Because energy conservation programs are generally voluntary, participating households
are different from nonparticipants in important, energy-related ways. This self-selection
bias complicates efforts to estimate energy savings due to these programs. This article
discusses several methods for dealing with self-selection. The choices include nonrandom
sampling of program nonparticipants, binary choice models that explicitly treat house
hold decisions to participate and to retrofit, or use of both methods. Because some of the
methods discussed are new and have not yet been applied to analysis of energy conserva
tion programs, we developed a "synthetic "data set. We conducted numerical experiments
with this data to examine the performance of these different methods. These experiments
show that the improved sample design and analytical techniques generally yield more
accurate estimates of program energy savings. Our experience also suggests that a small, well-defined synthetic data set is helpful in developing, debugging, and evaluating soft
ware associated with new analytical approaches.
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