Economic forecast is the process of making predictions about economic variables using time-series models. The goal is to develop a model that incorporates empirical regularities from historical data and a theoretical understanding of the economic processes behind those observations. The results are then used in a wide range of activities including monetary policy setting, state and local budgeting, financial management, and engineering design.
Most forecasts are geared toward predicting quarterly or annual Gross Domestic Product (GDP) growth rates, the top-level macro number on which businesses and governments base their decisions with respect to investments, hiring, spending, and other important policies that impact aggregate economic activity. Business managers rely on these numbers to make decisions about purchasing equipment and materials, as well as to plan their operating activities. Many companies employ in-house economists to focus on forecasts that are relevant to their specific business. Others rely on academic economists attached to think tanks or private consultants.
A variety of forecasting models have been developed over the years. The most sophisticated use mathematically rigorous econometric models that apply a computation to a series of inputs to generate a prediction for one or more variables. These models may be multivariate or n-variate and can incorporate either linear or nonlinear assumptions. In addition to the model-based methods, there are also a variety of judgmental techniques that rely on the expertise of individual forecasters. These include survey-based forecasts, economic base analysis, shift-share analysis and the Grinold and Kroner model.