Forecasting agricultural exports and imports in South Africa

Abstract

The implementation of wide-ranging policy reforms, including trade and exchange rate policies, is improving the efficiency of the South African economy and its reintegration into the global economy with rapid export expansion. Agricultural exports in the Southern African Customs Union increased from R8.14 billion in 1995 to R23.0 billion in 2003, whilst agricultural imports rose from R6.83 billion to R13.84 billion during the same period. This article uses alternative approaches to forecasting agricultural exports and imports in South Africa. The models used include: exponential smoothing, autoregressive integrated moving average (ARIMA), vector autoregression (VAR), Engle–Granger (EG) single-equation and vector error-correction models (VECM). We found that the ARIMA and EG methods outperform the VAR and VECM according to Theil's U-statistic. The VAR outperforms the VECM in forecasting agricultural exports in South Africa. The combined forecasts have a lower variance compared to individual forecasts, thereby, reducing the risks of making wrong decisions based on the forecasts. The article provides empirical evidence that is beneficial to policymakers and business leaders in South Africa as they strive to reduce poverty and inequality and increase economic growth.