SIZING

THE CLEAN 

ECONOMY

A NATIONAL AND REGIONAL GREEN JOBS ASSESSMENT 
CONTENTS

Executive Summary .........................................................................2

I. Introduction ....................................................................................6

II. Why The Metropolitan Clean Economy Matters ....................8

III. Defi ning And Measuring The Clean Economy ....................12

IV. Findings: Tracking The Clean Economy 

In U.S. Metropolitan Areas ............................................................18

V. Discussion And Strategies For Advancing 

The Clean Economy .......................................................................32

VI. Conclusion .................................................................................46

Appendix ..........................................................................................48

Endnotes ..........................................................................................54

Selected References......................................................................62
SIZING THE CLEAN 

ECONOMY

A NATIONAL AND REGIONAL 

GREEN JOBS ASSESSMENT 

BY MARK MURO, JONATHAN ROTHWELL, AND DEVASHREE SAHA 

WITH BATTELLE TECHNOLOGY PARTNERSHIP PRACTICE

THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM | 2011
2 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM
SIZING THE CLEAN ECONOMY | EXECUTIVE SUMMARY 3

EXECUTIVE SUMMARY

As a matter of aspiration, no swath of the economy 

has been more widely celebrated as a source of economic 

renewal and potential job creation. 

Again this year President Obama spoke in his State of 

the Union Address of “the promise of renewable energy” 

and environmental pursuits that will “strengthen our 

security, protect our planet, and create countless new 

jobs for our people.” Since then, a global “race to clean” 

has gained new urgency with numerous nations—such as 

China, Japan, and the United Kingdom—all having made new 

commitments to invest in the low-carbon and environmental 

goods sector as a source of quality jobs, exports, and 

industry growth.

Yet, the clean economy remains an enigma: hard to assess. 

Not only do “green” or “clean” activities and jobs related to 

environmental aims pervade all sectors of the U.S. economy; 

they also remain tricky to defi ne and isolate—and count. 

The clean economy has remained elusive in part because, 

in the absence of standard defi nitions and data, strikingly 

little is known about its nature, size, and growth at the 

critical regional level. 

Currently no comprehensive national database exists on 

the spatial geography of the clean economy and its subindustries, although important work has assessed the clean 

economy across states. And while numerous studies have 

analyzed individual regional clean or green industries, a 

proliferation of defi nitions and the absence of data for large 

numbers of regions has made it diffi cult to situate regional 

clean economies in a national and comparative context. 

The result: Debates about the so-called “green” economy 

and “green jobs” have frequently been short on facts and 

long on speculation, assertion, and partisanship. 

Which gets to the impetus of this report: Seeking to 

address some of these problems, the Metropolitan Policy 

Program at Brookings worked with Battelle’s Technology 

Partnership Practice to develop, analyze, and comment on 

a detailed database of establishment-level employment 

statistics pertaining to a sensibly defi ned assemblage 

of clean economy industries in the United States and its 

metropolitan areas.

Covering the years 2003 to 2010 for every county in 

the United States, the resulting information (available 

for download at http://www.brookings.edu/metro/clean_

economy.aspx) and this report represent the fi rst study of 

the U.S. clean economy to provide timely information that 

is both comprehensive enough in its scope and detailed 

enough in its categorization to inform national, state, and 

regional leaders on the dynamics of the U.S. low-carbon 

and environmental goods and services “super-sector” as 

they are transpiring in regions and metropolitan areas. This 

information is then employed in a discussion of how the 

nation, the states, and localities and regions might address 

a number of key policy problems that may be slowing the 

growth of the clean economy.

The “green” or “clean” or low-carbon 

economy—defi ned as the sector of the 

economy that produces goods and services 

with an environmental benefi t—remains at 

once a compelling aspiration and an enigma.
4 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM

Most importantly, ”Sizing the Clean Economy: A National 

and Regional Green Jobs Assessment“ concludes that: 

● The clean economy, which employs some 2.7 million 

workers, encompasses a signifi cant number of jobs 

in establishments spread across a diverse group of 

industries. Though modest in size, the clean economy 

employs more workers than the fossil fuel industry 

and bulks larger than bioscience but remains smaller 

than the IT-producing sectors. Most clean economy 

jobs reside in mature segments that cover a wide 

swath of activities including manufacturing and 

the provision of public services such as wastewater 

and mass transit. A smaller portion of the clean 

economy encompasses newer segments that respond 

to energy-related challenges. These include the solar 

photovoltaic (PV), wind, fuel cell, smart grid, biofuel, 

and battery industries

● The clean economy grew more slowly in aggregate 

than the national economy between 2003 and 2010, 

but newer “cleantech” segments produced explosive 

job gains and the clean economy outperformed the 

nation during the recession. Overall, today’s clean 

economy establishments added half a million jobs 

between 2003 and 2010, expanding at an annual rate of 

3.4 percent. This performance lagged the growth in the 

national economy, which grew by 4.2 percent annually 

over the period (if job losses from establishment 

closings are omitted to make the data comparable). 

However, this measured growth heavily refl ected the 

fact that many longer-standing companies in the clean 

economy—especially those involved in housing- and 

building-related segments—laid off large numbers of 

workers during the real estate crash of 2007 and 2008, 

while sectors unrelated to the clean economy (mainly 

health care) created many more new jobs nationally. At 

the same time, newer clean economy establishments—

especially those in young energy-related segments 

such as wind energy, solar PV, and smart grid—added 

jobs at a torrid pace, albeit from small bases

● The clean economy is manufacturing and export 

intensive. Roughly 26 percent of all clean economy 

jobs lie in manufacturing establishments, compared 

to just 9 percent in the broader economy. On a per 

job basis, establishments in the clean economy export 

roughly twice the value of a typical U.S. job ($20,000 

versus $10,000). The electric vehicles (EV), green 

chemical products, and lighting segments are all 

especially manufacturing intensive while the biofuels, 

green chemicals, and EV industries are highly 

export intensive

● The clean economy offers more opportunities and 

better pay for low- and middle-skilled workers than 

the national economy as a whole. Median wages in 

the clean economy—meaning those in the middle of the 

distribution—are 13 percent higher than median U.S. 

wages. Yet a disproportionate percentage of jobs in the 

clean economy are staffed by workers with relatively 

little formal education in moderately well-paying 

“green collar” occupations 

● Among regions, the South has the largest number 

of clean economy jobs though the West has the 

largest share relative to its population. Seven of the 

21 states with at least 50,000 clean economy jobs are 

in the South. Among states, California has the highest 

number of clean jobs but Alaska and Oregon have the 

most per worker

● Most of the country’s clean economy jobs and 

recent growth concentrate within the largest 

metropolitan areas. Some 64 percent of all current 

clean economy jobs and 75 percent of its newer jobs 

created from 2003 to 2010 congregate in the nation’s 

100 largest metro areas

● The clean economy permeates all of the nation’s 

metropolitan areas, but it manifests itself in varied 

confi gurations. Metropolitan area clean economies 

can be categorized into four-types: service-oriented, 

manufacturing, public sector, and balanced. New York, 

through mass transit, embodies a service orientation; 

so does San Francisco through professional services 

and Las Vegas through architectural services. Many 

Midwestern and Southern metros like Louisville; 

Cleveland; Greenville, SC; and Little Rock—but also 

San Jose in the West—host clean economies that are 

heavily manufacturing oriented. State capitals are 

among those with a disproportionate share of clean 

jobs in the public sector (e.g. Harrisburg, Sacramento, 

Raleigh, and Springfi eld). Finally, some metros—such as 

Atlanta; Salt Lake City; Portland, OR; and Los Angeles—

balance multi-dimensional clean economies

● Strong industry clusters boost metros’ growth 

performance in the clean economy. Clustering entails 

proximity to businesses in similar or related industries. 

Establishments located in counties containing a 

signifi cant number of jobs from other establishments 

in the same segment grew much faster than more 

isolated establishments from 2003 to 2010. Overall, 

clustered establishments grew at a rate that was 1.4 

percentage points faster each year than non-clustered 

(more isolated) establishments. Examples include 

professional environmental services in Houston, solar 

photovoltaic in Los Angeles, fuel cells in Boston, and 

wind in Chicago

The measurements and trends presented here offer a 

mixed picture of a diverse array of environmentally-oriented 

industry segments growing modestly even as a sub-set of 

clean energy, energy effi ciency, and related segments grow 

much faster than the nation (albeit from a small base) and in 

The clean economy permeates all of the nation’s metropolitan areas, but it manifests 

itself in varied configurations. 
SIZING THE CLEAN ECONOMY | EXECUTIVE SUMMARY 5

ways that are producing a desirable array of jobs, including 

in manufacturing and export-oriented fi elds. 

As to what governments, policymakers, and regional 

leaders should do to catalyze faster and broader growth 

across the U.S. clean economy, it is clear that the private 

sector will play the lead role, but governments have a 

role too. In this connection, the fact that signifi cant policy 

uncertainties and gaps are weakening market demand 

for clean economy goods and services, chilling fi nance, 

and raising questions about the clean innovation pipeline 

reinforces the need for engagement and reform. Not only 

are other nations bidding to secure global production and 

the jobs that come with it but the United States currently 

risks failing to exploit growing world demand. And so 

this report concludes that vigorous private sector-led 

growth needs to be co-promoted through complementary 

engagements by all levels of the nation’s federal system to 

ensure the existence of well-structured markets, a favorable 

investment climate, and a rich stock of cutting-edge 

technology—as well as strong regional cast to all efforts.

Along these lines, the report recommends that 

governments help:

● Scale up the market by taking steps to catalyze 

vibrant domestic demand for low-carbon and 

environmentally-oriented goods and services. 

Intensifi ed “green” procurement efforts by all levels of 

government are one such market-making engagement. 

But there are others. Congress and the federal 

government could help by putting a price on carbon, 

passing a national clean energy standard (CES), and 

moving to ensure more rational cost recovery on 

new transmission links for the delivery of renewable 

energy to urban load centers. States can adopt or 

strengthen their own clean energy standards, reduce 

the initial costs of energy effi ciency and renewable 

energy adoption, and pursue electricity market reform 

to facilitate the use of clean and effi cient solutions. 

And localities can also support adoption by expediting 

permitting for green projects, adopting green building 

and other standards, and adopting innovative fi nancing 

tools to reduce the upfront costs of investing in clean 

technologies

● Ensure adequate fi nance by moving to address the 

serious shortage of affordable, risk-tolerant, and 

larger-scale capital that now impedes the scale-up 

of numerous clean economy industry segments. 

On this front Congress should create an emerging 

technology deployment fi nance entity to address the 

commercialization “Valley of Death” and also work to 

rationalize and reform the myriad tax provisions and 

incentives that currently encourage capital investments 

in clean economy projects. States, for their part, can 

supplement private lending activity by providing 

guarantees and participating loans or initial capital for 

revolving loan funds targeting clean economy projects 

using new or improved technologies. And for that 

matter regions and localities can also help narrow the 

deployment fi nance gap by helping to reduce the costs 

and uncertainty of projects by expediting their physical 

build-out, whether by managing zoning and permitting 

issues or even pre-approving sites

● Drive innovation by investing both more and 

differently in the clean economy innovation system. 

With the needed major scale-up of investment 

levels unlikely for now, Congress at least needs to 

embrace continued incremental growth of key energy 

and environmental research, development, and 

demonstration (RD&D) budgets. At the same time, 

Congress should continue its recent institutional 

experimentation through measured expansion of 

such recent start-ups as the Energy Frontier Research 

Centers, ARPA-E, and Energy Innovation Hubs 

programs. Two worthy additional experiments would 

be the creation of a water sciences innovation center 

and the establishment of a regional clean economy 

consortia initiative. States can also advance the clean 

economy through maintaining and expanding their 

own RD&D efforts, perhaps by tapping state clean 

energy funds where they exist. All should be focused 

and prioritized through a rigorous, data-driven analysis 

of the nature, growth, and strengths of local clean 

economy innovation clusters

In addition, the “Sizing the Clean Economy“ emphasizes 

that in working on each of these fronts federal, state, and 

regional leaders need to:

● Focus on regions, meaning that all parties need 

to place detailed knowledge of local industry 

dynamics and regional growth strategies near the 

center of efforts to advance the clean economy. 

While the federal government should increase its 

investment in new regional innovation and industry 

cluster programs such as the Economic Development 

Administration’s i6 Green Challenge, states should 

work to improve the information base about local 

clean economy industry clusters and move to support 

regionally crafted initiatives for advancing them. 

Regional actors, meanwhile, should take the lead in 

using data and analysis to understand the local clean 

economy in detail; identify competitive strengths; and 

then move to formulate strong, “bottom up” strategies 

for overcoming key clusters’ binding constraints. 

Employing cluster intelligence and strategy to design 

and tune regional workforce development strategies 

will be a critical regional priority

* * *

The measurements, trends, and discussions offered here 

provide an encouraging but also challenging assessment 

of the ongoing development of the clean economy in the 

United States and its regions. In many respects, the analysis 

warrants excitement. As the nation continues to search for 

new sources of high-quality growth, the present fi ndings 

depict a sizable and diverse array of industry segments 

that is—in key private-sector areas—expanding rapidly at a 

time of sluggish national growth. With smart policy support, 

broader, more rapid growth seems possible. At the same 

time, however, the information presented here is challenging, 

most notably because the growth of the clean economy 

has almost certainly been depressed by signifi cant policy 

problems and uncertainties. 

In that sense, what is most challenging here is the 

fundamental question raised by the dynamic growth but 

modest size of the most vibrant and promising segments of 

the clean economy. 

That question is: Will the nation marshal the will to make 

the most of those industries?

In the end, it is a question raised frequently by these 

pages. ●
6 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM

INTRODUCTION

As a matter of aspiration, no swath of the economy 

has been more widely celebrated as a source of economic 

renewal and potential job creation.

Again this year President Obama spoke in his State 

of the Union Address of “the promise of renewable energy” 

and environmental pursuits that will strengthen our 

security, protect our planet, and create countless new jobs 

for our people.”

Likewise, scores of nations, dozens of states, and 

hundreds of U.S. regions and localities continue to beat the 

drum for the economic, security, and environmental benefi ts 

of clean and green industry development. 

Most notably, a global “race to clean” has now emerged, 

with numerous nations working to drive low-carbon and 

environmental industry growth. 

China—which now produces half of the world’s wind 

turbine and solar modules—recently announced it would 

accelerate its “clean revolution” over the next fi ve years and 

has set out aggressive growth plans for strategic emerging 

industries (SEIs) critical to economic restructuring, including 

multiple new energy categories, electric vehicles, and energy 

effi ciency products.1

Japan, in response to the Fukishima nuclear accident, has 

committed to achieving massive price reductions for solar 

The “green” or “clean” or low-carbon 

economy—defi ned as the sector of the 

economy that produces goods and services 

with an environmental benefi t—remains at 

once a compelling aspiration and an enigma 

as the nation and its regions search for new 

sources of growth.

I
SIZING THE CLEAN ECONOMY | I. INTRODUCTION 7

generation as part of a new renewables-oriented energy 

policy that will drive economic change through massive 

investments and yet-to-be-determined innovation.2

And, for its part, Britain’s Conservative-led coalition 

government recently outlined plans for the world’s fi rst 

state-backed green investment bank aimed at laying the 

foundation for clean industry growth.3

In short, while the emergence of the green or low-carbon 

economy originally fl owed from environmental concerns, a 

market vision now prevails—a vision in which new jobs and 

industries fl ow from the drive to reduce the environmental 

impacts of the economy. 

Along these lines, momentum for the business of “green” 

fl ows in part from the $154 billion in private capital invested 

worldwide in 2010 in renewable energy alone (up 650 

percent from 2004) and, looking forward, from the projected 

tripling to $2.2 trillion by 2020 of the broader world lowcarbon energy market.4 Or as Dow Chemical Company CEO 

Andrew Liveris wrote recently: “A renaissance is within 

reach. If Americans are the ones who design and build 

the new [clean economy] technologies it will re-energize 

commerce in the United States, creating, without a doubt, 

millions of high-paying jobs.”5

Such is the current form of the “green” economy 

aspiration.

And yet, for all that the clean economy also remains 

an enigma: hard to assess. Not only do “green” 

or “clean” activities and jobs related to 

environmental aims pervade all sectors 

of the U.S. economy; they also remain 

tricky to defi ne and isolate—and count. 

The clean economy, in this regard, 

is not only, or even mostly, a matter 

of dramatic and highly visible 

wind farms and solar parks. It also 

includes barely visible “green” 

variants of existing industries like 

food and appliance manufacturing 

along with industries such as 

sewage treatment or recycling whose 

environmental activities are so mundane 

as to be barely noticeable. 

But above all, the clean economy has also 

remained elusive because—in the absence of standard 

defi nitions and data—strikingly little is known about its 

nature, size, and growth at the critical regional level where it 

comes to ground. 

Currently no comprehensive national database exists on 

the spatial geography of the clean economy and its subindustries, although important work has assessed the clean 

economy across states.6 And while numerous studies have 

analyzed individual regional clean or green industries, a 

proliferation of defi nitions and the absence of data for large 

numbers of regions has made it diffi cult to situate regional 

clean economies in a national and comparative context. The 

upshot has been that national, state, and regional economic 

development actors of all kinds are largely without the 

high-quality, consistent, fi ne-grained data they need to 

set strategy and develop initiatives to advance the clean 

economy.

The result: Debates about the so-called “green” economy 

and “green jobs” have frequently been short on facts and 

long on speculation, assertion, and partisanship. 

Hence this report: Seeking to address some of these 

problems, the Metropolitan Policy Program at Brookings 

worked with Battelle’s Technology Partnership Practice 

to develop a detailed database of establishment-level 

employment in a sensibly defi ned assemblage of clean 

economy industries covering every county in the United 

States over the years 2003 to 2010. In that fashion, the 

pages that follow represent the fi rst study of the U.S. 

clean economy to provide timely information that is both 

comprehensive enough in its scope and detailed enough 

in its categorization to inform national, state, and regional 

leaders on the recent employment dynamics of the U.S. 

low-carbon and environmental goods and services supersector as they are transpiring in individual U.S. regions and 

metropolitan areas. Moreover, to begin promoting a greater 

continuity with other information, the defi nitions and 

measurements here anticipate the approach and structure 

of the federal government’s own forthcoming “green 

economy” count, due sometime next year at broader levels 

of geography.

What does the inquiry fi nd? Overall, the analysis depicts 

a clean economy that encompasses a modest-sized but 

growing and layered mix of diverse industries that varies 

widely in its distribution across U.S. metropolitan areas. To 

the growth question, while the clean economy’s aggregate 

employment growth remained modest in the 2000s (current 

clean economy employers added nearly half a million jobs 

between 2003 and 2010), young, high-profi le renewable 

energy, energy effi ciency, and related industries delivered 

hyper-growth, albeit from relatively small bases. 

Turning to the nature of the super-sector’s jobs, 

the new data confi rm that the clean economy is in fact 

delivering on hopes that it would generate a diverse array 

of quality positions that are at once more export- and more 

production-oriented than is the rest of the economy. Clean 

economy jobs tilt toward manufacturing and exporting and 

provide more opportunities with better pay for lower-skilled 

workers. At the same time, a cadre of highly trained 

innovators—scientists, engineers, architects—are 

also disproportionately demanded by the 

clean economy.

Beyond that, one of the most 

important fi ndings of this report has to 

do with the growth-promoting role of 

regional industry concentrations. Job 

growth in the clean economy has been 

signifi cantly faster in regional industry 

clusters than elsewhere. This means 

that understanding the region-by-region 

variation of the clean economy—whether 

in Albany or Little Rock or San Francisco—is 

not just an “interesting” bit of local color 

but critical for understanding the competitive 

strengths and potential of the clean economy 

wherever it is found. Gaining a sharper understanding of 

the nature and working of these concentrations can help 

national, state, and regional decision-makers identify 

centers of strength and focus strategies and investments 

for maximum growth in a time of limited resources. 

So this report aims also to help clarify some of what 

has remained opaque about the nation’s and its regions’ 

clean economy. 

To that end, the report begins by noting why the 

metropolitan clean economy matters and then proceeds 

to describe the defi nition, methods, and data used here 

to measure the clean economy nationally and across 

various levels of geography, with a focus on the 100 

largest U.S. metro areas. After that, the report reviews a 

series of measurements and trends that characterize the 

development of the clean economy across the nation and 

its regions. Finally, the report discusses those trends, and 

concludes by commenting on a number of policy problems 

that may be slowing the growth of the clean economy and 

suggesting some priorities for federal, state, regional, and 

private-sector work to advance clean economy growth.

In the end, the main takeaway is simple: The clean 

economy, as it stands today, is not a myth. It is real, 

ubiquitous, and growing—in some segments rapidly. And yet, 

for all that, too little is clearly known about the sector, which 

remains nascent, and which has not profi ted from the sort 

of policy environment that would best catalyze its growth. 

