Assessing Uncertainty in Small Area Forecasts: State of the Practice and Implementation Strategy

Forecasts are needed for everyday decisions and must be in the form of numbers. Yet forecasts invariably turn out to be different than the numbers that actually occur. Yet, most producers of forecasts only present a deterministic view of the future in the form of point predictions. However, the presence of uncertainty is inherent in management or policy decisions and there is often concern that benefits are overstated and risks are understated. Such concerns are difficult to address by providing only point forecasts with no assessment of their uncertainty. Having a better understanding of uncertainty can enhance the usefulness of forecasts and make the work of forecasting agencies an even more valuable product for planners, policy makers, and the public. The purpose of this paper is twofold. First, it presents an overview of the current state-of-the-practice is assessing forecast uncertainty. Second, it offers a guidelines and options for implementing and building uncertainty into small area forecasting processes. There are options for assessing forecasting uncertainty that can and should be implemented by most, if not all, producers of forecasts.     

Evaluating Population Forecast Accuracy: A Regression Approach Using County Data

Many studies have evaluated the impact of differences in population size and growth rate on population forecast accuracy. Virtually all these studies have been based on aggregate data; that is, they focused on average errors for places with particular size or growth rate characteristics. In this study, we take a different approach by investigating forecast accuracy using regression models based on data for individual places. Using decennial census data from 1900 to 2000 for 2,482 counties in the US, we construct a large number of county population forecasts and calculate forecast errors for 10- and 20-year horizons. Then, we develop and evaluate several alternative functional forms of regression models relating population size and growth rate to forecast accuracy; investigate the impact of adding several other explanatory variables; and estimate the relative contributions of each variable to the discriminatory power of the models. Our results confirm several findings reported in previous studies but uncover several new findings as well. We believe regression models based on data for individual places provide powerful but under-utilized tools for investigating the determinants of population forecast accuracy.     

The economic importance of air travel in high-amenity rural areas

The western United States offers a case study on the importance of access to large population centers and their markets, via road and air travel, for economic development. The vast distances between towns and cities in the American West can be a detriment to business, yet they also serve to attract technology and knowledge-based workers seeking to live in a picturesque setting. In spite of the increasing importance of amenities to migration and business location, also needed is access to markets, particularly via commercial air service. We test a new county classification system for the western United States to reflect differing degrees of access to population centers and account for the increasing importance of airports. Past classifications are based on population size and cross-county commuting. We examine the validity of this new classification and test for differences in economic performance among the three county types. Our findings show that there are three distinct Wests that can be classified using economic performance measures and socioeconomic characteristics. The results show that “metro” and “isolated” counties are clearly distinct, but “connected” counties, those that are rural in nature but have ready access to metropolitan areas via air travel, can be difficult to distinguish from “metro” and “isolated” counties. Much of the variation is explained by travel distance to airports. The findings illustrate the importance of airports in rural development, and the limitations facing those communities that are isolated from markets and population centers. The results apply to other parts of the world with similar characteristics that include large expanses of open space, natural amenities that attract migrants and stimulate new business, and different degrees of access to large population centers via road or air travel, and therefore different rates of economic growth.