Income Trends of Residential PV Adopters
An analysis of household-level income estimates
Galen Barbose, Naïm Darghouth, Ben Hoen, and Ryan Wiser
Lawrence Berkeley National Laboratory

April 2018

This analysis was funded by the U.S. Department of Energy Solar Energy Technologies Office under Contract No. DE-AC02-05CH11231

Acknowledgments
This analysis was funded by the U.S. Department of Energy Solar Energy Technologies Office under Contract No.
DE-AC02-05CH11231. We thank Garrett Nilsen, Elaine Ulrich, Odette Mucha, and Ammar Qusaibaty of the U.S.
Department of Energy’s Solar Energy Technologies Office (SETO) for their support of this work.
We would also like to thank participants in the SETO-funded project, State Strategies to Bring Solar to Low- andModerate-Income Communities, for providing invaluable input and feedback on this work. That project, led by the
Clean Energy States Alliance, includes representatives from public agencies across six states: Connecticut Green
Bank; District of Columbia Department of Energy and Environment; Minnesota Department of Commerce; New
Mexico Energy, Minerals and Natural Resources Department; Oregon Department of Energy; Oregon Energy Trust;and Rhode Island Office of Energy Resources. The work presented here was conducted, in part, to inform the effortsof those agencies in developing and implementing new strategies for expanding access and affordability of solar PV
among low- and moderate-income (LMI) residents and communities. Finally, we thank the many public agencies,
utilities, and other entities that provided the underlying PV system-level data used for this study.

2

Outline• Overview and Background• Data• Results– Median incomes of PV adopters vs. broader population– Income distribution of PV adopters– LMI adoption rates– LMI adopter characteristics• Conclusions• Appendix

3

Project Overview
Objective: Describe income trends among U.S. residential solar adopters, highlighting trends
related to low- and moderate-income (LMI) households
Unique features of this analysis– Household-level income estimates: Experian* address-level income estimates allows for more-precise
characterization of PV-adopter incomes– Relatively extensive coverage of the U.S. solar market: Based on Berkeley Lab’s latest Tracking the Sun(TTS) dataset, covering ~82% of the total U.S. market (with street addresses for ~63% of the market)

Scope– Rooftop solar on single-family homes: Underlying data consist primarily of single-family rooftop PV, but later
work may extend analysis to multi-family homes and also to community solar subscribers– Systems installed through 2016 in 13 states: Focuses on states in latest TTS dataset with address data
available for large fraction of the market; later work may evaluate more-recent adopters and additional states– Basic descriptive trends: Focus here is on establishing basic trends, but later work may examine underlying
causal factors more directly, using more-sophisticated statistical methods* Experian and the Experian marks used herein are trademarks or registered trademarks of Experian Information
Solutions, Inc. Other product and company names mentioned herein are the property of their respective owners.

4This work seeks to refine and expand upon prior analyses of PV
adopter income trends• Prior analyses have examined PV-adopter income and other demographic trends:– Kevala, Center for American Progress, GTM and PowerScout, UC Energy Institute, CT Green Bank,
Energy+Environmental Economics, SolarPulse, NREL, others• Though their data and methods vary, these prior studies generally:– Focus on somewhat limited geographies (single states or several larger state markets)– Rely on median incomes at the block-group or zip-code level as proxies for individual PV-adopter incomes (or, in
limited cases, survey data from a sample of households)– Are somewhat dated• These studies have yielded mixed results and messages:– Some show that PV adopters tend to be more affluent and educated than non-adopters, while perhaps
highlighting an attenuation of this trend over time
– Others emphasize that middle-class adopters are most common and that their numbers have risen over time
– Varying conclusions about the role of TPO in driving LMI adoption5Outline• Overview and Background• Data• Results– Median incomes of PV adopters vs. broader population– Income distribution of PV adopters– LMI adoption rates– LMI adopter characteristics• Conclusions• Appendix

6

Analysis builds off Tracking the Sun (TTS)• TTS 10 dataset (August 2017 release)– System-level PV data through 2016
– ~1.1 million residential systems in total– >800,000 systems with street addresses• This analysis focuses on the 13 states withrelatively complete address-level coverage(listed in table to the right)– Sample represents 89% of all residential systems in the
13 states covered, and 61% of all U.S. residential
systems installed cumulatively through 2016
– Missing from the analysis are a number of relatively
large state residential markets: AZ, CO, HI, MD, NJ
See appendix for additional details on data sources andsample sizes by installation year

