Lockdown 2.0 In Malaysia: Evaluating Forecast Performance of Goods Export with Box-Jenkins Methodology and ARIMA Model

Abstract

The purpose of this study is to model the forecast of Malaysia's export of goods using Autoregressive Integrated Moving Average Model (ARIMA) modelling with Box-Jenkins method. The time-series concerned is from the first quarter of 2015 to the first quarter of 2021 based on the Department of Statistics Malaysia (DOSM) data. The empirical analysis focuses on the five criteria for consideration towards the best model: high significant coefficient, high adjusted R-squared value, low sigma squared value, low Akaike Information Criterion (AIC) and low Schwarz Information Criterion (SIC). The study showed that ARIMA (2,1,2) would be the best model to forecast Malaysian export of goods from the second quarter of 2021 to the fourth quarter of 2022. The quarterly forecast opined the performance rate of Malaysian goods export to be at a stable positive rate of 4.9% throughout 2022, indicating the economic recovery progress that Malaysia would acquire from its vaccination programme and Movement Control Order (MCO) done in the previous year. The annual forecast showed a more precise value after comparing the actual and forecast growth value of exports in 2021. This finding is further supported with qualitative analysis about the validity of the forecast values via reports released by sources such as World Bank and Focus Economics.