For all of those reasons, it is time to assemble the facts and 

decide as a nation of regions how best to make the most of 

the emergence of the clean economy. ●
8 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM
SIZING THE CLEAN ECONOMY | II. WHY THE METROPOLITAN CLEAN ECONOMY MATTERS 9

WHY THE METROPOLITAN 

CLEAN ECONOMY MATTERS

But why? Why should this particular swath of 

establishments, fi rms, and industries matter inordinately to 

national and metropolitan leaders? 

Further, what is so important about the metropolitan 

clean economy? 

There are multiple answers to these questions—including 

the possibility that the future growth of the clean economy 

will be sizable—but the most important ones involve the 

interconnection of these industries with some of the most 

fundamental issues of present day economic life.

The clean economy matters because its 

emergence responds to critical global and 

national environmental, security, and 

economic trends.

To begin with, the clean economy merits attention because 

its growth responds to worldwide megatrends associated 

with critical national and world challenges—notably the 

growing demand for global environmental sustainability, the 

sharpening need for resource security, and the aspiration 

everywhere toward economic transformation.1 

Global demand for environmental sustainability. The clean 

economy matters, fi rst of all, because its emergence refl ects 

a growing demand for environmental sustainability given 

growing concerns about the already massive scale of global 

and national environmental deterioration.2

At the global scale, steady population growth is exerting 

increasing pressure on scarce resources. A dozen years after 

reaching 6 billion people, the earth’s population will grow to 

7 billion later this year, probably 9 billion before 2050, and 

over 10 billion by 2100.3

 Over the same period, economic 

development and the growing wealth of rising nations will 

propel over 1 billion more people into the global middle 

class. These new, mostly urbanized consumers will purchase 

energy-intensive goods like appliances and automobiles for 

the fi rst time, upgrade towards land- and water-intensive 

diets comprised of more meat and fewer basic staples, 

and generate increasing amounts of waste—all placing new 

pressures on world resources.4

An already stressed planet will be further strained in 

coming decades. On the water front, the U.N. reckons that 

after growing at a steady rate of 2 percent per year for the 

past half century, global demand for water has posted a 

long-term step change increase and will grow at 3 percent 

per year into the future.5 Consulting fi rm McKinsey & Co. 

sees a 40 percent shortfall between existing water supplies 

and projected demand in 2030 absent effi ciency gains.6

Global energy consumption, for its part, is projected to 

increase perhaps 50 percent in the years to 2035.7

 Yet if 

catastrophic climate change is to be averted, greenhouse 

gas (GHG) emissions from the combustion of conventional 

fossil fuels must be reduced substantially.8

Which points to another environment-related driver 

of clean economy growth: the likelihood of more and 

more stringent regulatory responses to the sustainability 

challenge around the world. Notwithstanding the collapse 

in late 2009 of efforts to craft a single global agreement to 

reduce GHG emissions and the foundering of congressional 

efforts to institute a “cap and trade” carbon pricing 

There is no doubt that the “clean,” or “green,” 

economy looms large in global, national, and 

regional economic debates.

II
10 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM

system, unprecedented national emission reduction targets 

were agreed to by over 75 countries at varying stages 

of development (including the United States) as part of 

the scaled-back Copenhagen Accord.9 Nations and major 

states in the United States have enacted no fewer than 

293 binding and accountable new emissions reduction 

commitments since June 2008.10 Looking forward, continued 

environmental concern in the United States and around 

the world will almost certainly motivate the adoption 

of additional environmental standards that will sharpen 

demand for low-carbon or environment-friendly goods 

and services. 

The bottom line: Environmental stress and policy 

responses to it are driving and will continue to drive waves 

of industrial change. Just as the growth of a post-war 

environmental consciousness (refl ected in the Clean Air 

and Water Acts in the U.S.) drove the emergence of a fi rst 

generation of clean economy industries such as recycling, 

pollution control, and remediation, concern about global 

sustainability and climate change are spurring the growth 

of a new set of energy related industries today—with more 

change inevitable.11

A sharpening need for resource security. The clean 

economy also matters for reasons of resource security: 

It refl ects new demands that this nation and others 

reduce their vulnerability to resource supply shocks and 

related confl ict.12

Currently, the United States consumes nearly 19 million 

barrels of oil per day—half of it imported—to power its 

economy, move its people and products, and manufacture its 

goods.13 That leaves the entire U.S. economy vulnerable to 

geopolitical instability and supply disruptions abroad.14 For 

example, the high and volatile energy prices of 2008 warned 

of a new, tighter, and more uncertain reality on the world 

market for fossil fuels, particularly oil.15 Today, economic 

recovery, the return of oil prices to over $100 per barrel, and 

the Arab Awakening’s uncertain course in the Middle East 

and North Africa have only sharpened these concerns. And 

rightly so: Such uncertainty and price volatility has been 

shown to reduce investment across the economy, increase 

business costs, disrupt household budgets, and so depress 

domestic growth.16

However, the “green” and low-carbon goods, processes, 

and services being developed by the clean economy 

represent an opportunity for the nation to insulate itself 

from price and supply shocks and begin to disentangle 

itself from the messy geopolitics of oil through effi ciency 

advances and a diversifi cation of the nation’s energy-source 

portfolio.17

In this connection, environmentally-oriented technologies 

and processes will likely contribute to resource security by 

reducing the environmental impact of exploiting the fossil 

fuels that are already abundant in energy-hungry countries 

like the U.S. and China, such as coal and shale gas—making 

uptake manageable by mitigating their adverse effects. Coal 

will remain an important source for generating electricity 

well into the future so it is likely that end-of-pipe mitigation 

technologies and carbon capture and sequestration systems 

will emerge as critical aspects of its use. Likewise, water 

and drainage treatment technologies are already seeing 

signifi cant new demand associated with managing the 

substantial fl ows of contaminated “process” 

water generated by the hydraulic fracturing 

techniques used in extracting gas and oil 

from shale deposits.18

Paralleling these dynamics are stresses 

involving the world’s water resources. Water 

security threatens to become a fl ashpoint in 

many already volatile regions of the world 

where supplies are at once scarce (the Middle 

East), facing signifi cant pressure in demand 

(South and East Asia), and vulnerable to 

a changing climate (everywhere).19 Since 

agriculture soaks up 70 percent of the 

water consumed globally, changes in water 

supply—which will be how climate change 

most tangibly affects daily human activity—

will have direct and global effects on food 

security.20 Exacerbating the issue, much of 

the population growth mentioned above 

will take place in regions with already 

overburdened or underdeveloped water 

infrastructure.21 Yet here, too, the waterrelated industries of the clean economy hold 

out the hope of minimizing shortfalls (and 

so confl ict) and securing supplies through 

effi ciency gains and advancements in 

purifi cation, management, and recycling technologies.22

A world-wide aspiration toward economic transformation. 

Finally, there remains a third increasingly ascendant factor 

behind the clean economy’s signifi cance: the prospect of 

industrial transformation. The clean economy matters, 

in short, because it interacts with nearly every aspect of 

the rest of the economy and is emerging as a site of rapid 

technological and process innovation world-wide.

Innovation, after all, remains a crucial driver of economic 

growth, and so clean economy innovation—motivated by 

the unprecedented environmental and resource challenge 

outlined above—appears a likely source of future economic 

development as fi rms of all kinds seek to invent new, 

environmentally friendly ways to decrease the world’s 

carbon and resource intensity.23

In fact, the likelihood of transformation is already 

attracting investment. Some $1 trillion in investment 

capital globally fl owed into clean energy segments alone 

between 2004 and 2010, as yearly investment levels nearly 

quintupled from $52 billion to $243 billion.24 Looking 

forward, a recent survey by Ernst & Young found that threequarters of major global corporations plan to increase their 

“cleantech” budgets from 2012 to 2014 and that 40 percent 

of that spending will fl ow into R&D.25 Turning to water, the 

prospect of innovation is also attracting increased investor 

attention. Most notably, venture capital (VC) fi rms poured 

nearly $1.25 billion into the historically staid sector between 

2005 and 2010 through close to 250 separate deals.26

In this regard, one of the most important heralds of 

both present and future innovation potential and economic 

transformation may be VC investment. VC backed fi rms are 

roughly three to four times more innovative (as measured by 

their patent production) than their counterparts that receive 

The largest 100 metros

contain 63 percent of the 

nation’s residential structures, 

64 percent of the nation’s 

vehicle miles traveled, and 

account for 56 percent of the 

nation’s carbon emissions.

 63% 64% 56% 63% 64% 56%
SIZING THE CLEAN ECONOMY | II. WHY THE METROPOLITAN CLEAN ECONOMY MATTERS 11

other forms of private investments and as it happens clean 

economy companies are increasingly in the sights of VCs.27

Between 1995 and 2010, the share of U.S. VC dollars fl owing 

to clean economy concerns increased from 2 percent in 1995 

to 16 percent in 2010.28 Looking forward, analysts predict 

increasing shares of global and U.S. VC investment to fl ow 

into clean economy technologies.29

Even now the pace of innovation has picked up in many 

clean economy sectors, and with it the possibility that the 

clean economy will create future jobs as well as new climatefriendly goods, services, and processes. On this front, 

patenting tells the story. According to the Organization for 

Economic Cooperation and Development (OECD), patent 

applications fi led at the European Patent Offi ce (EPO) 

related to the clean economy rose from 4.6 percent of all 

patents in 1987 to 7.4 percent in 2007, such that by 2007, 

over 9,000 clean economy patent applications were being 

fi led annually, just at the EPO. Some 17 percent of these 

patents originated with U.S. inventors.30

In short, the clean economy increasingly looks like a 

promising location for the emergence of signifi cant new 

technologies, processes, and industries that will shape the 

next economy and generate new jobs. That dozens of the 

world’s nations ranging from Brazil and China to South 

Korea and Turkey are investing heavily in such development 

both reinforces the emerging consensus and underscores 

that the “race to clean” has become an urgent competition 

among states for the resource productivity, jobs, and exportoriented manufacturing that will come with it.31

The metropolitan clean economy matters 

because that’s where the clean economy is 

being built, fi rm by fi rm and cluster by cluster. 

But why, then, does the metropolitan or regional clean 

economy matter inordinately? The reason has to do with the 

special importance of geography in economic life.

Regions contain, aggregate, and amplify the key “drivers” 

of innovation and economic dynamism.31 Far from being 

placeless, the economy—and economic change—is placebased. In this respect, the clean economy—like the rest of the 

economy—is neither disembodied nor “fl at,” but concentrates 

in particular places.33

This concentrated reality of the national and the clean 

economies is fi rst of all arithmetic. Just as the 100 largest 

U.S. metropolitan areas encompass two-thirds of the nation’s 

population but three-quarters of the nation’s economic 

output, such places contain and add up key pluralities of 

the nation’s clean economy markets and inputs. 

The largest 100 metros contain, for example, 66 percent of the nation’s population, 63 percent of the nation’s 

residential structures, and 64 percent of the nation’s 

vehicle miles traveled while accounting for 56 percent of 

the nation’s carbon emissions.34 As such, these regions 

represent the nation’s prime users of public water, electricity, 

and fuel; stand as the core generators of wastes and 

pollution that must be remediated; and so represent a 

prime global market for air and water management, energy 

effi ciency goods and services, building retrofi ts, renewable 

energy, low-carbon transportation solutions, and the smart 

systems needed to run them. Already, 73 percent of the 

nation’s LEED certifi ed green buildings stand in the nation’s 

top 100 metro areas.35

More than major markets for clean economy goods 

and services, however, the nation’s largest metro areas 

aggregate the key inputs to clean innovation. Two-thirds of 

the nation’s major research universities and environmental 

science and energy doctorate programs reside within the 

100 largest metropolitan areas as do three-quarters of the 

nation’s workers with degrees in science and engineering.36

Likewise, 48 out of nation’s 83 top environmental sciences 

and energy research laboratories operate there. 

At an early stage of the commercialization pathway, 

no fewer than 96 of the 119 companies and research 

organizations that have so far won grants from the 

Advanced Research Projects Agency—Energy (ARPA-E) 

for cutting-edge clean energy research projects are based 

in the largest U.S. metros.37 Farther along the path, 

Department of Energy (DOE) loan guarantees have also 

fl owed heavily to metropolitan centers of commercial 

activity and deployment. Some 86 percent of this fi nancing 

has fl owed to the 21 projects (out of 30 total) located in 

the 100 largest metro areas.38 On the environmental side, 

65 percent of Small Business Innovation Grants administered 

by the Environmental Protection Agency fl owed to the top 

100 metros. 

These results reinforce U.S. economic geography. The 

100 largest metropolitan areas are the nation’s innovation 

engines, generating some 78 percent of the nation's green 

patents.39 Their dynamism, moreover, means that 54 of the 

58 highest-impact U.S. cleantech fi rms called out in the 

2010 Global Cleantech 100 list are based in the 100 largest 

U.S. metropolitan areas. (Going further, 39 of the 58 are 

headquartered in just four metros characterized by vibrant 

clean economy industry clusters—Boston, San Francisco, San 

Jose, and Los Angeles).40

In short, metropolitan areas, large and small, are now 

and will increasingly be the nation’s critical centers of clean 

economy talent, innovation, and fi nance and so its top hubs 

of commercialization, deployment, and trade. 

Regions and metropolitan areas, in short, are not a part 

of the national clean economy; they are that economy, as 

Alan Berube has written.41

For all of its signifi cance, though, rather little is known 

about the size and shape of the clean economy, especially 

at the regional level. ”Sizing the Clean Economy“ is one 

response to that gap. ●
12 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM
III

SIZING THE CLEAN ECONOMY | III. DEFINING AND MEASURING THE CLEAN ECONOMY IN U.S. METROPOLITAN AREAS 13

DEFINING AND MEASURING 

THE CLEAN ECONOMY IN U.S. 

METROPOLITAN AREAS

Literally hundreds of disparate studies of the clean or 

green economy exist. In fact, the California Employment 

Development Department requires 24 pages in a recent 

digest to list all of the studies it tracks on the clean 

economy.1

 Many of these studies focus on individual states. 

Others create national data using various methods. And 

many of the analyses employ varied defi nitions of this 

heterogeneous sphere of economic activity. For their 

part, the state- or region-specifi c studies provide detailed 

information but usually can’t be compared across geographic 

units to place states or metropolitan areas in the national 

context. At the same time, the national studies either ignore 

sub-national geography or only provide information at a very 

high level of aggregation. 

Hence, what follows is the fi rst study of the U.S. clean 

economy to provide consistent and timely information that is 

both comprehensive enough in its scope and detailed enough 

in its categorization to inform national, metropolitan, and 

even local leaders on the recent dynamics of the U.S. lowcarbon and environmental goods and services super-sector—

with particular emphasis on regional growth and evolution.

Similarly, the pages that follow extend a large body of 

work at the Brookings Metropolitan Policy Program on 

the nature of the emerging “Next Economy” in the United 

States.2

 This work has focused on the possible underpinnings 

of future U.S. growth and moved to investigate the 

contention that the “next” U.S. economy needs to be more 

export-oriented, lower-carbon, and innovation-driven as 

well as opportunity rich. Key methodological decisions in 

developing this report were made with those preoccupations 

in mind. Further details are available in a detailed 

methodological appendix that is available separately from 

this report at the “Sizing the Clean Economy” project page 

on the Brookings website (http://www.brookings.edu/metro/

clean_economy.aspx).

DEFINITIONS AND CATEGORIES 

While there is no consensus on a defi nition of the clean 

economy, there are many points of agreement. Moreover, 

various studies have openly and thoughtfully addressed the 

diffi culties involved. In advancing a defi nition of the clean 

economy, therefore, this report seeks to align itself with 

well-established guidelines and precedents while laying out 

rules that are simple, internally consistent, transparent, and 

replicable.

The basic defi nition of the clean economy used in this 

study runs as follows:

The clean economy is economic activity—measured 

in terms of establishments and the jobs associated 

Whatever the terminology, the “clean” or 

“green” or low-carbon economy prompts 

almost as much confusion as it does curiosity 

and fascination. One reason: Defi ning it and 

measuring it have proven extraordinarily 

diffi cult.
14 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM

with them—that produces goods and services with an 

environmental benefi t or adds value to such products 

using skills or technologies that are uniquely applied to 

those products. 

To elaborate on this relatively succinct and conservative 

defi nition, a few words are in order on the precedents, terms, 

and approach employed here.

First, it bears noting that the language and distinctions 

used here draw heavily from both European and U.S. 

government statistical precedents. Most notably, key aspects 

of the present defi nition, categorization, and approach 

draw from previous defi nitional and measurement work 

by Eurostat and the Organization for Cooperation and 

Development (OECD) as well as by the U.S. Environmental 

Protection Agency (EPA) and the U.S. Bureau of Labor 

Statistics (BLS), which will next year release its own 

measurement of the “green” economy.3

 In that sense this 

measurement has sought continuity with other authoritative 

research rather than newness.

Second, it is also worth noting that this is an economic 

development study focused tightly on clean economy 

business establishments and the jobs they create. To 

elaborate on this orientation, this report is primarily about 

the establishments and jobs of U.S. enterprises whose 

products have an environmental benefi t, including those 

that add value as part of the clean economy supply chain. 

Given that, the report does not attempt to measure jobs in 

companies that conduct themselves in an environmentallyfriendly manner. Rather, it insists that companies and 

establishments sell, or in the case of the public sector, 

provide products or services with an environmental benefi t 

(either inherently, like environmental remediation services 

or relatively, like organic food or solar panels). For example, 

no effort was made here to count companies that adopt 

internal environmental goals, reform their processes to 

make them more environmentally responsible, or even 

contribute to general public knowledge about environmental 

issues. However valuable these activities are, this study 

excludes the jobs related to those activities from the clean 

economy. They could be thought of as “clean process” jobs, 

as opposed to “clean production” jobs.4

As stipulated above, moreover, a product must benefi t the 

environment to be deemed “clean.” This is consistent with 

the BLS standard for its clean production survey, and it is a 

slight variation on the Eurostat standard which mandates an 

environmental purpose.5 The environmental benefi ts include 

preventing or minimizing pollution (including greenhouse 

gas emissions), or natural resource depletion, or managing 

natural resources, including energy, air, and water, for 

greater effi ciency, conservation, or protection. 

The last part of the above defi nition—regarding 

companies that add value to clean economy products—is 

intended to capture the relevant aspects of the clean supply 

chain. Companies that directly produce clean technologies 

or services, like wind turbines, are unambiguously part of the 

clean economy, but it is less clear how to classify companies 

that supply parts or services to those clean producers, such 

as manufacturers of parts for turbines. Some suppliers 

provide products that are used across industries and 

purposes (e.g. screws, computer equipment, accounting, 

fi nancial management), but others make products that 

are only used in the clean technologies or require skills 

that are unique to clean technologies (e.g. blades, frames, 

environmental engineering). The guiding principle used 

in this study has been to only include the establishments 

of companies that add value uniquely to clean products, 

whether by supplying a special part or a service, using skills 

or technologies that are unique to the clean economy. For 

example, home weatherization, energy retrofi tting, and 

solar panel installation require skills that distinguish those 

services from traditional maintenance work or roofi ng.

Finally, some industry and impact studies estimate 

“direct” and “indirect” employment. By contrast, this study 

measures only employment in establishments that directly 

produce goods and services with environmental benefi ts, 

or produce uniquely tailored goods and services that add 

value to products with an environmental benefi t. Studies 

of “indirect” jobs, for their part, use information on crossindustry purchases to claim that one industry stimulates 

the creation of jobs in another. This method is useful for 

regional impact studies that estimate the effect of business 

relocations and national impact studies that estimate the 

effect of government stimulus during a downturn. In both 

cases, the source of added revenue can be thought of as 

external and temporary. However, such an approach is 

not appropriate for a study like this one where there is no 

external source of revenue. No establishment generates its 

own revenue out of nothing, and so every direct job is some 

other industry’s indirect job. 

Consequently, the job totals reported here will be lower 

than many studies which include “indirect” jobs. This isn’t to 

deny that clean economy fi rms are involved in rich networks 

of business relations with traditional “non-clean” fi rms; it 

is simply to say there is no reason to think of these general 

suppliers or customers as components of the clean 

economy sector.

This approach has the advantage of being fi rmly rooted 

in economic activity connected to supply and demand in 

competitive markets, rather than just voluntary business 

philanthropy. This focus, along with a “direct” jobs count 

from actual companies, makes the measurements akin to 

industry data from government agencies and provides the 

sort of straightforward information needed for strategic 

thinking about investments.
SIZING THE CLEAN ECONOMY | III. DEFINING AND MEASURING THE CLEAN ECONOMY IN U.S. METROPOLITAN AREAS 15

MEASUREMENT AND DATA

With the defi nition and method settled, the BrookingsBattelle team proceeded to measure the clean economy 

by building a database of clean economy companies and 

establishments “from the ground up.” That is, instead of 

doing a national survey, which would be extremely costly 

if it were to be locally representative and require an array 

of diffi cult assumptions about sampling, the team took on 

the task of identifying and locating every company (and 

ultimately establishment) in the clean economy that could 

reasonably be identifi ed using a variety of validated public 

and proprietary data sources. 

