The New Yorkers recent piece on the Jevons Paradox (gated) and the many responses it generated got me thinking back to a paper I wrote in graduate school about the strategy of using efficiency as a climate change mitigation policy. I don’t touch directly on the Jevons Paradox, which admittedly leaves a big gap in my argument, but do discuss one of my favorite intellectual curiosities, the efficiency gap. Anyway, I figured I’d share it since it never saw the light of day back in school.

———————

It is well understood the negative impact that emissions from power generation, along with other anthropogenic greenhouse gas (GHG) emissions, could have in forcing global climate change. The Intergovernmental Panel on Climate Change (IPCC) has proposed a number of mitigation options for different sectors of the economy (IPCC, 2007). The IPCC notes that the greatest CO₂ reduction per unit cost can be achieved in the building sector, citing increases in energy efficiency (IPCC, 2007: Figure SPM.6). This paper explores the topic of energy efficiency in buildings as a potential mitigation policy for climate change. Consideration goes beyond the obvious impacts on capital expenditure, reductions in energy use and the associated cost savings. The impetus for energy efficiency in buildings and the theory of an “efficiency gap” will be considered in brief before analyzing the costs and benefits of potential energy efficiency policies (EEPs).

Globally, buildings are responsible for roughly a quarter of all CO₂ emissions (Levine et al., 2007). Commercial and residential buildings account for approximately 30% and 39% of energy use in Canada and the United States, respectively (NRCan, 2006; US DOE, 2007). Given the magnitude of GHG emissions and energy use of buildings, they are a logical sector to consider if one wishes to reduce emissions associated with energy use and electricity generation. A study by Brown et al (1998) details a number of efficiency measures and their associated GHG reduction potential using an engineering-economic analysis. Brown and Southworth (2006) couple buildings and the urban form as further opportunity for climate change mitigation. There is a distinction, however, between choosing energy conservation measures (ECMs) in a free market and considering them as a policy instrument to combat climate change. A debate exists with regard to explaining the “efficiency gap,” the notion that the level of energy efficiency achieved is less than the level judged by market theory to be cost-effective (Howarth & Sanstad, 1995). A case can be made for policies that would narrow this gap even without climate change acting as an additional motivator. A general understanding of the issues regarding energy efficiency in terms of efficient economic markets is pertinent prior to reviewing the costs and benefits of an EEP.

Howarth and Sanstad (1995) thoroughly discuss theories behind the efficiency gap. One explanation is that consumers apply a high discount rate to energy-using technologies. A high rate implies a perceived risk in the efficiency investment, perhaps stemming from unknown future energy costs; the literature supports the high implicit discount rate theory with empirical evidence (Howarth & Sanstad, 1995: 102). Additional theoretical explanations of the efficiency gap have been discussed; many are rebutted and will not be elaborated upon here. However, market failures play a large role. Imperfect or asymmetric information is cited as a significant market failure when it comes to energy efficiency decisions, therefore buyers may unwittingly make choices that are not the most cost-effective. Additionally, the possibility of split-incentives serves as another market failure. Howarth and Sandstad use an example of a tenant and landlord to explain this phenomena: the landlord will not invest in ECMs because he sees none of the savings, the tenant will not invest as he may not reside in the apartment long enough to realize the full benefits. Mechanisms exist to address this problem but can add transaction costs thereby making the ECM less desirable. Another explanation holds that while consumers lack information, they more importantly lack expertise concerning the costs and benefits of energy efficient decisions. This issue, known as “bounded rationality,” has been observed in technical labeling programs having little effect on the quality of decisions. Howarth and Sandstad conclude by rationalizing the need for policies that correct market failures but urge this to be done on a case-by-case basis. The debate regarding the efficiency gap is pertinent if one is to consider energy efficiency a viable component of a climate mitigation policy. Not only would an effective mitigation policy close the gap, it would seek higher efficiencies by increasing the external cost of energy emissions. The explanation put forth by Howarth and Sandstad is valuable in considering the costs and benefits of energy efficiency programs.

