An economic forecast provides insight into the economy’s future, so businesses can make informed decisions. A business might use a forecast to decide whether to hire extra workers or buy new equipment. Government officials also rely on economic forecasts when crafting and implementing fiscal and monetary policies.
Creating an economic forecast involves two key components: data and a model. Data includes information about a number of variables that are likely to impact the economy, including GDP growth, inflation and unemployment rates. Then, a model is used to calculate the expected outcome of each variable in a specified time frame. Common models include econometric models and computational general equilibrium models.
The models that are used in economic forecasts can be complex, and many economists are trained in the application of statistics and econometric techniques. However, the complexity of these models does not necessarily guarantee that forecasts will be accurate. In fact, research has shown that even expert forecasters are subject to a range of biases and limitations.
For example, financial series like stock market prices can be difficult to forecast over short horizons because they are volatile. In contrast, interest rates are more predictable over short horizons because they tend to be fairly “sticky.” Thus, an expert can predict the direction of interest rates with a higher degree of accuracy than they can the direction of stock market prices. For this reason, it is important for experts to incorporate qualitative methods into their analytical process—just as a chef uses intuition and creativity when cooking, rather than simply following recipes.