Post tagged with "home size"


America’s energy distribution: the top 1% of homes consume 4 times more electricity than average (and why it matters)

  • By Barry Fischer
  • March 6, 2013

The novelist William Gibson is widely credited for noting that “the future is here, it’s just not evenly distributed.” That was back in the 1990s.

Since then, changes in how things are distributed in our society have been cause for both hope and concern.

On the one hand, improvements in semiconductor technology for things like computer chips and solar panels have made ideas like “distributed computing” and “distributed energy” a practical reality. On the other hand, recent economic turmoil has brought America’s uneven distribution of wealth and income under scrutiny.

With both of those threads in mind, we thought it would be interesting to consider how evenly energy consumption is distributed, and what that means for the viability of energy efficiency as a distributed resource.

So we’ve drawn upon our vast dataset of US electricity consumption to examine some key distribution-related questions:

  • Among American households, what’s the breakdown between high, medium, and low electricity users? 
  • What drives differences in electricity consumption across households?
  • Is electricity consumption as unequally distributed as the nation’s income?
  • What does the nation’s electricity distribution suggest about how to go about saving energy at scale?

Starting with 25.8 million homes for which we had 2011 electricity usage information, we narrowed the dataset to 8.57 million American homes that we confirmed have natural-gas heating systems (the prevalent heating fuel across the US).  In this way, we could make an apples-to-apples statistical comparison of different homes’ energy use.

We discovered that the top 1% of homes consume a full four times more electricity than average. Still, residential electricity usage ends up being much more evenly distributed than income. We’ll draw upon a couple key economic principles to explain why that is, and describe how the shape of the nation’s electricity distribution is a critical consideration in any large-scale effort to make America more energy efficient.

The Top 1% of households (by usage) consume 4% of residential electricity

Put another way, for every unit of electricity the average American home consumes, the top 1% of homes (by usage) are consuming four units.  And the heaviest 10% percent of users are responsible for nearly a quarter of all residential electricity use.

The top 1% of users consume 4% of residential electricity
What else does this mean?

  • The top 1% of households (by usage) spend approximately $4,000 per year on electricity, while the average household’s yearly electric bill is around $1,000.
  • Supplying electricity to each 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).

What’s driving the disparity in how Americans consume electricity?

Mega-Homes Mean Mega Usage (Usually)

Generally, the prime suspect in the search for causes of high energy use is large home size (i.e. square footage).

To investigate, we evaluated the relationship between electricity consumption and home size across more than 4.3 million residences in our dataset. We wanted to see how electricity usage of a mega home (i.e. among the largest 1% of homes) compares to that of an average-sized home in our dataset (approximately 1,600 square feet). 

Our findings reveal a marked difference: an average mega-home uses 2.5 times more electricity each year than a typical home.

The largest homes use 2.5x as much electricity

In this light, the chart below displays a predictable correlation: the larger the home, the higher the electric bill.

Average electricity usage by home size

But while a general correlation between home size and energy consumption makes intuitive sense (e.g. more space to cool, more rooms with TVs), a deeper examination of the data reveals a complication: there can be substantial variation in electricity use among homes that have the same square footage.

To see how this is true, take a look at the line graph below: it shows that among households of the same square footage, it is not uncommon for energy usage to vary by as much as six times. 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.

Variation in usage by size of home

Electricity usage is much more equally distributed than income

We’ve seen that the top 1% of electricity users consume 4% of the nation’s residential electricity. How should we view this in relation to income distribution in the US, where the top 1% of households take home nearly 20% of national income?

We shouldn’t be super surprised that household electricity consumption is more equally distributed than income. That’s because as a family’s income increases, their electricity consumption is likely to grow less than proportionally.

The principle at work here is a straightforward concept from Economics 101, called “diminishing marginal utility.”  Basically, 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 reason that the distribution of electricity is more equal than income is that, although wealthier Americans are likely to live in larger homes, they are also more able and likely to invest in energy-efficiency improvements like insulation and triple-pane windows.

A nifty way to compare the distribution of electricity and income is to use a statistical measure called a Gini coefficient (named after the Italian sociologist who created it), which is a number that ranges between zero and one. A Gini coefficient of 1 indicates a totally unequal situation (e.g. a single household using all the electricity in the country), whereas lower values (i.e. closer to 0) represent a more equal distribution of resources.

For instance, the Gini coefficient for land ownership in the Middle-Eastern country Qatar is equal to 0.9, as the Emir of Qatar owns almost all the land in that country. By contrast, land ownership in Norway has a Gini coefficient of 0.18, reflecting greater equality in the distribution of land there.