Normally, standard industrial codes would be used 

for such a measurement exercise, but because the clean 

economy pervades so many industries, many codes contain 

establishments that fall both inside and outside the clean 

economy while at the same time no existing industry 

classifi cation system breaks out green industries, whether it 

be solar energy activities, energy effi cient products, green 

materials production, or enterprises aimed at the reduction 

of greenhouse gases. Or as the BLS explained in its March 16, 

2010 Federal Register notice on approaches to measuring the 

green economy: “The studies reviewed showed that neither of 

the standard classifi cation systems used in the BLS data, the 

North American Industry Classifi cation System (NAICS) or the 

Standard Occupational Classifi cation (SOC), identifi es a green 

or environmental grouping of industries or occupations.” 

The upshot: Company and ultimately establishmentspecifi c information was needed to identify and quantify 

clean economy establishments and employment.

Identifying clean economy companies and 

establishments

Two approaches were taken to identify clean economy 

fi rms. First, a set of industries deemed exclusively part of 

the clean economy was identifi ed using the eight-digit SIC 

(Standard Industrial Classifi cation) system developed by 

the business intelligence fi rm Dun & Bradstreet (D&B) and 

maintained as a time series by Walls & Associates as the 

National Establishment Time Series (NETS).6 In performing 

research on the clean economy for the Pew Charitable Trusts, 

Collaborative Economics developed a list of industries that 

could be considered completely embedded in the clean 

economy, in that each establishment in that listing produces 

goods or services that have an environmental benefi t as 

defi ned above. More recently, Berkeley researchers worked off 

that list and added over 100 new SICs to it.7

 This study used 

the Berkeley list as a starting point and incorporated almost 

every company, establishment, and job in those industries and 

added relevant SICs for air, water, waste management and 

treatment.8 This industry-based approach yielded 49 percent 

of all jobs and 69 percent of all establishments included in 

this study (see external appendix for full list).9

The second approach employed for identifying clean 

economy fi rms and establishments was to create a validated 

master clean economy list to catalogue every known industry 

association, certifi cation, federal grantee, venture capital 

recipient, patent assignee, and product list that is relevant 

to the clean economy. In this fashion, over 60 lists of clean 

economy companies (see the appendix) were compiled to 

create a substantial list of fi rms. The team also considered 

and incorporated listings from market research organizations 

and proprietary industry data sources, such as the Environmental Business Journal and Plunkett’s Renewable, 

Alternative and Hydrogen Energy Industry Almanac. All of the 

lists were carefully validated. Lists were rejected if the team 

discovered that non-clean economy companies were allowed 

to join. The companies from the master list were incorporated 

into the study, and duplicate establishments were removed.

With the industry codes identifi ed and fi rm lists 

assembled, the next step was to fi nd statistics on the 

companies and their relevant establishments using Dun & 

Bradstreet. Establishment history and other characteristics 

were added through the use of NETS.

For companies that produce both “green” and “nongreen” products an effort was made to include only 

establishments that specialize in the clean economy 

production. This task was facilitated by Dun & Bradstreet 

and NETS because they employ detailed industry 

classifi cation schemes that distinguish activities across 

establishments of the same company and even within 

single locations. 

For cases where large establishments were known to 

produce both green and conventional products, information 

from companies, including their websites, was used to 

allocate a percentage of the site’s employees to the clean 

economy based on the relative importance of its clean 

products compared to all of its products. Because of the 

nature of the Dun & Bradstreet database, many of the 

smaller establishments of less than fi ve employees were a 

mix of independent contractors and fi eld offi ces rather than 

stand-alone establishments. In order to ensure consistency 

within the establishment and job count, those very small 

establishments were excluded from the Brookings-Battelle 

database. This resulted in a roughly fi ve percent reduction 

in the total number of clean economy jobs and a larger 

reduction in the number of establishments as most of them 

had zero jobs. (See appendix for details).

Classifying the establishments

Once the company, establishment, and job information was 

compiled, the next step was to classify it. The goal was to 

make the data as analytically useful as possible to facilitate 

research at various geographic levels and especially for 

regional economic development planning. There were a 

number of options, and ultimately this study reports the 

data in three ways.

First, through Dun & Bradstreet and NETS, the data 

is organized by NAICS categories, which is how the 

U.S. government reports data (e.g. for manufacturing, 

construction, fi nancial services, and so on). Second, 

because only a small fraction of NAICS categories reside 

within the clean economy, a second scheme was adopted 

that divided establishments into fi ve high-level categories 

(largely adopted from the BLS). Finally, to provide a third, 

fi ner-grained categorization, 39 segments designed by the 

Brookings-Battelle team was used to further narrow the 

class of business activity and allow for detailed analysis.10

Establishments were assigned to segments based on their 

industry code, the list used to identify them, or, in some 

cases, information provided by the company’s website.11 The 

external methods appendix presents a table that shows how 

the company lists were matched up to segments.

Other measures

A series of other measures were created using the clean 

economy database. Details on how these were calculated 

are available in the appendix document. A quick description 

follows: 

Because of the way companies were identifi ed—using 

member lists, grantee lists, and so on—no way existed for 

recreating the same universe of clean economy fi rms 

in previous years. Yet, the employment history of fi rms 

currently existing—including when they were born—was 

available through NETS from 2003 to 2009 (with D&B data 

providing the most current 2010 jobs fi gures—as downloaded 

in early 2011). This created a problem when calculating 

growth rates: The base year was artifi cially higher than 

it would otherwise be because the database contained no 

record of job losses from establishments that went out 

of business (only those that laid off workers). This is fi ne 

when comparing segments, states, or MSAs, because the 

bias is shared more or less evenly, but it won’t work for 

comparisons against the “non-clean” national economy. To 

adjust U.S. growth from 2003 to 2010 for the loss of jobs 

from closing establishments, information was obtained 

from the Bureau of Labor Statistics’ Business Employment 

Dynamics series and the NETS.12 The national base year 
Brookings-Battelle Category 

Agricultural and Natural Resources Conservation

Education and Compliance

Energy and Resource Effi ciency

Greenhouse Gas Reduction, Environmental Management, 

and Recycling

Renewable Energy

Brookings-Battelle Detailed Segments

Conservation

Organic Food and Farming

Sustainable Forestry Products

Regulation and Compliance

Training

Appliances

Battery Technologies

Electric Vehicle Technologies

Energy-saving Building Materials

Energy-saving Consumer Products

Fuel Cells

Green Architecture and Construction Services

HVAC and Building Control Systems

Lighting

Professional Energy Services

Public Mass Transit

Smart Grid

Water Effi cient Products

Air and Water Purifi cation Technologies

Carbon Storage and Management

Green Building Materials

Green Chemical Products

Green Consumer Products

Nuclear Energy

Pollution Reduction

Professional Environmental Services

Recycled-Content Products

Recycling and Reuse

Remediation

Waste Management and Treatment

Biofuels/Biomass

Geothermal

Hydropower

Renewable Energy Services

Solar Photovoltaic

Solar Thermal

Waste-to-Energy

Wave/Ocean Power

Wind

16 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM

could then be adjusted to calculate what growth would have 

been nationally if no jobs were lost from establishments that 

closed. The job growth fi gures reported in this report refl ect 

this adjustment, and therefore are higher than actual net 

growth rates.

Exports from each establishment were estimated 

by allocating national exports for a given three or fourdigit NAICS industry to establishments based on the 

establishment’s share of total U.S. employment in that 

three or four-digit industry. A similar approach was applied 

to metropolitan areas in recent Brookings research and is 

described in detail in that report.13 The same sources and 

techniques were used here.

Data on the number of occupations, type of occupations, 

wages, and education requirements for each job were 

calculated using national statistics from the BLS’s 

Occupational Employment Statistics (OES) program and 

Employment Projections Program (EPP).14 OES provides 

estimates for the number and type of occupations in each 

four-digit NAICS, and EPP provides education attainment 

estimates for each occupation. Occupations that fell within 

the middle range of the median wage distribution were 

classifi ed as moderate-wage “green collar” pursuits.

Establishments were identifi ed as clustered if they were 

located in a county with a signifi cant number of jobs in other 

establishments in the same segment. The threshold was 

whether or not the number of other-establishment jobs in a 

county’s segment was greater than one percent of the U.S. 

jobs for that the segment. Other defi nitions—including the 

use of relative shares—yielded similar results. 

LIMITATIONS AND CHECKS

While the goal of this report was to measure every 

establishment and job in the clean economy, that is 

clearly an impossible task. The study surely left out many 

companies that are rightfully part of the clean economy, and 

there is no doubt that the employment fi gures and location 

data from Dun & Bradstreet and NETS will not always exactly 

match the real world. 

One reason for this is the fact that for whatever reason 

some clean economy companies fail to appear on any of the 

lists used to compile the bulk of the database. 

Take the car-sharing business, for example, which claims 

to reduce the demand for cars and the consumption of gas 

through its convenience and fuel-effi cient car-sharing fl eets.15

These assertions are supported by academic research 

on car-sharing.16 Critics could counter that car-sharing 

encourages driving over more environmentally-friendly 

public transportation, and there is evidence that car-sharing 

Table 1. Brookings-Battelle Clean Economy Industry Categories and Segments
SIZING THE CLEAN ECONOMY | III. DEFINING AND MEASURING THE CLEAN ECONOMY IN U.S. METROPOLITAN AREAS 17

is more common where public transit is readily available.17

But whatever its true environmental impact, no car-sharing 

company is in this database. The reason is that they did 

not win any clean economy grants, join any green industry 

associations, obtain any green certifi cations, develop any 

clearly identifi able green economy patents, or receive money 

from a cleantech venture fund. There are surely other 

companies that many people would consider to be “green” 

that likewise did not make it into this database for the 

same reason.

With these caveats in mind, there is compelling evidence 

that the Brookings-Battelle clean economy database 

provides a reasonably accurate estimation of the clean 

economy.

To assess and improve accuracy, a preliminary version 

of this database was shared with research partners with 

regional expertise in metropolitan areas like Sacramento, 

Chicago, the counties of the Northeast Ohio region, and the 

states in New England. The research partners were asked 

to identify, by their judgment, mistakes in the database 

including, especially, clean economy fi rms that were left out 

of the Brookings-Battelle database. Some of these research 

partners embarked on extensive efforts of data collection, 

including interviews with local industry leaders and analysts. 

Where signifi cant oversights or discrepancies were identifi ed 

the Brookings-Battelle team redoubled its efforts to locate 

new lists with broader coverage of those sectors that were 

originally under-counted. The resulting effort added several 

hundred thousand jobs to the database. This process was 

repeated on several occasions.

To get a general sense of the accuracy of the fi nal 

database, one can compare it to other studies of the clean 

economy. In this fashion, the Brookings-Battelle database 

contains 2.7 million jobs. This fi gure runs to the higher end 

of recent estimates but lies within the range reported by the 

U.S. Department of Commerce in a recent report. For that 

matter it is three to fi ve times higher than national estimates 

produced in recent years by the Pew Charitable Trusts and 

the U.S. Conference of Mayors. 

At the state level, the number of clean economy jobs 

reported in this count tends to slightly exceed that reported 

by various state survey estimates. The present count runs 

between 12 and 25 percent higher than the total number 

of jobs estimated by state government surveys in Oregon, 

California, and Connecticut.18 Estimates by a state agency 

for Washington in 2008 were roughly half of the BrookingsBatelle estimates but after a methodological change the 

2009 edition of the survey yielded a jobs number 19 percent 

higher than the Brookings-Battelle estimates.19 Two states—

Missouri and Kansas—came up with “direct job” estimates 

that were one-third to one-fourth lower than the BrookingsBattelle fi gures.20 Michigan was the only state with a major 

green jobs survey that produced a substantially higher 

number than the Brookings-Battelle employment estimate.21

There, the Brookings-Battelle estimate came in about 30 

percent lower than the Michigan number. Finally, a study of 11 

large counties in California by researchers at the University 

of California at Berkeley located 110,000 clean economy jobs 

in those counties—a fi gure that compared with a BrookingsBattelle fi gure of 169,000 for the same counties.22

Finally, the Brookings team also compared job levels in 

this database to various industry reports. In almost every 

case, the industry reports—which frequently reported 

“indirect” as well as “direct” jobs—exceeded the present 

estimates. However, when direct jobs are compared, the 

Brookings numbers are much closer. The Solar Energy 

Industries Association has estimated 24,000 direct jobs 

in the solar industry.23 This number is slightly lower than 

the 29,531 estimated by Brookings and Battelle. The 

Solar Foundation, in conjunction with Green LMI, did a 

national survey suggesting that there were 93,502 solar 

energy jobs (mostly in California) but only 24,916 jobs in 

solar manufacturing.24 This comparison reveals that the 

Brookings-Battelle estimates probably undercount jobs in 

solar installation; those workers are diffi cult to measure 

because the work is done by companies that are heavily 

involved in traditional construction and installation activities. 

For its part, the National Hydropower Association estimates 

that hydropower accounts for 60,000 direct jobs, compared 

to 55,433 estimated by Brookings-Battelle.25 Likewise, the 

American Wind Energy Association estimates 30,000 direct 

jobs; Brookings-Battelle estimates 24,294 wind jobs.26 And 

fi nally, the Geothermal Energy Association estimates 9,000 

direct jobs, while the Brookings-Battelle fi gure is 2,720.27

Overall, while not perfect matches, these comparisons 

suggest the database presented here is fairly reliable, 

though coverage of solar installers is probably lacking.

To gauge how well the database picked up specifi c 

companies, a fi nal quality check was conducted using 

the Global Cleantech 100 list produced by The Guardian 

newspaper in partnership with Cleantech Group. These 

100 highly-rated companies were selected by a panel of 

60 experts from around the world under the criteria that 

the companies represent the highest potential for market 

impact, are for-profi t and private, and are not listed on any 

major stock exchange.28 Of these, 81 percent (or 47 out of 

58) were included in the Brookings-Battelle database. Those 

missed were either not covered by Dun & Bradstreet or 

had fewer than fi ve employees in the D&B record; the only 

exception was a car-sharing company, which did not make it 

on to any public list except the Global Cleantech 100.

In short, through comparisons with other national, 

regional, and even industry studies and refi ned lists of 

new fi rms like those on the Global Cleantech 100, the 

evidence suggests that the Brookings-Battelle method 

offers a reasonably accurate measure of the clean economy. 

National and state comparisons provide no evidence that 

this method has signifi cantly undercounted the number of 

clean economy jobs. Indeed, most studies of comparable 

geographies have found many fewer jobs, and yet, the strict 

requirements for inclusion mean that an over-count is highly 

improbable. 

In addition to accuracy, the “bottom-up” method utilized 

here makes this arguably the most comprehensive study 

to date. No other dataset provides such fi ne-grained 

classifi cation and no other dataset provides national, state, 

and metropolitan data across the entire United States. What 

is more, while the forthcoming BLS green jobs study will 

provide some of these geographic advantages (state data 

will be available), it will probably not be able to disclose job 

numbers in many locations because of survey-participation 

agreements. Likewise, it will report the data at the two-digit 

NAICS level but will not offer the segment detail provided in 

the Brookings-Battelle database. 

Ultimately, the two surveys should prove complementary. 

While the BLS survey will be valuable, it may not fully satisfy 

the demand from state and metropolitan actors for detailed 

geographic and segment information, which means existing 

sub-national measurement efforts, such as this study, will 

probably need to be continued as long as there is interest in 

measuring the clean economy.

In conclusion, while many studies of the green or clean 

economy have often seemed to play out as proxy wars in the 

larger debate over climate change policy, this work tries to 

step back from those issues. By embracing sound precedents 

and transparency, this effort seeks simply to deliver a 

reasonably accurate and locally useful measurement of the 

fi rms, establishments, and jobs in the United States that 

are providing goods and services related to protecting the 

environment, mitigating climate change, conserving energy, 

and generating clean power. The sections that follow analyze 

the data and discuss various policy implications. At the same 

time, for those who want to drill down on all of the jobs 

data, as well as selected clean economy indicators for the 

nation, the states, and the 100 largest metropolitan areas, 

that material is available for free download at the Brookings 

website (http://www.brookings.edu/metro/clean_economy.

aspx). ●
18 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM
IV

SIZING THE CLEAN ECONOMY | IV. MEASURING AND TRACKING THE CLEAN ECONOMY IN U.S. METROPOLITAN AREAS 19

MEASURING AND TRACKING

THE CLEAN ECONOMY IN 

U.S. METROPOLITAN AREAS

1. The clean economy, which employs some 2.7 million 

workers, encompasses a signifi cant number of jobs 

in establishments spread across a diverse group of 

industries. In 2010, 2.7 million jobs in the United States 

directly contributed to the production of goods and services 

that had an environmental benefi t. The jobs were spread 

over 57,501 different establishments in 41,185 companies and 

existed in almost every industry.

Encompassing 2 percent of all positions, the clean 

economy represents a modest slice of the U.S. economy. By 

contrast, the healthcare sector—the nation’s largest source 

of private employment—employs 13.8 million workers, and 

accounts for 10.2 percent of jobs.1

 Yet, compared to many 

other cross-industry sectors, the clean economy looks much 

more signifi cant (see Figure 1). For example, just 1 percent 

of jobs (1.3 million) directly support the production of fossil 

fuel-based energy, derivative manufactured products, and 

machinery; that number rises to 1.8 percent (2.4 million) 

if all wholesale and retail distributors and transporters 

are included such as gas station employees.2

 Likewise, the 

biosciences sector—a focus of much investment interest—

supports just 1.4 million employees.3

 Producers in the 

So what does this assessment of the U.S. clean 

economy fi nd? This analysis of establishmentlevel data compiled by the Metropolitan Policy 

Program at Brookings and Battelle covering 

the entire United States and focusing on the 

nation’s 100 largest metropolitan areas reveals 

a series of key takeaways: 

Figure 1. The Clean Economy Compared with 

Other Sectors of the U.S. Economy

Source: Biosciences: Battelle and Biotechnology Industry Organization, “State 

Bioscience Initiatives 2010” (2010); Fossil Fuels: Brookings analysis of County 

Business Patterns and Bureau of Labor Statistics data; Information Technology: 

Moody's Analytics; Clean Economy: Brookings-Battelle Clean Economy Database

The job levels reported here refl ect data from multiple years: Biosciences from 

2008; Fossil fuels from 2009; and the remainder from 2010.

Clean 

Economy

2.7

Biosciences Fossil

Fuels

1.4

2.4

Millions of Jobs

Information 

TechnologyProducing

4.8
20 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM

important information technology (IT) sector do employ 

more workers than the clean economy—approximately 

4.8 million—but almost one third of those jobs are in 

wholesale and retail.4

In terms of its sectoral profi le, the clean economy 

encompasses a wide variety of activities that extends far 

beyond high-profi le renewable energy and energy effi ciency 

sectors. In fact, the vast majority of clean economy jobs 

produce goods or services that protect the environment or 

reduce pollution in ways that have little to do with energy 

or energy effi ciency. Nearly one-fi fth of clean economy 

jobs, for example, involve agriculture and conservation, 

which includes a variety of land and forestry management 

jobs, as well as those in organic farming. Another 40 

percent of clean economy jobs benefi t the environment 

through greenhouse gas (GHG) reduction, the management 

of resources like air and water, and recycling. Businesses 

involved in renewable energy, by contrast, comprise just 

5 percent of all clean economy jobs. Nuclear energy, 

considered clean but non-renewable, comprises 3 percent of 

jobs: roughly 75,000.

Getting into more detail, the largest single segment of the 

clean economy involves waste management and treatment, 

which employs nearly 400,000 workers—14 percent of all 

clean economy jobs. Here, the U.S. Bureau of Reclamation 

is the largest employer, followed by the waste management 

and water operations of the city of Los Angeles and the city 

of New York. The second largest segment is public mass 

transit, which employs another 350,000 workers and yields 

an environmental benefi t by displacing single-passenger 

vehicles. First Student Inc., a nationwide school bus operator 

(which displaces less effi cient personal-vehicle travel), is the 

largest single employer in transportation, followed by the 

National Railroad Passenger Corporation (known as Amtrak), 

and the operators of the dense Northeast corridor: the 

Long Island Railroad and the New York and Washington, DC 

metropolitan transit authorities. The third largest segment 

is conservation, a substantial number of workers in which 

are employed by the U.S. Fish and Wildlife Service, the U.S. 

Forestry Service, and National Park Service, as well as state 

and local governments. 

