Analysis of Price Behavior in Sri Lankan Vegetable Market

Q2 Business, Management and Accounting
Jayamini Champika, A. Mugera
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引用次数: 0

Abstract

Vegetables are important source of nutrient for the Sri Lankan population and both farmers and consumers are adversely affected by vegetable price volatility. The lack of price analysis and forecasting has made it difficult to establish an effective early warning system for the vegetable farming sector in Sri Lanka. This study investigates the price behaviour of selected fresh vegetables - carrot, cabbage, and tomato - and forecasts the future prices and volatilities using time series techniques. Analysis of weekly price data from 1997 to 2018 revealed that all three - price series had one structural break, but none coincided with the policy change when the government introduced fertilizer subsidies for vegetable producers in the agriculture sector. The autoregressive integrated moving average (ARIMA) model estimations show that the best model for forecasting carrot price is ARIMA (3,1,2) (0,0,2)[52]* capable of predicting retail prices at 71% accuracy while the best model for cabbage prices is ARIMA(1,1,1)(0,0,1)[52] with a prediction accuracy of 55%. All three-price series exhibit serial correlation in residuals; hence GARCH estimations were used to model and predict volatility. Of the fitted ARMA GARCH models, the best model for estimating the volatility of carrot and cabbage were GARCH (1, 2) ARMA (3, 2) and GARCH (1,1) ARMA (3 ,2), respectively. The volatility predictions for the first ten weeks for the year 2019 indicate a gradual decrease in volatility in the carrot price series whilst a gradual increase in volatility in the cabbage price series.
斯里兰卡蔬菜市场价格行为分析
蔬菜是斯里兰卡人口的重要营养来源,农民和消费者都受到蔬菜价格波动的不利影响。由于缺乏价格分析和预测,很难为斯里兰卡的蔬菜种植部门建立有效的预警系统。本研究调查了选定的新鲜蔬菜——胡萝卜、卷心菜和西红柿的价格行为,并使用时间序列技术预测了未来的价格和波动性。对1997年至2018年每周价格数据的分析显示,所有三个价格序列都有一个结构性突破,但都与政府向农业部门的蔬菜生产者提供肥料补贴时的政策变化不一致。自回归综合移动平均(ARIMA)模型估计表明,预测胡萝卜价格的最佳模型是ARIMA(3,1,2)(0,0,2)[52]*,能够预测零售价格的准确率为71%,而预测卷心菜价格的最佳模型是ARIMA(1,1,1)(0,0,1)[52],预测准确率为55%。三个价格序列在残差上均表现为序列相关;因此,GARCH估计用于建模和预测波动率。在拟合的ARMA - GARCH模型中,对胡萝卜和卷心菜的波动率估计最好的模型分别是GARCH (1,2) ARMA(3,2)和GARCH (1,1) ARMA(3,2)。2019年前十周的波动率预测表明,胡萝卜价格系列的波动率逐渐下降,而卷心菜价格系列的波动率逐渐上升。
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来源期刊
Journal of International Food and Agribusiness Marketing
Journal of International Food and Agribusiness Marketing Business, Management and Accounting-Business and International Management
CiteScore
4.90
自引率
0.00%
发文量
28
期刊介绍: The Journal of International Food & Agribusiness Marketing is a timely journal that serves as a forum for the exchange and dissemination of food and agribusiness marketing knowledge and experiences on an international scale. Designed to study the characteristics and workings of food and agribusiness marketing systems around the world, the journal critically examines marketing issues in the total food business chain prevailing in different parts of the globe by using a systems and cross-cultural/national approach to explain the many facets of food marketing in a range of socioeconomic and political systems.
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