The purpose of the financial forecast is to evaluate current and future fiscal conditions to guide policy and programmatic decisions. A financial forecast is a fiscal management tool that presents estimated information based on past, current, and projected financial conditions. This will help identify future revenue and expenditure trends that may have an immediate or long-term influence on government policies, strategic goals, or community services. The forecast is an integral part of the annual budget process. An effective forecast allows for improved decision-making in maintaining fiscal discipline and delivering essential community services.
The GFOA recommends that governments at all levels forecast major revenues and expenditures. The forecast should extend several years into the future. The forecast, along with its underlying assumptions and methodology, should be clearly stated and made available to stakeholders in the budget process. It also should be concisely presented in the final budget document. The forecast should be regularly monitored and periodically updated. The key steps in a sound forecasting process include the following:
Define Assumptions. The first step in the forecasting process is to define the fundamental issues impacting the forecast. The results of this initial step will provide insight into which forecasting methods are most appropriate and will help create a common understanding among the forecasters as to the goals of the forecasting process. There are four key questions to consider when defining assumptions for the forecast:
- What is the time horizon of the forecast?
- What is the objective of the government's forecasting policy? For example, a "conservative" forecast underestimates revenues and builds in a layer of contingencies for expenditures. This might make it harder to balance the budget, but reduces the risk of an actual shortfall. On the other hand, an "objective" forecast seeks to estimate revenues and expenditures as accurately as possible, making it easier to balance the budget, but increasing the risk of an actual shortfall. Therefore, a government should be transparent concerning its own forecasting policy and underlying assumptions.
- What are the political/legal issues related to the forecast? Be aware of current laws or expected changes in laws that affect forecasts.
- What are the major revenues and expenditure categories?
Gather Information. To support the forecasting process, use statistical data as well as the accumulated judgment and expertise of individuals inside and perhaps also outside the organization. For instance, department heads may have an insight into activities within their own section. This step is designed to increase the forecaster's expert knowledge about the forces impacting revenues and expenditures. This would also include events that could cause a disruption in the operating environment and in prevailing trends. Both are important for forecasting because they allow the forecaster to more intelligently build quantitative models and to make a forecast using his or her own judgment. Assumptions should be documented for future reference, so the financial forecasting process has some basis to start from at the beginning of each cycle. Also, become familiar with other longer-term planning efforts of the organization or other organizations that impact financial decisions and the fiscal environment. Such plans might include comprehensive development and/or capital improvement programs.
Preliminary/Exploratory Analysis. The analysis should include an examination of historical data and relevant economic conditions. This improves the quality of the forecast both by giving the forecaster better insight into when and what quantitative techniques might be appropriate and also is useful for supplementing forecasting methods. The forecaster is looking for consistent patterns or trends. In particular, the forecaster should look for evidence related to:
- Business cycles. Does the revenue (or expenditure) tend to vary with the level of economic activity in the community or are they independent of cycles? How do broader market forces impact key expenditures, such as pension contributions affected by investment returns?
- Demographic trends. Are population changes affecting service demands and/or revenues?
- Outliers and historical anomalies. Does the data contain any extreme values that need to be explained? It could be that these represent highly anomalous events that don't add to the predictive power of the data set.
- Relationships between variables. Are there important relationships between variables that could aid in forecasting?
Select Methods. Determine the quantitative and/or qualitative forecasting methods that will be used. Keep in mind that the chosen method for one program may differ for another. While complex techniques may get more accurate answers in particular cases, simpler techniques tend to perform just as well or better on average. Also, simpler techniques require less data, less expertise on the part of the forecaster, and less overall effort. Three basic models of forecasting to consider include:
- Extrapolation. Extrapolation uses historical revenue data to predict future behavior by projecting the trend forward. Trending is very easy to use and is commonly employed by forecasters. Moving averages and single exponential smoothing are somewhat more complex, but should be well within the capabilities of most forecasters.
- Regression/econometrics. Regression analysis is a statistical procedure based on the relationship between independent variables (factors that have predictive power for the revenue or expenditure source) and a dependent variable (expenditure source being predicted). Assuming a linear relationship exists between the independent and dependent variables, one or more independent variables can be used to predict future revenues or expenditures.
- Hybrid forecasting. Hybrid forecasting combines knowledge-based forecasting (knowledge-based forecasting consists of using the forecaster's own knowledge and feel for the situation, rather than data and statistics, as the basis for the forecast) with a quantitative method of forecasting. Hybrid forecasting methods are very common in practice and can deliver superior results.
Implement Methods. Making the forecast and using forecast ranges are included within the implementation methods.
- Making the forecast. Put into practice one or more of the forecasting methods described above.
- Forecast ranges. It may be wise to develop a range of possible forecast outcomes, with the use of different scenarios. Multiple projections should be a part of a well-planned and thoroughly discussed approach.
Use Forecasts. The purpose of a forecast is to inform and assist in decision-making. Three items that are essential to a compelling and informative forecast presentation include:
- Credibility of the forecaster. Credibility of the forecast's presenters is essential if a forecast is to be trusted.
- Presentation approach. A good forecast presentation revolves around a clear message. The following steps can be helpful in promoting clarity:
- Linking forecast to decision-making. In order to maximize decision-makers' interest in the forecast, it will be important to emphasize the importance of the forecast as a key factor in the planning and budgeting process. This means imparting a long?term perspective to the budgeting process and emphasizing financially sustainable decisions. The following financial policies might be particularly helpful for promoting interest in financial forecasting:
- Best Practice: A Framework for Improved State and Local Government Budgeting, NACSLB, 1998.
- Best Practice: Long-Term Financial Planning, 2008.
- Best Practice: Appropriate Level of Unrestricted Fund Balance in the General Fund, 2002, 2009.
- Best Practice: Inflationary Indices in Budgeting, 2010.
- Best Practice: Appropriate Levels of Working Capital in Enterprise Funds, 2011.
- Best Practice: Structurally Balanced Budget Policy, 2013.
- Financing the Future, Shayne Kavanagh, GFOA, 2007.