: 18.10.2018.

Türkiye’de Kişi Başına Düşen Et Tüketiminin Modellenmesi ve Geleceğe Yönelik Tahmini

Year 2019, Volume: 16 Issue: 2, 122 - 129, 08.08.2019

Doğukan Özen

https://doi.org/10.32707/ercivet.595626

Cited By: 5

Abstract

Bu araştırmanın amacı Türkiye’de kişi başına düşen kırmızı et tüketiminin çeşitli zaman serisi yöntemleri ile modellenmesi, oluşturulan modellerin öngörü yeteneğinin değerlendirilmesi ve kişi başına düşen kırmızı et tüketim miktarına etki edebilecek değişkenlerin dönemsel bazda (kısa-uzun) kointegrasyon yöntemi ile incelenmesidir. Çalışmanın materyalini 1993-2017 yılları arasında Türkiye’de kişi başına düşen kırmızı et tüketimi, yıllık toplam nüfus, besi yemi fiyatları, gayri safi yurtiçi hasıladan tarım ve hayvancılık sektörünün payı ve toplam gayrisafi yurt içi hasıla bilgileri oluşturmaktadır. Kişi başına düşen kırmızı et tüketimi serisinin modellenmesi için ARIMA (0,1,0) ve Brown üstel düzgünleştirme yöntemleri kullanılmış olup, kişi başına düşen kırmızı et tüketimi ile elde edilen diğer değişkenler arasındaki koentegre ilişki Johansen yöntemi ile incelenmiştir. Modelleme sonuçlarına göre kişi başına düşen kırmızı et tüketiminde artan bir trend öngörülmektedir. Ayrıca kişi başına kırmız et tüketimi ile elde edilen tüm değişkenler arasında istatistiksel açıdan anlamlı kısa dönemli bir ilişki bulunmuştur. Kırmızı et tüketiminin ekonomik gelişmişlik ile olan ilişkisi düşünüldüğünde yapılan projeksiyonların, oluşturulacak politikalar açısından önemli olduğu düşünülmektedir.

Keywords

ARIMA, kırmızı et tüketimi, modelleme, zaman serisi

References

1. Akbay C, Bilgiç A, Miran B. Demand estimation for basic food products in Turkey. Turkish J Agri Econ 2008; 14(2): 55-65.
2. Akın AC, Arıkan MS, Çevrimli MB. Effect of import decisions in Turkey between 2010-2017 on the red meat sector. 1st International Health Sciences and Life Congress. 2-5 May 2018; Burdur, Turkey.
3. Armağan G, Akbay C. An econometric analysis of urban households’ animal products consumption in Turkey. Appl Econ 2008; 40(15): 2029-36.
4. Bilgic A, Yen ST. Demand for meat and dairy products by Turkish households: a bayesian censored system approach. Agr Econ 2014; 45(2): 117-27.
5. Box GEP, Jenkins GM, Reinsel GC, Ljung GM. Time series analysis: forecasting and control. USA: Holden Day Inc, 2015; p:47.
6. Box GEP, Pierce DA. Distribution of residual autocorrelations in autoregrresive integrated moving average time series models. J Am Stat Assoc 1970; 65(332): 1509-26.
7. Brockwell P, Davis R. Introduction to Time Series and Forecasting. 2nd. Ed., Springer, 2002; p:179.
8. Cenan N, Gurcan IS. Türkiye çiftlik hayvan sayılarının ileriye yönelik projeksiyonu: ARIMA modellemesi. Vet Hekim Der Derg 2014; 82(1): 35-42.
9. Dagdemir V, Demir O, Keskin A. Estimation of supply and demand models for chicken meat in Turkey. J Appl Anim Res 2004; 25(1): 45-48.
10. Duy TA, Thoma MA. Modelling and forecasting cointegrated variables: some practical experience. J Bus Econ Stat 1998; 50(3): 291-307.
11. Engle RF, Yoo BS. Forecasting and testing in cointegrated systems. J Econom 1987; 35(1): 143-59.
12. Engle RF, Granger CWJ, Hallman JJ. Merging short and long-run forecasts: an application of seasonal cointegrating to monthly electricity sales foreacasting. J Econom 1989; 40(1): 45-62.
13. Fanchon P, Wendel J. Estimating VAR models under non-stationarity and cointegration: alternative approaches for forecasting cattle prices. Appl Econ 1992; 24(2):107-217.
14. Faostat. Food and Agricultural Organization. http://faostat.fao.org; Access Date: 12.09.2018.
15. Hall DA, Anderson HM, Granger, CWJ. A cointegration analysis of treasury bill yields. Rev Econ Stat 1992; 74(1): 116-26.
16. Hatırlı SA, Öztürk E, Aktaş AR. An analysis of demand of red meat, sheep and chicken using full demand system approach. J Suleyman Demirel Uni Inst Soc Sci 2007; 6(2): 211-21.
17. Hoffman DL, Rasche RH. Assessing forecasting performance in a cointegrated system. J Appl Econom 1996; 11: 495-517.
18. Johansen S, Juselius K. Maximum likelihood estimation and inference on cointegration with applications to the demand for money. Oxford B Econ Stat 1990; 52(2): 169-210.
19. OECD. Meat consumption indicator. https://data.oecd.org/agroutput/meat-consumption.htm; Access Date: 15 December 2018.
20. Pensel NA. The future of red meat in human diet: outlook on agriculture. Int Cent Agricult Biosci 1997; 26: 159-64.
21. Sacli Y, Özer OO. Analysis of factors affecting red meat and chicken meat consumption in Turkey using an ideal demand system model. Pak J Agr Sci 2017; 54: 933-42.
22. Sevükteki̇n M, Nargeleçekenler M. Ekonometrik Zaman Serileri Analizi. Ankara: Nobel Yayınevi, 2007; p.397.
23. TURKSTAT. Turkish Statistical Institute, Agricultural statistics database. http://www.tuik.gov.tr; Access Date: 22.09.2018.
24. Uzunöz M, Karakaş G. Socio-economic determinants of red meat consumption in Turkey: A case study. Çankırı Karatekin Univ J Instit Soc Sci 2014; 5(1): 037-052.
25. Yavuz F, Zulauf RC. Introducing a new approach to estimating red meat production in Turkey. Turk J Vet Anim Sci 2004; 28(4): 641-8.
26. Yavuz F, Bilgic A, Terin M, Guler IO. Policy implications of trends in Turkey’s meat sector with respect to 2023 vision. Meat Sci 2013; 95(4): 798-804.
27. Yaylak E, Taşkın T, Koyunbenbe N, Konca Y. A study on determination of red meat consumption behaviours in Ödemiş, İzmir. Agric Prod 2010; 5(1): 21-30.
28.YEM-BİR. Türkiye Yem Sanayicileri Birliği, Access: http://www.yem.org.tr/, Accessed on: 18.10.2018.

