sample (or a subset of one year’s sample), and the procedures could be fully implemented—or revised, if necessary—for the following year’s sample. In some years, there will be some overlap in the reference period for the data collected by the three energy consumption surveys, which could also have some analytic advantages.

Although the transition to a new sample design and new data collection operations will involve some temporarily increased costs compared to the typical start-up costs associated with the current design of the survey, the expectation is that, at least for the most straightforward implementation of the rotating design (Option 1 described below), over time the costs would be at least comparable—and possibly lower than—the cost of conducting the survey once every four years. EIA could phase in the first subset of the sample gradually, for example, over the course of a two-year period, instead of aiming to complete a quarter of the interviews during the first year of the implementation.

An operational advantage is that the survey would not have to be resurrected every four years, and there may be some cost savings and data quality improvements associated with uninterrupted operations, since there would be more continuity in the activities performed by staff and, in particular, the field interviewers, who require extensive training. It is possible that the decrease in the number of interviews conducted each year might lead to a decrease in efficiency in terms of ability to provide interviewers with an optimal caseload in their respective geographic areas. However, as discussed later, the panel encourages EIA to explore the possibility of collecting some of the data by web, which would also contribute to a drop in the field interviewer workload and would likely necessitate the restructuring of interviewer assignments. This could be accomplished, for example, by crosstraining interviewers to perform additional tasks.

The rotating design would also integrate well with a longitudinal approach, which would involve following a subset of the sample over time. This would improve estimates of change and would allow researchers to assess how changes in the economy or in incentive programs affect energy consumption patterns. EIA experimented with longitudinal data collection for the CBECS in the 1980s but found that inconsistencies in reporting and other sources of error were sometimes confounded with the actual changes of interest, which limited the usefulness of the longitudinal data (French, 2007). However, techniques for reducing inconsistencies and controlling for confounders in longitudinal studies have become more sophisticated



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