Economic forecast is the process of estimating future economic variables such as unemployment, GDP or inflation. Forecasts are important to businesses as they can help make informed decisions about purchasing equipment or resources to increase sales. Forecasts are based on a variety of data inputs and use a range of models to predict future trends, including historical patterns and data revisions. Economic forecasts include both judgmental approaches that rely on the expertise of the individual forecaster and dynamic stochastic general equilibrium (DSGE) models that utilize modern economic theory to produce a forecast disciplined by economic theory.
The forecasting industry has a long history of research and development. The early work was aimed at understanding the nature of economic fluctuations, and the resulting methodologies have progressively advanced to incorporate the knowledge gained from those experiences into more sophisticated forecasting models. In addition, research has been focused on improving the communication of economic forecasts. This includes the use of graphical representations and commentary to help interpret the results.
As a result, the forecasting industry has a long list of cutting-edge time series models and methods. Examples of these techniques include factor models, mixed frequency models, non-linear models and forecast combinations. Some of these models are more applicable to certain forecasting horizons than others, but all are continually being improved as new developments emerge. Many of these innovations are aimed at reducing the impact of data revisions on the forecasts, with the hope of delivering more accurate forecasts.
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