Nowcasting South African GDP using a suite of statistical models
Byron Botha, Geordie Reid, Tim Olds, Daan Steenkamp and Rossouw van Jaarsveld
Last Modified Date:
2022-02-16, 12:28 PM
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Given lags in the release of data, a central bank must ‘nowcast’ current GDP using available quarterly or higher frequency data to understand the current state of economic activity. This paper uses various statistical modelling techniques to draw on a large number of series to nowcast South African GDP. We also show that GDP volatility has increased markedly over the last 5 years, making GDP forecasting more difficult. We show that all the models developed, as well as the Reserve Bank’s official forecasts, have tended to over-estimate GDP growth over this period. However, several of the statistical nowcasting models we present in this paper provide competitive nowcasts relative to the official Reserve Bank and market analysts’ nowcasts. We also demonstrate the usefulness of statistical models in quantifying forecast uncertainty and interpreting data surprises.