Uncertainty in applied macroeconomic policy analysis arises from three distinct sources. The first, often referred to as model uncertainty, arises because the models used for policy analysis are simple abstractions of the complex behavioural interactions that occur in an economy. The second source, denoted shock uncertainty, arises from unforeseen events that the analysis cannot explicitly factor in ex ante. Finally, starting-point uncertainty reflects the fact that given data lags and revisions, often it is difficult to assess the current state of the economy. This paper discusses the approach the Reserve Bank has taken to enable its Forecasting and Policy System (FPS) to quantify the implications that the typical level of shock uncertainty might be expected have on the analysis of alternative policy actions designed to achieve the objectives of monetary policy.