State

CA
CT
DC
MA
MN
NC
NM
NV
NY
OH
OR
RI
VT
Total

Analysis Sample

Market Coverage

Residential systems in TTS
Percent of all state
dataset with addresses and residential systems through2016 in analysis sample
matched to Experian data
595,84792%
18,989
82%
2,573
94%
61,422
95%
597
26%
4,697
93%
10,591
87%
20,15085%
47,343
64%
1,765
66%
11,684
94%
1,936
97%
3,559
59%
781,153
89%

Notes: Market Size is based on maximum value reported across three sources: EIA Form 861 data,
GTM Solar Market Insight, and TTS 10. MN: Analysis sample consists solely of projects installed
through the Made in Minnesota program, representing roughly 50% of statewide installations overthe 2014-2016 period. VT: Analysis sample consists primarily of installations through 2015; much of
the gap in market coverage is thus associated with 2016 installations.

7Experian household income estimates
Used to characterize income of PV households• All PV addresses geocoded and sent to Experian for matching– Person- or household-level match for 77% of PV addresses– Zip+4 match for 23% (zip+4 is one side of one block of a street—typically ~5-10 households)*– <1% not matched• Experian household income estimates– Estimated using individual, household and neighborhood level data via an algorithm designed to
predict multiple income levels– Validation steps include numerous data comparisons and iterations to increase predictive accuracy
and outcome– Estimates are fit to census income distribution nationally and at a small geographic level (Census
Block Group)*We conducted robustness checks and found no material or consistent difference in PV-adopter income trends whenexcluding addresses for which income was matched based on zip+4, rather than an exact household-match
8

Census data
Used to characterize income of broader population• American Community Survey (ACS) 2016 5-year averages– Downloaded from factfinder.census.gov• Analysis makes use of variables relating to household median income, household income
distributions, and owner occupied / renter status– Depending on the element of our analysis, we use Census data published at the level of the blockgroup (BG), county, Metropolitan/Micropolitan Statistical Area (MSA), or state– Variables associated with each PV system by first matching the system address to a census block,which then determines its BG, county, and MSA• PV adopters classified as LMI based on income relative to Area Median Income (AMI)– AMI is calculated from Census data, based on MSA median household income (for urban addresses)
or county median household income (for rural addresses)• Experian income data is fit to Census data, implicitly allowing comparability

9

A note on defining the “reference” population• Throughout the analysis, PV adopters are compared orcharacterized relative to some “reference” population• These reference populations can vary according totheir geographical scope– Our analysis uses reference populations based on
MSAs, states, and the collection of all states• Reference populations can also be defined in terms of
sub-populations within a given geographical area
– We consider reference populations based on: (a) all
households (HH) as well as (b) just owner-occupied
households (OO-HH)– Ideally, we would also use reference populations
based on just owner-occupied, single-family
households (as most PV adopters fall within thisgroup), but Census data do not provide income
segmented by single vs. multi-family

Diagram not drawn to scale10Outline• Overview and Background• Data• Results– Median incomes of PV adopters vs. broader population– Income distribution of PV adopters– LMI adoption rates– LMI adopter characteristics• Conclusions• Appendix

11

The median income of all PV adopters is notably higher than other
HHs, but difference is much smaller when compared to just OO-HHs

Median Household Income($1,000/yr)

Median Incomes (across all states in sample)
$100
$80
$60
$40
$20
$0

$92

$60

All PV Adopters All Households
through 2016$79
All Owner
OccupiedHouseholds

Notes: Multi-state median incomes are calculated as a weighted average of eachindividual state median, weighted based on the relevant population (i.e., the populationof PV adopters, all households, or all owner-occupied households).

