I recently did a little research attempting to understand the effects of Citizens' Climate Lobby's carbon fee and dividend proposal on people in the lowest quintile of income earners. Below is the result of that research.
Above Average Carbon Emitters Among Low
Income Households[*]
Alan Mattlage,
Ph.D., M.L.S.
One of many strengths of Citizens’ Climate Lobby’s (CCL)
carbon fee and dividend proposal is that it provides a net benefit to 86% of
households in the lowest quintile of income earners (Ummel, 2016). The progressive distribution of benefits is
driven by the fact that lower income households tend to have lower than average
carbon footprints but will receive a modified equal per capita share of the
revenues from the fee (one share for each adult and one-half share for each
child up to two children per family). This
makes the proposal one of the most economically progressive methods for
transitioning to a de-carbonized economy.
See Figure 1. Benefiting 86% still
leaves 14% of the lowest quintile worse off – that’s about 2.8% of all American
households or about 3.5 million households (U.S. Census Bureau, 2016). The following is an attempt to understand why
these households are made worse off, how significant the burden is, and what
can be done to relieve that burden.
The short answer is that we cannot know precisely who is
burdened, but there are data that can give us a general understanding of the
circumstances that will tend to make a household worse-off.
Figure 1 – Distribution of
benefits and burdens across quintiles
Why are households
made worse-off?
The obvious reason households are made worse off is that
their dividend is less than the cost they incur from the carbon fee. This is true no matter which quintile the
household is in. To answer the question
why are 14% of the lowest income households made worse off, we need to
understand why a household might have above-average emissions. Some of those reasons will be particularly
common to low income households.
A net financial loss is probably the result of some
combination of the following factors:
1. the household is composed of a single person,
2. the household’s electricity is provided
disproportionately by a carbon-intensive fuel, like coal,
3. the household is located in a particularly harsh
climate,
4. the household is poorly insulated and has inefficient HVAC
equipment and appliances,
5. the household’s transportation costs are particularly
high, and
6. the household buys an unusually large amount of carbon
intensive consumer goods and services.
1. Household Composition
Perhaps the most important factor of all is the
household’s size. Single person
households will receive only one dividend share, while needing to cover the
entire cost of maintaining the household, e.g., utilities, transportation, and
necessary household consumer goods.
Meanwhile, a two-adult household will receive twice the dividend, but they
will share many of the costs of maintaining the household. Consequently, single person households are
likely to be disproportionately represented in those households suffering a
loss no matter what income quintile they are in.
This has been borne out by the household impact study
conducted by Kevin Ummel for Citizens’ Climate Lobby. Ummel compared the net benefits going to two
household types: “minority households” and “elderly households.” Minority households are composed of more
members (sometimes more than two adults which compounds the dividend). Elderly households are, by definition,
composed of only one or two adults. These
households have similar incomes, but the mean benefit accruing to minority
households would be significantly greater than the mean benefit accruing to
elderly households: $148/year for
minority households versus $2/year for elderly households considering all
households (Ummel, 2016, p. 31; U.S. Census Bureau, 2016). For households in just the lowest quintile,
99% of families of four are benefitted, while 81% of elderly households are
benefitted. The mean benefits for these
households are $596/year and $138/year respectively. These disparities show that living in a small
or single person household contributes to a financial burden under the fee and
dividend proposal.
2. Local Carbon Intensity of Electricity
Ummel also broke down the consumer habits of each income
quintile into nine categories and determined the carbon tax burden for each
category. See Figure 2. The largest single category for all but the
top quintile is “utilities.” Consequently,
households that run on especially carbon intensive electricity would be
disadvantaged by the carbon fee, while households running on clean energy would
tend to benefit (Ummel, 2016, p. 34).
The importance of this factor is suggested by comparing Figures 3 and 4. There is a rough correlation between the
geographic distribution of the carbon intensity of the electricity supply and
the financial impact on households in the lowest quintile.
3. Harsh Climates
Little need be said about this. Households in especially cold or hot climates
certainly will have higher utility costs than households in milder climates;
however, in light of Figure 4, this factor does not seem to be particularly
significant as many regions of the country experiencing harsh climates tend to
enjoy
Figure 2
– National tax burden by quintile
relatively greater benefits, e.g. New England, Florida,
the Southwest, and Montana. With
inevitable changes to the climate, many climates will become harsher,
increasing the importance of this factor.