Gini Coefficients of Land in Norway and Qatar

The Gini coefficient for income in the US is around 0.47.  Based on our dataset, the Gini for residential electricity consumption is 0.34 (see Methodology), further suggesting that it is much more equally distributed than income. This finding is consistent with other studies that have statistically examined the distribution of energy and utilities.

Why understanding energy distribution is important for realizing efficiency opportunities

We’ve seen that, at least when compared to income, residential electricity consumption in the US is relatively evenly distributed. The top 1% of US homes, although they use 4 times more electricity than average, only account for a sliver of overall national consumption.

Therein lies an important implication for how to go about reducing residential energy consumption: 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).

Instead, saving energy at scale requires a broad-based approach that works well for homes across the usage spectrum. And such approaches do exist, as evidenced by Opower’s own behavioral efficiency programs – which have enabled millions of households to save energy, regardless of their geographic location, home size, income segment, age, and initial level of consumption.

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 bills, 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. 

While there are differences in how American homes use energy, there are often similarities in their ability and reasons to use less.  To explore which savings opportunities are most relevant to you, your utility’s website or the new EnergySavers portal from the US Department of Energy are great places to start.  Because the future is here…and it’s full of potential for energy efficiency. 

Special thanks to David Moore, Jon Margolick, Chris Corcoran, Katie Dewitt, Jillian Cairns, Efrat Levush, Ashley Sudney, Tyler Curtis, and Arhan Gunel.

Follow @OpowerOutlier on Twitter

Appendix: Questions for the curious reader to consider

The foregoing analysis has left a few questions lingering in our heads:

1. Are we underestimating energy usage inequality by not accounting for multiple-home ownership?

We evaluated the distribution of electricity by treating every household as a distinct energy-consuming unit. Given that some families consume electricity across multiple homes, our analysis may be understating inequality. In some cases, multiple-home ownership may be nontrivial. The 2010 Census found that 3.5% of homes nationwide are for seasonal, recreational, or occasional use.  And in some states, that fraction exceeds 10%.

 2. Are the heaviest electricity users necessarily less energy efficient?

No. From an environmental and energy-efficiency perspective, high electricity consumption may not always be a bad thing. For example, a large multi-generational family living under one roof is likely to face a high electricity bill, but compared to a scenario where all family members live in separate homes, per capita energy consumption may be quite low.

Similarly, if you own a plug-in electric car, your annual electricity consumption will increase significantly.  Consider an all-electric Nissan Leaf vehicle driven 12,000 miles per year: at a fuel economy of 34 kilowatt-hours (kWh) per 100 miles, it will require 4,080 kWh of electric charging— increasing an average home’s annual electricity usage by 40-50%.  But, relative to driving an average gasoline-powered car, your environmental impact and overall energy costs will decrease.

3. How does the distribution of residential electricity compare to other measures of energy inequality?

To fully assess Americans’ relative energy and carbon footprints, it’s necessary to look beyond household electricity usage. 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.

For example, market research from the airline industry suggests that 17 million Americans (less than 6% of us) account for 58% of all flights taken by Americans.  And the energy-related carbon emissions from flying are disproportionately large: the global warming pollution from one round-trip flight between San Francisco and New York (for a single customer) is equivalent to ~1 month of an average home’s electricity use. A recent New York Times analysis suggests that if you take five long flights a year, they may well account for three-quarters of the total pollution you create.

Day-to-day, the energy consumed for getting around town may exhibit a similarly unequal distribution, especially through a suburban versus urban lens: the EPA has calculated that the transportation energy use of a household in a typical suburban area is more than double that of a household in a transit-accessible area.


For the purposes of comparability, we narrowed our dataset to 8.57 million homes that have natural-gas heating systems.  Analyzing gas-heat homes helps reduce the effect of exogenous/climate-related factors on our analysis.  For example, Minnesota’s winter is much colder than northern California’s winter, but our analysis is to a significant degree insulated from this variation because the homes we considered do their heating with natural gas rather than electricity. This approach is especially important because heating represents a large fraction (42%) of home energy use.

Estimates for annual electricity costs are based on the average 2011 US retail electricity rate of $0.118/kWh. Note that average annual US household consumption is estimated at 11,496 kWh.  Our average value (8,548 kWh) is lower largely because we have intentionally restricted our dataset to gas-heat households.

To compute a Gini coefficient for residential electricity consumption, we divided the 8.57 million households in our dataset into 100 groups of equal size, to determine percentiles of consumption. We computed each percentile group’s share of total electricity consumption, and then determined the cumulative share of consumption up to each percentile level. This data series allows for the construction of a Lorenz curve equation, L(X), which we integrated between 0 and 1 using a Riemann-sum approach across the 100 subintervals.