Despite their small size, meanwhile, the activities 

most strongly identifi ed with the clean economy may 

be renewable energy production and energy-saving 

technologies. The largest renewable segments are 

hydropower, wind energy, and solar photovoltaic (PV) 

energy, which provide about three-quarters of all renewable 

energy jobs, or just over 100,000 jobs. Large fi rms in these 

segments include General Electric, Rosendin Electric, and 

Vestas in wind and MEMC Electronic Materials, First Solar, 

and Sharp in solar. Other energy-focused segments include 

fuel cells, smart grid, battery technologies, and electric 

vehicles, with many small, young fi rms, as well as large 

companies like Ball Aerospace & Technologies and 3M, key 

players in fuel cells; Itron and Black & Veatch Corp in smart 

grid; and Exide Technologies and Delphi in batteries. These 

segments provide some 55,000 “direct” jobs.

The rest of the green economy, fi nally, involves 

Table 1. Segments of the Clean Economy 

Category Segment Jobs, 2010 

Agricultural and Natural Resources Conservation Conservation 314,983 

Organic Food and Farming 129,956 

Sustainable Forestry Products 61,054 

Education and Compliance Regulation and Compliance 141,890 

Training 266 

Energy and Resource Effi ciency Public Mass Transit 350,547 

Energy-saving Building Materials 161,896 

HVAC and Building Control Systems 73,600 

Green Architecture and Construction Services 56,190 

Professional Energy Services 49,863 

Appliances 36,608 

Energy-saving Consumer Products 19,210 

Battery Technologies 16,129 

Smart Grid 15,987 

Electric Vehicle Technologies 15,711 

Lighting 14,298 

Water Effi cient Products 13,066 

Fuel Cells 7,041 

Greenhouse Gas Reduction, Environmental Management, Waste Management and Treatment 386,116 

and Recycling Professional Environmental Services 141,046 

Recycling and Reuse 129,252 

Green Consumer Products 77,264 

Green Building Materials 76,577 

Nuclear Energy 74,749 

Recycled-Content Products 59,712 

Remediation 56,241 

Air and Water Purifi cation Technologies 24,930 

Green Chemical Products 22,622 

Pollution Reduction 9,986 

Carbon Storage and Management 391 

Renewable Energy Hydropower 55,467 

Wind 24,294 

Solar Photovoltaic 24,152 

Biofuels/Biomass 20,680 

Solar Thermal 5,379 

Waste-to-Energy 3,320 

Geothermal 2,720 

Renewable Energy Services 1,981 

Wave/Ocean Power 371 

Source: Brookings-Battelle Clean Economy Database 
SIZING THE CLEAN ECONOMY | IV. MEASURING AND TRACKING THE CLEAN ECONOMY IN U.S. METROPOLITAN AREAS 21

everything from regulation and compliance (such as the 

EPA's activities), to research and engineering (enterprises 

like Oak Ridge National Lab), green architectural services, 

building products, and more. Over 77,000 clean economy 

jobs, for example, can be found in companies that make 

a diverse array of “green” consumer products, or those 

with environmentally sustainable ingredients. This includes 

companies—such as L’Oreal, Maybelline, Pfi zer, and 

Johnson and Johnson—whose products have received high 

environment marks from the GoodGuide, an independent 

consumer products rating enterprise.5

Yet beyond these categories and segments there is 

one more way to think about the clean economy and that 

is in terms of the era of the environmental concern being 

addressed. In this respect, over 90 percent of clean economy 

jobs lie in older segments that provide goods or services 

that solve long-appreciated environmental problems. Many 

of these jobs reside in government but others populate 

commercial segments like lighting, water effi cient products, 

green building materials, recycling and reuse, and pollution 

reduction. At the same time, though, a newer layer of 

establishments has emerged that is working on other 

environmental problems, the dangers of which have only 

recently been widely understood—such as global warming 

and the side effects of fossil fuel production. They are doing 

so through the creation of new forms of energy, as well as 

energy saving, storage, and mitigation products.

2. The clean economy grew more slowly in aggregate 

than the national economy between 2003 and 2010 

but newer “cleantech” segments far outperformed the 

nation during the period, as did the clean economy overall 

during the recession. Overall, today’s clean economy 

establishments added more than half a million jobs between 

2003 and 2010, expanding at an annual rate of 3.4 percent. 

This performance somewhat lagged behind in the national 

economy, which grew by 4.2 percent annually over the 

period (if job losses from establishment closings are omitted 

to make the data comparable).6 A nd yet, during the middle 

of the recession—from 2008 to 2009—the clean economy 

grew faster than the rest of the economy, expanding at a 

rate of 8.3 percent. This is likely due, in part, to the American 

Recovery and Reinvestment Act (ARRA), which channeled 

large sums of public spending towards clean energy projects 

through much of 2009.

In interpreting these numbers, the reader should keep 

in mind that the Brookings-Battelle database lacked any 

information on establishments that died (i.e. closed) before 

2010, but was able to get establishment history for those 

enterprises operating in 2010 and identifi ed as part of the 

clean economy. Therefore, all the clean economy job growth 

fi gures reported in this report are higher than they would 

otherwise be since, for example, jobs that existed in 2003 at 

an establishment that closed in 2005 would not have been 

captured by our searches in 2010—to the effect of lowering 

the job count in 2003. To make the data comparable, U.S. 

growth data is adjusted similarly, removing job losses from 

establishment deaths. This was done using data from NETS 

(through 2008) and the Bureau of Labor Statistics’ Business 

Employment Dynamics series (through 2010). (Figure 2). 

Which layers of the clean economy grew fastest? 

Young establishments in a few key segments drove most 

of the job growth. Excluding closings, 78 percent of all job 

gains between 2003 and 2010 came from establishments 

born in 2003 or later. Most new jobs are created by new 

enterprises across the broader economy, too, but the 

impact per establishment is not as marked as in the clean 

economy.7

 There, only 22 percent of all establishments were 

created in or after 2003 and yet they generated that large 

majority of the job creation.8 To put this in perspective, 

old establishments in the clean economy (those born 

before 2003) created an average of just three jobs for 

every one establishment from 2003 to 2010 while new 

establishments created 37 jobs. This compares favorably to 

new establishments nationally which created just 10 jobs per 

establishment over the same period (excluding job losses 

from deaths).9 The takeaway: Young establishments in the 

clean economy had a substantially greater job creation 

impact per establishment than their “non-clean” peers in the 

national economy. 

Which segments grew fastest? Again, the youngest did. 

The 13 segments in which the bulk of establishments date to 

later than 1996 grew by 8.3 percent annually from 2003 to 

2010—a fi gure that easily outstripped the 3.2 percent growth 

of older segments as well as the 4.2 rate for the national 

economy over the same period (Table 2). 

Along these lines, four of the fi ve fastest-growing 

segments during this seven-year period were in renewable 

energy. Solar thermal grew at a torrid pace, expanding by 

18.4 percent annually over the seven years and adding 

Figure 2. Clean Economy Job Growth Compared with Overall Job Growth, 

Excluding Establishments That Closed, 2003-2010

Source: Brookings-Battelle Clean Economy Database, National Establishment Time Series (NETS), and the Bureau of Labor Statistics 

Clean economy data was only available for establishments that were in business in 2010 and therefore data for prior years do not refl ect jobs losses due to 

establishment closings. To be comparable, the total U.S. jobs data presented here from NETS are only for establishments that were in business in 2009, as NETS 

data for 2009 and 2010 was not available to the study. The total U.S. jobs data from BLS presented here were also adjusted to account for job losses due to 

establishment closings. To make the adjustment, the number of job losses in future years up until 2010 was subtracted from total employment in the base year, 

using data from the Business Employment Dynamics program.
22 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM

3,700 jobs. The wind power industry added 15,000 jobs, 

growing 14.9 percent per year. Solar PV added 12,286 

jobs with 10.7 percent average annual growth. Moreover, 

biofuels, another renewable segment, added 9,300 jobs 

with 8.9 percent growth each year over the period.

Young, technology-heavy segments were also adding jobs 

at elevated rates each year over the period. For example, 

establishments involved in fuel cell production created 

roughly 3,500 jobs while those working in smart grid 

added 7,000, with annual growth of 10.3 and 8.6 percent 

respectively. 

The slowest growing segments, by contrast, saw job 

losses from establishment contractions overwhelm job 

gains from expansions and openings. Many of these losses 

took place in older building- and building infrastructurerelated segments that were evidently hurt by the housingcentered recession, including, for example: water effi cient 

products (e.g. plumbing and bathroom equipment); green 

chemical products (house paint); appliances; and energysaving consumer products (offi ce equipment, glass, home 

weatherization services). Hydropower and nuclear energy 

also experienced weak growth, with the former actually 

losing jobs. 

3. The clean economy is manufacturing and export 

intensive. Manufacturing and exporting are strengths of 

the clean economy. Engaged in the production of everything 

from house paint to fuel cell components and refrigerators, 

approximately 26 percent of all clean economy jobs are 

involved in manufacturing, compared to just 9 percent of 

jobs in the economy as a whole.10 In addition, Brookings 

estimates that in 2009 clean economy establishments 

exported an estimated $49.4 billion in goods, representing 

5.3 percent of all U.S. goods exports. Such establishments 

were also responsible for an additional $4.5 billion in 

service exports.

Manufacturing, for its part, accounts for a majority of 

the jobs in over half of the clean economy segments: 20 

to be exact. Several segments—including electric vehicle 

technologies, water effi cient products, green chemical 

products, appliances, sustainable forestry products, lighting, 

recycled-content products, and energy-saving consumer 

products—are particularly manufacturing intensive, with 

roughly 90 percent or more of their jobs residing in 

manufacturing establishments. Both solar-related segments, 

along with wind energy, have more than two-thirds of 

their jobs in manufacturing. Even the organic food and 

farming segment is largely comprised of manufacturing 

Table 2. Job Growth and Median Year of Establishment Birth by Clean Economy Segment

 Absolute Change Annual Average Change Median Year of

Segment in Jobs, 2003-2010 in Jobs, 2003–2010 (%) Establishment Birth

Wave/Ocean Power +273 20.9 2005.5

Solar Thermal +3,732 18.4 2001

Wind +15,110 14.9 2004

Carbon Storage and Management +228 13.3 2002

Solar Photovoltaic +12,286 10.7 2005

Fuel Cells +3,499 10.3 2000

Biofuels/Biomass +9,296 8.9 2004

Smart Grid +7,001 8.6 1999.5

Conservation +121,147 7.2 1996

Professional Energy Services +18,702 6.9 2001

Professional Environmental Services +51,793 6.8 1996

Geothermal +998 6.7 1998

Green Architecture and Construction Services +19,678 6.4 1989

Renewable Energy Services +687 6.3 2002

Electric Vehicle Technologies +5,447 6.3 2001.5

Regulation and Compliance +46,826 5.9 1995

Recycling and Reuse +39,668 5.4 1993

Remediation +15,539 4.7 1996

Air and Water Purifi cation Technologies +6,858 4.7 1993

Public Mass Transit +82,601 3.9 1989

Waste-to-Energy +754 3.7 1990

Waste Management and Treatment +79,401 3.3 1994

HVAC and Building Control Systems +14,946 3.3 1993

Energy-saving Building Materials +25,985 2.5 1993

Organic Food and Farming +15,025 1.8 1987

Nuclear Energy +7,813 1.6 1994

Battery Technologies +1,524 1.4 2002

Green Building Materials +7,081 1.4 1989.5

Recycled-Content Products +3,237 0.8 1992

Green Consumer Products +232 0.0 1992

Sustainable Forestry Products -4,299 -1.0 1992

Pollution Reduction -1,038 -1.4 1992

Lighting -1,971 -1.8 1992

Energy-saving Consumer Products -4,405 -2.9 1993

Appliances -9,063 -3.1 1989

Green Chemical Products -6,173 -3.4 1992

Hydropower -16,158 -3.6 1990

Water Effi cient Products -9,189 -7.3 1992

Training +266 N/A* 1989

Aggregate Clean Economy +565,337 3.4 1995

*The training segment had zero jobs in 2003 

Source: Brookings-Battelle Clean Economy Database 
SIZING THE CLEAN ECONOMY | IV. MEASURING AND TRACKING THE CLEAN ECONOMY IN U.S. METROPOLITAN AREAS 23

establishments involved in food processing.

Moreover, the share of all manufacturing jobs engaged in 

clean economy production is on the rise. From 2003 to 2010, 

clean manufacturers added 35,832 jobs (excluding closings), 

while U.S. manufacturers overall laid off 3.3 million workers.11 

Clean economy manufacturing employment expanded at a 

rate of 0.8 percent each year (or 5.5 percent over the entire 

period); meanwhile, U.S. manufacturers at large shed jobs at a 

rate of 1.5 percent per year (for a growth rate of -10.1 percent 

over the period). Again, both of these rates exclude jobs losses 

from establishments that closed over the period, since that 

data was not available for the clean economy.

Manufacturing frequently is linked to exporting, meanwhile, 

and so it is in clean economy. In fact, on a per job basis, 

the clean economy is about twice as export-oriented as 

the national economy. To be precise, Brookings estimates 

conclude that some $20,129 worth of exports is sold for every 

job in the clean economy, compared to just $10,390 in exports 

for the average U.S. job.12 The most export-oriented segment—

on an exports per job basis—is biofuels, which generates an 

Figure 3. Exports Per Job in 

the Clean Economy Versus 

the Overall U.S. Economy, 2009

Source: Brookings-Battelle Clean Economy Database; Brookings analysis 

of United States International Trade Commission, Bureau of Economic 

Analysis, and Moody's Economy.com data

estimated $189,000 in exports per job. This is followed by 

green chemicals, electric vehicle technologies, wind, battery 

technologies, solar PV, fuel cells, air and water purifi cation 

technologies, and recycled-content products, which export 

roughly $63,000 per job. 

These export estimates were calculated by Brookings 

based on the NAICS industry of each clean economy 

establishment. The external methods appendix document 

discusses the methodology in more detail.

4. The clean economy offers more opportunities and 

better pay for low-skilled workers than the national 

economy as a whole. Another strength of the clean 

economy is the access it affords to decent jobs up and down 

the skills ladder. Typical wages in the clean economy exceed 

those in the aggregate U.S. economy by roughly 13 percent, 

based on an analysis of the dataset. The median wage of a 

typical clean economy job approaches $44,000. This fi gure 

far exceeds the compensation level of the typical job in the 

United States. The national median wage is just $33,190 

(or $38,616 if calculated using a weighted average of the 

medians, as was done for the clean economy). 

This should not be interpreted to mean that clean 

economy fi rms are somehow more generous towards their 

workers, which may or may not be true. Indeed, previous 

research suggests that clean producers act like other 

companies in whatever industry they occupy.13 Rather, as the 

methods section and external methods appendix describes, 

these wage statistics were estimated based on the (fourdigit NAICS) industry group, which generated occupational 

estimates and fi nally wages. In other words, the better pay 

refl ects the fact that the clean economy jobs are in better 

paying industries with better paying occupations.

In fact, a large majority of jobs in the clean economy are 

middle-wage “green collar” occupations defi ned here as 

those having a median wage that falls within 20 percentage 

points of the national median wage of $33,190 ($26,552 to 

$39,828). Of the 22 major occupational groups defi ned by 

the Bureau of Labor Statistics, the six that fall below this 

range are classifi ed as low wage/low skill occupations, the 

seven that fall within it as middle wage/middle skill, and 

the nine above it as high wage/high skill occupations (see 

Appendix E). 

As Figure 4 shows, more than two-thirds of all clean 

economy jobs fall within this middle-wage “green-collar” 

category, compared to 43 percent of jobs in the broader 

economy (see data appendix for details). This middle-wage 

clean economy orientation refl ects the large number of 

installation and construction occupations in the sector 

(these are over 1.5 times more prevalent in the clean 

economy than in the national one) as well as its tilt toward 

occupations in production and transportation (which 

are over twice as prevalent in the clean economy). As 

a complement to the clean economy’s middle-income 

occupational profi le, numerous technical occupations 

populate the sector. Along these lines, the clean economy 

employs a higher percentage of scientists, architects, and 

engineers (10.1 percent) than the national economy (5.4 

percent) and a much lower percentage of workers in the 

worst-paying occupations such as food preparation, sales, 

and healthcare support. Overall, just 6.9 percent of clean 

economy jobs lie in the lowest paying occupations while 28.3 

of U.S. jobs fall into this tier. 

 There is also one more attractive feature of the clean 

economy opportunity structure: The clean economy 

not only pays well, but pays well even for those without 

post-secondary degrees. Almost half of all jobs in the 

clean economy are held by workers with a high school 

diploma or less, compared to only 37.2 percent of U.S. 

jobs. These clean economy jobs—many of which are in 

“green collar” occupations involved in making and moving 

products—provide higher wages than typical “low-skill” 

jobs: Approximately 28.1 percent of all occupations in the 

clean economy are strong-wage (paying above the U.S. 

Clean 

Economy

Overall U.S. 

Economy

$20,129

$10,390

Figure 4. Occupations

in the Clean Economy, 2010

Source: Brookings-Battelle Clean Economy Database and U.S. Bureau 

of Labor Statistics Occupational Employment Statistics and Employment 

Projections Program 

■ Share of all Clean 

Economy Occupations

■ Share of all U.S 

Occupations

Scientists and 

Engineers

10.1%

5.4%

Green Collar 

Occupations

68.7%

42.9%

Low Wage/Low 

Skill Occupations

6.3%

28.3%
24 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM

median) and low-skill (the percentage of workers with a 

high school diploma or less is higher than the national 

average) compared to 13.3 percent in the national economy. 

Conversely, only 32.5 percent of clean economy jobs are 

weak-wage (paying below the U.S. median) and low-skill, 

compared to 41.4 percent nationally. Table 3 shows how 

green collar occupations and education requirements vary 

across segments.

5. Among regions, the South has the largest number 

of clean economy jobs though the West has the largest 

share relative to its population. Turning to the geography 

of the clean economy, it turns out that almost one-third of 

all clean jobs are located in the U.S. South. The West comes 

next with nearly one-quarter of these jobs, followed by the 

Midwest with 23 percent and the Northeast with 20 percent. 

Measured as a percentage of total employment, the West 

commands the largest relative share, as 2.2 percent of the 

region’s jobs are in the clean economy. The Northeast also 

manages to beat the national average for its percentage 

of jobs in the clean economy (2.1 percent), followed by the 

Midwest (2.0 percent) and the South (1.8 percent). 

In terms of absolute employment numbers, California 

clean economy establishments lead the nation by providing 

318,156 jobs, well over 100,000 more jobs than in the next 

largest state, New York, whose establishments support 

185,038 jobs. Texas (144,081) is third and four more states 

register six-digit employment levels. Impressively, seven 

southern states tally at least 50,000 jobs in the clean 

economy. These states include Florida, Georgia, North 

Carolina, Tennessee, Virginia, and South Carolina.

Turning to the relative size of each state's clean economy, 

half of the 10 states possessing the highest job shares in 

the clean economy are in the West. Alaska has the largest 

total share of its jobs in the clean economy (4.7 percent), 

the majority of which involve conservation and management 

of the environment given the state’s massive parklands. 

Oregon (3.4 percent) is a big producer of organic food, as 

well as green building materials and sustainable forestry 

products; Montana contains vast public lands with park 

rangers and related professions but also jobs in solar PV 

and hydropower. Washington and Idaho also fall into the top 

ten. Yet much of West’s advantage on clean intensity comes 

from its historic possession of national parklands. In terms 

of private activity, the West has a slightly lower share of 

jobs in the clean economy than the Northeast and Midwest. 

Alaska, Montana, and Idaho fall out of the top ten. Vermont, 

with a disproportionate number of jobs in organic food and 

farming, as well as green building materials, has the highest 

private-sector clean economy job share (as a percentage 

of total state employment) at 2.6 percent; Oregon remains 

second and Wisconsin moves up to fourth, with a strong 

showing in water effi cient products, sustainable forestry 

products, recycled-content products, various building 

and appliance related segments, battery technologies, 

and fuel cells.

6. Most of the country’s clean economy jobs and recent 

growth concentrate within the largest metropolitan 

areas. Focusing now on metropolitan geography, some 

84 percent of all clean economy jobs resided in the nation’s 

metropolitan areas in 2010; some 64 percent congregated 

in the largest 100 metros alone. That supermajority falls 

slightly short of the 66 percent share of the nation’s 

population living in those metros but the gap is closing: 

Large metros’ share of clean economy jobs has increased 

by 3.3 percentage points (from 60.5 percent) since 2003. 

All told, three-quarters of clean economy jobs created from 

2003 to 2010 were created in large metros.

Some clean economy segments are more “metro-centric” 

than others, however, and this concentration has been highly 

correlated with job growth. 

To the fi rst point, the varying degrees of segment 

concentration in large metros are noteworthy. For example, 

the largest 100 metros contain over three-quarters of the jobs 

in some 13 clean economy segments that include, starting 

with the most concentrated: training, professional energy 

services, architecture and construction, renewable energy 

services, waste-to-energy, wind, professional environmental 

services, battery technologies, smart grid, solar PV, and mass 

transit. By contrast, eight segments have fewer than half of 

their jobs in the 100 largest metropolitan areas. These include 

farming and resource-oriented activities such as hydropower, 

sustainable forestry products, and biofuels. 

