Forecasting of Apricot Production of Turkey by Using Box-Jenkins Method

Year 2018, Volume: 02 Issue: 2, 20 - 26, 31.12.2018

Bakiye Kılıç Topuz Mehmet Bozoğlu Uğur Başer Nevra Alhas Eroğlu

https://doi.org/10.34110/forecasting.482914

Cited By: 7

Abstract

Turkey is the first largest apricot
producer in the world. In 2016, Turkey was responsible for 9,21% of world
apricot production with 730 thousand tons. Turkey also generated 11,31% of
world apricot exports in 2016. The main aim of this research was to forecast
apricot production of Turkey for the period of 2017-2022. The data of this
study was obtained from the database of the Food and Agriculture Organization
and the time series covered the period of 1961-2016. Box-Jenkins Model was used
to forecast apricot production. In the study, it was determined that the time
series were not stationary and the series became stationary after the first
difference was taken. Moving Average Model ARIMA (2, 1, 1) was determined as
the most appropriate model for the stationary data type. The research results
show that apricot production quantities of Turkey in 2017 was forecasted as
minimum 383.206 tons, maximum 920.409 tons and, average 651.808 tons. However,
Turkey’s the apricot production amount in 2022 was forecasted as minimum 271.734
tons, maximum 1.193.113 tones and average 732.423 tons. Considering the
increase in demand, it is thought that apricot production will not be
sufficient for the country. To protect the current leading position of the
country, it is recommended that the government should give enough support to
increase apricot production in Turkey.

Keywords

Apricot production, Time Series Analysis, ARIMA, Box-Jenkins, Turkey

References

• [1] FAO, 2018. Food and Agricultural Organization, http://www.fao.org/faostat/en/#data/PP (Accessed: 27.09.2018) [2] TURKSTAT, 2018. Turkish Statistical Institute, https://biruni.tuik.gov.tr/medas/?kn=92&locale=tr (Accessed: 01.10.2018). [3] İ. Fidan, Economic Analyses of Apricot Production in Igdir Province, Ataturk University, Graduate School of Natural and Applied Sciences, Department of Agricultural Economics, Master Thesis (2009). [4] Y. E. Ertürk, K. Karadaş, M. K. Geçer, Production and Marketing of Apricot in Igdir Province, VII. Bahçe Ürünlerinde Muhafaza ve Pazarlama Sempozyumu, 04-07 October, (2016).pp. 44-49. [5] A. Aslan, The Comparative Economic Analysis of Organic and Conventional Apricot Farms in Malatya Province, Kahramanmaraş Sütçü İmam University, Department of Agricultural Economics, Master Thesis. (2013). [6] O. Gunduz, V. Ceyhan, E. Erol, F. Ozkaraman, An Evaluation of farm Level Sustainability of Apricot Farms in Malatya Province of Turkey, Journal of Food, Agriculture & Environment Vol.9, no, 1, (2011), pp. 700-705. [7] O. Gunduz, Effect of Exchange Rate on Dried Apricot Export in Turkey: A Vector Autoregression (VAR) Analysis, African Journal of Agricultural Research, vol. 5, no, 18, (2010), pp. 2485-2490. [8] O. Gunduz, V. Ceyhan, K. Esengun, Measuring The Technical and Economic Efficiencies of The Dry Apricot Farms in Turkey, Journal of Food, Agriculture & Environment, vol.9, no, 1, (2011), pp. 319-324. [9] M. Karahan, Statistical Demand Forecasting Methods: An Application of Product Demand Forecast With Artificial Neural Networks Method, Selcuk University, PhD thesis, (2011). [10] İ. Dellal, A.A. Koç, An Econometric Analysis of Apricot Supply and Export and Demand in Turkey, Turkey Journal of Agriculture and Forestry, vol. 27, (2003), pp. 313-321. [11] C. Chatfield, “The Analysis of Time Series: An Introduction”, Boca Raton, FL: CRC Press, (2003). [12] G. E. P., Box, G. M., Jenkins, and G. C. Reinsel, “Time Series Analysis: Forecasting and Control”, San Francisco, CA: Holden-Day, (1970). [13] E. Erdogdu, “Natural Gas Demand in Turkey”. Appl. Energy, vol. 87, (2010), pp. 211–219. [14] B. L., Bowerman, T. O. C., Richard, and A. B. Koehler, “Forecasting, Time Series, and Regression: An Applied Approach”. Belmont, CA: Thomson Brooks/Cole, (2005). [15] A., Zaharim, A. M., Razali, T. P., Gim, and K. Sopian, Time Series Analysis of Solar Radiation Data in The Tropics, Euro. J. Sci. Res. 25, (2009), pp. 672–678. [16] D. A., Dickey, W. A. Fuller, “Likelihood Ratio Statistics For Autoregressive Time Series With A Unit Root”, Econometrica, vol. 49, no. 4, (1981), pp. 1057-1072.