ABSTRACT
Nowcasting, a combination of “now” and “forecast”, is the estimation of a target variable's current state, or a close approximation of it, either forwards or backwards in time, utilizing information that is available in a more timely manner. It has a wide range of applications, all of which attempt to supplement and assist users' decisions. This research applied auto-regressive moving average, neural network models, and support vector regression technique for modelling and nowcasting selected imports and exports in Bangladesh considering annual data from 1976–2020. The findings revealed that support vector models had superior performance compared to the other models considered in this study. In economic growth modelling and nowcasting purpose, the author recommends using the machine learning methodologies. It also suggests that the results be compared to classic econometric and time series models considering other variables with longer data periods.
