Energy Journalism: Cleaning up the Numbers

Energy journalism can be challenging for reporters. An article on SmartPlanet.com spells out the reasons energy journalism is often low-quality and offers some suggestions for improvement. Since I worked for an energy efficiency research organization for two years and wrote my graduate thesis on the media coverage of the Arctic National Wildlife Refuge oil drilling controversy, I’m going to start where the author ended and provide suggestions for cleaning up energy-related stories.

Question Authorities

Uncritical acceptance of authorities’ statements can cause problems in energy journalism. Here are some litmus tests for reporters:

  1. Is the authority qualified to answer the question? If one is quoting politicians on the amount of oil present in a wildlife refuge, for example, errors are very likely. I’ve seen many examples of journalists missing opportunities to fact-check numbers from non-experts.
  2. Who is funding the research? If the funding is tied to a specific industry or organization, that funding agency may influence the results. The relationship will vary depending on the organization involved.
  3. Is the research public or proprietary? It’s hard to check numbers if their sources are confidential.
  4. Has a third party confirmed the numbers? Checking third-party statements can end speculation.

Don’t Trust Statistics

The SmartPlanet article advocates “reading the small print” and “doing the math.” While checking details is important, there are some baseline assumptions energy reporters should understand before digging into the numbers.

  1. Economic calculation methods, especially discounting, can be deceptive. Financially savvy experts can adjust discount rates easily to show environmentally friendly investments are impractical. Discount rates can make renewable energy or smart grid investment appear worthless because of the time it takes to recoup the money. Would the next generation agree? I doubt it. Discount rates are a way to account for short-term thinking; this doesn’t mean they are a gold standard which we should use to make all of our decisions.
  2. Many energy programs lack effective outreach and marketing. According to Dan Ariely’s comments at the Behavior, Energy and Climate Change conference in 2009, telling customers that they will save a tiny monthly amount on their electricity bills may be much less effective than telling them your company has already donated to charity in their name. The lack of social science in program outreach may mean that programs underestimate the savings they could achieve.
  3. There’s a large margin of error in estimates of fossil fuel resources. For example, some organizations will say peak oil has already passed us by. Other organizations allow much more time. Typically, in evaluating how much of a fossil fuel is present underground, companies and even government organizations will not have exact numbers for your story. If someone quotes a precise number, be skeptical.
  4. Statistics may not include the amount of time and money involved in transitioning to a new technology. If you hear a “before vs. after” comparison without an estimate of the transition cost, pay attention. Companies do evaluate these costs internally, but they rarely become sound bytes. For example, if a company is considering a new nuclear power plant, the cost of insuring the plant should be part of the decision.
  5. Experts may omit the social and environmental cost of an energy choice. Energy experts who focus on some questions – such as availability of oil or changes in electric rates – may never mention the local environmental impacts of oil production, the cost to society of air pollution and global warming, and other effects they did not quantify. The insurance industry is concerned about global warming for a reason; these “externalities” are real expenses.

Critical thinking matters in energy journalism. Many of these assumptions and credibility issues are subtle. One can’t expect reporters to view discount rates or oil reserve estimates cautiously. I hope this post will point other writers in the right direction.

P.S. All of the opinions here are my own and are based on my experience working with science news and energy data.

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