• Median income of all PV adopters in thesample is $32k (54%) higher than all HH• But more than half of that difference isassociated with home ownership– Home ownership rates much higher for HHs above
state median income (77%, on average) than below(44%); see slide 31 in appendix for additional details– Standard “split incentive” barrier endemic to distributed
energy resources generally, including energy efficiency• Median income of PV adopters is $13k (17%)
higher than that of all OO-HH• Gap is amplified by the concentration of PV
adopters in relatively high-income states– Pulls PV median upward, while medians for all HHs
and OO-HHs reflect distribution of broader population
12

Similar trends exhibited in most states, with greatest PV-adopter
income disparities in states with relatively low statewide incomesMedian Incomes by StateAll PV Adopters through 2016

All Households

All Owner Occupied Households

Median Household Income($1,000/yr)

$120
$100

• PV-adopter median incomes acrossthe 13 states in the sample are ~$20k$30k (30%-70%) higher than for all HH• Differences consistently much smallerwhen comparing to just OO-HH• Gap between PV adopters and all OOHHs vary with overall statewide
income levels

$80
$60
$40
$20
$0
DC MA CTCA NY

RI MN OR NV VT OH NC NM

Notes: States ordered from highest to lowest based on median income of all owner-occupied households.

– Gap is smaller for high-income states—andis even inverted for the three states (DC,MA, CT) with the highest statewide incomes– In states with relatively low statewide
incomes, PV-adopter incomes are also
lower, but not to the same extent as theoverall population of OO-HHs
13

PV-adopter median incomes converging toward broader population• Prior results focused on all PV adopters
cumulatively, but annual trends show that PVadopter median incomes have been trending
downward in recent years

Annual PV-Adopter Median IncomesMedian Household Income($1,000/yr)(across all states in sample)
$120
$100

PV Adopters

All HHsAll OO-HHs

$80

$79

$60

$60

$40

• PV adopters converging toward median incomeof all OO-HHs: PV-adopter median income 10%
higher than all OO-HHs in 2016 ($87k vs. $79k),
compared to 27% higher in 20102016 $87

2015 $87

2014 $95

2013 $98

2012 $98

2011 $98

2010 $100• Figure here focuses on period since 2010; later
slide contrasts these trends with the earlier era$0• Aggregate PV-adopter median income acrossall states is driven heavily by CA, but mostNotes: See earlier slide for method used to calculate multi-state median incomes. Income
levels for PV adopters in each year are based on estimated current income of those HHs,
states show similar downward trend$20

not the income in the year of installation. Accordingly, the reference incomes shown for
all HHs and all OO-HHs are fixed over time based on the latest Census data.

14

Most states show a decline in PV-adopter median incomes over timeMedian Household Income($1,000/yr)

Annual PV-Adopter Median Income by State
CA

$140

CT

DC

MA

MN

$140

NC

NM

NV

$140

$120

$120

$120

$100

$100

$100

$80

$80

$80

$60

$60

$60

2010

2012

2014

2016

2010

2012

2014

2016

NY

OH

2010

2012

OR

RI

2014

VT

2016

Notes: States divided among figures alphabetically, simply to aid visual comprehension. For several states (MN, RI, VT), sufficient sample sizes are available for only a portion of the time
period shown. Income levels for PV adopters in each year are based on estimated current income of those HHs, not the income in the year of installation.

• Notwithstanding some inter-annual volatility, median PV-adopter incomes in most states havegenerally been trending downward in recent years• Some states (NY, OH, OR, VT) show little change or even slight increases in PV-adopter
incomes over the period shown, but these also tend to be states with relatively low PV incomes15

2016 PV-adopter median incomes in most states were greater thanother OO-HHs, though four states have reached “income parity”

140%

Declining OO-HH median income

120%
100%
80%
60%

132%

118%

120%

113%

105%

114%

122%

107%

108%

100%

89%

89%

20%

68%

40%

110%

Ratio of Median PV Income toMedian Income for All OO-HH

PV-Adopter Median Incomes Relative to Median
Income of all OO-HHs (2016 PV Adopters)

0%
All States DC MA CT CA NY RI MN OR NV VT OH NC NM

Notes: States ordered from left to right according to declining median income of all OO-HHs (see slide 13
for those values). For VT, we use data for 2015 PV adopters, owing to the limited sample size for 2016.