4. Poor Insulation and Inefficient HVAC Equipment and
Appliances
Again, it is obvious that households which live in poorly
insulated housing and have inefficient HVAC equipment and appliances will bear
a greater burden from a carbon tax as more energy will be required to achieve
the same results. This is a particularly
significant problem for poor, low income households. Such households often live in rental
property, the owner of which is unconcerned about energy efficiency since the
utilities are paid by the tenants. Low
income housing stock is significantly less efficient than average. If low income housing were brought up to the
national average, low income households would see a 35% reduction in their
utility costs (Drehbol and Ross, 2016).
5. Transportation
The second largest category is “gasoline,” but while our
common acquaintance with gasoline as a fossil fuel might lead us to think this
would be the most significant factor in establishing a household’s carbon
footprint, it actually makes up less than 25% of the total carbon footprint of
U.S. households. Still, if a household
uses more gasoline than the national average, this factor will contribute to
reducing the benefit they would receive from the carbon dividend and might, like
other carbon-intensive factors, push them into a net loss.
Figure 3 – Carbon intensity of energy supply
Figure 4 – Lowest quintile households
benefited by fee and dividend
However, simply comparing gasoline costs between the
lowest quintile and other quintiles might not be very revealing, since a
disproportionate number of households in the lowest quintile likely will not
have cars. This means the gasoline costs
borne by households in the lowest quintile will fall mainly on the car-owning
households.
6. Indirect Costs
Utility costs and gasoline costs are “direct” energy
purchases. For the lowest income
quintile, they make up 50% of the total costs.
The other categories are “indirect” energy purchases that appear as
embodied energy in the goods and services that a household purchases. Any household which purchases goods and
services which are in total more carbon intensive than those purchased by the
average household will find their net financial benefits lowered by these
categories of expenditures, possibly pushing them into a net loss. Because indirect purchases make up 50% of the
lowest quintile’s energy purchases and even larger percentages of higher
quintiles, these purchases are especially important in determining a household’s
net benefit. Indirect costs are the primary
factor that burdens the higher quintiles and benefits the lowest income
quintile, but lowest quintile households that purchase consumer products with
an above average carbon footprint, nevertheless, will be penalized by these
categories of purchases.
If a household remains well-enough below average in
enough of the consumption categories, it will likely benefit from the fee and
dividend mechanism, despite a high carbon footprint in other categories;
however, if their consumption is in total above average across these
categories, they will suffer a loss. The
worst-case scenario would likely be a single-person household, reliant upon
carbon-based electricity, in a harsh environment, living in a poorly insulated
house, with a long commute, purchasing unusually carbon-intensive goods and
services. Surely not every one of these
conditions need hold to push someone into a loss, but various combinations of
these factors could do so. No single
profile of a low-income household can tell the story for all 3.5 million
households.
How significant is
the burden?
Forty-seven percent of all households suffer a loss and
their median loss amounts to $195/year.
Among the lowest income quintile, only 14% of households suffer a loss
and their median loss is only $96/year or $8/month. Consequently, the absolute burden is least
for households in the lowest income quintile, but their median loss amounts to
0.79% of their income while the median loss nationally is only 0.25% of
income. So even as the lowest quintile
is much more carbon virtuous than higher quintiles, their low income could make
managing their loss nevertheless more difficult.
There are additional considerations that are aggravating factors:
1. steadily rising fee,
2. limited conservation options for households in the
lowest income quintile, and
3. the ability of higher income quintiles to achieve
conservation savings.
CCL’s fees are proposed to begin at $15 in the first year
and rise $10 in each subsequent year.
This means that the households (in all quintiles) that benefit will gain
greater benefits as more revenue is collected, but burdened households will be
made increasingly worse-off. This could
become a significant problem over time for households in the lowest quintile,
unless those households are able to reduce their carbon footprint. In many cases, we cannot reasonably expect
this. Furthermore, if households in
higher quintiles are able to reduce their emission faster than households in
the lowest quintile, less revenue will be collected without a comparable
reduction of costs for the lowest quintile.
Households in the lowest quintile might be left behind in the race to
reduce carbon emissions.
There are several mitigating
factors, however. Ummel’s study does not seek to predict how
the quintiles will fair in future years, but another study by Regional Economic
Modeling, Inc. has projected the consequences of the fee and dividend
nationally and regionally. It provides
some consolation that the fee and dividend will boost economic growth and
create 2.1 million jobs in the first ten years.
These potentially could help reduce the harms across the board and
soften the burden for the lowest quintile.