Turning to the association of metro concentration with 

growth, the story is even more striking. Looking at the years 

2003 to 2010, the segments that started the period as more 

concentrated in metros grew signifi cantly faster—roughly 1.7 

percentage points faster annually for every 10 percentage 

point increase in the share of jobs in large metros. None 

of the fi ve slowest-growing segments over the period—

water effi cient products, hydropower, green chemicals, 

appliances, and energy-saving consumer products—were 

disproportionately concentrated in large metros in 2003. By 

Table 3. Share of Clean Economy Jobs 

That Are Green Collar by Segment, 2010

 Share of Jobs Share of Jobs

 That Are That Require 

 Green a Diploma

Segment Collar (%) or Less (%)

Public Mass Transit 90.3 54.4

Green Building Materials 85.3 61.1

Recycled-Content Products 85.0 58.1

Sustainable Forestry Products 83.7 60.1

Energy-saving Building Materials 81.6 58.7

Green Consumer Products 78.9 55.4

Remediation 78.7 52.9

Electric Vehicle Technologies 78.1 53.7

Appliances 77.8 54.0

Waste-to-Energy 76.6 49.4

Waste Management and Treatment 76.4 46.6

Recycling and Reuse 75.4 51.3

Wind 75.1 49.8

Geothermal 73.6 46.8

Water Effi cient Products 72.9 50.2

Green Chemical Products 72.8 48.9

Lighting 71.4 49.6

Energy-saving Consumer Products 71.4 49.2

Solar Thermal 70.8 53.3

Hydropower 68.8 37.5

Air and Water Purifi cation Technologies 67.9 47.6

Biofuels/Biomass 67.1 45.3

Solar Photovoltaic 66.7 45.0

Nuclear Energy 66.0 36.7

HVAC and Building Control Systems 65.2 45.0

Organic Food and Farming 65.1 59.5

Battery Technologies 64.0 44.9

Renewable Energy Services 63.6 40.5

Regulation and Compliance 59.1 29.0

Carbon Storage and Management 55.3 38.4

Conservation 50.6 27.1

Training 50.3 40.2

Smart Grid 48.2 33.4

Fuel Cells 46.1 33.9

Pollution Reduction 41.4 31.0

Green Architecture and Construction 

Services 32.9 26.0

Professional Environmental Services 26.7 20.2

Professional Energy Services 26.2 20.5

Wave/Ocean Power 23.0 19.6

Source: Brookings-Battelle Clean Economy Database and Bureau 

of Labor Statistics 
SIZING THE CLEAN ECONOMY | IV. MEASURING AND TRACKING THE CLEAN ECONOMY IN U.S. METROPOLITAN AREAS 25

contrast, of the fi ve fastest-growing segments from 2003 

to 2010, only the tiny carbon storage and management 

segment (which employs technologies like carbon capture 

and sequestration) started off the period with fewer than 

70 percent of its jobs in one of the 100 largest metropolitan areas. 

The connection between fast growth and metro 

concentration is not surprising, meanwhile. As discussed 

in Chapter II, large metros disproportionately claim many 

of the assets and resources companies need to succeed, 

such as educated workers, infrastructure, top-research 

universities, and venture capital fi nancing.14 Likewise, 

younger, more dynamic companies often start in large 

metros before moving out to less populated areas, once their 

production techniques are refi ned, to take advantage of 

lower costs.15

7. The clean economy permeates all of the nation’s 

metropolitan areas but it manifests itself in varied 

confi gurations. In this respect, the clean economy exists in 

every region, in part because of the ubiquity of such basic 

clean economy activities as wastewater management, public 

transit, and environmental regulation. And yet, for all of its 

pervasiveness, the clean economy varies widely in size and 

shape. Most notably, because many of its companies are 

exporters and have adapted to varied market and policy 

dynamics, the clean economy is spread unevenly across 

U.S. metropolitan areas.

Employment levels and segment diversity

In terms of population, New York and Los Angeles are 

the nation’s largest metropolitan areas. Accordingly, they 

also possess the most clean economy jobs: 152,000 and 

Table 4. Metro Areas with the Most Clean Economy Jobs, 100 Largest Metros, 2010

Metro Area Clean Economy Jobs Clean Share of All Jobs (%)

New York-Northern New Jersey-Long Island, NY-NJ-PA 152,034 1.8

Los Angeles-Long Beach-Santa Ana, CA 89,592 1.7

Chicago-Joliet-Naperville, IL-IN-WI 79,388 1.8

Washington-Arlington-Alexandria, DC-VA-MD-WV 70,828 2.3

Philadelphia-Camden-Wilmington, PA-NJ-DE-MD 54,325 2.0

San Francisco-Oakland-Fremont, CA 51,811 2.7

Atlanta-Sandy Springs-Marietta, GA 43,060 1.9

Boston-Cambridge-Quincy, MA-NH 41,825 1.7

Houston-Sugar Land-Baytown, TX 39,986 1.6

Dallas-Fort Worth-Arlington, TX 38,562 1.3

Source: Brookings-Battelle Clean Economy Database and Moody's Analytics

A Diversifi ed Portfolio: Atlanta’s Clean Economy

Atlanta-Sandy Springs-Marietta is the most diverse metropolitan area clean economy in the nation. Its approximately 

43,000 clean economy jobs are very evenly spread across the 39 segments of the clean economy. With this breadth 

and depth, Atlanta—the seventh largest metro clean economy in the country—is well positioned to be a major hub in a 

variety of clean activities.

Even with that diversity, two export-oriented segments are highly clustered—in that employees at one establishment 

are surrounded by a substantial number of workers at other establishments in the same segment. These segments 

are green architecture and construction services—with major fi rms like Heery International, Winter Construction, and 

tvsdesign; and smart grid—led by GE, USI Energy, and Ista, amongst others. Across these segments, Atlanta has 5,605 

jobs spread over 26 establishments. 

The region also has another 8,332 jobs from 59 establishments in six moderately clustered segments: recycled 

content products (Rock-Tenn, Rehrig Pacifi c); green building materials (Shaw Industries); water effi cient products (Toto); 

green chemical products (Arch Chemical, Sherwin-Williams); battery technologies (Exide and Enrev); and appliances (Hill 

Phoenix).

This wide presence across segments has helped make Atlanta a clean economy contender. Its growth performance 

has been solid—21st out of the 100 largest metros from 2003 to 2010. But more importantly perhaps, the median age of 

its establishments is just 12 years, making the Atlanta clean economy the sixth-youngest in the nation, among the 100 

largest metros. This entrepreneurial dynamism, along with its diversity, bodes well for its future. 

Source: Brookings-Battelle Clean Economy Database

In short, the measurements and trends reviewed 

here offer a mixed picture of a diverse array of 

industry segments that is in many places making significant progress despite a very 

difficult economic and policy environment.
26 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM

89,600, respectively. Chicago comes in third with 79,388. 

Washington has the fourth most clean economy jobs with 

70,828, followed by Philadelphia and San Francisco, each 

with over 50,000. Atlanta, Boston, Houston, and Dallas

round out the top 10. 

These large metros have very different profi les. 

New York and Washington are uniquely specialized in 

public-goods providing segments. In the former, over 

50 percent of the metro’s jobs come from public mass 

transit and waste management and treatment. In 

Washington, roughly 48 percent of the jobs come from 

conservation and regulation and compliance activities. By 

contrast, in nine highly diversifi ed metros, including Atlanta, 

Boston, Dallas, and San Francisco, less than 30 percent of 

the metros’ jobs reside in the two largest segments.

Generally, large metros are extremely diversifi ed in their 

segment concentrations, meaning that the share of clean 

economy jobs coming from each segment is relatively small. 

This is especially true of Atlanta—the most diverse clean 

economy with strengths in segments like smart grid, water 

effi cient products, appliances, and architecture—but also 

Milwaukee, Boston, Seattle, and San Francisco. Milwaukee

is strong in water effi cient products and batteries; Boston

establishments are disproportionately represented in 

such varied domains as improved coal technology, wasteto-energy, solar PV activities, pollution reduction, HVAC 

and building control systems, fuel cells, and professional 

environmental services. Seattle’s jobs cut across renewable 

energy services, green architecture, smart grid, and forestry 

products. For its part, San Francisco is a center for smart 

grid development but specializes as well in temperature 

control equipment, solar PV, electric vehicles, architecture, 

environmental research, solar thermal, and remediation.

Assessed by their orientation to the clean economy 

(measured by clean jobs as a share of total jobs), many of 

the clean economy’s regional focal points are mid-sized 

Table 5. Metro Areas with the highest share of clean economy jobs,

100 Largest Metro Areas, 2010 

Metro Area Clean Economy Jobs Clean Share of All Jobs (%)

Albany-Schenectady-Troy, NY 28,087 6.3

Knoxville, TN 16,135 4.9

Sacramento--Arden-Arcade--Roseville, CA 37,319 4.5

Harrisburg-Carlisle, PA 13,025 4.0

Toledo, OH 11,831 3.9

Springfi eld, MA 10,443 3.5

Madison, WI 12,337 3.5

Little Rock-North Little Rock-Conway, AR 11,934 3.4

Greenville-Mauldin-Easley, SC 10,127 3.4

Raleigh-Cary, NC 16,677 3.3

Source: Brookings-Battelle Clean Economy Database and Moody's Analytics 

Figure 5. Clean Economy Intensity in the 100 Largest Metro Areas, 2010

Source: Brookings-Battelle Clean Economy Database and Moody's Analytics
SIZING THE CLEAN ECONOMY | IV. MEASURING AND TRACKING THE CLEAN ECONOMY IN U.S. METROPOLITAN AREAS 27

metros. They include six state capitals, which is largely a 

function of the outsized role played by the public sector in 

maintaining environmental health. The Albany region, for 

example, has the largest share of local jobs (6.3 percent) in 

the clean economy of any large metro nationwide. As both 

a state capital and a home to GE dating back to Thomas 

Edison’s tenure, it has a massive presence in wind-related 

activities, battery technologies, professional energy services, 

fuel cell development and production, and regulation 

and compliance—its largest segment. It is also overrepresented in hydropower, remediation, conservation, and 

environmental research among others. 

Among clean economy intensive locales, Albany is 

followed by Knoxville, with 4.9 percent of its jobs in 

the clean economy, and then two state capital regions, 

Sacramento and Harrisburg, which have clean jobs that 

stand at 4.5 and 4.0 percent, respectively, of total jobs. 

With over half of its jobs coming from just one segment—

professional energy services—Knoxville has one of the least 

diversifi ed clean sectors in the nation, largely because Oak 

Ridge National Laboratory has such a major presence. As 

the seat of a large state government, Sacramento’s clean 

economy is largely composed of the public conservation and 

regulatory sector, and yet it also has a strong presence in 

professional environmental services, recycling, and public 

mass transit. Harrisburg is similarly weighted towards the 

public sector but as home to Three Mile Island also has a 

large number of jobs in nuclear power.

Toledo and Madison represent the Midwest in the top 

10 most clean-oriented major metros, while Greenville, SC; 

Little Rock, and Raleigh comprise the strong southern 

contingent. Toledo has the third-highest percentage of 

private sector jobs in the clean economy, at 3.7 percent. 

Solar PV is a leading segment along with fuel cells, battery 

technologies, regulation, green chemicals, green consumer 

products, solar thermal, and nuclear energy. Greenville, SC 

is similar to Albany in its strength across a number of clean 

technologies, including wind, electric vehicles, lighting, and 

water effi cient products. Little Rock gathers a large number 

of jobs in green consumer products as well as electric 

vehicles, while Raleigh has a disproportionate number of 

jobs in training, smart grid, pollution reduction, regulation, 

and architecture and construction services. Chattanooga, 

fi nally, as another strong southern performer, has over 1,000 

jobs in each of three major sectors—green building materials, 

nuclear energy, and hydropower—while housing a smaller but 

still disproportionate coterie of jobs in geothermal, battery 

technologies, and wind.

Employment growth

Employment growth also ranges widely. In 53 of the 

nation’s 100 largest metros, establishments in the clean 

economy added jobs at a faster clip than those outside of 

it from 2003 to 2010.16 Clean economy establishments in 

Knoxville, Raleigh, Des Moines, and Little Rock registered 

the fastest growth of all large metros with annual growth 

rates above 10 percent. Growth in Knoxville was fueled by 

the professional energy services segment and Oak Ridge 

National Laboratory. In Raleigh, job expansions were largely 

attributable to the government and public transit segments, 

with small contributions from smart grid and a few others. 

In Des Moines too, the public sector, via conservation, drove 

growth, along with waste management. On the other hand, 

green consumer products provided the bulk of job growth in 

Little Rock. For Albany, which had the fi fth-fastest growing 

clean economy among large metros, gross job expansions 

were almost evenly shared between regulation and 

compliance and the region’s strong wind presence.

On the opposite end, Grand Rapids lost clean economy 

jobs most quickly from 2003 to 2010. Even excluding 

potential job losses from closing establishments, it lost 9.1 

percent of its clean economy workforce annually (a loss 

of nearly 50 percent over the entire period). Much of this 

came from thousands of layoffs in green consumer products. 

These devastating losses were only somewhat offset by 

solid job gains in the HVAC and building controls systems 

segment and organic farming and food processing. San 

Jose, surprisingly, considering its innovation prowess, was 

ranked 95th amongst large metros on job growth in the 

clean economy from 2003 to 2010. Massive losses—adding up 

to thousands of jobs in lighting and energy-saving consumer 

products—outweighed the substantial job gains in the wind 

and solar PV segments. Job losses in New Orleans’s nontradable segments—namely public mass transit and waste 

Leading the Way: Albany’s Clean Sweep

With a higher concentration of clean jobs than any other major metro area in the country, Albany-Schenectady-Troy, 

NY is a surprise leader in the clean economy. 

Nearly one in 15 Albany area workers—over 28,000 people—make their living in the clean economy. Two major players 

stand out in driving the capital region's outsize performance: General Electric (GE) and the state government. 

GE, for its part, still locates a number of critical and growing clean economy operations in its birthplace of Schenectady, 

including: its global renewable energy headquarters, its power and water division headquarters, and a wind and water 

turbine manufacturing facility. GE‘s advanced battery research center—the only U.S. Department of Energy-designated 

Energy Frontier Research Center led by a private company—completes the conglomerate’s striking clean economy 

presence in the region.

As the capital of the third-most populous state, meanwhile, New York’s “Capital District” contains another 10,500 jobs 

in public sector-oriented segments like regulatory and compliance and conservation too.

Yet Albany’s clean economy has a richness extending beyond these two major players that hints at the emergence of 

a robust cluster. Over 4,000 scientists and engineers complement a concentration of over 6,000 manufacturing workers. 

Nearly 4,000 individuals spread across a network of 33 establishments provide professional energy and environmental 

services. And a solid industry presence fortifi ed by an institutional research emphasis exists in the fuel cells segment. 

Recent activity in the region’s thick network of academic institutions and public-private partnerships bodes well for 

the region’s clean economy future. The New York state Energy Research and Development Agency's (NYSERDA) energy 

and environmental technology energy incubator, iCLEAN, is maturing and its parent, the College of Nanoscale Science 

and Engineering (CSNE) at the University of Albany, has since its establishment in 2004 emerged as a global leader in 

semiconductor and nanotech research—technologies that drive “cleantech.” For its part, the Rensselear Polytechnic 

Institute hosts the New York State Center for Future Energy Systems, which along with NYSERDA’s activities, leverages 

the region’s position as the state capital to establish a central node in a state-wide, cross-disciplinary, market-oriented 

clean economy knowledge network. 

Sources: Brookings-Battelle Clean Economy Database; College of Nanoscale Science and Engineering website; General Electric Company press releases: 

January 21, 2011; February 1, 2010; May 19, 2009.
28 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM

management—could be attributed to decreased demand 

from population declines. These losses were not fully offset 

by gains in remediation and professional environmental 

services.

Exports

Turning to exports—domestically produced goods or services 

sold to foreign markets—the clean economy exhibits a 

distinctive geographic pattern. Older clean exporting 

establishments tend to be located outside of large 

metros, while newer fast-growing ones tend to be located 

inside them.

On the one hand, the nation's clean economy export 

activity occurs most intensively in locations outside the 

nation's 100 largest metros, which produce just 55 percent 

of U.S. clean exports despite containing 65 percent of the 

population. According to Brookings estimates, the three 

segments that generate the most exports by value are green 

chemicals, biofuels/biomass, and organic food and farming. 

These are all disproportionately non-metropolitan.

Table 7. Metro Areas with the Highest and Lowest Exports per Job in the Clean Economy, 

100 Largest Metros

 Clean Economy Exports Clean Economy Exports Per

Metro Area (millions of 2009 dollars) Jobs, 2010 Job, 2009 

Greenville-Mauldin-Easley, SC $872.4 10,127 $86,143 

Little Rock-North Little Rock-Conway, AR $686.4 11,934 $57,514 

Albany-Schenectady-Troy, NY $1,239.0 28,087 $44,114 

Memphis, TN-MS-AR $467.7 11,515 $40,621 

Grand Rapids-Wyoming, MI $349.2 8,812 $39,631 

San Jose-Sunnyvale-Santa Clara, CA $726.8 18,868 $38,521 

Louisville-Jefferson County, KY-IN $531.9 14,447 $36,817 

Charleston-North Charleston-Summerville, SC $151.2 4,369 $34,605 

Cleveland-Elyria-Mentor, OH $830.7 24,664 $33,682 

Cincinnati-Middletown, OH-KY-IN $554.3 18,525 $29,922 

 

McAllen-Edinburg-Mission, TX $12.7 2,203 $5,759 

New Orleans-Metairie-Kenner, LA $40.9 7,298 $5,604 

Palm Bay-Melbourne-Titusville, FL $19.2 3,446 $5,568 

Honolulu, HI $47.8 9,269 $5,161 

Sacramento--Arden-Arcade--Roseville, CA $185.7 37,319 $4,975 

Virginia Beach-Norfolk-Newport News, VA-NC $46.8 9,594 $4,883 

Ogden-Clearfi eld, UT $9.8 2,111 $4,657 

Youngstown-Warren-Boardman, OH-PA $13.1 2,977 $4,402 

Springfi eld, MA $42.6 10,443 $4,079 

Colorado Springs, CO $5.4 1,934 $2,770 

Source: Brookings-Battelle Clean Economy Database and Brookings analysis of United States International Trade Commission, Bureau of Economic Analysis, 

and Moody's Economy.com data 

Table 6. Metro Areas with the Fastest and Slowest Clean Economy Job Growth, 

100 Largest Metros, 2003-2010

 Average Annual

 Average Annual Change (Less 

 Clean Economy Clean Economy Change, Public Administration), 

Metro Area Jobs, 2003 Jobs, 2010 2003-2010 (%) 2003-2010 (%)

Knoxville, TN 6,206 16,135 14.6 14.6

Raleigh-Cary, NC 6,788 16,677 13.7 11.4

Des Moines-West Des Moines, IA 2,472 5,256 11.4 2.4

Little Rock-North Little Rock-Conway, AR 5,916 11,934 10.5 9.9

Albany-Schenectady-Troy, NY 15,557 28,087 8.8 6.0

Ogden-Clearfi eld, UT 1,184 2,111 8.6 6.1

McAllen-Edinburg-Mission, TX 1,243 2,203 8.5 7.2

Tulsa, OK 4,076 7,130 8.3 5.4

Toledo, OH 6,873 11,831 8.1 8.5

Albuquerque, NM 5,851 9,912 7.8 4.3

 

Columbia, SC 8,099 8,568 0.8 1.4

El Paso, TX 2,570 2,695 0.7 0.3

Buffalo-Niagara Falls, NY 13,952 14,452 0.5 -0.3

Milwaukee-Waukesha-West Allis, WI 13,516 13,471 0.0 -0.2

San Jose-Sunnyvale-Santa Clara, CA 19,360 18,868 -0.4 -1.0

Modesto, CA 2,974 2,688 -1.4 -2.3

New Orleans-Metairie-Kenner, LA 8,385 7,298 -2.0 1.4

Augusta-Richmond County, GA-SC 9,110 6,106 -5.6 -5.8

Palm Bay-Melbourne-Titusville, FL 6,204 3,446 -8.1 -13.5

Grand Rapids-Wyoming, MI 17,232 8,812 -9.1 -9.4

Source: Brookings-Battelle Clean Economy Database 
SIZING THE CLEAN ECONOMY | IV. MEASURING AND TRACKING THE CLEAN ECONOMY IN U.S. METROPOLITAN AREAS 29

And yet, much of what is exported from outside of these 

large metros appears to be long-standing, more traditional 

commodities rather than new technologies—with the 

exception of biofuels. Approximately two-thirds of growing

exporters, on the other hand, are located in one of the 100 

largest metropolitan areas.17 The newer exporting clean 

economy, therefore, is disproportionately happening in and 

around the nation’s largest cities. 

