An economic forecast is a prediction of future economic activity (e.g., real GDP growth). It involves analyzing past data and anticipating what the economy will do in the future, often by using mathematical models. This information is useful for businesses because it allows them to make more informed planning decisions that will help increase profits and lower costs.
A key question for any model of economic activity is the extent to which it captures large swings in growth. This is particularly challenging in advanced economies which have experienced a pattern of deep recessions followed by fast recoveries over the last two decades. These rapid changes have made it very difficult for linear time series models to predict future GDP growth. More recently, nonlinear models have shown some promise in capturing these swings, although there are many other challenges for them to overcome as discussed below.
Many professional economists use statistical methods that form and estimate mathematical equations to produce forecasts. The content of these equations might be suggested by general economic theory, but they are essentially statistical in nature and have become a specialty in their own right. These statistical methodologies are often referred to as macroeconometric models. They require not just knowledge of how economic variables behave, but also a great deal of acquired expertise in the representation and estimation of patterns of such behavior. These methods are also referred to as econometrics, and they have achieved a level of popularity among economists because of their replicability and technical sophistication.
About the Author