There are, however, more immediately recognizable mitigating factors:
1. the pass-through assumption,
2. under-reported high quintile expenditures,
3. price insensitivity among high income quintiles,
4. home ownership,
5. family wealth, and
6. temporary loss of income.
1. The Pass-Through Assumption
Perhaps most significant mitigating factor is that Ummel
has assumed that 100% of the fee is passed on to consumers. This undoubtedly will not happen. For excise taxes generally, businesses
commonly assume roughly 25% of the cost by reducing returns to capital and
restricting or reducing wages (Tax Policy Center, 2017). To some extent, as wages are reduced across
all wage levels and as stockholders tend to be in higher income quintiles, the
costs borne by the business will largely burden households in the higher
quintiles. So, the 14% of low-income
households or 3.5 million households that are projected to lose financially is
an overestimate. Other analyses use
different pass-through assumptions. For
example, the Department of Treasury’s Office of Tax Analysis assumes no costs
are passed on to the consumer (Horowitz, 2017).
2. Under-Reported Expenditures
Ummel also noted that there is a discrepancy between
expenditures reported in the Bureau of Labor Statistics’s Consumer Expenditure
Survey and the Personal Consumption Expenditures component of the U.S. Bureau
of Economic Analysis’s national accounts.
The consequence of this is that reported expenditures are known to be
underestimates of actual expenditures.
Utilities, gasoline, and a few other expenditures are reported more or
less accurately, but other categories were under-reported by 47%. Importantly, expenditures made by households
in higher income quintiles are disproportionately under-reported. Nonetheless, Ummel assumes that
under-reporting is uniform across all income levels. In a footnote, he recognizes that this will
underestimate spending among the rich (Ummel, 2016, p. 4-6). Underestimating these expenditures means that
the aggregate revenue will be larger than estimated, and the dividend to the
lowest income quintile also will be larger.
This is especially important as the underestimated expenditures are
indirect expenditures and make up 60% of the expenditures of the highest income
quintile. Again, this will not only
increase the dividend to all households, it will reduce the percent of lowest
income households that are expected to be made worse off by the fee and
dividend.
3. Price Insensitivity
Perhaps one of the reasons that expenditures are
under-reported by households in the higher quintiles is that they are less
concerned about their expenditures than less well-off households. Consequently, they do not notice those
expenditures. They also are likely to be
less price sensitive than the less well-off.
They will be willing to make the same purchases even as prices rise
somewhat. According to Randy Schnepf of
the Congressional Research Service, this is true for consumers making food
purchases, “low-income consumers who spend a significant share of their
household budget on food are likely to be … more responsive to price changes …
than high-income consumers with lower food budget shares” (Schnepf, 2013, p.
28). In the long run, this is very good
news for households in the lowest income quintile. That households in the higher quintiles will
be relatively insensitive to price changes will mean that the lowest income
households will be better able to keep pace with any conservation efforts made
by those in higher quintiles.
4. Home Ownership
Not everyone who is in the lowest income quintile is
poor. Many people have substantial
wealth in their houses. Retirees who
have paid off their mortgage can live comfortably with a relatively low income. Others may have substantial savings
conservatively invested. While their
income is low, they nonetheless could enjoy a lifestyle that involves higher
than average expenditures and large carbon footprints. Nationally, there are 6,896,000 homeowners
with incomes less than $30,000 who are 65 years old or older (U.S. Census
Bureau, 2015). Some of these still might
be carrying a mortgage, but the number is likely small. While they may not have the security of
people in the highest quintiles, their ability to afford the increased costs of
a carbon fee might be similar to middle class households. The existence of these households reduces the
percent of households about which we should be acutely concerned.
5. Family Wealth
Like homeowners with low incomes, other households in the
lowest quintile are not poor in the concerning sense. They may be nominally distinct households,
but benefit from their wealthy families.
Some college students would be good examples of these “households.” While officially falling within the lowest
quintile, they could have resources that allow them to make above average
expenditures and thereby be among the households that are made worse off by the
fee and dividend. Roughly 20.5 million
students attended college in fall of 2016.
A plurality of them came from the highest income quartile of families,
i.e., families with an income of at least $116,000. 87% of high school students in the highest
quartile went on to college (National Center for Education Statistics, 2017;
Pell Institute, 2016). Again, many
“households” composed of college students from this stratum of society might be
nominally in the lowest income quintile, but well-able to afford an increase in
the cost of carbon intensive goods and services.
