Author Description

This paper describes the recent work to strengthen the nowcasting capacity at the Central Bank of Samoa (CBS). It compiles available high-frequency datasets such as tourism receipts, agriculture market survey, remittances, among others, to nowcast real GDP in Samoa. Nowcasting enables the estimation of the present and near-term forecast. It employs standard nowcasting methods such as Bridge, Mixed Data Sampling (MIDAS), and Unrestricted MIDAS (U-MIDAS). All methods significantly outperform the naive forecasts. Our analysis show that forecast combination of the three methods minimizes the root mean squared error (RMSE) for both full and pre-COVID-19 samples, while U-MIDAS performs better during crises, particularly in identifying turning points during the COVID-19 pandemic. Strengthening nowcasting capacity is important for Samoa, where real GDP data release experiences up to a 90-day lag.