What metros export the most? With an estimated 

$2 billion of clean economy exports per year, Chicago

is the nation’s largest metropolitan exporter of clean 

technologies, goods, and services. The metro has seven 

segments that export over an estimated $100 million per 

year, the largest of which is energy-related professional 

services. Most of this segment’s $500 million in annual 

exports are from a single large diversifi ed company that 

does, among other things, energy effi cient engineering 

research in the petro-chemicals industry. HVAC and building 

control systems is the second largest exporting segment in 

Chicago, followed by biofuels, green consumer products, air 

and water purifi cation technologies, green chemicals, and 

organic food.

Los Angeles, New York, Albany, and San Francisco also 

contribute over $1 billion per year each to the clean export 

economy. Los Angeles’s leading exports are in organic food, 

green building products, green consumer products, recycledcontent products, and water effi cient products. New York’s

exports consist largely of green consumer products, organic 

food, professional environmental services, and recycledcontent products. In Albany, wind energy dominates. 

San Francisco exports clean products from a more diverse 

group of segments, including HVAC and buildings control 

systems, professional energy services, and electric vehicles.

Greenville and Little Rock also emerge as surprisingly 

strong exporters, both falling in the top 15 on total value of 

exports. Moreover, they are the two most export-intensive 

clean economies of all the large metros, based on the total 

value of exports per job. Roughly two-thirds of Greenville’s 

clean economy exports are derived from wind turbine 

manufacture, but substantial contributions also come from 

electric vehicle technologies and building products. Little 

Rock also exports electric vehicles but derives most of its 

clean industry earnings from green consumer products, 

which grew robustly over the period. Other export-intensive 

metros include Wichita, a major exporter of biofuels; 

traditional manufacturing hubs like Cleveland and Grand 

Rapids; and logistic hubs like Memphis, Louisville, and 

Cincinnati. 

Occupations

For every large metropolitan area except one (Knoxville), 

the majority of clean economy jobs reside in mid-wage 

“green collar” occupations, meaning those with moderate 

wages and moderate educational requirements in 

production, installation, maintenance, transportation, 

construction, social services, offi ce support, or protective 

services. In 10 of the 100 largest metropolitan areas, 

moreover, these jobs represent at least three-quarters of all 

clean economy jobs based on Brookings estimates. Almost 

four out of fi ve (78 percent) clean economy jobs fall in the 

green collar category in Augusta, GA, the nation’s most 

“middle-job” oriented clean economy, with most of the 

relevant occupations lying in construction (26 percent 

of all occupation), and large shares in transportation 

(14 percent), offi ce administration (13 percent), and 

production (13 percent). Other heavily green collar 

metros offer different confi gurations. Green collar jobs in 

Dayton, Colorado Springs, and Salt Lake City are heavily 

weighted towards transportation (26, 29, and 26 percent 

respectively). The largest share of Louisville’s (37 percent) 

and Chattanooga’s (27 percent) green collar jobs are in 

production.

Because green collar jobs are abundant within the clean 

economy and pay relatively well for their skill requirements, 

they arguably hold out the richest opportunities for lowskill workers in the clean economy. In fact, in every one 

of the 100 largest metros, the majority of clean economy 

jobs are available to workers without a college degree—and 

most are in mid-wage green collar occupations. Modesto, 

with a disproportionate number of jobs in organic food 

and farming, stands out with the highest share of jobs 

available to non-college graduates (82 percent). Stockton

(81 percent) has a similar profi le. Augusta, GA (81 percent), 

with high job shares in remediation and nuclear energy, 

is the second most non-college graduate-friendly clean 

economy. Rochester (81 percent) has a high percentage of 

jobs in public transportation. Grand Rapids and Louisville, 

by contrast, are heavily concentrated in the manufacturing 

segments like appliances. Grand Rapids also has large 

job shares in green consumer products and wind, while 

Louisville gets a large share from air and water purifi cation 

technology.

At the other end of the spectrum, Knoxville, Albany, and 

Harrisburg offer the lowest percentages of clean economy 

jobs requiring less than a college degree amongst large 

metros (with shares of 56, 66, and 68 percent respectively). 

For Harrisburg, this is primarily due to the large public 

sector presence. For Albany, a large public sector and job 

concentrations in professional energy services and fuel 

cells raise educational and scientifi c skill requirements. 

Knoxville, in fact, has the highest percentage of science and 

engineering-related occupations amongst all large metros 

(34 percent). Las Vegas, with its many green architects is 

second on that measure (24 percent), while San Francisco—

through architecture and professional services—is third 

(22 percent).

* * *

To put it all together, at least four rough types of 

regional clean economy can be discerned amid much 

variation and local distinctiveness. One sub-set of regional 

clean economies appears to be dominated by services—

transportation, professional services, construction, 

administration, waste management, and remediation. 

These metros are more likely to have grown rapidly over 

the last seven years and include fast growers like Knoxville, 

San Diego, Hartford, Orlando, Honolulu, Las Vegas, and 

San Francisco. Another signifi cant group of metropolitan 

clean economies appears heavily engaged in 

manufacturing. These metros had mixed growth rates—

depending on the particular mix of their segments and 

specializations—but all export intensively and provide 

plentiful green collar opportunities. Among these metros 

reside numerous Midwestern and Southern metros such 

Table 8. Metro Areas with the Largest 

Share of Clean Economy Jobs That Are 

Green Collar, 100 Largest Metros, 2010 

 Share of Clean Economy Jobs 

Metro Area that are Green Collar (%)

Augusta-Richmond County, GA-SC 77.9

Dayton, OH 76.8

Louisville-Jefferson County, KY-IN 76.1

Chattanooga, TN-GA 75.8

Colorado Springs, CO 75.6

Rochester, NY 75.3

Salt Lake City, UT 75.3

Youngstown-Warren-Boardman, OH-PA 75.1

Stockton, CA 75.0

Cincinnati-Middletown, OH-KY-IN 74.9

Source: Brookings-Battelle Clean Economy Database and U.S. Bureau of 

Labor Statistics Occupational Employment Statistics and Employment 

Projections Program 
30 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM

as Grand Rapids, Greenville, Louisville, Memphis, Little 

Rock, and Cleveland, but also San Jose out West. On the 

other hand, the public sector supplies roughly half of 

clean economy jobs in state capital metros like Harrisburg, 

Sacramento, Raleigh, and Des Moines, helping these areas 

score highly on clean job intensity. Finally, a signifi cant 

number of diverse metros exhibit fairly balanced profi les 

across the major industry groupings. This array of multidimensional clean economy centers includes Atlanta; 

Stockton; Portland, OR; Providence; Salt Lake; Detroit; and 

Los Angeles. In short, the clean economy pervades all of the 

nation’s metropolitan areas but it manifests itself in many 

different confi gurations.

8. Strong industry clusters boost metros‘ growth 

performance in the clean economy. A fi nal fi nding 

pertains to the role in economies of industry clustering—

geographic concentrations of interconnected fi rms often 

accompanied by supporting or coordinating organizations. 

In this connection, it turns out that establishments in the 

clean economy add jobs markedly faster when they are 

located near peer establishments in the same county and 

same segment. To be precise, doubling the size of a clean 

economy cluster—the number of same-segment jobs in 

a county—increased job growth of establishments in the 

cluster by roughly 2.1 percent from 2003 to 2010, holding 

all else equal in a model tested here and discussed in the 

external methodological appendix.18 In 2003, for example, 

jobs in clustered establishments represented 16.6 percent 

of all clean economy jobs. By 2010, that share increased to 

19.0 percent.19 These fi ndings are consistent with volumes 

of academic work showing that clusters benefi t economic 

performance in a variety of industries.20

The benefi ts of peer proximity are reinforced and 

magnifi ed in large metros. The average clean economy 

establishment in a large metropolitan area is located in the 

same county as 1,130 other jobs in the same segment. By 

contrast, the county level of exposure to same-segment jobs 

was just 190 for clean economy establishments outside of 

the 100 largest metros. That difference in peer proximity 

is worth 5.5 percent higher job growth annually over the 

seven-year period ending in 2010, holding all else equal.21 In 

this respect the clean economy is like most industries where 

new, fast-growing fi rms disproportionately emerge from 

large metro agglomerations.22

The fi ndings above use a “continuous” defi nition of 

clusters based on the size of other establishments in 

the same segment. However, an alternative “binary” 

defi nition can be employed to compare clustered to isolated 

establishments. For these purposes, an establishment had 

to be located in the same county as at least 1 percent of 

national jobs in its segment to be considered clustered. 

Other defi nitions were used, which obtained similar 

results, but the 1 percent defi nition proved to be the 

strongest predictor of job growth. With this defi nition, 

clustered establishments grew at a rate of 4.6 percent 

annually from 2003 to 2010, while isolated establishments 

grew at a rate of just 3.2 percent.23 This defi nition gives 

larger counties an advantage but that advantage appears to 

be justifi ed: As discussed in the external methods appendix, 

the benefi ts from clustering are robust to controls for 

county-size.

At the metropolitan level, the analysis was restricted to 

establishments in the tradable or export-oriented segments 

of the clean economy. This excluded all nine segments that 

export less than $4,000 per worker on average.24

In 13 of the largest 100 metropolitan areas, at least 

20 percent of clean economy establishments are embedded 

in clusters—as defi ned above as proximity to at least one 

percent of U.S. jobs in an export-oriented segment. By that 

standard, Houston provides a clustered environment for 

74 percent of its clean economy establishments—the highest 

percentage for the nation’s 100 largest metropolitan 

areas. In fact, in nine of its segments, at least 75 percent 

of the establishments are clustered. These segments are: 

renewable energy services, geothermal, green architecture 

and construction services, professional energy services, 

energy-saving building materials, wind, professional 

environmental services, HVAC and building control systems, 

and biofuels/biomass. They range from as few as two 

establishments (in the small segment geothermal) to 123 (in 

professional environmental services). 

Clean establishments in metropolitan Los Angeles 

are also exceptionally clustered, with 73 percent of 

establishments meeting the cutoff. Here, six segments 

are completely clustered: energy-saving consumer 

products, solar PV, pollution reduction, organic food and 

farming, green architecture and construction services, 

and professional environmental services. Another eight 

segments in Los Angeles cluster at least 75 percent of 

An Emerging ‘Blue’ Innovation Hub: Milwaukee’s Water Industry Cluster

The regional clean economy consists of much more than high-profi le renewable energy or energy effi ciency 

specializations. In metropolitan Milwaukee, the buzz surrounds water technology, as the region has recently emerged 

as a “blue” innovation hub with a high concentration of manufacturing and research in water effi cient products, water 

purifi cation technology, and waste management equipment and treatment. 

In 2010, the Milwaukee metro region encompassed no fewer than 200 fi rms in the water industry that employed 

about 1,167 workers in the water effi cient products segment alone--good for about 9 percent of all jobs in the U.S. in that 

segment, according to the Brookings-Battelle Clean Economy Database. From 2003 to 2010 the region saw a 23 percent 

increase in jobs in the “blue” sector with 39 percent of these jobs in companies that develop water effi cient products 

and 13 percent in companies that produce water purifi cation technologies. These companies develop a wide range of 

technologies that include equipment to measure and control the fl ow of water, emergency water supply, and drinking 

and waste water treatment equipment. Companies in the water effi cient products and water purifi cation technologies 

segments have on average about six establishments each in the metro region and have been producing groundbreaking 

building products to conserve water and energy that will help builders achieve LEED building certifi cation.

Meanwhile, the cluster is gaining strength. Companies from outside the region are beginning to recognize the 

signifi cance of Milwaukee’s water innovation hub by moving to join it. American Micro Detection Systems, Inc., a 

California-based sensor technology manufacturer, located its fi rst major operations in Milwaukee in July 2010 and 

Badger Meter relocated about 25 engineering professionals from its Oklahoma facility to Milwaukee in 2010. And for their 

part business and academic leaders in Milwaukee teamed up in 2009 to develop the Milwaukee Water Council to leverage 

the metro region’s resources into an innovation cluster that can turn the next wave of water technologies into successful 

companies that have the potential for serious growth. 

Sources: Brookings-Battelle Clean Economy Database; Dean Amhaus, Executive Director, Milwaukee Water Council, telephone interview, May 17, 2011; 

Milwaukee Water Council, “Overview of Milwaukee’s World Water Hub;” “Milwaukee lands federal grant to develop water cluster,” BizTimes.com, September 3, 

2009; Milwaukee Water Council, “Executive Briefi ng,” April 4, 2011.
SIZING THE CLEAN ECONOMY | IV. MEASURING AND TRACKING THE CLEAN ECONOMY IN U.S. METROPOLITAN AREAS 31

establishments. Seattle is high on the list with 45 percent 

clustering, through professional energy services, green 

architecture and construction, professional environmental 

services, organic food and farming, sustainable forestry 

products, wind, and smart grid. Metropolitan Pittsburgh—

with a clustering rate of 36 percent—has highly clustered 

segments such as professional environmental services, 

wind, pollution reduction, and solar thermal. The Boston 

metropolitan area clusters roughly 30 percent of its 

establishments in segments like fuel cells, green architecture 

and construction, solar PV, professional energy services, and 

energy-saving consumer products. By contrast, Little Rock’s 

green consumer product makers are highly clustered while 

no other segment is.

Under this strict 1 percent defi nition of clusters, 37 large 

metropolitan areas completely lack clustered establishments. 

Many of these have location quotients above one for various 

segments—indicating a disproportionate number of jobs in 

the segment relative to the United States—but these jobs 

largely come from a single large establishment or are spread 

out in different counties within the metro. The metros 

have proven that they have the workforce, infrastructure, 

or business climate to sustain successful clean economy 

companies and yet they haven’t been able to fully generate 

the benefi ts of a densely clustered network of similar fi rms 

in any one segment.

* * *

 In short, the measurements and trends reviewed here 

offer a mixed picture of a diverse array of industry segments 

that is in many places making signifi cant progress despite a 

very diffi cult economic and policy environment.

On the positive side, the data depict a modest-sized but 

widely distributed set of industries that already employ 

more people than the fossil fuels and biotech industries 

and which is already nearly half the size of the nation’s 

formidable IT industry.

Measured aggregate growth created nearly half a million 

new jobs in the years between 2003 and 2010 and some 

“hot” segments—high-fl ying renewable energy categories like 

wind energy and solar PV—doubled and tripled in size (albeit 

from small bases).

What is more, the data make clear that the clean 

economy is producing an array of positions useful to the 

nation’s need to renew its economic base. Clean economy 

jobs are inordinately oriented toward manufacturing and 

exporting. Likewise, they offer an attractively balanced 

array of jobs and occupations, with substantially more 

opportunities and better pay for lower-skilled workers along 

with many positions in fast-growing “innovation” fi elds.

And yet, it must be said that the clean economy remains 

at present more an aspiration than a large center of 

present-day employment. A fraction of the size of the health 

industry, the U.S. clean economy remains small where it 

is fast-growing and relatively slow-growing on balance, as 

defi ned here. Moreover, the green economy encompasses—

along with its newer, smaller, expanding private-sector 

fi rms—signifi cant numbers of mature or public sector 

establishments that will not likely yield substantial growth in 

the future. 

Overall, then, the clean economy in the U.S. and its 

regions should be deemed a diverse, multi-layered complex 

of both established and innovative pursuits, the older 

of which are important but sometimes mundane while 

the newer ones are frequently dynamic, emergent, and 

potentially transformative. ●

Figure 6. Metro Area Establishment Clustering, 2010 

Source: Brookings-Battelle Clean Economy Database

An establishment in a given segment is defi ned to be in a cluster if other establishments in the same county comprised 

at least one percent of all U.S. employment for the given segment.
32 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM
V

SIZING THE CLEAN ECONOMY | V. ADVANCING THE CLEAN ECONOMY 33

ADVANCING THE CLEAN 

ECONOMY 

As a result, near double-digit annual growth in key 

segments and in key regions really does point to the 

possibility of the clean economy generating signifi cant 

numbers of jobs in a variety of emerging global industries, 

whether it be cutting-edge renewable energy solutions and 

improved energy effi cient building systems or integrated 

systems for water purifi cation and environmental 

remediation. 

And yet, notwithstanding the lack of comparable crossnational data in this report, serious questions surround the 

relative size and growth rate of the clean economy in the 

United States compared to in other countries.

Bloomberg data on the renewable energy sector depict a 

massive, growing shortfall between U.S. and Chinese asset 

fi nancings—that of hard infrastructure like solar arrays, wind 

farms, or cellulosic ethanol refi neries, which represent the 

most tangible form of industry scale-up.2

Likewise, while the nation still runs an overall trade 

surplus in environmental technologies on the “green” and 

“blue” side of the clean equation, U.S. fi rms are losing 

market share both at home and abroad to competitors from 

other nations.3 

Fueled by innovation and private-sector 

entrepreneurship, numerous clean economy 

industries—particularly in the cleantech space—

have emerged from the recent fi nancial crisis 

and are progressing rapidly along relevant 

technology, cost, and employment measures.1

Figure 1. U.S. and China Clean Energy 

Asset Finance

Source: Bloomberg New Energy Finance
34 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM

All of which raises the question of what governments and 

regional leaders should do—if anything—to catalyze faster, 

broader growth across the U.S. clean economy.

To be sure, the private-sector—infl uenced by local and 

world technology and market dynamics—will play the lead 

role in driving growth. 

Much as they did in past waves of economic change, 

private initiative and private capital will do the lion’s share 

of the work of turning ideas into business concepts and 

business plans into large-scale market breakthroughs. 

In that sense, private-sector fi rms can and will step up 

with their own responses to environmental, security, and 

economic opportunity, whether by greening their ongoing 

business processes as Wal-Mart has because it reduces costs 

and appeals to customers, or moving as Google has done to 

build critical infrastructure with its plan to help construct a 

$5 billion underwater transmission line for future wind farms 

off the Atlantic coast, or collaborating to promote urban 

sustainability as a consortium of Charlotte businesses has 

with its Envision: Charlotte effort.4 Private decisions, in this 

regard, will ultimately determine the size and impact of the 

clean economy in America and its regions.

However, the success of the private sector in delivering 

the clean economy will also depend on the existence of wellstructured markets, a favorable investment climate, and a 

rich stock of cutting-edge technology—all matters shaped to 

a varying extent by government. 

In this connection, the complication of virtually every 

segment of the clean economy—whether it be the water 

and wastewater industries or the energy segments—with 

a profusion of fundamental market fl aws and institutional 

problems alone argues for a government role in unleashing 

greater market activity. 

Likewise, the fact that signifi cant policy uncertainties are 

likely depressing investment in the clean economy reinforces 

the need for engagement and reform. After all, neither 

entrepreneurs and companies, nor investors will commit 

large sums of capital to clean economy enterprises in the 

absence of a predictable policy outline.

And so it is clear that before truly vibrant private-sector 

growth and scale-up can occur in the clean economy supersector there must be in place a clear, supportive, and stable 

policy outline that:

● Fosters demand and structures a vibrant 

domestic market

● Ensures the availability of adequate fi nance

● Promotes innovation

At the same time, it is essential that supportive 

conditions exist that:

● Keep the focus on regions

The regional build-out of the clean economy matters 

because local markets and regional industry clusters are 

where the clean economy actually takes place. Regions, after 

all, are the prime site of the day-to-day interactions by which 

real companies in real places develop new technologies, start 

new businesses, hire workers, and grow. 

To that end, this report points to three critical areas of 

needed engagement—as well as the need to put regions at 

the center of future efforts—as Americans weigh how to 

advance clean economy growth at a time of global challenge.

In each case private sector-led growth needs to be copromoted through complementary engagements by all levels 

of the nation’s federal system.

MAKE A MARKET: CATALYZE VIBRANT 

DOMESTIC DEMAND 

A fi rst priority for unleashing clean economy growth must 

be to catalyze stronger market demand for clean economy 

goods and services. 

Vibrant domestic market is critical because strong 

demand—or the expectation of strong demand—in a large 

and growing domestic market signals opportunity, attracts 

investment, and induces incremental innovation.5 Over time, 

the presence of strong and steady domestic demand allows 

fi rms to scale up steadily and rapidly, lower their costs, and 

manufacture at home. Ultimately, strong and discerning 

domestic demand furnishes a route to global leadership.6

And yet, the hard fact is that the United States does not yet 

boast strong demand for clean economy goods and services.

The problem: Policy gaps and uncertainties are 

depressing domestic demand

An array of policy gaps and uncertainties currently weaken 

the U.S. clean economy market. Some of these problems 

pervade almost the entire clean economy; others apply 

only to narrower portions of it, such as the clean energy 

segments encompassing energy effi ciency and renewable 

energy or the water industry.7

 In any event, these market 

policy problems pose signifi cant challenges to scaling up the 

clean economy.