• Across the 13 states in the sample,
PV-adopter median incomes in 2016
ranged from 68%-132% of the medianincome for all OO-HHs• Four states (DC, MA, CT, CA) havereached “income parity”, with PV
adopter median incomes equal to or
below other OO-HHs• For reasons discussed previously,
variation in results across states isstrongly associated with the overall
median income of OO-HHs– Lower ratio of median income in states withhigher overall incomes for OO-HHs
16

Even if often under-represented, “moderate-income” households
nevertheless constitute a sizeable share of cumulative PV adopters
State Income Quintiles
80-100th60-80th
40-60th20-40th
0-20th

DC
CT
MA
CA
MN
NY
RI
VT
OR
NV
OH
NC
NM

100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

All States

Percent of PV Adopters

Income Distribution of All PV Adopters through 2016 • 43% of all PV adopters in the sample

Other Income Ranges*
Pew Middle Class<200% of FPL*See notes below for
definitions of these ranges

Notes: States ordered left to right according to declining median income of all OO-HHs. Income quintiles
based on all HHs in each state; the distribution for “All States” uses the quintiles for each PV adopter’s
respective state. See slide 33 for distributions in absolute dollar terms. The Pew Research Center defines“middle class” households as those with incomes of 67% to 200% of the U.S. median household income($53,889 in 2016). The Federal Poverty Level (FPL) was equal to $20,420 for a 3-person household in 2016.

(33%-50% across individual states) fallwithin the lower 3 income quintiles• 48% of all PV adopters (47%-60% acrossindividual states) fall within Pew’s
definition of “middle class” (see notes)• Even low-income groups are represented,
with 15% of all PV adopters below 200%of the Federal Poverty Level: a common
benchmark used in low-income programs– Though some questions exist about income
estimates at the lower end, discussed later• Cross-state differences largely driven by
more-general income differences acrossstates (slide 32 shows this more clearly)
17

PV adoption has generally been trending towards more-moderate
income HHs in recent years, in contrast to earlier trend
Income Distribution of PV Adopters by Install Year

Percent of PV Adopters

100%

State Income
Quintiles

90%80%

80-100th60-80th
40-60th20-40th
0-20th

70%
60%
50%
40%
30%

Other Income Ranges
Pew Middle Class<200% of FPL

20%
10%

2016

2014

2012

2010

2008

2006

2004

2002

2000

0%

Notes: The distributions are based on all states in the sample. Income distribution for PV adopters in eachyear is based on estimated current income of those HHs, not the income in the year of installation.

• Prior to 2010: PV adoption becomesincreasingly skewed toward higher
income households– Early adopters, nascent markets in moststates (mostly CA)• Since 2010: Share of adopters frommore-moderate incomes (<60thpercentile) steadily increasing– Rapid cost declines, growth of TPO,
maturing markets, programmatic initiatives
and business models targeting LMIWhile the aggregate temporal trend across allstates is heavily driven by CA, most otherstates show similar trends since 2010.

18

Most states also trending toward more-moderate income adopters
With some exceptions, depending on the set of income quintiles considered
Income Distribution of 2010 vs. 2016 PV Adopters (or closest available years)
100%
80%
60%
40%
20%
0%

All States

DC

CT

MA

NC

MN

State Income
Quintiles
80-100th
2010

2016

NM

2010

2016

2010

NV

2016

2010

NY

2016

2010

OH

2016

2014

OR

2016

2010

RI

2016

VT

60-80th
40-60th20-40th
0-20th

2014
2015
2016

100%
80%
60%
40%
20%
0%

CA

2010

2016

2010

2016

2010

2016

2010

2016

2010

2016

2013

2016

2010

2015

Notes: A narrower range of years is shown for several states (MN, RI, VT) due to limited or unavailable data for 2010 or 2016. Income distributions for PV adopters in each year are basedon estimated current income of those HHs, not the income in the year of installation.

19

Methodological Side-Bar: Using Experian HH income estimates yields
materially different results than using Census BG or zip code median incomes2016 PV Adopter Income Distributions
Comparison of three income estimates
Percent of PV Adopters

100%

State Income
Quintiles

80%

80-100th60%

60-80th40%

40-60th20-40th20%

0-20th0%Experian

Census(BG)

Census(zip code)

Notes: For the Census (BG) distribution, the income assigned to each PV system isthe corresponding BG median income. For the Census (zip code) distribution, theincome assigned to each PV system is the average of the BG median incomes within
the corresponding zip code, weighted by the residential population in each BG.

