Practical economic forecasting for small regions

Business Economics, July, 1991 by John R. Fiske, James C. Lamb, Mark F. Morss

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Forecasts of regional economic variables, such as income and employment, represent valuable information to businesses that serve regional markets and to government agencies that must implement programs at the county or regional level. Their value is greatly enhanced to the extent that they are derived in a manner consistent with economic theory, subject to objective review and capable of being reproduced over time. This paper reports on an econometric modeling approach that has been used successfully in a practical setting.

DETAILED PROJECTIONS of regional economic activity, produced by region-specific forecasting models, can be of great benefit to businesses such as utilities and commercial banks that serve regional markets, and to state and local governments that must plan or implement programs for multicounty areas.

In practice, however, the costs of building and maintaining regional economic models and the constraints on data availability often discourage the modeling efforts necessary to develop regional economic forecasts. Typically, businesses and government agencies interested in regional economic projections either make do with rough impressions not supported by much analysis or simply "allocate" to the regional level from a more aggregated geographic entity for which projections are available.

The regional economic literature provides numerous examples of regional models (see Bolton for a recent survey). But these models, for the most part, are not readily applicable to forecasting in a practical setting, be it industry or government. The typical model reported in the literature is designed to test hypotheses about regional economic structure, and therefore emphasizes theoretical completeness and structural detail. As a consequence, it is likely to possess a degree of sophistication, in its specification or in its estimation, that quickly confronts the resource limits of all but the largest practitioners. The typical forecaster in a practical setting will value a model primarily for its ability to produce reasonable and tolerably accurate forecasts in a regular and timely manner.

In the context of limited resources available, ease of data collection and maintenance, and also simplicity of model specification and estimation, are likely to be more highly valued than structural or econometric sophistication. Another limitation of reported models from the viewpoint of practical forecasting is that they are typically built for predefined geographic entities, such as states or Metropolitan Statistical Areas (MSA), and rely heavily on data that are available for those entities but not available in general. Yet it is not often that the region of interest to a business coincides with a state or an MSA; for the typical business, greater flexibility of regional definition is needed. Even state government agencies, whose ultimate responsibility is a state jurisdiction, may find that the aggregated data mask important intrajurisdiction differences.

This paper reports on a regional economic modeling approach used by East Kentucky Power Cooperative, Inc. (EKPC), a rural electric cooperative that serves 280,000 residential customers and 15,000 commercial customers in east-central Kentucky. These models use quarterly, county-level data to produce regional forecasts of income, employment, wages, population, labor force and the unemployment rate. They are comparatively easy to estimate, utilizing ordinary least squares within a linear framework, and are specified with a view toward obtaining plausible and realistic simulation properties. The endogenous data set is confined to a limited number of concepts that are available, in principle, for all U.S. counties, and are relatively easy to update from U.S. government-supplied tapes. The use of county level data facilitates a bottom-up approach to the construction of economic regions, introducing a high degree of flexibility into the process of regional definition. The approach presented here thus reflects the concerns of regional economic modeling in practice.

The purpose behind EKPC's regional model is to provide data for use in forecasting electricity sales. The importance to EKPC's load forecast of regional economic projections is heightened by two factors: (1) the geographic extent of its service area; and (2) the composition of its customer base. The roughly eighty counties served by EKPC reflect a wide variety of economic activity. Coal mining dominates the economy of the southeast portion of the service territory; heavy industry, such as steel and chemicals, is very important to the economy of the northeast portion; and service-based employment, along with state government employment, provides the economic base for much of the western part of the service area. This diversity suggests the value of regional economic detail in forecasting the demand for electricity. In addition, the growth prospects of EKPC's customer base, which consists mostly of residential and small commercial accounts, is highly dependent on regional employment and income. This dependence is in contrast to the electric utility whose customer base is dominated by large industrial customers, whose prospects are likely to be more directly influenced by national or even international economic events.