How Do You Measure the Impacts of Energy Efficiency Policies?

Gita Subramony for Zondits, February 17, 2015

Energy efficiency policies have long been evaluated in order to examine if claimed savings are in fact achieved and if program processes work successfully to reach these goals. One tricky part of this analysis is figuring out if energy savings are in fact attributable to a program’s intervention strategies or if savings were simply a result of free ridership or other market effects. One idea is that energy efficiency evaluation can take a page from drug manufacturers and use randomized trials to prove that programs are key drivers of energy savings. Although creating control groups to test energy efficiency policies is more challenging than doing the same in a medical setting, the potential for gaining valuable data on which policies work best is high.


Randomised Trials of Energy Efficiency Policy

The Energy Collective, February 11, 2015

Greater use of randomised trials could help the uptake of energy efficiency by identifying which policy interventions work best.

More efficient use of energy is high on almost everyone’s list of good ways to reduce CO2emissions.  It can lead to large scale emissions reductions, is often cost-effective, and tends to be highly compatible with other policy goals such as energy security.

Efficiency standards for buildings, vehicles and appliances have played a critical role in improving energy efficiency, and will continue to do so.  But standards are not the whole story.  Rates of uptake of more efficient technology and processes and other changes in consumers’ behaviour can matter greatly.

However it is often impossible to know in advance how innovative policy interventions will affect behaviour. Consumers’ responses to novelty are unpredictable, and judging likely response is further complicated because consumers’ circumstances are often complex and varied.  Even afterwards it may be difficult to judge whether an intervention has been effective because it’s impossible to say what would have happened otherwise.

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