Bringing Fairness to Energy Programs
Extend effective programs to low income households, but scrap the bad ones for everyone.
Energy programs for low-income households are on the chopping block. President Trump’s proposed federal budget would eliminate energy programs including the $270 million per year Weatherization Assistance Program (WAP). The WAP program pays to make the homes of low-income households more energy efficient.
Low-income households already receive a smaller share of government and utility spending on energy programs than higher income households, but the proposed budget cuts would make matters worse.
Energy Institute at Haas research illustrates just how regressive programs for rooftop solar systems, energy efficiency and clean vehicles already are.
For example, in a 2015 Energy Institute at Haas Working Paper, Severin Borenstein analyzed participants in the California program that subsidized rooftop solar installations. He estimated that between 2007 and 2013 the top 40% earning households participated in the program at three times the rate of the lowest 40% earning households. This means the federal tax breaks and utility incentives for rooftop solar, which averaged $10,000 to $20,000 per household, were heavily skewed toward higher income households.
The same pattern shows up in energy efficiency programs. California households with more than $100,000 in annual income have participated in energy efficiency programs at twice the rate of households earning less than $50,000, according to analysis of the U.S. Energy Information Administration’s Residential Energy Consumption Survey.
The picture is even starker for clean vehicle tax credits. Taxpayers with incomes greater than $75,000, roughly the top 20% of taxpayers, received about 90% of federal tax credits for plug-in electric vehicles between 2006 and 2012.
Should we be concerned if these policies are regressive?
Some argue that policies like these can encourage innovations and cost reductions that will make cleaner energy technologies more commercially viable. Elon Musk has articulated this progression in the “master plan” for Tesla, the electric vehicle company: start by selling a low volume, expensive car, then incorporate the learning to make progressively more affordable cars. Subsidy policies could accelerate this process by encouraging more private money to, in effect, co-fund the technology development process.
But some state policymakers aren’t satisfied with these arguments. They want fairer programs now.
In California the legislature is particularly concerned with inequality in energy. This isn’t surprising since the state has among the nation’s highest levels of income inequality – ranked #4 based on 2015 Census survey data.
The main thrust of policymaking to address inequities has been to spend more on programs for low-income households. Households living in areas that experience high levels of pollution have received special attention. This has included earmarking 25% of the state’s revenues from selling greenhouse gas cap-and-trade permits to programs that benefit “disadvantaged” communities. Disadvantaged communities are identified based on an index that takes into account pollution- and poverty-related factors. In effect, these are the subset of low-income communities that are also exposed to high levels of pollution. As part of this effort California has budgeted a cumulative $174 million since 2014, so far, for weatherization and solar in these low-income communities.
Is ramping up spending on energy efficiency and solar for low-income communities the best approach? It depends. If the policies are cost-effective, then yes. But, if the low-income policies are not cost effective then increasing spending won’t benefit low-income households or society. In fact, there are likely cases where the best way to achieve equity is to cut back the subsidies going to higher income households rather than increasing the subsidies for lower income households.
Research suggests that residential home upgrade programs may be a good place to aim the microscope.
In a 2017 working paper released by the E2e Project, Hunt Allcott and Michael Greenstone examined programs in Wisconsin that offered subsidized audits and home upgrades. The programs were open to participants at any income level. They found the programs had a negative rate of return of 4%. Among the challenges, many households who took subsidies for the audits did not implement any energy savings measures, and the households that did take action after the audits were influenced by aesthetic and other non-energy factors. As a result they collected significant subsidies for upgrades that saved very little energy.
A previous study by Meredith Fowlie, Michael Greenstone and Catherine Wolfram of a low-income home upgrade program in Michigan also found poor results.
Ineffective programs such as these should be eliminated or radically redesigned, not expanded for low-income households.
In other cases, however, programs targeted at low-income households could generate significant benefits.
Judson Boomhower and Lucas Davis evaluated energy savings from a program that subsidized energy efficient central air conditioners in southern California. They evaluated how energy savings varied based on household demographics. Consistent with other energy programs, households in lower income zip codes participated at only half the rate of higher income zip codes, making this another highly regressive energy program.
The analysis also pointed to opportunities. The households in lower income zip codes that participated saved just as much energy as those in higher income zip codes. As Boomhower and Davis pointed out previously, this program saves energy at peak times, when energy is particularly valuable. This suggests that policymakers should find ways to increase these valuable upgrades in lower income households.