The scale of the climate change problem lends itself to large mitigation policies that will include social costs and benefits. As such, it is important to consider an energy efficiency program in the broader social context. Precedent policies for energy efficiency programs are abundant. While in the past such policies may not have ultimately been created as part of a climate mitigation strategy, a reduction in energy use can usually be linked to a reduction in GHG emission. Considering the ubiquity of the climate change problem, it is useful to consider a mitigation strategy under different geographical and socio-economic conditions in order to understand its global plausibility. Goodacre, Sharple and Smith (2002) consider energy efficiency to be a “central axiom” in sustainable development and apply a cost benefit analysis to heating and domestic hot water upgrades within the English housing stock. Clinch and Healy (2001) perform a similar analysis on the Irish housing stock and include upgrades to building envelopes (e.g. – added insulation and draught stripping). These two studies offer insight as to what impacts a broad energy efficiency program might have in a developed nation with an older and/or energy inefficient housing stock. A study of improvements to urban low-cost housing in South Africa, by Winkler et al (2002), is especially pertinent with growing urban populations worldwide. Koomey et al (1998) reviewed the US residential and commercial building sectors. This study follows more of an engineering-economic approach but cites indirect benefits (e.g. – improved health, comfort and safety) as important factors in addition to energy cost savings and GHG emission reductions. The significance of the Koomey et al study is that the EEPs under review (medium and high efficiency scenarios) yield financial gains.

These studies all conclude that the respective energy efficiency policies have a net positive benefit. The most socially compelling analyses are by Goodacre, Sharple and Smith and Clinch and Healy. These studies link the issue of fuel poverty, defined as the inability to pay for adequate levels of heating, with occupant comfort and health. This addresses an issue common to energy efficiency programs in recognizing a socio-economic divide between those that could benefit most from efficiency upgrades and their ability to pay. Low-income households pay a higher percentage of their disposable income on heating their homes. As a result homes are often maintained below comfort levels. This fact, coupled with an inefficient housing stock, can lead to an increase in cold and dampness related illness or death. While these studies are focused within the United Kingdom, similar analogies between being able to afford space-conditioning energy inputs and occupant comfort and health could be made in other jurisdictions and climates. The reduction in health care costs resulting from changes in mortality and morbidity make up a considerable proportion of the gross benefits in both cases. Additionally, the UK studies include job creation as a social benefit. This element, while not a dominant component of the gross benefit, is significant. Energy efficiency upgrades can be labour intensive. The synergy between a climate mitigation policy and job creation should not be overlooked.

The approaches taken in the UK reports are the most inclusive and discuss the broader implications of an energy efficiency program for buildings. Winkler et al’s study of low-cost urban housing could be improved by incorporating benefits associated with health and employment. The opportunities to improve quality of life while encouraging job creation are seemingly obvious benefits especially when considering a low-income demographic. However, assuming these effects are net positive benefits, they would only add to the attractiveness of the policy reviewed. Their analysis results in net benefit to the consumer when disregarding external costs (as per a process detailed in (CEC, 1987)). These costs were included in the social analysis. While seemingly incomplete in assessing the full spectrum of costs and benefits, the Winkler et al study does a good job of addressing the affordability of capital improvements for the very poor. Many South Africans in the study have little savings or access to low-cost credit; a portion of the households included families living in shacks. The capital subsidy proposed recognizes that the poor place some value on energy efficiency. This value is subtracted from the incremental capital cost of the efficiency upgrade to determine the required subsidy (Winkler et al, 2002: 600).

Clinch and Healey and Goodacre, Sharple and Smith evaluate over a range of discount rates, Koomey et al use a fixed rate of 7%, but Winkler et al take a unique approach to discounting. Their analysis assigns a different rate to the social benefits (8% as per the South African Reserve Bank) and consumer benefits (30%). Their use of a high consumer discount rate is justified as noted in Howarth and Sanstad, although evaluating components of a program at different discount rates is generally considered bad practice. The high consumer discount rate, however, likely results in a more realistic calculation of the subsidy required for an energy-efficiency program in low-income settings. As it is the rate used in the subsidy calculation, this rate corresponds more closely with how low-income consumers make investment decisions. Use of the social rate in this case would result in a subsidy payment that is too small. A similar analysis could be applied in other developing countries should they use EEPs as climate mitigation tools. Both UK studies found the costs greater than the benefits with a discount rate higher than about 10%. A long term public investment in energy efficiency as part of a climate mitigation strategy would likely be discounted at a rate lower than what investors might expect as a return on a standard financial instrument. If this is true, then the appropriate discount rate will likely be below 10% resulting in a net social benefit from these programs.

