Dealing with Uncertainty: Statistics for an Aging Population

Abstract

Uncertainty in statistics and demographic projections for aging and other policy purposes comes from four sources: differences in definitions, sampling error, nonsampling error, and scientific uncertainty. Some of these uncertainties can be reduced by proper planning and coordination, but most often decisions have to be made in the face of some remaining uncertainty. Although decision makers have a tendency to ignore uncertainty, doing so does not lead to good policy-making. Techniques for estimating and reporting on uncertainty include sampling theory, assessment of experts' subjective distributions, sensitivity analysis, and multiple independent estimates.

Key Words:

• Nonsampling error
• Sensitivity analyses
• Demographic projections
• Forecasting
• Decision analysis
• Policy analysis