An economic forecast is an estimate of future economic trends, including real GDP growth, inflation and unemployment rates. In addition to assisting government policy-makers in setting interest rate levels, these predictions help companies make business plans and investment decisions. Economic trends are influenced by various factors, such as global events and political instability, that can cause them to fluctuate, necessitating adjustment in forecasts.
Using a variety of tools, analysts can better prepare and mitigate major economic risks by understanding how different influences affect market movements. This holistic approach enables forecasters to develop more accurate economic forecasts that are based on a full range of information.
Quantitative forecasting relies on models that use historical data inputs to perform calculations and generate predictions of one or more variables. Examples of quantitative models include econometric analysis, regression analysis and computational general equilibrium models.
While models provide an excellent basis for economic forecasts, they can also introduce errors due to human judgment. Historically, estimating uncertainty was pure judgment; however, scientists are now developing numerical measurements to incorporate into forecast models. McCracken explained that a model might predict a certain level of unemployment, but a person might believe the number will be higher because they have insight into an unmeasured factor.
The state of the business cycle can also influence forecasts, especially during periods of transition. For example, unemployment tends to be harder to forecast when the economy is shifting toward a recession because it becomes more volatile and less “sticky” than other indicators.