6. Temporary Loss of Income
The unemployment rate is currently 4.3% or 6.86 million
people and the average length of unemployment is about 26 weeks. Only a quarter of the unemployed remain
unemployed for longer than 26 weeks (U.S. Bureau of Labor Statistics,
2017). Loss of employment will surely
send some number of households into the lowest income quintile for a time. All other things being equal, they will
likely not moderate their consumption habits significantly, if they have some
savings to tide them over the period of temporary unemployment. As household consumption correlates strongly
with income, some number of them likely will be above the national
average. What this means is that some
number of households with large carbon footprints will be in the lowest
quintile only temporarily and will have greater resources in future years to
recoup whatever burdens they experience during their weeks or months of
unemployment. These households will, in
essence, be more likely to have high consumption habits and be more financially
secure than those with chronically low incomes.
Recent research has revealed that in addition to people losing
employment, income is often temporarily lost because of reduced hours during a
business downturn (Morduch and Schneider, 2017). The same situation faces small business
owners suffering temporary losses. We,
of course, should be concerned about all of these groups, but their plight can
be distinguished from households with chronically low incomes and for which we
should be acutely concerned.
These six mitigating factors or
categories of households all reduce the number of households and the burden
they would suffer from the fee and dividend.
That is, each will reduce the percent of households in the lowest income
quintile that are made worse off by the fee and dividend, such that 14% is an
over estimate of households that will be significantly or chronically
disadvantaged. Additionally, the first
three factors (the pass-through assumption and under-reported expenditures and
price insensitivity by the higher income households) should increase the
dividend for everyone and the mean net financial returns for the lowest income
quintile.
Finally, data indicate that the
burden among the lowest quintile will fall less on the lowest decile (Ummel,
2016 and Horowitz, 2017).
What can be done to relieve the burdens that remain?
Despite the expected reduction
in the number of households that will suffer a net financial loss and the
expected reduction in the size of that loss, some households in the lowest
income quintile will continue to suffer losses.
Consequently, it will be important to find ways to relieve those
burdens. One simple way would be to
modify the formula for distributing revenue.
CCL is promoting a modified per capita distribution (one share for each
adult and one-half share for each child up to two children per family). CCL believes the simplicity of this formula will
be a political selling point, but it tends to burden single person
households. Other distribution formulas,
nearly as simple, could be implemented that would protect those households.
Another significant method to
protect people in the lowest quintile would be to reduce their carbon intensive
expenditures. As the largest single
category of expenditures is utilities, significant relief can be achieved by de-carbonizing
electricity generation. This is
precisely what the carbon fee and dividend is most likely to accomplish. With rising costs for generating coal and gas
fueled electricity, wind, solar, and other clean energy sources will gain
greater and greater market share.
Already, coal-fired power plants are closing around the country and are
announced to be retired sooner than initially planned. If, ideally, all electricity was generated
from clean sources, the carbon-based expenditures of the lowest quintile would
be reduced significantly. As this
expenditure is proportionately larger than expenditures by higher income
households, the net benefits to the lowest income households would further
improve. As electricity becomes cleaner,
the carbon fee burden associated with consumer goods would also fall. Businesses will seek to reduce their
production costs by making use of low-carbon inputs, thereby reducing the cost
of the fee to consumers. So, the success
of the fee and dividend would reduce both the fee and the dividend, essentially
making it less and less relevant to household finances. The problem of the steadily rising fee would
be counter-acted by the reduced number of goods and services to which the fee
applies.
The increased cost of gasoline
production would stimulate more fuel-efficient transportation. Already, hybrids and electric vehicles are
gaining market share. Countries such as
Norway, India, China, and France have already announced intentions to promote
or move entirely to electric vehicles. These are, of course, foreign markets,
but they indicate the direction that the automobile industry is heading. Virtually all major auto manufacturers are
now producing an all-electric car. While
the upfront cost of new hybrid or
electric vehicles will be beyond the reach of most all low-income households,
more efficient vehicles in the used car market will become within reach. As these vehicles appear on the market, the
carbon-intensity of transportation expenditures by the lowest quintile will
fall. Here, too, the fee and dividend is
designed to make itself obsolete.
