There are four issues in interpreting the results of a
cost-benefit model.
First, while the model is simple, it is no easy task to obtain appropriate
measures. Almost always in public sector applications, the measures of program
benefits are poor estimates of something that does not easily lend itself to
measurement. The measurement error introduced by this estimation process could,
in some cases, reverse the conclusions to be drawn; it certainly clouds the
issue in most cases.
Second, it is important to compare only roughly comparable programs. The
mathematics of the model will not warn you if you are comparing programs that
have nothing in common. Feed a computer garbage, it
will merrily give garbage back to you. The problem is that the interesting
questions frequently involve programs which are not comparable. Morris Hill's
article (1968) is particularly instructive in this matter.
Third, the analyst should expect to be frustrated by the inability to obtain
quickly the necessary data. It would be nice if you had the leisure to examine
programs in detail; usually the decision-maker needs the answer yesterday. Some
quantitative analytical tools are designed to use secondary data, data which is
already on the shelf, gathered by the census bureau or the demographer's
office. Benefit/cost analysis does not lend itself to that approach; each
analysis is unique. This makes time for data collection all the more precious.
Finally, the analyst should realize that what is offered here is a general
model. It will probably need to be expanded and modified each time to suit the
specific setting. This was alluded to in the discussion of discounting; but it
is applicable to all elements of the analysis. As long as the user loads and then
removes the template disk, the model in memory can be freely modified with no
damage to the original template. The modified templates can even be saved
(preferably on a different disk and with a different name) for future
consultation.
© 1996 A.J.Filipovitch
Revised 11 March 2005