Comparative Forecasting of Export Quantity of Pepper via the Use of Different Statistical Methods

Abstract

The objective of this study was to forecast the export quantity of pepper via the use of different statistical methods. The monthly average data, which were gathered from the website of the Office of Agricultural Economics during January 2011 to December 2020 for 120 months were divided into 2 datasets. The first dataset, which consisted of 108 months from January 2011 to December 2019 was used for constructing the forecasting models via the use of 7 statistical methods, namely, Box-Jenkins method, Holt’s exponential smoothing method, Brown’s exponential smoothing method, damped trend exponential smoothing method, simple seasonal exponential smoothing method, Winters’ additive exponential smoothing method, and Winters’ multiplicative exponential smoothing method. The second dataset, which consisted of 12 months from January to December 2020 was used to evaluate the accuracy of the forecasting models via the use of the lowest root mean square error. The results indicated that the most accurate method was the damped trend exponential smoothing method.