• Prior analyses of PV-adopter income trends haveoften used zip-code average incomes (for want ofcustomer street addresses) or median BG incomes(for want of HH-level income data)– Roughly 600 HH per BG; 3000 HH per zip code

• One of the chief innovations of the present analysis
is to use HH-level income estimates for eachavailable PV street address• The results differ materially in two ways
1. Shift in the distribution toward wealthier households:
PV adopters tend to have higher incomes than other HHs
in their BG and zip code
2. Greater representation among the “tails” of theincome distribution: Using median incomes across BGsor zip codes dampens income variability
20

Methodological Side-Bar: There are some questions about the accuracy of
the income estimates at the lower end of the spectrum

Number of 2016 PV Adopters

Comparison of Income Levels vs.
Home Values for 2016 PV Adopters
30,00025,000State Home
Value Quartile

20,0000-25th15,00025-50th

10,00050-75th5,000

75-100th

0State Income Quintile
Notes: The home value for each PV adopter is binned according to the distributionof home values in the corresponding state (which are available as quartiles)• For PV adopters in most income groups, home values
more-or-less correspond to income• However, for PV adopters in the lowest income quintile,
the home-value distribution is flat, suggesting a
relatively high share of these customers may not, infact, be “low income”– One theory explored, but ultimately refuted, is that adisproportionate share of low-income PV adopters are retirees• Data on participation in CA low-income electricity rates(see slide 34) also show a larger number of estimatedlow-income PV adopters than expected• Possible explanations: (1) less-robust data available forthe estimated income model for low-income HHs versus
higher incomes; (2) the process of fitting income
estimates to census data may skew low-income results
21

Estimating LMI Adoption Rates
PV Adoption Rate: Number of PV adopters divided by total number of (applicable) HH• We estimate adoption rates among all HHs and among just OO-HHs, on both a cumulative and annual basis• We assume that the income distribution of our PV-adopter sample for each state is representative of all PV
adopters in the state• We compare adoption rates for LMI households vs. overall PV adoption rates  provides a measure of whether
and to what extent LMI adoption lags behind the broader market

Defining “LMI”: Following the convention of many LMI-oriented solar programs, we classify
households as LMI based on their income relative to Area Median Income (AMI)• Specific AMI thresholds vary by program (typically anywhere from 60% to 120% of AMI), depending in part onwhether the focus is just on low-income or on low- and moderate-income• Side note: Using state median incomes rather than AMI yields almost identical LMI adoption rates for most states(suggesting that PV adopters are relatively well-dispersed within each state)22

PV adoption rates by LMI customers lag behind the broader market
Though the disparity is smaller when focusing just on OO-HHs and 2016 installs
PV Adoption Rates: LMI compared to All Incomes
Aggregate results across all states in the sample
1.5%
1.2%

3.4%

0.6%

Among
all HHAmong
OO-HH only

0.0%

Among
all HH

0.71%

2.8%

2.6%

2.4%

2.3%

1.5%

1.3%

1.1%

0%

0.3%

0.44%

1%

0.56%

0.39%

LMI Adopters

0.33%

All PV Adopters
2.2%

0.28%

2%

0.94%

0.9%

0.84%

3%

0.79%

4%

LMI Threshold (% of AMI)
<60%
<80%
<100%
<120%

2016 PV Installations

0.73%

5%

0.9%

PV Adoption Rate (% of HH)

Cumulative PV Installations

Among
OO-HH only

In general, results mirror and reinforce
earlier comparisons of median incomesand PV-adopter income distributions• In aggregate across all states in thesample, the LMI adoption rate is below theoverall market adoption rate
• The gap is smaller for more-expansive
LMI definitions (120% vs. 60% of AMI)
• The gap is also smaller, in relative terms,
when focused specifically on adoption
among OO-HHs (given lower rates ofhome-ownership among LMI customers)• The gap is smaller among 2016 installs,
as PV adoption shifts towards moremoderate income HHs, but still persists
23

LMI adoption in each state also tends to lag the broader market
DC is an exception, in part because of how the MSA is defined
Ratio of LMI to Overall Statewide Adoption Rates
2.00%

175%

1.75%

Ratio of Adoption Rates
LMI Adoption Rate (Annual)

