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Title: Methods to deal with self-selection in estimating conservation-program energy savings: use of synthetic data to test alternative approaches

Technical Report ·
OSTI ID:6388838

Because energy-conservation programs are generally voluntary, households that choose to participate in the programs are almost certain to be different from nonparticipants in important energy-related ways. This self-selection bias greatly complicates efforts to estimate energy savings due to the program. Several methods for dealing with self-selection are discussed. The methods involve either nonrandom sampling of program nonparticipants, binary choice models that explicitly treat household decisions to participate and to retrofit, or both. Because some of the methods discussed are new and have not yet been applied to analysis of energy-conservation programs, a synthetic data set was developed. Numerical experiments were conducted 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 very helpful in developing, debugging, and evaluating software associated with new analytical approaches.

Research Organization:
Oak Ridge National Lab., TN (USA)
DOE Contract Number:
W-7405-ENG-26
OSTI ID:
6388838
Report Number(s):
ORNL/CON-120; ON: DE83008138
Country of Publication:
United States
Language:
English