There are a number of ways to
reduce the cost of the fee to the lowest quintile that lie outside the fee and
dividend proposal: local, state, and
federal support for energy efficiency upgrades for affordable housing, support
for “Energy Star” appliances, “cash for clunkers” programs, and progressive
utility rate structures are a few obvious tools. Money for these programs could be raised by
allowing households to voluntarily decline their dividend. Checks would come to them with a notice that
if they chose not to cash the check in a specific time period, the money would
be used to support energy efficiency programs or perhaps research and
development into alternative fuels. Given
that most of the revenue generated would come from the highest quintiles and
that these checks would make up typically only about 0.2% of their annual
income, many well-off households likely would be willing to make this
contribution.
Finally, the costs and benefits
examined here are only financial.
De-carbonizing our economy will benefit vulnerable communities located
near polluting power plants. This is a significant
concern among environmental justice advocates.
Cap-and-trade carbon pricing plans do not address this problem. Under a cap-and-trade system, polluting power
plants can purchase off-sets and continue to operate polluting plants usually
affecting poorer neighborhoods. In
contrast, a fee and dividend plan puts market pressures on all fossil fuel
plants equally, thereby promoting healthier conditions for vulnerable
communities. The study conducted by
Regional Economic Modeling, Inc. for CCL found that CCL’s fee and dividend plan
would prevent 230,000 premature deaths in the courses of 20 years.
While we cannot expect that all
households within the lowest quintile will be benefitted by CCL’s carbon fee
and dividend, it is clear that the proposal is extremely progressive and that
the estimate that 14% of the lowest quintile will suffer a burden is an
overestimation. There are clearly ways
in which the households in the lowest quintile can be protected. Among these is simply the fact the fee and
dividend plan is designed to make itself obsolete, particularly in those expenditure
categories that are most damaging to the lowest quintile.
Sources
Drehbol, Ariel and Lauren Ross, “Lifting the High Energy
Burden in America’s Largest Cities: How Energy Efficiency Can Improve Low
Income and Underserved Communities,” American Council for an Energy-Efficient
Economy, April 2016.
Horowitz, John, et al., “Methodology for Analyzing a Carbon
Tax,” Working Paper 115, Office of Tax Analysis, U.S. Department of Treasury,
January 2017.
Morduch, Jonathan and Rachel Schneider, The Financial Diaries: How American Families Cope in a World of
Uncertainty, Princeton: Princeton University Press, 2017.
National Center for Educational Statistics, “Fast Facts,”
U.S. Department of Education, 2017 https://nces.ed.gov/fastfacts/display.asp?id=372,
retrieved 6/26/2017.
Nystrom, Scott and Patrick Luckowk, “The economic, climate,
fiscal, power, and demographic impact of a national fee-and-dividend carbon
tax,” Washington, D.C., Cambridge, Mass.:
Regional Economic Modeling, Inc. and Synapse Energy Economics, Inc.,
June 9, 2014.
Pell Institute, “Indicators of higher education equity in
the United States: 2016 historical trend report,” 2016, http://www.pellinstitute.org/downloads/publications-Indicators_of_Higher_Education_Equity_in_the_US_2016_Historical_Trend_Report.pdf,
retrieved 6/26/2017.
Schnepf, Randy, “Consumers and food price inflation,”
Congressional Research Service, Sept. 13, 2013.
Tax Policy Center, “Briefing Book,” Urban Institute and
Brookings Institution, 2017, http://www.taxpolicycenter.org/briefing-book/who-bears-burden-federal-excise-taxes,
retrieved 6/26/2017.
Ummel, Kevin, “Impact of CCL’s proposed carbon fee and
dividend policy: A high-resolution analysis of the financial effect of U.S.
households,” prepared for Citizens’ Climate Lobby, Working Paper v1.4, April,
2016.
U.S. Bureau of Labor Statistics, 2017, https://www.bls.gov/home.htm,
retrieved 7/6/2017.
U.S. Census Bureau, “America’s Families Living
Arrangements,” 2016, https://www.census.gov/data/tables/2016/demo/families/cps-2016.html,
retrieved 6/26/2017.
U.S. Census Bureau, “American Housing Survey,” 2016, https://www.census.gov/programs-surveys/ahs/data/interactive/ahstablecreator.html#?s_areas=a00000&s_year=n2015&s_tableName=Table1&s_byGroup1=a1&s_byGroup2=a1&s_filterGroup1=t1&s_filterGroup2=g1,
retrieved 6/26/2017
[*] I
would like to thank Rebecca Schaaf, Ellyn Dooley, David Brittain, and Danny
Richter for editorial comments and general guidance.
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