A particularly important input if considering an EEP for climate mitigation is the cost of carbon. The studies reviewed were priced at different times and in different currencies. Koomey et al cost carbon (CO₂ in particular) the highest at US$50.00/tonne in 1998 dollars. The others had CO₂ valued under US$10.00/tonne in their respective years (all after 1998). Holding all other things constant, a higher cost of carbon is incentive to push for better efficiency improvements. However, in terms of the energy efficiency upgrades in the UK studies, it was the difference in energy use and greenhouse gas emission before and after the upgrade that were included in the cost benefit analysis. A higher price of carbon results in a greater net benefit from the upgrade. This sort of accounting could create a situation where lower efficiency (and presumably lower cost) options would become more attractive as even a small marginal greenhouse gas emission reduction could have high value (assuming sufficiently high cost of CO₂). This could create a situation where policy makers maximize net benefit but do not maximize potential emission reductions. This is not the case, however, if the total annual building energy use is taken into account (and associated GHG emissions), as appears to have been done by Koomey et al.

While it has been shown that EEPs for buildings are likely to yield net social and financial benefits, it is important to evaluate the results more broadly in the context of mitigating climate change. The high efficiency scenario from Koomey et al estimates a 60 MtC (or 222 MtCO₂) reduction from a business as usual scenario in 2010. Consider that the total carbon emissions in the United States from 2005 were 5,495 MtCO₂ (US DOE, 2007: 343). While it is not completely fair to compare a 2010 projection to 2005 data, doing so shows the high efficiency case described by Koomey et al results in roughly a 1% decrease in national CO₂ emissions. This analysis can be a bit misleading as greater efficiency improvements are possible, especially in new construction. However, it does reveal the fact that energy efficiency in buildings can only contribute in part to what would likely be required of a climate change mitigation effort. While EEPs may not be a dominant component in controlling atmospheric emissions, these studies have shown they have the capacity to create jobs, increase health and improve overall quality of life. For these reasons alone they warrant the attention of policymakers.

References:

Brown, M. A., Levine, M. D., Romm, J. P., Rosenfeld, A. H., & Koomey, J. G. (1998). Engineering-economic studies of energy technologies to reduce greenhouse gas emissions: Opportunities and challenges. Annual Review of Energy and Environment, 23, 287-385.

Brown, M. A., & Southworth, F. (2006). Mitigating climate change through green buildings and smart growth, working paper #23. Environment and Planning A, Forthcoming

California Energy Comission (CEC). (1987). Standard practice manual: Economic analysis of demand-side management programs. Sacramento, CA: CEC.

Clinch, J. P., & Healy, J. D. (2001). Cost-benefit analysis of domestic energy efficiency. Energy Policy, 29, 113-124.

Goodacre, C., Sharples, S., & Smith, P. (2002). Integrating energy efficiency with the social agenda in sustainability. Energy and Buildings, 34, 53-61.

Howarth, R. B., & Sanstad, A. H. (1995). Discount rates and energy efficiency. Contemporary Economic Policy, 13, 101-109.

IPCC. (2007). Summary for policymakers. in: Climate change 2007: Mitigation, contribution of working group III to the fourth assessment report of the intergovernmental panel on climate change. Cambridge, UK and New York, NY, USA: Cambridge University Press.

Koomey, J. G., Martin, N. C., Brown, M. A., Price, L. K., & Levine, M. D. (1998). Cost of reducing carbon emissions: US building sector scenarios. Energy Policy, 26(5), 433-440.

Levine, M., urge-Vorsatz, D., Blok, K., Geng, L., Harvey, D., Lang, S., et al. (2007). Residential and commercial buildings. in Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK and New York, NY, USA: Cambridge University Press.

Natural Resources Canada (NRCan). (2006). Energy use data handbook: 1990 and 1998 to 2004. Retrieved 10/13, 2007, from www.oee.nrcan.gc.ca/Publications/statistics/handbook06/pdf/handbook06.pdf

US Department of Energy (US DOE). (2007). Annual energy review 2006. Retrieved 10/08, 2007, from http://www.eia.doe.gov/emeu/aer/contents.html

Winkler, H., Spalding-fecher, R., Tyani, L., & Matibe, K. (2002). Cost-benefit analysis of energy efficiency in urban low-cost housing. Development Southern Africa, 19(5), 593-614.