Affiliations: [a] Arkansas Institute For Economic Advancement, College
of Business Administration, University of Arkansas at Little Rock, 2801 S.
University Avenue, Little Rock, Arkansas 72204-1099, USA | [b] San Diego Association of Governments, 1st Interstate
Plaza, Suite 800, 401 B Street, San Diego, California 92101, USA | [c] Pacific Northwest Laboratories, P.O. Box 999,
Richland, Washington 99352, USA
Abstract: Utility has recently been proposed as a criterion for evaluating forecasts
because of problems that arise from evaluations that focus exclusively on
accuracy, which is the normative expectation for evaluating forecasts. Utility
is used to evaluate the lagged ratio-correlation method as a short-term
projection tool. The utility of the lagged ratio-correlation is compared with
two alternatives, exponential extrapolation and the Cohort-Component Method,
using data from a case study for Washington State counties at three points in
time, 1970, 1980 and 1990. Together, these three projection methods represent
the range of current practice in regard to resource requirements and accuracy.
Each method's utility is measured using Proportionate Reduction In Error (PRE)
techniques. These show the reduction in average error across counties that
occurs by using each projection method instead of the previous census as a
forecast of county population, which is virtually a no-cost forecasting tool.
Reductions in error are examined relative to the higher “cost” associated with
each of the three projection methods. The evaluation suggests that the lagged
ratio-correlation method consistently has a high level of utility for all three
timepoints. It achieves reductions in error that are comparable to those
achieved by the Cohort-Component Method, yet with much less resource
requirements. The exponential extrapolation method is found to have high and
moderate utility in two of the three timepoints.