149%

150%
125%

1.25%

100%

25%

58%

0.75%
59%

73%

73%

78%

80%

84%

87%

93%

89%

50%

1.00%
98%

75%

1.50%

0.50%
0.25%

0.00%
0%
All States DC CT MA NV OR CA NY RI MN NC OH NM

LMI Adoption Rate

200%

83%

Ratio of Adoption Rates(LMI / All Incomes)(2016 PV installs, OO-HHs only, LMI defined as ≤100% of AMI)

• Annual LMI adoption rates vary widely
across states, from <0.01% to 1.8% of OOHHs in 2016, using the particular LMI
definition here (see slide 35 for cumulative
LMI adoption rates)• Generally range from 70-90% of the overall
state adoption rate, though LMI rate is nearor above broader market rate in several
states (DC, CT, MA)• In general, less lag in states with higher
overall incomes, as LMI HHs in these states
have higher absolute income levels• This dynamic further accentuated in DC, as
it is part of a larger MSA that includes highincome areas of VA and MD, further raising
the absolute income threshold for LMI
24

LMI PV systems tend to be somewhat smaller, more likely to be TPO
But few apparent differences in system price, module efficiency, or microinverter use• Median system size: ~5.4 kW for LMI
customers (≤100% of AMI) vs. 6.2 kW
for non-LMI customers
Third-party

PV System Characteristics for LMI vs. Non-LMI(2016 PV Installations, LMI defined as ≤100% of AMI)
PV System
Price ($/W)
4.5

7

4.0

6

3.5
3.0

5

2.5

4

2.0

3

1.5
1.0

2

0.5

1

0.0

0

PV System
Size (KW)

20%

ModuleEfficiency

15%
10%
5%
0%

LMI (≤100% AMI)

35%

Microinverter
Adoption

70%

30%

60%

25%

50%

20%

40%

15%

30%

10%

20%

5%

10%

0%

0%

Ownership

Non-LMI– Larger systems cost more, and lowerincome HHs are more constrained
financially; LMI HHs may also have lessenergy consumption to offset and smallerroofs• Third-party ownership (TPO): 57% of
LMI customers vs. 48% for non-LMI– LMI HHs may have greater cash constraints,
less access to other financing options, andless ability to directly monetize tax benefits

Notes: Figure is based on all systems in the analysis sample installed in 2016 for which the relevant data
(e.g., module efficiency, inverter type, system ownership type) are available.

25

Outline• Overview and Background• Data• Results– Median incomes of PV adopters vs. broader population– Income distribution of PV adopters– LMI adoption rates– LMI adopter characteristics• Conclusions• Appendix

26

Conclusions• The choice of data and metrics clearly matter: For example, results and associated take-away
messages can differ significantly depending on use HH-level data vs. Census BG medians or zip-code average
incomes; and depending on whether PV adopters are compared to all HH or just OO-HHs• Home-ownership is a key driver for differences in PV adoption among income groups:
Reinforces importance of business models and programs aimed at renters• PV-adopter incomes are diverse: While PV adopters as a whole are higher-income than the population atlarge, it should not be overlooked that “moderate-income” or “middle-class” households are already a significant
beneficiary of existing solar markets• The income profile of residential PV adopters is dynamic and evolving: Suggests some value
in periodically re-assessing PV-adopter income trends, and raises questions about the underlying drivers for recent
trends and about how those trends may evolve going forward• Local and regional factors impact the income characteristics of PV adopters: Though muchof the cross-state variation in PV income trends is a function of more-general statewide income differences, othermarket and policy drivers likely play a role as well, and could become more significant in the years ahead

27

Outline• Overview and Background• Data• Results– Median incomes of PV adopters vs. broader population– Income distribution of PV adopters– LMI adoption rates– LMI adopter characteristics• Conclusions• Appendix

28

Analysis Sample: Data Sources
State

Data Sources

Analysis Market
Sample Coverage

MN
NC

CPUC: Currently Interconnected Dataset, CSI Working Dataset, Self-Generation Incentive Program
CEC: New Solar Homes Partnership, Emerging Renewables Program
Imperial Irrig. District: All net-metered systems, California Solar Initiative
CT Green Bank: Various incentive programs
DC PSC: Systems certified for RPS eligibility
MA DOER: SREC I and SREC II certified systems
MassCEC: Various incentive programs
MN Dept. of Commerce: Made in Minnesota program
NC Sustainable Energy Association: Applications with the NC PUC for a CPCNNMNM Energy, Minerals & Natural Resources Dept: State income tax credit program
PNM: All interconnected systems