The resulting Gini coefficient (G) for residential electricity consumption, G = 1- 2 ∫ L(X) dx, was 0.34. This result parallels the 0.37 Gini coefficient for US residential electricity consumption computed by Jacobson, Milman, and Kammen (2004). It makes sense that our Gini coefficient is slightly lower (i.e. reflecting a more even distribution) than the literature’s existing estimate, as our analysis controls for heating type while Jacobson et al. appears not to.

Households in our dataset for this analysis are distributed across 23 states.  Although geographically diverse, this dataset is not a perfectly representative sample of American households. However, we are confident that it is the largest dataset ever analyzed for the purpose of examining the distribution of US residential energy consumption, and that our analytical results are validly indicative of a national phenomenon.

Sierra Leone’s national electricity consumption was 111,600 MWh in 2009. The average annual electricity usage of a top-1% household in our data set is 33,654 kWh. Extrapolative multiplication of this usage by 1,147,614 households (i.e. 1% of the US’ 114,761,359 households) yields 38,621,802 MWh/year, or (dividing by 365) 105,813 MWh per day. This amount of electricity is approximately equivalent to Sierra Leone’s total annual consumption across all sectors. 

The greenhouse gas pollution from one round-trip flight between San Francisco and New York is 675 kg CO2, according to the International Civil Aviation Organization’s carbon emissions calculator. 675 kg CO2 is tantamount to approximately 1 month of an average home’s electricity use, according to the EPA’s Greenhouse Gas Equivalencies Calculator.

Data Privacy: All data analyzed here are anonymous and treated in strict adherence to Opower’s Data Principles.

Author’s note: The analysis and commentary presented above solely reflect the views of the author(s) and do not reflect the views of Opower’s utility partners.

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You’ve got mail: How AOL and Hotmail households consume electricity

  • By Barry Fischer
  • June 20, 2012

Many readers enjoyed our post last week about how/why Yahoo Mail subscribers spend $110 more per year on electricity than Gmailers. But, some commenters were curious about AOL and Hotmail. That got us curious too.

Our initial analysis of the relationship between email address and electricity consumption focused on Yahoo Mail and Gmail because they were the most popular domains (representing 1.15 million homes) in our data set. The next two most common email services were AOL and Hotmail. And so today we examine the energy use of an additional 594,000 homes, corresponding to AOL Mail and Hotmail.

The results…

AOL Mail users (sorry, Mom) are on average spending $182 more per year on electricity than Gmail users (a difference of 18%).

AOL Mail users use 18% more electricity than Gmailers

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The Triumph of Gmail? How Yahoo users are spending $110 more per year on electricity.

  • By Barry Fischer
  • June 14, 2012

In this inaugural post of the Outlier, we delve into our storehouse of household energy data (covering 40 million US homes) to examine how people’s energy usage is correlated with their email address.

We looked at the correlation between email address and electricity usage across 2.8 million American households.  Of those, we focused on Yahoo Mail and Gmail because they were the most popular domains in our dataset. The email addresses correspond to the member of the household who manages the electricity bill.

We realize that Yahoo has had a rough stretch lately:


Now we have more bad news for Yahoo…

We found that the average Yahoo Mail household uses 11% more electricity per year than a Gmail household.  It’s a sizeable, statistically significant difference (see Methodology).

Consider this: the aggregate difference in annual electricity use between 1 million Yahoo households and 1 million Gmail households is…equal to the entire annual electricity consumption of Barbados, a reasonably well-off country of 287,000 people.

Let’s dig into the numbers and find out what’s going on here…

The average Yahoo Mail household spends $110 more per year on electricity than a Gmail household.

The usage difference — 939 kilowatt-hours per year — is stark: Yahoo households consume almost a whole extra month of electricity relative to Gmail households. At an average going-rate of 11.8 cents/kWh, that’s a difference of $110 per year.

Yahoo subscribers consume 11% more electricity than Gmail users

It’s as if, relative to the average Yahoo household, the average Gmailer is strictly hang-drying their laundry, forgoing high-definition TV, and hand-washing their dishes with cold water for a year.

939 kWh is equivalent to...

We can establish off the bat that the “email-domain versus usage” relationship is one of correlation, not causation. So then, what underlying differences exist between Gmail and Yahoo users that can help explain their dramatic disparity in electricity usage?

Exploring reasons for the disparity between Gmailers’ and Yahoo users’ electricity consumption

There are some key demographic and lifestyle differences between Gmailers and Yahoo users that are likely to affect their household electricity usage.

