Published on March 8th, 2013 | by Andrew1
US Electricity Consumption Much More Evenly Distributed Than Income, Wealth
March 8th, 2013 by Andrew
Widening gaps in income and wealth in the US over the past three-plus decades have been receiving a lot of attention in recent years. The top 1% of US households take home nearly 20% of national income, while the top 10% of US households account for nearly 75% of total net worth, or national wealth. The bottom 40% barely have any, while the less affluent half accounts for just 1.1%. These trends have worsened since the 2008-2009 financial meltdown and recession, troubling signs for US democracy and capitalism.
The attention being paid to US income and wealth distribution led Opower — developer of an award-winning residential energy management platform now being used by more than 75 utilities and 15 million homes around the world — to examine the distribution of electricity consumption among US households, “and what it means for the viability of energy efficiency as a distributed resource.”
Opower found that electricity consumption is much more evenly distributed than income in the US: the top 1% of households consume 4% of total US residential electricity and spend 4x more per year on electricity than the the average household – $4,000: $1,000. Casting a wider net and digging deeper into the data revealed insights with far-reaching implications when it comes to crafting energy policies, reducing energy consumption, and enhancing energy efficiency in US homes.
Disparities In US Residential Electricity Use & Income
In order to make apples-to-apples statistical comparisons, Opower analysts narrowed down the data set of 25.8 million homes for which it had 2011 electricity usage information to the 8.57 million that it confirmed have natural-gas heating systems, “the prevalent heating fuel across the US,” Opower’s Barry Fischer explains in the report.
PayScale’s “CEO Pay Put into Perspective” and “Fortune 50 ratio of CEO-to-worker pay ratio analysis” highlight the huge, and growing, disparities in income and wealth in the US. According to the latter study, income among US CEOs ranged from a low of 10x to 1,737x that of the average workers in their companies.
With the top 1% of US households consuming an average 4x more electricity per year than the average US household, the distribution of energy consumption is much more evenly distributed than that for US income and wealth, Opower found. The heaviest 10% of households by usage account for nearly 25% of total residential electricity use. But that’s just the beginning of the story.
According to Opower’s analysis:
- Supplying electricity to each US household in the top 1% entails greenhouse gas pollution from power plants equivalent to driving 5 gasoline-powered cars for a year. In comparison, the average household’s electric usage contributes pollution equivalent to 1.25 cars.
- 1 day of combined residential electricity usage across the top 1% of US households (comprising approximately 3.1 million people) is roughly equal to 1 year of total electricity consumption in the African country of Sierra Leone (a nation of 5.5 million people).
The Gini’s Out Of The Bottle
Gini coefficients are commonly used as a metric for succinctly describing the distribution of a wide range of data types, from income and wealth to land ownership and electricity usage. A Gini coefficient of 0 represents an equal distribution across a sample population, while a Gini coefficient of 1 indicates a single member has or uses all of the variable in question.
Citing an example, nearly all the land in Qatar is owned by the Emir of Qatar. Hence Qatar’s Gini coefficient for land ownership is 0.9. Land ownership in Norway, in contrast, is much more evenly distributed across society. Its Gini coefficient is 0.18.
The US Gini coefficient for income is 0.47, whereas the US Gini coefficient for residential electricity consumption is 0.34 based on Opower’s data set, a finding “consistent with other studies that have statistically examined the distribution of energy and utilities.”
These disparities led Opower’s analysts to broaden their perspective, as well as dig deeper into the data, in order to determine what’s driving them.
Confirming the results of previous studies, Opower found a strong, positive correlation between US residential electricity use and home size. The average US mega-home (among the largest 1% by square feet) uses more than 2.5x the electricity of the average US home (approximately 1,600 square feet).
Larger homes use more electricity; thats makes intuitive sense. Yet Opower also found substantial variation in US homes of the same size: residential energy usage commonly varies by as much as 6x in homes of the same square footage.
According to the report authors:
“This wide degree of variation suggests that while home size can serve as a rough predictor for usage, other factors – such as income, occupancy, climate, construction features, and especially behavior – are also important drivers.”
As it turns out, the economic concept of diminishing marginal utility is important to understanding why US electricity usage is so much more evenly distributed than income or wealth. As Opower explains, at its most basic level, diminishing marginally utility hypothesizes that “as we obtain more of a good, we value each additional unit less.
“For example, there’s a big difference between having no fridge and one fridge in a home. But there is much less incremental value of going from four fridges to five fridges. In other words, people’s demand for electricity has its limits, even as their income may grow.”
Another factor explaining the difference is that wealthier Americans living in larger homes are also more willing and able to invest in energy efficiency improvements, such as insulation and triple-pane windows, according to Opower.
While the top 1% of US homes use 4x as much electricity than average, they only account for a small percentage of overall consumption. That has important implications when it comes to “how to go about reducing residential energy consumption,” Opower’s analysts point out.
“Large-scale energy efficiency efforts (e.g. cutting energy waste in half by 2030) can’t exclusively focus on the very highest users, for the simple reason that such homes are in limited supply (e.g. only 4% of homes).”
Opower’s innovative residential energy management platform and business model are illustrative of the broad-based approach that is required enhance national energy efficiency and reduce energy consumption, the report authors state. Its “behavioral efficiency programs have enabled millions of households to save energy, regardless of their geographic location, home size, income segment, age, and initial level of consumption,” they note.
Moreover, they continue:
“Energy efficiency initiatives that successfully reach large swathes of the population are likely to do more than save a lot of energy: they may also provide certain groups — such as seniors and low-income families — with much-needed relief from burdensome energy costs.
“For example, recent statistics show that elderly and needy American families routinely see 19-26% of their paycheck go toward utility costs, compared to just 4% for the median American household. This suggests that effective broad-based energy efficiency programs like Opower’s can be beneficial along multiple dimensions — environmental, social, and monetary.”
Limited as it is to analyzing the distribution of electricity usage among US homes, a comprehensive assessment of Americans’ relative energy and carbon footprints would have to encompass the transportation, commercial and industrial sectors as well, Opower points out. “A peek at the transportation sector suggests that Americans’ energy usage in the air and on the roads may be more unequal than in their homes.”
The report authors cite airline industry market research indicating that less than 6% of the US populace – some 17 million Americans – account for 58% of all flights taken by Americans. Associated carbon emissions “are disproportionately large: the global warming pollution from one round-trip flight between San Francisco and New York is equivalent to ~1 month of an average home’s electricity use.”
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