The economic forecast is the effort to predict the future of an economy. A wide range of methods are used to make these predictions. Some are based on econometric models, which seek to find statistical patterns in past data to predict the future. Others are more judgmental, relying on the experience and expertise of individual forecasters to fine-tune model-based projections. The results of these two types of projections can be very different.
The most commonly forecasted indicator of economic activity is gross domestic product (or GDP), which is the monetary value of all the finished goods and services produced within an economy’s borders. A closely related concept is gross national product (or GNP), which includes the production of an economy by its residents, regardless of whether they live within its borders.
Global growth is projected to remain subdued in 2025, amid rising trade barriers and elevated policy uncertainty. Risks to the outlook are tilted to the downside, including tighter global financial conditions, a possible surge in violent conflict and social unrest, declines in official aid, and more frequent natural disasters.
In many countries and regions, GDP growth is reported on a quarter-ahead basis and is often presented as a year-over-year growth rate. This convention stems from the greater availability and accuracy of annual GDP estimates than quarterly data, and can produce some unusual effects if the model used to generate forecasts is revised as new data become available. In this article, we compare the output of a series of models that use various combinations of individual economic variables to produce forecasts of risk-factor excess returns.
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