Econometrics forecasting involves making predictions based on economic factors. While economics is a base for this study, other tools — primarily statistics and mathematics — provide the additional techniques for making forecasts. A few common types of econometrics forecasting include models, decision trees, and market representations. Even though econometrics takes into account several different factors for business purposes, it is by no means perfect. Though the estimates may be close to reality, there is no way for a company to completely simulate a market economy to make decisions.
The use of models is quite common in econometrics, especially for forecasting. A model starts with inputs gathered from the current market on a particular topic. For example, econometrics forecasting requires data from which to make estimates about future events or potential outcomes. The inputs go into a model that computes an answer for decision makers. The purpose may be to determine how to increase production output, whether to change the quality of materials or what sales methods to alter in order to improve sales revenue.
A common type of econometrics forecasting model is a decision tree, common in statistical measurements. A company outlines several different types of decisions that may result in certain outcomes labeled as high, medium, or low. Different factors can affect whether a company achieves each of these levels. Econometrics places statistical percentages on each of these potential outcomes, allowing the company to ascertain the possibility of success for each level. Though not 100 percent accurate, the decision tree does provide a base for understanding how to make other decisions about the company based on these probabilities.
Another purpose for econometrics forecasting is to simulate market conditions and recreate market representations. Gathering statistical inputs over an extremely large time period should provide enough data to recreate market situations. This allows a company to plan for future market conditions that may be similar to the simulation. When a company recognizes these conditions are occurring, the information gleaned from econometrics forecasting helps in preparations. Again, not completely accurate, this method simply prepares the company for a different market environment and allows for maintaining success.
Other types of econometrics forecasting may be available to companies. The source for these forecasts most likely comes from individuals with particular educations or backgrounds. For example, individuals with PhDs are the most common sources for econometrics forecasting. These individuals have high training in statistics, mathematics, and econometrics in order to create models and other forecasts.
