Modelling beef consumption in Turkey: the ARDL/bounds test approach
The study aimed to examine the short-run and long-run relationship between beef consumption and beef prices, chicken
meat prices, and per capita income for the period of 1994?2014 in Turkey by employing the ARDL/bounds test approach. After deciding
on the presence of cointegration between the related variables, a parsimonious VECM model was estimated to conduct the structural
analyses of the impulse response function and variance decomposition. The results of the bounds test suggest a long-run equilibrium
relationship between beef consumption and its selected determinants. In addition, the empirical findings indicate that chicken meat
prices and per capita income level have a positive effect on beef consumption. The results of variance decomposition reveal that the
portion of beef prices in explaining beef consumption is large, whereas chicken meat prices have decreasing impact and income level has
increasing impact on beef consumption in the long run. The results of the impulse response function are also consistent with the theory.
The findings suggest that beef consumption is sensitive to beef prices and responds negatively to a shock in beef prices.
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- GTHB. Gıda Tarım ve Hayvancılık Bakanlığı, Hayvancılık
Genel Müdürlüğü, Kırmızı et stratejisi. Ankara, 2015 (in
Turkish).
- BESD-BİR.
Beyaz Et Sanayicileri ve Damızlıkçıları Birliği
Derneği, Piliç eti sektör raporu (üretim, tüketim, dış ticaret,
sorunlar, görüşler). Ankara, 2014 (in Turkish).
- TÜİK. Türkiye İstatistik Kurumu, Kırmızı et üretimi, tarımsal
fiyat, dış ticaret, ulusal gelir istatistikleri. Ankara, 24 December
2015. Available at http://www.tuik.gov.tr/PreTabloArama.
do?metod=search&araType=vt.
- A
kbay C, Bilgiç A, Miran B. Türkiye’de önemli gıda ürünlerinin
talep esneklikleri. Tarım Ekonomisi Dergisi 2008; 14: 55-65
(article in Turkish with an English abstract).
- Bilgic A, Yen ST. Demand for meat and dairy products by
Turkish households: a bayesian censored system approach. Agr
Econ 2014; 45: 117-127.
- Armağan G, Akbay C. An econometric analysis of urban
households’ animal products consumption in Turkey. Appl
Econ 2008; 40: 2029-2036.
- Aadland D, Bailey DV, Feng S. A theoretical and empirical
investigation of the supply response in the U.S. beef-cattle
industry. Economic Research Institute Study Papers 2000; 188:
1-38.
- Sulgham A, Zapata H. A dynamic approach to estimate
theoretically consistent US meat demand system. Annual
Meeting of American Agricultural Economics Association,
2006.
- Kunova D, Bielik P. The modelling of meat consumption in
Slovakia. ŽEMĖS ŪKIO MOKSLAI 2007; 181-183.
- Antonova M, Zeller M.
A time-series analysis of the beef
supply response in Russia: implications for agricultural sector
development policies. 104th Seminar, Budapest, Hungary.
European Association of Agricultural Economists, 2007.
- Gosalamang DS, Belete A, Hlongwane JJ, Masuku M.
Econometric analysis of supply response among beef farmers
in Botswana. African Journal of Agricultural Research 2010;
Vol 7, No 31.
- Ndayitwayeko WM, Odhiambo MO, Nyangweso PM, Korir
MK. Determinants of beef meat supply in Burundi: A Vector
Error Correction Model Approach Applied to structural
Nerlov Paradigm. Eighth AFMA Congress, African Farm
Management Association (AFMA), 2012.
- Dagdemir V, Demir O, Keskin A.
Estimation of supply and
demand models for chicken meat in Turkey. J Appl Anim Res
2004; 25: 45-48.
- Hatırlı SA, Öztürk E, Aktaş AR. An analysis of demand of red
meat, fish and chicken using full demand system approach.
Süleyman Demirel Üniversitesi Sosyal Bilimler Enstitüsü
Dergisi 2007; 6: 211-221 (article in Turkish with an English
abstract).
- 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: 798-804.
- Studenmund AH.
Using Econometrics: A Practical Guide.
Boston, MA, USA: Addison-Wesley, 2001.
- Pesaran MH, Shin Y, Smith RJ. Bound testing approaches to
the analysis of level relationships. J Appl Econom 2001; 16:
289-326.
- Kirchgässner G,
Wolters
J. Introduction to Modern Time Series
Analysis. 1st ed. Berlin, Germany: Springer, 2008.
- Engle RF, Granger CWJ. Cointegration and error correction
representation: estimation and testing. Econometrica 1987; 55:
251-276.
- Johansen S. Statistical analysis of cointegrating vectors. J Econ
Dyn Control 1988; 12: 231-254.
- Johansen S. Likelihood-based Inference in Cointegrated Vector
Autoregressive Models. Oxford, UK: Oxford University Press,
1995.
- Ghatak S, Siddiki J. The use of ARDL approach in estimating
virtual exchange rate in India. J Appl Stat 2001; 28: 573-583.
- Banerjee A, Donaldo J, Galbraith J, Hendry D. Co-Integration,
Error-Correction, and the Econometric Analysis of Non-
Stationary Data. New York, NY, USA: Oxford University Press,
1993.
- Pattichis CA. Price and income elasticities of disaggregated
import demands: results from UECMs and an application.
Appl Econ 1999; 31: 1061-1071.
- Mah JS. An empirical examination of the disaggregated
import demand of Korea - the case of information technology
products. Journal of Asian Economics 2000; 11: 237-244.
- Tang TC, Nair M. A cointegration analysis of Malaysian import
demand function: reassessment form the bounds test. Appl
Econ Lett 2002; 9: 293-296.
- Brown RL, Durbin J, Evans JM. Techniques for testing the
constancy of regression relations over time. J R Stat Soc 1975;
37: 149-163.