There are 28 citations in total.

Details

Primary Language	English
Journal Section	Articles
Authors	Doğukan Özen 0000-0003-1943-2690
Publication Date	August 8, 2019
Submission Date	February 28, 2019
Acceptance Date	May 30, 2019
Published in Issue	Year 2019 Volume: 16 Issue: 2

Cite

APA	Özen, D. (2019). Modeling and Forecasting Meat Consumption per Capita in Turkey. Erciyes Üniversitesi Veteriner Fakültesi Dergisi, 16(2), 122-129. https://doi.org/10.32707/ercivet.595626
AMA	Özen D. Modeling and Forecasting Meat Consumption per Capita in Turkey. Erciyes Üniv Vet Fak Derg. August 2019;16(2):122-129. doi:10.32707/ercivet.595626
Chicago	Özen, Doğukan. “Modeling and Forecasting Meat Consumption Per Capita in Turkey”. Erciyes Üniversitesi Veteriner Fakültesi Dergisi 16, no. 2 (August 2019): 122-29. https://doi.org/10.32707/ercivet.595626.
EndNote	Özen D (August 1, 2019) Modeling and Forecasting Meat Consumption per Capita in Turkey. Erciyes Üniversitesi Veteriner Fakültesi Dergisi 16 2 122–129.
IEEE	D. Özen, “Modeling and Forecasting Meat Consumption per Capita in Turkey”, Erciyes Üniv Vet Fak Derg, vol. 16, no. 2, pp. 122–129, 2019, doi: 10.32707/ercivet.595626.
ISNAD	Özen, Doğukan. “Modeling and Forecasting Meat Consumption Per Capita in Turkey”. Erciyes Üniversitesi Veteriner Fakültesi Dergisi 16/2 (August 2019), 122-129. https://doi.org/10.32707/ercivet.595626.
JAMA	Özen D. Modeling and Forecasting Meat Consumption per Capita in Turkey. Erciyes Üniv Vet Fak Derg. 2019;16:122–129.
MLA	Özen, Doğukan. “Modeling and Forecasting Meat Consumption Per Capita in Turkey”. Erciyes Üniversitesi Veteriner Fakültesi Dergisi, vol. 16, no. 2, 2019, pp. 122-9, doi:10.32707/ercivet.595626.
Vancouver	Özen D. Modeling and Forecasting Meat Consumption per Capita in Turkey. Erciyes Üniv Vet Fak Derg. 2019;16(2):122-9.