FORECASTS ARE MADE and used in numerous fields. To develop a feel for the tremendous diversity of forecasting applications, let’s sketch some of the areas where forecasts feature prominently.
One key field is economics, broadly defined. Governments, businesses, policy organisations, central banks, financial services firms, and economic consulting firms around the world routinely forecast the major economic variables, such as gross domestic product (GDP), unemployment, consumption, investment, the price level, and interest rates.
Governments use such forecasts to guide monetary and fiscal policy, and private firms use them for strategic planning, because economy-wide economic fluctuations typically have industry-level and firm-level effects.
In addition to forecasting/standard variables such as GDP, economists sometimes make more exotic forecasts, such as the stage of the business cycle (expansion or contraction), the state of future stock market activity (bull or bear), or the state of future foreign exchange market activity (appreciation or depreciation).
Again, such forecasts are of obvious use to both governments and firms – if they’re accurate!
Another key area is business in all its sub-fields. These include management strategy of all types, including operations management and control (hiring, production, inventory, investment and so on), marketing (pricing, distributing, advertising and so on), and accounting (budgeting using revenue and expenditure forecasts).
Sales forecasting is a good example. Firms routinely forecast sales to help guide management decisions in inventory management, sales force management, and production planning, as well as strategic planning regarding product lines, new market entry, and so on.
More generally, firms use forecasts to decide what to produce, when to produce, how much to produce and how much capacity to build.
Forecasting is also crucial in financial services, including asset management, asset pricing, mergers and acquisitions, investment banking and insurance.
There are many objects that we might want to forecast. In business and economics, the forecast object is typically one of three types: event outcome, event timing, or time series.
Event outcome forecasts are relevant to situations in which an event is certain to take place at a given time but the outcome is uncertain.
Event timing forecasts are relevant when an event is certain to take place and the outcome is known, but the timing is uncertain.
Time series forecasts are relevant when the future value of a time series is of interest and must be projected.
There are at least two reasons why time series forecasts are by far the most frequently encountered in practice.
First, most business, economic and finnancial data are time series; thus, the general scenario of projecting the future of a series for which we have historical data arises constantly.
Second, the technology for making and evaluating time series forecasts is well developed and the typical time series forecasting scenario is precise, so time series forecasts can be made and evaluated routinely.
In contrast, the situations associated with event outcome and event timing forecasts arise less frequently and are often less amenable to quantitative treatment.
Francis Diebold is Paul F and Warren S Miller Professor of Economics and Professor of Finance and Statistics at the University of Pennsylvania.
