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A Proposal to Create a Pan-Canadian Energy Information Organization (CEIO)

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  • Michal C. Moore

    (The School of Public Policy, University of Calgary)

Abstract

Canada is a safe and stable resource-rich nation in an increasingly energy-hungry world. While this state of affairs imbues our riches with strategic importance, it also creates an acute need for accurate data collection guided by nationally accepted methods, tools and approaches, to cut through the tangle of overlapping jurisdictions that confuse present attempts to understand the Canadian energy sector as a whole. Prepared at the request of the Alberta Department of Energy, this paper proposes the creation of the Canadian Energy Information Organization (CEIO), an independent, objective energy information agency similar, but not identical, to the Energy Information Administration in the United States and the International Energy Agency serving OECD member countries. Funded through modest provincial contributions and working with Statistics Canada, the CEIO would support federal and provincial energy regulatory mechanisms; offer timely energy forecasts, analysis and statistical interpretations; lower research costs for the provinces; promote clear and uniform reporting standards; and aggregate facts and figures in an easily accessible database functioning as an official information portal, educating the public and ensuring that Canada makes the most of its energy bounty. A nationally recognized authority on the Canadian energy sector is long overdue, and in sketching one (right down to the level of corporate governance, budgeting and staffing), this paper fills in a major gap in Canada’s energy landscape.

Suggested Citation

  • Michal C. Moore, 2012. "A Proposal to Create a Pan-Canadian Energy Information Organization (CEIO)," SPP Research Papers, The School of Public Policy, University of Calgary, vol. 5(11), March.
  • Handle: RePEc:clh:resear:v:5:y:2012:i:11
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    Cited by:

    1. Bistline, John E.T. & Merrick, James H., 2020. "Parameterizing open-source energy models: Statistical learning to estimate unknown power plant attributes," Applied Energy, Elsevier, vol. 269(C).

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