Forecasting the Index of Industrial Production of Sri Lanka

Developing countries are required to continuously monitor and forecast the industrial output. However, there are few studies to the date that have analyzed the Index of Industrial Production (IIP) of Sri Lanka. This study aims to fill this gap by determining the best fit for forecasting future values of the IIP in Sri Lanka. Utilizing 93 observations from January 2016 to September 2023, it employed time series and deep learning techniques to predict IIP data, assessing their accuracy and reliability in capturing the underlying trends and seasonal patterns. The models are evaluated using standard statistical metrics such as the Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) to determine the best fit for forecasting future values of the IIP.