10,581

87%

NV

NV Energy: All interconnected systems

20,15085%

NY

NYSERDA: Various incentive programs

47,34064%

OH

OH PUC: All in-state systems certified for RPS eligibility

1,765

66%

OR

11,693

94%

RI

Energy Trust of Oregon: Various incentive programs
OR Dept. of Energy: State income tax credit programs
RI Commerce Corporation: Various incentive programs
National Grid: All net-metered systems and all systems participating in RE Growth Program

1,936

97%

VT

VT Energy Investment Corporation: Various incentive programs

3,558

59%

CA
CT
DC
MA

595,892

92%

18,989
2,572

82%
94%

61,418

95%

597
4,689

26%
93%

Notes
Projects matched across overlapping datasets to avoid
double-counting

Projects matched across overlapping datasets to avoid
double-counting
Only includes data on 2014-2016 installs
Data from the state tax credit program includes only hostowned systems. Projects matched across overlapping datasets
to avoid double-counting.
Market coverage relatively low because street address data
unavailable for a substantial fraction of systems
Market coverage relatively low because a substantial fractionof street addresses could not be matched with either a HH or
zip+4-level income estimate
Projects matched across overlapping datasets to avoid
double-counting
Projects matched across overlapping datasets to avoid
double-counting
PV incentives expired in 2015, thus effectively no market
coverage of 2016 installations

29

Analysis Sample: Annual PV Adopters by State
State

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

CA

85

900

1,572

2,616

4,111

3,826

5,878

8,602

8,972 15,194 19,011 26,627 36,507 65,074 94,423 150,110 152,339

CT

0

0

0

0

0

32

87

165

269

469

475

404

597

1,285

3,139

6,693

5,374

DC

0

0

0

0

0

1

2

3

5

89

178

178

207

309

362

615

624

MA

1

1

0

50

98

60

197

181

319

686

545

1,093

2,907

4,804

MN

0

1

0

0

1

0

1

1

0

0

0

0

0

0

114

189

290

NC

0

0

0

0

0

3

13

20

40

102

179

350

444

435

846

1,274

991

NM

1

4

6

7

11

7

60

65

152

382

905

1,086

1,162

1,203

1,197

1,733

2,610

NV

0

0

0

0

8

58

72

92

82

166

279

127

55

235

1,410 14,587

2,979

NY

0

0

0

37

84

86

188

326

360

669

684

699

1,563

2,271

OH

0

0

1

2

4

5

9

16

27

65

137

285

240

234

248

293

199

OR

23

46

31

84

140

96

149

220

245

456

1,104

1,322

1,342

986

1,307

2,006

2,127

RI

0

0

0

0

0

0

0

1

2

1

3

0

35

54

86

339

1,415

VT

0

0

0

1

63

36

54

61

85

147

177

377

473

807

931

332

15

Total

110

952

1,610

2,797

4,520

4,210

6,710

8,970 20,295 21,215

5,762 15,650 18,964

9,753 10,558 18,426 23,677 32,548 45,532 77,697 118,795 214,116 209,142
30

Home-Ownership Rates for All Households
Home-Ownership Rate by Income Group(All households, not specific to PV customers)
120%

Income Range<$50k$50-100$100-150≥$150– Home-ownership rates are roughly doublefor HHs above $150k (83% across all 13
states) than for those below $50k (42%)

Home-ownership rate

100%
80%
60%
40%
20%
0%
All States• The figure presented here provides
further detail illustrating lower rates ofhome ownership for lower income
households

CA CT DC MA MN NC NM NV NY OH OR RI VT• As discussed throughout the report,
higher income groups represent a
disproportionate share of residential
rooftop PV adopters, and have higher
adoption rates, in large part as a resultof differences in home-ownership rates
across income groups

31Differences in PV-adopter incomes across states is partly a functionof more-general differences in statewide incomes

Percent of PV Adopters

Comparison of PV-Adopter Income Statistics with
Each State’s Median HH Income
60%

