Development of SARIMA Model to Predict Quarterly Apparel and Textile Export Revenue in Sri Lanka

Abstract

Apparel and textile exports play a significant role in the Sri Lankan economy. The USA, UK, Italy, Germany, and Belgium are the main markets of apparel and textile exports in Sri Lanka. Advanced knowledge of export revenue is vital important for various reasons. A Seasonal Autoregressive Integrated Moving Average (SARIMA) model of the type (1,1,0) x (0,1,1)4 was developed to model apparel and textile export revenue in Sri Lanka using quarterly data from year 2004 quarter 1 (2004Q1) to year 2021 quarter 4 (2021Q4). The errors of the model were found to be random and have a constant variance. The best fitted model was identified by comparing various statistical indicators, namely, the Akaike info criterion, Schwarz criterion, Hannan-Quinn criterion, Log likelihood criterion and volatility of six possible models decided based on sample ACF and PACF of the stationary series. The model was validated for data from year 2022Q1 to 2023Q1. The Mean Absolute Percentage Error (MAPE) for the training data set and validation data set were 7.68% and 11.35% respectively. The predicted revenues (Mn USD) for the 2023Q2 to 2024Q4 are 1074.23, 1263.30, 1222.22, 1206.74, 1058.38, 1265.00 and 1216.58, respectively. The forecasted values for short-term periods can be effectively used by the decision makers for various activities. The model developed is easy to use and reliable.