How to Measure Job Creation from Energy Efficiency and Renewable Energy Programs

Community and Economic Development – Blog by UNC School of Government

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How to Measure Job Creation from Energy Efficiency and Renewable Energy Programs

By Glenn Barnes

Published December 22, 2015

In past posts, we have discussed how governments can use financing programs to encourage energy improvements and how energy improvements can turn undesirable properties into economic opportunities.  In fact, economic development and job creation are some of the major benefits touted by governmental energy programs, even above and beyond the potential environmental benefits of such programs.

The non-profit American Council for an Energy-Efficient Economy (ACEEE) has written extensively on the job creation benefits of energy programs, including a fact sheet and a series of case studies.  Many other entities have put out their own case studies, such as World Resources Institute (WRI).

But what is the best way to measure job creation?  Is there a consistent, accepted methodology to measure the economic impact of energy programs so that programs can be compared to each other?

This past fall, ACEEE put out a white paper detailing current practices and recommendations for verifying energy efficiency job creation.  The paper first discusses various approaches to job verification.  It then details current practices based on a survey of energy programs across North America.  The paper then explains the barriers to obtaining credible job creation estimates and concludes with guidelines for estimating and reporting job creation benefits.

The authors found that different programs use different methodologies, examine different impacts, use different standards to account for the impacts, and even at times use different definitions for key terms.  For example, about half of the programs interviewed determine verify job creation through what the authors call a “bottom-up” approach, using surveys, contractor databases, and other methods to count the number of people employed in various aspects of energy programs.  The other half of the programs use what the authors call a “top-down” approach where they use economic models to estimate job creation impacts based on changes in spending patterns.  Some programs used a hybrid of both models.

“Bottom-up” approaches were not even consistent with each other, nor were “top-down” approaches, in particular with the different types of job creation impacts to count: jobs directly related to the energy installation vs. jobs created due to program participants spending money on items other than energy bills, for example, or jobs created when the energy improvement is installed (“program implementation phase”) vs. jobs created due to the ongoing energy bill reductions resulting from the energy improvement (“savings phase”).

The authors don’t propose a single, uniform methodology for measuring job creation but do suggest ways for measuring different types of job impacts.  For example, they argue that, during the program implementation phase, direct impact jobs are best measured through a headcount or other bottom-up approach, whilst the job impacts further up the supply chain are best measured with a multiplier.  Since savings phase jobs are very difficult to observe directly, the authors also suggest using a multiplier to estimate the job creation during this phase.

Job creation is a major potential benefit of renewable energy and energy efficiency programs, and it is one that the public expects to know when public dollars are used for programs.  The ACEEE white paper provides some suggestions for programs to ensure that their numbers are more accurate and consistent.