Data Availability in Appliance Standards and Labeling Program Development and Evaluation

TitleData Availability in Appliance Standards and Labeling Program Development and Evaluation
Publication TypeReport
LBNL Report NumberLBNL-6282E
Year of Publication2013
AuthorsRomankiewicz, John, Nina Khanna, Edward L. Vine, and Nan Zhou
Date Published05/2013
PublisherLawrence Berkeley National Laboratory
Keywordsappliance, data, labelling, standards

In this report, we describe the necessary data inputs for both standards development and program evaluation and perform an initial assessment of the availability and uncertainty of those data inputs in China. For standards development, we find that China and its standards and labeling program administrators currently has access to the basic market and technical data needed for conducting market and technology assessment and technological and economic analyses. Some data, such as shipments data, is readily available from the China Energy Label product registration database while the availability of other data, including average unit energy consumption, prices and design options, needs improvement. Unlike some other countries such as the United States, most of the necessary data for conducting standards development analyses are not publicly available or compiled in a consolidated data source. In addition, improved data on design and efficiency options as well as cost data (e.g., manufacturing costs, mark-ups, production and product use-phase costs) – key inputs to several techno-economic analyses – are particularly in need given China’s unconsolidated manufacturing industry. For program evaluation, we find that while China can conduct simple savings evaluations on its incentive programs with the data it currently has available from the Ministry of Finance – the program administrator, the savings estimates produced by such an evaluation will carry high uncertainty. As such, China could benefit from an increase in surveying and metering in the next one to three years to decrease the uncertainty surrounding key data points such as unit energy savings and free ridership.

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