The economic forecast is an attempt to predict future economic activity, such as real GDP growth. Many different methodologies have been developed to achieve this goal. These include statistical methods and mathematical models, such as regression analysis, and qualitative methods, such as expert judgment and surveys.
The process of preparing an economic forecast typically begins with collecting historical data on a number of variables of interest. These data can be obtained from a wide variety of sources, both print and electronic. The economist then examines the relationship between one or more of these variables and the dependent variable, typically using regression analysis. This information is then used to create a model of the relationship between the variables that can be used to make predictions about the dependent variable in future periods.
In order to improve the accuracy of the economic forecast, a number of assumptions are made. For example, the values of some of the variables will be assumed to remain at certain levels within each forecast time period. Whether these values are stated explicitly as forecast assumptions or implied by the behavior of the model depends on the particular model and the context in which it is being applied.
In addition, the economic forecaster must consider risks, events or conditions that could cause the forecast result to differ from the initial estimate. This information is often included in the commentary provided alongside the economic forecast numbers. These complexities make it difficult to predict the future with absolute accuracy, but also help explain why the quality of the economic forecast is sometimes so variable.