$120k

50%

$100k

40%

$80k

Median Income,All HH (right-axis)% of PV Adopters in:
Bottom Three
Income Quintiles
Pew Middle Class• In states with relatively high incomes:– Income quintiles shifted upward; thus PV
more-accessible to HHs in the bottom threequintiles– Smaller fraction of population is <200% of
FPL and in Pew middle class; fraction of PV
adopters in those groups thus also smaller• Converse is true for states with lower
overall income levels
20%$40k• More of a “mathematical” phenomenon<200% of FPL
10%$20kthan an empirical one
0%
$k
$0k
• Other cross-state differences in PVadopter income trends (as suggested
Notes: States ordered from highest to lowest based on median income of all households. The trend-lines
by deviations from the trend-lines) may
included in the figure are intended to illustrate the general direction of the trend, but the specific slopes of
those lines do not have any technical significance given that the x-axis is non-numeric.
be driven by policy and market factors
$60k

DC
CT
MA
CA
MN
NY
RI
VT
OR
NV
OH
NC
NM

30%

32

PV-Adopter Income Distribution in Terms of Absolute Income Levels

100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

Income Bins≥$200k/yr$150k-$200k/yr$100k-$150k/yr$50k-$100k/yr<$50k/yr• This figure supplements the income
distribution presented earlier, which uses
state income quintiles• Reinforces the same basic conclusion that“moderate-income” households comprisea sizeable share of PV adopters– 55% of all PV adopters in the sample have
HH income <$100k (~50-70% across theindividual states)

NV
VT
OH
OR
NM
NC
RI
NY
MN
MA
CT
CA
DC

• Cross-state differences highly correlate to
overall statewide income levels
All States

Percent of PV Adopters

Income Distribution of PV Adopters– E.g., greater share of PV adopters <$100k
in states with relatively low statewide
income (see previous slide), given thegreater share of the overall population belowthat income level33

Benchmarking Experian Income Estimates against PV-Customer
Enrollment in Low-Income Rates for California IOUs
Experian Data vs. Enrollment
in Low-Income Rates
Enrolled in Low-Income Rates

20%– We focus here on just SCE and SDG&E, due to issues with the rate
data for PG&E

• As shown in the figure, enrollment in low-income rates by PV
customers is much lower than the estimated percentage of eligible
PV customers (10% vs. 16% for SCE, 4% vs. 12% for SDG&E)

15%
10%
5%

SDG&E

0%

SCE

Percent of PV Adopters

Experian Income <200% of FPL• California’s IOUs offer low-income electricity rates; eligibility isbased on HH income <200% of the FPL• LBNL receives data from the CPUC on the retail electricity tariff inwhich each PV customer is enrolled (at the time of interconnection)– One explanation is simply that some customers may be eligible for lowincome rates but do not enroll– It may also indicate a larger number of estimated low-income
households (with income <200% of FPL) than expected for theseutilities (for reasons discussed on slide 21)

34

LMI adoption in each state also tends to lag the broader market
DC is an exception, in part because of how the MSA is defined
Ratio of LMI to Overall Statewide Adoption Rates(Cumulative installs, OO-HHs only, LMI defined as ≤100% of AMI)

20%

5%

3%
2%
1%

0%
0%
All States DC MA CT NV CA OR NY RI MN VT NC OH NM

LMI Adoption Rate

59%

64%

69%

72%

74%

75%

4%

76%

6%

53%

40%

Ratio of Adoption Rates
LMI Adoption Rate (Cumulative)
78%

60%

80%

80%

82%

100%

88%

118%

7%

77%

Ratio of Adoption Rates(LMI / All Incomes)

120%• LMI PV adoption rates vary widely acrossstates, from <0.1% to 7% of OO-HHs,
using the particular LMI definition here
• Generally range from 60-80% of thebroader market adoption rate
• Lag in LMI adoption rates generally lessacute in states with higher overall incomes– Consistent with earlier discussion, LMI HHs
in these states have higher absolute income
levels, and thus greater access to PV• Results for DC also impacted by the factthat it is part of a larger MSA that includes
high-income areas of VA and MD, further
raising the LMI threshold

35

For Further Information
Contact the authors
Galen Barbose, glbarbose@lbl.gov, 510-495-2593
Naïm Darghouth, ndarghouth@lbl.gov, 510-486-4570

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