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A State-of-the-Art Energy Consumption Data Collection Program
The panel’s recommendations in this report are based on a careful balance between what the data needs are and what is most realistic to implement in the short term. This chapter offers some additional ideas that may be less feasible in the short term or are perhaps less critical but that could help U.S. Energy Information Administration (EIA) as it plans for the future.
A COMPREHENSIVE SURVEY OF ALL ENERGY-CONSUMING PREMISES
Due to practical considerations, the three current energy consumption surveys, the Commercial Buildings Energy Consumption Survey (CBECS), the Residential Energy Consumption Survey (RECS), and the Manufacturing Energy Consumption Survey impose somewhat arbitrary divisions between the energy-consuming sectors, particularly as they apply to premises on the boundaries between the sectors. Furthermore, some energy-consuming premises are treated as out of scope by all three of the existing surveys. This is not unusual or inconsistent with other federal surveys. Still, it is possible to envision a comprehensive design for collecting building energy consumption based on a sampling frame that includes all buildings, regardless of type. Buildings would be sampled from this frame and would then be classified into categories such as commercial, residential, or industrial, instead of being divided into categories first and then sampled.
A variation on the area sampling approach that is becoming more feasible with today’s technology is to develop a grid with small enough cell sizes to capture buildings and then lay that grid over a map of the United States. A computer program can perform clustering and determine whether a given cell contains any buildings by, for example, using satellite mapping to identify buildings. The panel anticipates that most buildings could be accurately classified by EIA without the need to rely on field visits. Field procedures would still have to be developed for handling cases that cannot be classified or that are misclassified, but it would be possible to implement an approach of this type in a significantly more cost-effective way than current designs that rely primarily on field listing.
Drawing a random sample of buildings based on satellite maps may be another way to approach a design of this type. For example, the street-view function of programs such as Google maps could help in assigning many of the selected buildings to an energy-consuming sector, although it would not work in all cases, and there are some areas for which the street-view function is not available. The technology and the availability of features are constantly changing, and this should also be an important consideration.
INTERACTIVE ONLINE TOOLS
Few government surveys have embraced the use of interactive online tools as a means to build awareness about a data collection and to encourage survey participation. As it becomes more and more difficult to maintain high response rates, agencies are being forced to invest more and more resources into nonrespondent follow-up, but most agencies rely on a limited number of techniques to gain respondent cooperation. In the case of a survey such as the RECS, in particular, innovative strategies involving interactive online tools may be able to engage sample members who are interested in learning about their homes’ energy consumption. Fostering a sense of involvement and reciprocity around the data collection programs will change the dynamics and could help EIA maintain high-response rates at least among a specific segment of the population.
There are a number of possibilities for integrating interactive online tools. A relatively simple approach would be to start an online community for sample members and offer online calculators or tools that would allow users to compare their homes’ energy use and features to those of an average home or to those of homes in their community. Such tools would not
only engage users but would also produce data that could be “scraped” and analyzed by EIA, for example, to track trends in the behavior of the users.
A more involved approach that would work particularly well in combination with a web survey would be to provide each respondent with a brief analysis of his or her responses once the questionnaire is completed. This is a concept similar to one used by the National Health and Nutrition Examination Survey (NHANES), which provides survey participants with the results of their physical examination as an incentive to participate.1 The results provided to the RECS respondents might compare their homes’ energy use to energy efficiency standards or to the energy use of similar houses in the neighborhood, state, or climate zone. The most compelling, although also most resource-intensive way to implement this feature would be to generate the analysis “live” at the end of the survey. Alternatively, or in combination with the live online feedback, a process could be developed for mailing a respondent the report after the interview is completed.
One concern that arises is whether techniques such as these may be disproportionately more likely to engage sample members who are particularly interested in the topics measured by the survey—for example, in the subject of energy efficiency—and who therefore are likely to be different from the rest of the sample. This concern can probably be mitigated by aiming to maintain high overall response rates. In other words, even if the interactive tools attract a subset of the population which differs from the rest of the sample, intensive nonresponse follow-ups, including through different modes, should assure that any bias introduced by disproportionate interest in the incentives among a subset of the population is minimized after follow-up.
The question of how such feedback could affect participation in the proposed longitudinal survey deserves particular attention. An interactive feature could serve as an especially strong incentive if a longitudinal design is introduced. However, it is possible that the feedback provided will alter the behavior of respondents in the longitudinal sample, not only in terms of their likelihood of participating in a second survey, but also in terms of their energy consumption. The benefits and associated risks would have to be evaluated.
1 For an example of the Final Report of Findings prepared for NHANES respondents, see http://www.cdc.gov/nchs/data/nhanes/nhanes_07_08/ROF_07_08_eng.pdf [December 2011].
DIGITAL PHOTOGRAPHS
EIA has considered the use of digital photographs in the past, and this idea could be revisited, at least as a one-time research effort. Photos may provide valuable information to supplement the interviews conducted in face-to-face administration. They could also be useful in evaluating the quality of self-reported data in web-administered questionnaires. Pictures can help headquarters staff determine whether the definition of a commercial building was applied correctly in the field, or to better understand the layout of residential buildings. Pictures of critical equipment, including nameplates, when it is possible to obtain these, may be useful in the data cleaning and editing process (for example, for reconciling ambiguous or questionable entries). Using cameras in this way, however, would likely involve privacy and confidentiality considerations, and these would have to be researched before the use of cameras could be implemented.
SURVEYS ON SPECIAL TOPICS AND OTHER OPPORTUNITIES FOR EIA
Given the burden that the questionnaire already imposes on respondents, EIA should evaluate creative alternatives for collecting additional data without increasing the overall burden on respondents. For example, EIA could collect data on some specialized topics, such as knowledge, attitude, and behavior related to energy consumption, in the form of a separate survey, independent of the current CBECS or RECS. EIA has added specialized modules to individual cycles of the survey in the past, and it should consider reinstating this practice. There are many possible ways that such specialized data collections could be funded, but one possibility to consider would be a collaboration with other government agencies or organizations that have interest in the data. EIA might even consider serving as the coordinator or data center for research on a number of special topics or special populations.
Collaborations with energy suppliers could also be pursued beyond what is required to obtain data for nonrespondents. Many utilities offer energy efficiency incentives to their customers and sometimes commission studies to evaluate the effectiveness of these programs. EIA could explore opportunities for data collections partially funded by energy suppliers if data could be produced that is helpful for the utilities. If recommendations to collect energy consumption data about all of a utility’s customers
(instead of just sample members who do not provide adequate data) can be implemented, providing utilities with some data could also become more feasible. A collaboration of this type could serve as an incentive that encourages energy suppliers to standardize their reporting in ways that enables EIA to more efficiently integrate the data received from them.
Additional opportunities for more active dissemination and closer collaboration with the research community include working with other groups collecting extensive data in limited regions or building types. Collaborations with stakeholders can not only be useful in the short term but can also help EIA plan for the future. Providing cost-recoverable custom analysis to the public may be another area to explore.
The panel expects that interest in energy consumption data will continue to grow. Rapid changes in the energy landscape combined with changes in the survey-taking environment require data collection approaches that are continuously updated. Investments into state-of-the-art data collections are necessary to assure that EIA remains at the forefront of energy consumption research.