Program expansion could be funded by eliminating the least effective parts of the program. Specifically, households in milder zip codes could be excluded. A full 80% of participants lived in these areas, in which energy savings were modest or non-existent. If the subsidies paid out between 2010 and 2014 in the milder zip codes had instead gone to additional participants, including low-income participants, in the hotter regions, energy savings from the program would have more than doubled.
More rigorous analysis of energy programs is needed, as is better demographic data on program participation and impact. The California Energy Commission has highlighted the need for better demographic data in their recent report summarizing barriers to energy programs for low-income households.
Advocates for greater equity in energy programs should use the upcoming federal budget debate to push for more spending on effective programs for the poor and less spending on ineffective programs for everyone.
Categories
Andrew G Campbell View All
Andrew Campbell is the Executive Director of the Energy Institute at Haas. Andy has worked in the energy industry for his entire professional career. Prior to coming to the University of California, Andy worked for energy efficiency and demand response company, Tendril, and grid management technology provider, Sentient Energy. He helped both companies navigate the complex energy regulatory environment and tailor their sales and marketing approaches to meet the utility industry’s needs. Previously, he was Senior Energy Advisor to Commissioner Rachelle Chong and Commissioner Nancy Ryan at the California Public Utilities Commission (CPUC). While at the CPUC Andy was the lead advisor in areas including demand response, rate design, grid modernization, and electric vehicles. Andy led successful efforts to develop and adopt policies on Smart Grid investment and data access, regulatory authority over electric vehicle charging, demand response, dynamic pricing for utilities and natural gas quality standards for liquefied natural gas. Andy has also worked in Citigroup’s Global Energy Group and as a reservoir engineer with ExxonMobil. Andy earned a Master in Public Policy from the Kennedy School of Government at Harvard University and bachelors degrees in chemical engineering and economics from Rice University.
Energy Institute Blog 
“the households that did take action after the audits were influenced by aesthetic and other non-energy factors. As a result they collected significant subsidies for upgrades that saved very little energy.”
Were these for “aesthetic” or much more fundamental home maintenance reasons? This is a population in which the housing stock is likely to be in much poorer condition than the average. Did the study account for this difference? It may be that the program was designed for one purpose, but created a significant co-benefit for another purpose. Like the US EPA, these studies should account for these other co-benefits in their calculations.
Several of the previous comments address the ‘agency problem’ or fact that lower income customers rent rather than own their housing, which almost always disqualifies them from participating in state funded programs. Targeting won’t change this issue since renters don’t have any legal standing to change someone elses property. The most viable solution to the ‘agency problem’ is to take a long-term perspective and consider using a building code approach that like ADA legislation which mandates certain efficiency upgrades whenever there is a change in tenant occupancy or when the property is sold. More efficient appliances, thermostats, and other minor improvements might be reasonable on a tenant occupancy change. More costly window, roofing, and insulation changes could be considered on a property sale.
None of these efficiency changes address the ‘implementation’ or behavioral problems which can undermine any structural investment.
The lowest income group reside in apartments and section 8 buildings, if not on the streets. Improving energy efficiency in apartments in the form that requires no payment from the renters would benefit the lowest income groups except those on the streets.
The subsidy benefits only home owners who can afford and are willing to pay the non-subsidized part of the costs. Those struggling to pay their mortgages would be prevented, even if they are willing to pay, from benefiting owing to their inability to afford additional credit.
Allocation efficiency can be increased if the program does not require any payment from the beneficiary.Coupled with education, the poor home owners are most likely to participate just like their richer counterparts.
Budgetary constraints would limit even further the number that would benefit but the repressiveness would be reduced if not eliminated.
Or to put it another way, the effectiveness of a redistribution instrument can be judged by the leakiness of its transfer bucket. This allows programs to be evaluated according to their efficiency. Adverse consequences for the poor should be offset by increasing the transfers from the least leaky buckets (Kaplow and Shavell).
This article appears to be calling for retargeting of EE programs rather than ending spending on higher income households, e.g., HVAC upgrades in less moderate climate zones. But this article doesn’t address what is probably the single biggest factor in the disparity of program reach: homeowners are also typically higher income. Lower income customers are renters who have little or no control over investing in EE measures. They can’t even sign up for SmartAC load control without a landlord’s consent. We need to address the “agency problem” to reach lower income groups.