Modelling Uncertainty: An Application to Forecasting International Reserves

Abstract

Being able to accurately predict international reserves is an extremely important task for pegged exchange rate economies. Barbados’ 1992 experience with vanishing reserves has left its mark on the economy, being brought to mind most recently when reserve levels began to slide sharply in 2013. However, forecasting remains an approximate science and it has become increasingly important to recognize and capture the uncertainties involved in model-based forecasting. This paper attempts to capture parameter uncertainty, model selection uncertainty, and future uncertainty by employing a combination of regression ensembles, randomized model selection, linear opinion pooling and equal or RMSE weights. The importance of density forecasting in predicting international reserves is displayed by using the 2013 unexpected and unexplained decline in net international reserves as the out-of-sample test. This paper agrees with the proposal that density forecasting should be employed to provide policy makers with greater information describing the various uncertainties in economic forecasting. Notably, being able to understand the uncertainty of forecasting international reserves would have provided policymakers with a head start in dealing with declining reserves in 2013.