We’re not the first researchers to think that Yahoo and Gmail users are different:

  • Last year, discovered, among other things, that Yahoo users tend to lounge around in pajamas at home and enjoy sweet snacks; Gmail folks, on the other hand, are more likely to lounge in jeans and prefer salty snacks.
  • The personal finance company Credit Karma has found that Yahoo users have noticeably lower credit scores (652) than Gmail users (682).
  • Last week, the online-dating site determined that Gmail users tend to have a higher “desirability quotient” than Yahoo users

But let’s explore some of the differences between Yahoo users and Gmailers that are likely at play in driving the disparity in their electricity consumption.

Do Yahoo users and Gmailers live in fundamentally different climates or use different fuels to heat their home?

No.  It’s true that climate and heating fuel vary significantly by region, and can have a large effect on energy consumption. For example, of the 1.8 million Michigan homes in our database, nearly 60% of them get through frigid winters by heating their homes with natural gas.  In contrast, the majority of the 780,000 North Carolinian homes in our database use electric heating systems (and they also face a milder climate).

But neither climate nor heating fuel should be expected to correlate meaningfully with email address domain here.

The reason is that the 1.15 million Gmail and Yahoo users in our dataset are spread out across 23 states and several distinct climate zones. There is no clear pattern that emerges wherein Gmail or Yahoo Mail is more popular in one particular state or climate zone than another.  This geographic spread of Gmail and YahooMail makes sense: anyone is free to sign up for either domain.

Do Yahoo users consume more electricity simply because they live in larger homes?

Yes and No. Yahoo users do appear to live in larger residences, which increases their total energy needs. But they also consume more electricity per square foot than Gmail users.

How do we know that Yahoo users tend to live in larger homes? Our friends at Experian and have found that Yahoo users tend to live in suburbs and rural areas, while Gmailers live in cities.  Data sourced from the 2009 US American Housing Survey suggest that suburban-rural residences (i.e. where the Yahoo Mailers live) are on average 7-13% larger than in cities (where Gmailers live), and also have more occupants (i.e. extra electricity-using human beings in Yahoo homes).

Our own household characteristics data similarly suggest that Yahoo users reside in larger residences: Yahoo households are approximately 10% more likely than Gmail households to live in single-family residences (as opposed to apartments and condos).

But, even controlling for home size, we found that Yahoo households are still more energy-intensive than Gmail households. Based on square footage data that we have for single-family residences, we found that the typical YahooMail household uses 12% more electricity per square foot of living space (6.84 kWh/sqft) than the typical Gmail household (6.09 kWh/sqft).

Yahoo subscribers consume 12% more electricity per square foot

Do Gmailers and Yahoo users have different lifestyles?

Yes. and Experian have found that Gmailers are more likely to be younger, single people.  Credit Karma found the average Gmailer’s age to be 34, while the average Yahoo user clocked in at age 38.  Being young and single means going out more; less time at home – and fewer occupants – means less electricity usage.

By contrast, Yahoo users are more likely to be in relationships and have children. Additionally, Hunch found that Gmail users are more likely to be active travelers (having journeyed to 5 or more countries), and so might be away from home more often.

Our own data also suggest that Gmail users may have a greater interest in energy-efficiency. Among the approximately 10 million US households that have access to utility web-based energy-efficiency advice tools that Opower manages, Gmail users are 30% more likely than Yahoo users to sign up for an in-depth analysis of how they can reduce their energy usage.

Gmail users are 30% more likely to sign up for an online energy analysis

It’s not definitive, but it appears that several lifestyle choices correlated with Gmail use are also correlated with lower home energy use.

What are Yahoo Mail users to do?

If Yahoo households want to slash their energy consumption to Gmail levels, it’s probably going to involve more than just switching to a Gmail account (nice try!). For the benefit of Yahoo users and Gmailers alike, we’ll aspire to sprinkle in energy-efficiency advice in future posts that will help all folks reduce their energy bills.

Update: Some commenters were curious about AOL and Hotmail. That got us curious too. Check out those results here.

Special thanks to my data-crunching partner Jillian Cairns and our all-star designer Efrat Levush. They are proud Gmail users.

Methodology: Annual electricity usage of households is based on 2011 data. Of the 2.8 million household electricity customers with email addresses in Opower’s dataset, 1.15 million were Gmail or Yahoo users.  The usage difference between Yahoo users and Gmail users is statistically significant at the 99% confidence level based on a t-distribution.

Barbados’ electricity consumption in 2008 was 945 million kWh. Dryer usage based on 1.89 kWh/cycle, derived from LBNL paper. TV usage based on 40″ Digital HD model from US DOE. Dishwasher usage based on 1 kWh/cycle (Energy Star) from NRDC.

Data Privacy: All data analyzed here are anonymous and treated in strict adherence to Opower’s Data Principles.

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