Abstract:
The apparel industry in Sri Lanka contributes predominantly to the country’s
economy. Therefore, it is crucial for policymakers and other stakeholders to
know about the apparel and textile export behavior to make informed decisions.
Thus, the main aim of this study was to model and forecast Sri Lankan apparel
and textile exports using the data for the period of January 2007 to December
2022 and provide accurate forecasts. ARIMA model was employed for the
univariate time series analysis with modelling and forecasting. Among the
candidate models, ARIMA (1,1,1) (2,0,0)12 was the best-fitted model based on the
information criteria: AIC, AICc and BIC. Then, the model adequacy checking of the
selected model was done using residual diagnostic graphs, the portmanteau test,
the Ljung-Box test, and the characteristic roots of the model, which found that
the model was adequate for forecasting. Subsequently, the forecasts were
generated for two years ahead, and the forecast accuracy was checked with
metrics such as MAPE, RMSE and MAE. The best-fitted model was found to have
an average prediction error of 11.77%, while RMSE and MAE were 78.57 and
59.92, respectively. Further, an analysis of the major fluctuations of the time
series during the period of study was done, and it was found that despite the
inevitable adverse impact of the COVID-19 pandemic in its initial phase, the
apparel sector swiftly adapted and showed a significant improvement in export
earnings during the post-COVID period.
