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Modelling and Forecasting of Tea Production, Consumption and Export in Bangladesh

Modelling and Forecasting of Tea Production, Consumption and Export in Bangladesh

Original Research ArticleAug 2, 2021Vol. 22 No. 2 (2022) 10.55003/cast.2022.02.22.009

Abstract

Bangladesh is the world’s 9th largest tea producer and the tea industry is a major contributor to the country’s economy.   In order to provide information about the demand, supply and foreign trade of tea in the future, forecasting plays a vital role in adjusting the gaps and formulating policy. Taking all of this into account, this study aims at modelling and forecasting tea production, consumption and export in Bangladesh using ARIMA modelling for the period of 2019 to 2028. Forty-seven years of time-series data from 1972 to 2018 were obtained from the Bangladesh Tea Board. Forecasts were computed on the basis of models that were selected using three important information criteria such as Akaike's Information Criterion (AIC), Schwarz's Bayesian Information Criterion (BIC) and Correction for Akaike's Information Criterion (AIC). The study identified that the best-fitting models were ARIMA (0, 1, 0), ARIMA (0, 2, 2) and ARIMA (1, 1, 2) for tea production, consumption and export, respectively. Forecasting showed an upward trend for tea production from 83.40 to 94.88 million kg and consumption from 94.35 to 131.71 million kg over the period of 2019 to 2028. On the contrary, the forecast for tea exports shows a decreasing trend. Such forecast results indicate that the government should immediately take action to accelerate the growth of the tea industry in Bangladesh. Otherwise, the economic development of the country will be hampered by reduced export earnings while relying on imports to meet the domestic demand.

Keywords: tea production; tea consumption; tea export; ARIMA Model; forecasting; Bangladesh

 

*Corresponding author: Tel.: +88(02)920531-14 (Ext- 2414)

                                             Fax: +88(02)9205333

                                             E-mail: anlaboni@bsmrau.edu.bd

 

References

1
Rahman, A., 2017. Modeling of tea production in Bangladesh using Autoregressive Integrated Moving Average (ARIMA) Model. Journal of Applied & Computational Mathematics, 6(2), 349-357.
2
Hossain, M.M. and Abdulla, F., 2015. Forecasting the tea production of Bangladesh: Application of ARIMA model. Jordan Journal of Mathematics and Statistics, 8(3), 257-270.
3
Nasir, T. and Shamsuddoha, M., 2011. Tea productions, consumptions and exports: Bangladesh perspective. International Journal of Educational Research and Technology, 2(1), 68-73.
4
Wang, H., Wen, Y., Du, Y., Yan, X., Guo, H., Rycroft, J., Boon, N., Kovas, E. and Mela, D., 2010. Effects of catechin enriched green tea on body composition. Obesity, 18, 773-79.
5
Dhekale, B.S., Sahu, P.K., Vishwajith, K.P., Mishra, P. and Noman, M., 2014. Modelling and forecasting of tea production in West Bengal. Journal of Crop and Weed, 10, 94-103.

Author Information

Richard J. Culas

Department of Agribusiness, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur-1706, Bangladesh

Richard J. Culas

Department of Statistics, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur-1706, Bangladesh

Richard J. Culas

Department of Agribusiness, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur-1706, Bangladesh

Richard J. Culas

Department of Agribusiness, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur-1706, Bangladesh

Richard J. Culas

Department of Agribusiness, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur-1706, Bangladesh

Richard J. Culas

School of Agricultural and Wine Sciences & Institute for Land Water and Society, Charles Sturt University, Orange NSW 2800, Australia

About this Article

Current Journal

Vol. 22 No. 2 (2022)

Type of Manuscript

Original Research Article

Keywords

tea production;
tea consumption;
tea export;
ARIMA Model;
forecasting;
Bangladesh

Published

2 August 2021

DOI

10.55003/cast.2022.02.22.009

Current Journal

Journal Cover
Vol. 22 No. 2 (2022)

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