To begin with, the lack of a coherent carbon pricing 

system places clean economy goods and services in the 

categories of energy and resource effi ciency; greenhouse 

gas reduction, environmental management, and recycling; 

and renewable energy at a serious price disadvantage—which 

weakens demand for almost three-quarters of the clean 

economy. Absent such a price signal, clean economy goods 

and services remain relatively more expensive than they 

would if the harmful externalities of coal, oil, and other fossil 

fuel use—which range from greenhouse gas emissions and 

other air pollutants, to adverse health impacts such as lung 

disease and infant mortality to national security costs—were 

factored in.8 As a result, the incentive for both households 

and businesses to buy clean goods and services and for the 

private sector to develop them is reduced.9

Spotty public-sector procurement efforts are another 

issue—missed opportunities for governments, as early 

adopters, to help create the market for clean economy goods 

and services. Given that the federal government purchases 

$500 billion in goods and services annually (states and 

local governments spend an additional $400 billion), 

occupies nearly 500,000 buildings, and operates more 

than 600,000 vehicles, the procurement of clean energy 

products and services, green buildings, and environmental 

remediation services represents an enormous opportunity 

for government supply chains to create and drive the market 

for clean economy growth.10 Unfortunately, public sector 

procurement efforts remain limited and fragmented for a 

variety of reasons, including inadequate information on 

the environmental impacts and benefi ts of products and 

services, a lack of common standards for defi ning “green,” 

real and perceived cost barriers to buying green products, 

and market and technical uncertainties about their benefi ts.11

Inadequate access to low-cost end-user fi nancing for 

energy effi cient (EE) retrofi ts and renewable energy (RE) 

installations stands as another hurdle to unleashing strong 

market growth. Low-carbon solutions—whether for installing 

water-effi cient products and solar panels or undertaking 

deep whole-home retrofi ts—remain inherently capital 

intensive, with “fi rst cost” investment barriers having proven 

diffi cult to overcome.12 Therefore, it is unfortunate that while 

a variety of policy responses have been attempted, they have 

remained limited in scale, whether the mechanism be direct 

incentives such as grants and rebates; federal and state 

tax credits; or such fi nance instruments as revolving loan 

funds, utility on-bill fi nancing, energy savings performance 

contracting, and property assessed clean energy (PACE).13
SIZING THE CLEAN ECONOMY | V. ADVANCING THE CLEAN ECONOMY 35

Even these programs may now be threatened given current 

state budget shortfalls and the looming ARRA funding “cliff,” 

by which hundreds of millions of dollars in stimulus programs 

for clean energy projects will soon wind down.14

A series of structural and regulatory barriers in the 

electric power and water sectors also impede the adoption 

of clean technology solutions. Quasi-monopolistic and 

heavily regulated, electric utilities heavily intermediate 

consumer markets and demand, and do so with a mandated 

bias toward the least-cost, least-risk solutions. That means 

that these powerful incumbents have until recently been as 

slow to draw in renewable sourcing as they have been to help 

customers save electricity (both of which would elevate the 

demand for clean solutions). Similarly, the slow introduction 

of competition and deregulation into the drinking water 

and wastewater sector has led to a “safe and slow” mindset 

and a bias towards using conventional, familiar systems and 

technologies rather than innovative new ones.15

Finally, two policy problems that directly affect marketmaking in the renewable energy segment are worth noting. 

First, the lack of a national clean or renewable energy 

standard—a binding law that would require that utilities 

acquire a percentage of their electricity from renewable 

and other clean energy sources, perhaps including 

energy effi ciency—has likely depressed demand for clean 

solutions. Even though the country has experimented 

with such standards at the state level with some success, 

it has not maximized their potential by developing a fully 

national market with the associated economies of scale 

that would help renewable energy technologies become 

cost-competitive.16 The second problem affl icting this 

sector pertains to the effi cient delivery of clean energy 

to metropolitan consumers which hinges on the existence 

of adequate transmission capacity to deliver the energy. 

Here too a welter of policy problems involving the planning, 

fi nancing, siting, licensing, and building of transmission lines 

has contributed to delivery “bottlenecks,” and rendered 

the current transmission line development system “close to 

dysfunctional.”17

Overall, the combined effect of these policy gaps is a 

greatly weakened demand for clean economy goods and 

services and delays in the emergence of a vibrant, robust 

market in those products. 

The strategy: Improve market access 

and demand

In view of these problems, a number of policy responses 

on the part of federal, state, and local leaders could help 

unleash more vibrant demand in the U.S. domestic market, 

essential for supporting innovation and exports.

In more expansive times, the federal government 

might take the lead in creating market making conditions 

through smart policy interventions with the states playing 

a collaborative and active role in reinforcing clean economy 

market creation. Ideally, Congress would put a price on 

carbon pollution to stimulate demand for clean products 

and raise revenue for needed RD&D investments. Or it 

might pass a national clean energy standard (CES) that 

creates a “fl oor” rather than a “ceiling” for state standards 

and insists on substantial renewable energy use to bring 

consistent, large-scale demand to clean electricity markets.18

Or for that matter, Washington could establish a series of 

clean economy “Races to the Top” to spur states, utility 

commissions, and regions to develop and execute bold clean 

energy deployment plans or to accelerate the deployment 

and uptake of new and cleaner generation technologies.19

(For a particularly bold national effort at market-making, see 

the sidebar on Germany’s use of feed-in tariffs).

Unfortunately, however, such moves do not appear 

forthcoming in Washington. And yet, if “game-changing” 

major steps are not likely, progress actually seems possible 

on other important fronts in market-making.

At the federal level, redoubled efforts to employ 

government procurement—especially leveraging and 

reorienting the Department of Defense’s vast purchasing 

power toward cleaner energy sources—as a source of 

stable demand appear possible via executive order and 

congressional action.20 Similarly, progress on appliance 

and equipment energy effi ciency standards ought to be 

possible in Congress and would save consumers money even 

as they ensured a strong domestic market for energy and 

water effi cient products and services. And for that matter 

the Federal Energy Regulatory Commission (FERC) might 

well manage to institute regulatory adjustments to ensure 

more rational cost recovery on new transmission links 

needed to deliver renewable and other energy to urban load 

centers.21

Creating a Market for Renewables: Germany’s Feed-in Tariff

Germany is way ahead on renewable energy deployment and a key reason is the world’s most aggressive marketmaking strategy.

A decade ago, Germany set out to create a transparent, stable, and predictable domestic market for renewables. 

Most notably, the ambitious Renewable Energy Sources Act, which came into force in 2000, established a feed-in tariff 

program that guaranteed that electricity produced from renewable energy sources (including hydropower, wind, solar PV, 

concentrated solar, biomass, geothermal, and landfi ll or sewage gas) would receive an above-market rate of return for 20 

years. The tariff is designed to cover the cost of energy production plus a profi t of 5 to 7 percent, with the rates adjusted 

every four years to refl ect technological and price developments. 

The tariff, in any event, has had several effects. For one thing, it has accelerated the uptake of renewable electricity in 

Germany to the point that the renewable sourcing has surged from 5 percent of the electricity market in the 1990s to 17 

percent today. This vibrant domestic demand unleashed by the tariff has driven the growth of a large domestic market—

and export base—for clean energy, with all of the attendant economic benefi ts. 

Investment returns on renewable energy projects have been attractive in Germany, and ensured that numerous 

American companies like Google, First Solar, and Good Energies have invested there. In fact, clean energy investments 

in Germany reached $41.2 billion in 2010, a level that surpassed U.S. investment by a wide margin. As a result, moreover, 

signifi cant job creation and export prowess have followed. In 2004, the renewable energy industry employed 160,000 

people but by 2009 the number had jumped to more than 300,000. Germany is now also a global leader in the 

production of wind and hydroelectric turbines as well as solar panels.

As to the future of the program, it seems secure, notwithstanding opposition from big utilities as their losses of 

market share have increased. For one thing, initiatives to drive further renewables uptake will grow even more important 

in Germany with its recent decision to phase out nuclear energy development. For another, the feed-in tariff’s success in 

increasing installed capacity, growing the manufacturing industry, attracting investment, and creating jobs has made it a 

popular program. In that sense, economic development success has bred political consensus.

Sources: Federal Ministry for the Environment, Nature Conservation, and Nuclear Safety website and Energy Concept Paper (September 2010); Pew 

Charitable Trusts, “Who’s Winning the Clean Energy Race?” (2011).
36 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM

States, on their part, can continue to play a critical role 

in inducing demand for clean economy goods and services. 

In this respect states have long led the nation in catalyzing 

market demand for clean goods and services. They have 

addressed this in multiple ways, ranging from their multistate experiments with carbon pricing and their frequent 

RPS statutes to their energy effi cient building codes and 

renewable fuel standards to their innumerable rebate and 

incentive programs, tax credits, and other programs aimed 

at reducing end-user costs.22 Nonetheless, tremendous 

opportunities exist for states to accelerate their involvement 

in the market-making front.

To start with, states should build on their past leadership. 

Whether or not a national CES becomes a reality, states can 

increase the demand for clean electricity by strengthening 

or adopting state-level clean energy standards. These 

standards have worked well in increasing clean energy 

deployment and boosting local economies.23 Therefore, 

states that have established CES or RPS rules should 

consider ratcheting up their targets for utilities while the 15 

states that lack a target should consider implementing one.24

Similarly, states should step up their own procurement 

efforts, through which they can at once drive signifi cant local 

demand for green and clean products and services even as 

they achieve cost savings across their facilities, operations, 

and fl eets. One way to do this would be by establishing 

a comprehensive framework to underpin state-wide 

procurement policy, which would allow both for scaling up 

preexisting efforts and achieving economies of scale across 

programs while generating more demand for clean, green, 

and new sourcing.25 And for that matter states should further 

drive demand by continuing to work on reducing the initial 

costs of EE and RE investments for residential, commercial, 

industrial, and institutional customers. This has been an 

important past role of the states, which should now innovate 

again as they design and implement a new generation of 

creative fi nancing mechanisms that overcome fi rst cost 

barriers, leverage private with public capital, and create 

fi nancial products adapted to each distinct target sector.26

Finally, electricity market reform represents a 

signifi cant market-making opportunity for states. Here too 

states can institute a range of reforms from developing 

regulatory structures to promote utility investment in clean 

energy programs (e.g., through program cost recovery, 

revenue stability, and performance-based incentives) to 

establishing uniform interconnection requirements for 

connecting distributed generation applications to the grid. 

More fundamentally, states should consider moving to the 

more transparent, competitive, and fl exible model in which 

independent system operators (ISOs) or FERC-approved 

regional transmission organizations (RTOs) administer the 

planning of new infrastructure and the pricing of wholesale 

electricity. In addition to its role in lowering prices, the ISO / 

RTO model is more conducive to clean energy because the 

market shares generation and transmission over a larger 

geographic area and harbors fewer confl icts of interest 

in expanding capacity to accommodate new renewable 

generators or in allocating costs to market participants.27

Yet those are only federal and state engagements. 

Local governments and regional actors across the nation 

can also play a role in generating more robust demand for 

goods and services within the clean economy sector. This 

they can do in a multitude of ways. Local governments 

can accelerate renewable energy use by buying renewable 

energy for public buildings, expediting permitting for 

projects, reusing contaminated lands—such as brownfi elds, 

landfi lls, and Superfund sites—for renewable energy projects, 

and adopting fi nancing tools such as PACE and power 

purchase agreements.28 Local governments can also adopt 

green building policies and ordinances for new buildings 

while creating retrofi t programs for existing buildings.29 And 

for that matter, local governments can improve the fuel 

effi ciency of fl eets servicing their community which will 

drive the demand for clean vehicles and clean fuels from 

the bottom up. Local governments can also step up to the 

challenges posed by climate change by setting targets 

and drafting climate action plans to reduce greenhouse 

gas emissions.30

Figure 2. Many federal clean economy tax and related incentives expire in the next few years

Advanced Energy 

Manufacturing Tax Credit

Brownfi elds 

Tax Incentive

Clean Energy 

Renewable Bonds

Section 1705 DOE 

Loan Guarantee

Energy Effi cient Appliance 

Manufacturing Tax Credit

Energy Effi cient New Homes 

Tax Credit for Builders

Section 1603 

Treasury Grant 

PTC for Renewable 

Energy (Wind)

PTC for Renewable 

Energy (Other)

ITC for Renewable 

Energy

Recovery Act

Tax Relief Act of 1997

Ret. = Retroactively extended

Ext. = Extended

EPAct = Energy Policy Act

2005 EPAct Ext. Recovery Act

2005 EPAct Recovery Act

2005 EPAct Extended

2005 EPAct Ext. Ext. Ret. Ext.

Recovery Act Ext.

1992 EPAct

1992 EPAct

2005 EPAct

2005 EPAct

Recovery Act

Recovery Act

Extended

Extended

Extended

Extended

Ret.

Ret.

Ext.

Ext.

Ext.

Ext.

2005 EPAct Ext. Extended through 2016

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Ret. Ret. Ext. Ret. Ext. Ret. Ext.

ARRA Funding Cliff 

Dec 2011/Jan 2012

u

Ac
SIZING THE CLEAN ECONOMY | V. ADVANCING THE CLEAN ECONOMY 37

ENSURE ADEQUATE FINANCE: 

ADDRESS THE 

COMMERCIALIZATION GAP 

Market-making policies won’t be enough, however. A second 

priority must be to address the serious fi nance problems 

that surround clean economy scale-up.

On this front, the availability of affordable capital of the 

right scale and with the right tolerance for risk is essential 

to all companies. Access to affordable fi nance matters 

inordinately in the clean economy because promising 

clean enterprises—whether in renewable energy or energy 

effi ciency or water technology or air purifi cation—often draw 

together intriguing but new technology, unusually heavy upfront capital requirements, and tricky regulatory or market 

settings.31 Yet here again, the nation’s current patchwork of 

responses to clean economy fi nance needs—especially in the 

energy fi eld—remains sub-optimal and requires attention.

The problem: Responses to the deployment 

fi nance gap remain inadequate 

On this front, the entire development chain through which 

clean economy goods and services are invented, proven, 

deployed, and scaled-up commercially is beset with fi nance 

challenges—challenges that have been thrown into relief by 

the massive recent clean energy investments of state-owned 

Chinese banks.32 And yet, while signifi cant attention over 

the years has focused on earlier-stage R&D and proofof-concept challenges (the technology creation “Valley 

of Death”), larger fi nance problems located at the laterstage demonstration and deployment stage of the growth 

pathway now cry out the most for response—and yet remain 

unresolved. 

The core issue is that a truly gargantuan “commercialization (or deployment) Valley of Death” now exists between 

the earlier R&D / technology proving stage and full-scale 

commercial roll-out, whether in energy or in other areas.33

At the earlier stage, government research dollars and VC 

capital are still managing to generate good ideas and provide 

entrepreneurial start-up companies with investments 

ranging from a few million to $20 million. At the very 

latest stages, traditional project fi nance and bank lending 

(ranging from perhaps $100 million to billions) is available 

for building out large, asset-based installations applying 

proven technology—whether it be a utility-scale solar array 

or a 50 million gallon cellulosic ethanol plant. However, in 

the intervening chasm—between the initial proof of concept 

that a VC can fund and the full-scale commercial roll-out 

typically fi nanced by banks—few sources of capital exist for 

building critical initial pilot plants or scaling up advanced 

manufacturing facilities. 

For which reason, a number of federal and to a lesser 

extent state initiatives have been set up to address the 

investment challenges of the commercialization Valley of 

Death—most notably the DOE's Loan Guarantee Program 

as well as a variety of federal and, in some cases, state tax 

credits. Unfortunately, though, multiple problems weaken 

the ability of these programs to draw private money into 

deployment and clean economy build-out.

The Loan Guarantee Program—which backs private loans 

to promising companies with new technologies—has been 

criticized as too slow-moving, too much engaged in ”picking 

winners,“ as well as too conservative.34 On the latter point, 

industry leaders, innovators, and analysts say that the 

program’s requirements remain so stringent and prudent 

that they effectively replicate private-sector risk aversion—

the problem the program is meant to address.35

As to the tax credits, these remain unstable—and are 

diminishing. Investors and deals require certainty, or at 

least predictability, about the terms and timeframe of the 

investment. However, U.S. deployment fi nance policy on the 

clean economy has been neither certain nor predictable 

(See Figure 2).36 Cases in point are the federal Production 

Tax Credit (PTC) and the Investment Tax Credit (ITC) which 

have been allowed to lapse before being granted shortterm extensions multiple times.37 In fact, this unstable, 

on-again, off-again instability has affected multiple other 

important fi nance programs such as the EPA’s Brownfi elds 

Tax Incentive. 

Yet now things are poised to get worse. Most notably, 

the wind-down of ARRA’s multiple provisions combined with 

other “sunsettings” of multiple tax code programs promises 

not just more “starts-and-stops” but a lot of “stops.” A review 

of coming changes confi rms, for example, that multiple clean 

economy-related tax provisions will expire by the end of 2011, 

including the Brownfi elds Tax Incentive, the Energy-Effi cient 

Appliance Manufacturing Tax Credit, the Energy-Effi cient 

New Homes Tax Credit for Home Builders, the Section 

1603 Treasury Grant, and the Section 1705 Loan Guarantee 

Program. Other clean economy incentives such as the PTC 

for wind energy projects and the Clean Renewable Energy 

Bonds (CREB) program are set to expire by the end of 2012 

(PTC for other qualifying projects end in December 2013). 

In short, the whole rickety structure of the nation’s 

main federal responses to the fi nance challenges faced by 

the clean economy faces a moment of reckoning—this at a 

time when the states’ own engagements in clean economy 

fi nance also face resource shortfalls and rarely have the 

resources to address fi rms’ later-stage need for large 

amounts of capital to support commercial-scale deployment. 

The strategy: Address key fi nance gaps 

Given these challenges, effective mechanisms need to 

be designed at all levels of the American system to draw 

in private capital and ensure the availability of adequate 

fi nance for clean economy scale-up.

To this end, the single most catalytic action that 

could be taken to advance the scale-up of new clean 

economy manufacturing and infrastructure could well 

be focused action by Congress to create an emerging 

Figure 3. Multiple fi nance gaps complicate the scale-up of clean technologies

Source: Bloomberg New Energy Finance
38 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM

technology deployment fi nance entity to address the 

commercialization Valley of Death. (For China’s aggressive 

parallel actions see sidebar). 

To be sure, debates persist about the exact design of 

such a new entity. However, several sound models appear 

promising, including the proposed Clean Energy Deployment 

Administration (CEDA), which would provide loans, loan 

guarantees, and other credit enhancements to facilitate less 

expensive lending in the private sector; and the so-called 

Energy Independence Trust (EIT) concept developed by the 

Coalition for Green Capital, which would also expand access 

to low-cost fi nancing to increase investment and lower the 

cost of deployment. Still other concepts being explored by 

the Coalition for Green Capital and the New England Clean 

Energy Council would channel stranded off-shore capital 

into U.S. clean economy scale-up through a qualifi ed tax 

cut.38 Either way the political moment—concerned about 

large scale deployment in China; frustrated with the DOE 

loan guarantee program—appears surprisingly favorable for 

what would actually be a cost-effective initiative with large 

returns. CEDA requires a $10 billion appropriation to catalyze 

a self-sustaining fl ow of private-sector fi nance for innovative 

deployment projects. The EIT, aimed at commercial-scale 

deployment of more mature technologies, would be 

authorized to borrow from the Treasury and repay the loans 

and so would require no appropriation. In both cases, any 

up-front costs could be paid off from a share of the revenue 

stream—making the programs virtually costless to taxpayers. 

For their part, the capital repatriation schemes would cost 

next to nothing. And yet, while the cost would be minimal, 

these mechansims‘ role in “de-risking” and helping fi nance 

large projects and so deploying game-changing technologies 

at scale could be no less catalytic than the Export-Import 

Bank’s role in reducing the risk faced by exporters who 

contract with foreign buyers, or the Federal Crop Insurance 

Corporation’s role in promoting investment in agriculture. 

Such institutions offer usable precedents for new clean 

economy fi nance mechanisms.

Also helpful on the fi nance front would be a push to 

rationalize and reform the myriad tax provisions and 

incentives that currently encourage capital investments 

in clean energy projects. In this respect, the expiration of 

multiple elements of the nation’s mish-mash of federal 

deployment fi nance supports in fact represents an 

opportunity for reform. Such reform might well pair selective 

extensions of key production, investment, and manufacturing 

tax credits as well as the Treasury grant cash-back program 

with staged, technology-specifi c phase-outs, which would 

at once provide new industries support, predictability, and a 

nudge toward innovation and cost-reduction.39 Alternatively, 

such a reform drive—which could be paired with a new look 

at reducing or eliminating subsidies to fossil fuel industries 

as well—might utilize competitive tendering processes 

like reverse auctions to contain subsidy expenditures and 

maximize the returns from given outlays.40 In any event, the 

expiration of so many existing incentives at once is going 

to force a debate in the next two years and reform along 

the lines noted here might appeal at once to defi cit hawks, 

members eager to provide tax benefi ts to the private sector, 

and others focused on unleashing investment and jobcreation. Such a debate in Washington—paired with a serious 

focus on responding to the deployment fi nance gap—would 

be an auspicious development for the clean economy. 

And yet, states and even regions themselves can play 

a huge role in accelerating the scale-up and deployment 

of new clean technologies and projects—as some are. For 

example, state development authorities—notwithstanding 

their limited fi nancial and staffi ng resources—might consider 

supplementing private lending activity by providing 

guarantees and participating loans to in-state companies 

with promising new technologies. To be sure, the size of 

the relevant deals will surely fall below the $100 million 

to $500 million cited as the most intractable fi nancial 

Valley of Death. However, when combined with private 

capital and other lending, state programs can still play 

a signifi cant role in catalyzing the commercialization 

and deployment of clean technologies. Connecticut and 

California provide good examples of how this is being 

done.41 The Connecticut Development Authority (CDA) 

provides up to $5 million in guarantees or supplemental 

fi nancing for companies seeking to expand the production 

of promising new technologies. The CDA also leverages and 

Ensuring Finance: China’s Clean Economy Investment Strategy

China now leads the world in clean economy deployment. By the end of 2010 its 103 gigawatts of installed renewable 

energy generation capacity was more than double that of U.S. installations. 

What explains China’s success in rapid clean economy build out? 

A huge part of the answer has to do with China’s ability to channel vast sums of affordable capital into innovative 

large-scale deployment projects—something that the U.S. continues to struggle with. The numbers speak for themselves. 

In 2010, China put into place a staggering $54.4 billion in clean energy investments. Of this, asset fi nancing—funding for 

hard assets like wind farms and solar arrays—accounted for more than $47 billion of the total. By contrast, U.S. private 

investment in clean energy totaled $34 billion, with just $21 billion or so in asset fi nance. Now the gap is widening further, 

with Chinese asset fi nance investment in Q1 2011 clocking in $10.9 billion as compared to just $2 billion in the United 

States.

What is China’s secret in ensuring deployment fi nance? China has been inordinately successful in mobilizing large 

volumes of low-cost capital through its state-owned banks and other fi nancial institutions. Clean energy projects have 

received preferential access to bank loans at interest rates far below what is available in other countries. Moreover, 

state-owned enterprises, especially the “Big Five” power companies, have been major investors across a broad range of 

energy conservation, pollution control, and renewable energy projects. For instance, China Guodian Corporation—one of 

the Big Five—recently announced a plan to invest $3 billion over the next fi ve years in a variety of clean energy projects, 

including thermal, wind, natural gas, and biomass power stations in southwest China.

But that is only part of the story. Critical to China’s success is its articulation of a comprehensive and long-term state 

clean energy build out policy that sends clear signals to investors. Through its 12th Five Year Plan, China has identifi ed 

“new energy” as one among seven “strategic emerging industries” and will invest $760 billion over the next 10 years 

in this sector alone. A range of complementary policies will guide these investment decisions, including the Renewable 

Energy Law, national demand-side management regulations, and pilot carbon taxes, among others. China has swiftly 

made itself a clean energy power, in large part by ensuring the availability of copious, affordable capital at a time it has 

been short in the United States.

Sources: Bloomberg New Energy Finance; Pew Charitable Trusts, “Who’s Winning the Clean Energy Race?” (2011); The Climate Group, “Delivering Low-Carbon 

Growth: A Guide to China’s 12th Five Year Plan” (London: HSBC, 2011); written testimony by Julian Wong, Center for American Progress Action Fund, before 

the U.S.-China Economic and Security Review Commission (July 2010)
SIZING THE CLEAN ECONOMY | V. ADVANCING THE CLEAN ECONOMY 39

partially guarantees loans to clean economy companies by 

partnering with the U.S. DOE’s Loan Guarantee Program 

through the Financial Institution Partnership Program 

(FIPP). Likewise, the California Energy Commission 

administers an Alternative and Renewable Fuel and Vehicle 

Technology Program, which authorizes loan guarantees 

and other fi nancial measures out of an annual pool of 

approximately $100 million.

And states could go farther: In a related way, they could 

catalyze follow-in investment by setting up and providing 

the initial funding for revolving loan funds targeting clean 

economy projects using new or improved technologies.42

Under this model, the state capital contribution could 

potentially be leveraged through the issuance of bonds 

to be repaid out of debt service. As repayments are made 

funds would be re-circulated into new loans. Such a model 

would be novel but not entirely different from California’s 

Infrastructure and Economic Development Bank (I-Bank) or 

the revolving loan funds that many states use to support 

drinking and wastewater projects.

For their part, regions and localities can also help 

narrow the deployment gap, not so much through direct 

deployment fi nance as by reducing the costs and uncertainty 

of projects by expediting their physical build-out. In this 

respect, regional and local strategies to manage zoning and 

permitting issues or even pre-approve sites to facilitate 

new factory or project development would in their own way 

accelerate build-out by saving time and money.43

DRIVE INNOVATION: ACCELERATE 

TECHNOLOGY DEVELOPMENT

Recharging and renewing the U.S. innovation system is going 

to be critical too.44

Innovation (both radical and incremental) matters 

because too few clean technologies can yet compete with 

their incumbent competitors on an unsubsidized price basis—

which remains the ultimate requirement if clean and green 

new technologies, processes, or services are to pervade the 

U.S. and world economy.45

To be sure, policies to catalyze market demand and 

facilitate fi nancing will help scale up proven technologies 

and incremental innovations. However, a near consensus 

also insists on the imperative of complementing efforts 

to unleash demand with a strong push on technology 

development and deeper-going innovation.46 Only through 

such a sustained technology push will society offset the 

serious market problems that prevent private fi rms from 

investing adequately to generate the next waves of products, 

processes, and business models, whether in cheap renewable 

energy, green materials, environmental remediation, or 

super-effi cient water purifi cation. 

Yet, serious policy shortcomings continue to weaken the 

U.S. clean technology and processes innovation system and 

need to be addressed. 

The problem: The nation’s clean economy 

innovation system remains inadequate

Certainly, signifi cant efforts have been made to improve the 

nation’s innovation standing in recent years. However, these 

efforts remain inadequate in terms of both their scale and 

their format—and now appear in jeopardy. 

In terms of their basic size, U.S. clean energy and 

environmental-sector technology development investments 

remain insuffi cient to ensure a steady stream of future 

incremental and radical technical advances. 

On this front, a proliferation of market failures has long 

been recognized as arguing for a strong public investment 

role given that such problems discourage private fi rms 

from investing adequately in the technology development.47

Yet even so, past Brookings reports (and many others) 

have documented the sub-optimal levels of recent federal 

innovation investments in the energy domain even as the 

current administration and Congress moved to improve 

them.48 These recent steps forward have increased federal 

energy research, development, and demonstration (RD&D) 

investment—the sum of federal investments in energy system 

transformation—from just under $3.0 billion a year through 

much of the last decade to $4.7 billion in 2010 and to over 

$5.0 billion in the FY 2011 and 2012 budget requests.49 Yet 

even these recently increased investment levels in energy 

innovation refl ect a relatively low national investment 

intensity. To put current efforts in perspective, several 

analyses suggest a national expenditure of at least $15 

billion to $25 billion annually would be necessary to bring 

the research intensity of the U.S. energy sector in line with 

that of other innovation-oriented sectors such as IT, biotech, 

or the semiconductor industry.50 For more context, note that 

over the past two decades prior to the stimulus package U.S. 

energy R&D (which excludes demonstration) had declined 

steadily as a share of GDP to two-thirds of the OECD level.51

U.S. investments in water and environmental sciences 

also remain modest. For example, the EPA—far from the only 

federal agency to conduct environment-related R&D, but the 

one with the most applied and technology-focused portfolio—

saw its R&D budget dwindle by a quarter to a low of $505 

million in 2008 from its 2004 peak before it grew modestly 

to $538 million in 2010.52 These investments amount to less 

than 0.01 percent of U.S. GDP—a fi gure just one-quarter the 

level registered by the rest of the OECD.53

And yet, even the sub-optimal investment levels detailed 

here now appear in jeopardy. Most notably, with the waning 

of federal stimulus investments and the rise of federal defi cit 

anxiety, recent progress on improving the level of federal 

innovation investments of all kinds appears vulnerable. 

And neither will future reversals likely be offset by the 

increasingly active engagements on RD&D on the part of 

dozens of states—which, for their part, face tough choices on 

the use of their limited resources. Past state investments in 

energy R&D in particular have generated useful commercial 

innovations, but additional and sustained funding will 

be needed to create and build out innovative capacity in 

universities, industry, and the labor market—and it may not 

be available.54

But the problems weakening the nation’s low-carbon and 

environmental innovation system go beyond the inadequate 

scale of current efforts. In addition, the format of innovation 

efforts also remains inadequate. Too much of the nation’s 

past energy and environmental research has been based on 

an obsolete research paradigm, oriented heavily to either 

individual campus-based research projects or else to the 

highly “siloed,” often insular and bureaucratic efforts of the 

DOE’s energy laboratories.55 On this front too, the Obama 

administration and Congress have in recent budget cycles 

responded—at least on the energy side—to calls for reforms. 

Most notably, the nation has begun to fund a trio of novel 

DOE start-up programs aimed at renovating the insular, 

stovepiped research approaches of the department. These 

include the Energy Frontier Research Centers (EFRCs), 

focused on multi-disciplinary scientifi c research on current 

barriers to technology progress; the Advanced Research 

Projects Administration-Energy (ARPA-E), focused on “highrisk, high-reward” projects in the translation stage; and 

the Energy Innovation Hubs, spanning the innovation and 

commercialization chain from invention to adoption.56 Also 

laudable is the EPA’s support of the Southeast Ohio-centered 

Water Technology Innovation Cluster (WTIC) program.57

Budgetary uncertainty now surrounds all of these 

experiments. After a stimulus infusion of $400 million for 

use in FY 2009 and 2010, for example, ARPA-E was allocated 

only $50 million in the initial FY 2011 budget proposal in H.R. 

1 and ultimately received a modest $180 million in overall 

funding as a result of the recent budget deal struck by 

Congress.58 Likewise, Congress has so far funded only three 

of the originally requested eight energy hubs, with funding 

for future years and more institutes appearing dicey.59
40 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM

Fostering Regional Innovation in Northeast Ohio: NorTech’s Advanced Energy Roadmaps

Northeast Ohio—home to over several hundred clean economy companies—is well positioned to emerge as a leading 

center for innovation in technologies related to electric vehicles, energy storage, the smart grid, and waste-toenergy processes. Now, a regional economic development organization is moving to make sure that happens.

Serving as the focal point in Northeast Ohio for the advanced energy cluster, NorTech, a regional nonprofi t economic 

development organization, is leading the development of a series of advanced energy technology and industry cluster 

roadmaps. Because industry roadmaps provide strategic guidance for economic development efforts to accelerate 

innovation and commercial activity, they can be a dynamic tool for setting priorities, allocating resources, aligning 

stakeholders, and focusing efforts. Along these lines, NorTech is using its extremely collaborative roadmapping model 

to identify the distinctive strengths of the region, characterize the relevant global markets‘ drivers and opportunities, 

assess the competitive landscape, articulate a shared vision for the region, and outline opportunities. 

To begin with—and also to differentiate itself from other regions that are trying to build energy-related industries—

NorTech has identifi ed four sectors with compelling regional assets, global market opportunities, and potential to result 

in signifi cant regional economic impact in the near term. Leveraging a $300,000 grant from the federal Economic 

Development Administration, NorTech has crafted roadmaps for the energy storage, smart grid, fuel cells, and waste-toenergy sectors that will ultimately enable the region to claim a large chunk of the burgeoning advanced energy market. 

As part of the roadmapping process, NorTech is also using “cluster sourcing” as a mechanism to foster innovation 

within the advanced energy cluster. Through this process, NorTech organizes and facilitates innovation working groups 

consisting of cluster members, researchers and other manufacturers in the value chain to attack specifi c challenges 

within the cluster and to develop new products in response to market opportunities.

In this way, the effort underway by NorTech and its Northeast Ohio partners epitomizes the sort of “bottom-up,” datainformed organizing that fosters regional clusters, innovation, and job growth and advances the clean economy region by 

region. 

Source: NorTech Energy Enterprise website; e-mail correspondence with Rebecca Bagley, NorTech.

Advancing Energy Innovation and Technology: NYSERDA’s Clean Energy Business 

Incubator Program

New York State is rapidly emerging as a leader in clean energy innovation, including through its statewide programs 

funding early-stage R&D, business incubators, and clean energy demonstration projects. Many of the state’s 

efforts are being orchestrated by the New York State Energy Research and Development Agency (NYSERDA), a public 

benefi t corporation created in 1975 by the New York State Legislature. NYSERDA’s annual budget is approximately $620 

million and its primary funding is derived from an assessment on the sale of electricity in New York State. NYSERDA 

has distinguished itself by undertaking a strong, tailored regional approach to promoting investment in emerging 

technologies and encouraging growth of the renewable and clean energy industry in New York state metro areas.

One way NYSERDA is fostering cleantech innovation is through promoting successful partnerships between earlystage cleantech companies and regional incubators that provide guidance, technical assistance and consultation to 

companies to help them develop and commercialize clean energy technologies. Since 2009, NYSERDA has invested 

nearly $9 million in six cleantech incubators through the Clean Energy Business Incubator program: Long Island High 

Technology Incubator, Inc. at Stony Brook University; Rochester Institute of Technology’s Venture Creations; the 

University of Buffalo’s Offi ce of Science, Technology Transfer, and Economic Outreach; the Tech Garden at Syracuse; the 

NYC Accelerator for a Clean and Renewable Economy (ACRE); and the Incubator for Collaborating and Leveraging Energy 

and Nanotechnology (iCLEAN) at the University of Albany.

As of the end of 2010, with only 18 months of operation and $2.5 million in program expenditures, the Clean Energy 

Business Incubator program has already achieved signifi cant results. The six incubators have nurtured the creation of 

several hundred net new jobs at client startup companies and the introduction of 26 new products to serve the clean 

energy market. They have assisted client companies in raising $16 million in private capital and attracting $11 million in 

federal funding, leveraging state expenditures by more than 10 to 1.

NYSERDA’s efforts to help clean energy businesses develop and commercialize new energy technologies has been 

critical in helping New York create and retain the types of the companies that form the bedrock of a clean energy 

economy.

Source: NYSERDA’s Clean Energy Business Incubators, available at www.nyserda.org/BusinessDevelopment/ourpartners.asp; E-mail correspondence with 

Janet Joseph, NYSERDA.
SIZING THE CLEAN ECONOMY | V. ADVANCING THE CLEAN ECONOMY 41

The prospects are even bleaker for as-yet-unimplemented 

proposals such as one to create a number of regionally 

based clean economy innovation consortia to better connect 

the research community to market players in U.S. regions.60

The strategy: Keep working to improve the 

clean economy innovation system 

To stave off retrenchment, then, and ideally to maintain 

forward progress on innovation system enhancement, 

federal, state, and regional actors will all need to combine 

doggedness and creativity. 

Clearly no massive scale-up of energy and environmental 

innovation investment is likely in the near term. However, it 

ought to be possible for Congress to embrace incremental 

growth of the energy and environmental RD&D budgets 

even in the context of defi cit reduction. And it ought 

to be possible for the body to affi rm the value of its 

recent institutional experiments and make incremental 

investments in the ramp up of the Energy Frontier 

Research Centers, ARPA-E, and the Energy Innovation 

Hubs. Congress should therefore consider measured 

expansion of all of these programs and others, including a 

tripling of the ARPA-E budget, the creation of new hubs, the 

creation of a water sciences innovation center, and the 

establishment of a regional clean economy consortium 

initiative.

61 For resources there is no shortage of options: 

Revenue to support these investments could be located 

through the phasing out of counter-productive energy 

subsidies, the “off-budget” establishment of a small 

surcharge on electricity sales, the implementation of a small 

fee on imported oil, the dedication of revenues from a very 

low carbon tax, or even from the repatriation of "stranded" 

off-shore capital.62

But those are federal policy options. For their part, 

more states may choose to engage on innovation at a 

moment of rising need and limited resources. Many states, 

after all, are highly alert to the benefi ts of fostering the 

emergence of innovative clean industries and bring to the 

task important local knowledge and business connections. In 

this connection, state RD&D activity has been an important 

complement to federal leadership for years, and so many 

states have implemented a multitude of mostly modestscaled efforts to invest in the RD&D process at all stages, 

whether by investing directly in research; supporting 

incubators in connection with local research universities; 

establishing seed funds to fi ll the funding gap between lab 

research and venture funding; or supporting demonstration 

projects.63 (See sidebar on New York state’s ambitious 

approach).

In view of that, it would be a good thing for the growth 

of the nation’s clean economy if the states found ways to 

maintain or expand their effort on RD&D notwithstanding 

budgetary stress. And here there is a little-known resource 

to draw on—the state clean energy funds that exist in 

more than 20 states, supported by small public-benefi t 

surcharges on electric utility bills.64 These funds generate 

about $500 million per year in dedicated revenue, most 

of which goes to support individual project fi nance and 

deployment. Given the needs of the moment, channeling 

more of those fl ows into critical innovation (as well as 

economic development) activities represents an important 

option for maintaining and recharging states’ clean economy 

innovation system. Yet, states will never have suffi cient 

funds to invest comprehensively in traditional R&D and 

RD&D programs, making it critical that states focus and 

prioritize their innovation investments. To do this, states 

should complement stepped up investment effort with a 

sharper focus on the precise needs of promising innovation 

segments in the state economy. Central to this be a rigorous 

embrace of detailed sector, industry, and innovation system 

analysis such as a number of states and regions are now 

pursuing. (For background on Northeast Ohio’s technology 

roadmapping exercise see sidebar). Only by employing 

fi ne-grained data and analysis to target interventions, drive 

design, and track performance will states maximize the 

impact of scarce innovation dollars.

* * *

Clarity on each of these fronts will drive growth because 

it will allow actors in the clean economy to locate customers, 

structure fi nance deals, and draw on leading-edge 

technology in a vibrant, predictable environment.65

But predictability of market-making, fi nance, and 

innovation will not be suffi cient. Also important will be 

regional strategies, which more and more entrepreneurs, 

fi nanciers, economic development leaders, and policymakers 

believe can play a critical role in bringing it all together. This 

priority runs along the lines that follow:

FOCUS ON REGIONS: 

BUILD THE CLEAN ECONOMY 

CLUSTER BY CLUSTER

Regions and the regional industry clusters they contain 

play a critical role in growth because they foster innovation, 

entrepreneurship, and job creation while promoting 

economic effi ciency.66

Regions are the places where—within the federalist 

system—research is conducted, technologies are developed, 

ideas are shared, and new businesses started.67 Regions, 

likewise, are the places where markets are tested, deals 

done, projects sited, and workers and suppliers located. 

In fact, the importance of regions and clusters pervades 

this study, one of the most important fi ndings of which 

remains the fact that the number of jobs in “clustered” clean 

economy establishments grew signifi cantly faster than did 

the number in their more isolated counterparts. In this vein, 

industry clustering in the clean economy and elsewhere 

has increasingly been recognized as providing a useful and 

practical framework for shaping economic policy; catalyzing 

“bottom-up” strategy and execution; and coordinating 

fragmented policy offerings. And yet, notwithstanding a 

modest embrace of cluster concepts in recent economic 

discourse, much room exists for a more concerted focus on 

the importance of regions in clean economy development 

efforts. 

The problem: Clean economy development 

efforts have placed too little emphasis on 

regional and industry cluster strategies 

Too often place and the fact of industry clustering—the 

geographic concentration of interconnected fi rms and 

supporting or coordinating organizations—are left out of 

national clean economy discussions.68

To be sure, the reality of clustering in the clean economy 

has begun to inform federal policymaking in recent 

budget cycles, building on earlier inroads at the state 

level. Multiple federal agencies including the Economic 

Development Administration (EDA), the Small Business 

Administration, the Department of Agriculture, the National 

Science Foundation, and the Department of Labor now 

offer competitive grant programs for the modest support 

of regional cluster initiatives, including “green” ones.69 In 

fact, several initiatives—such as the DOE’s Energy Regional 

Innovation Cluster (Effi cient Buildings) hub as well as this 

year’s pending i6 Green Challenge to promote clean energy 

innovation and job growth—explicitly adopt cluster strategies 

into clean economy growth initiatives.70 Likewise, a longerstanding orientation toward cluster strategies at the state 

level has seen the continued and accentuated application 

of the paradigm to clean economy initiatives in a number 

of states. States like Colorado, New York, and Oregon, have 

all applied a strong regional and cluster focus to their clean 

economy development initiatives.71
42 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM

Nonetheless, the leveraging of regional industrial and 

innovation dynamics for clean economy growth remains an 

under-exploited opportunity. 

At the federal level, the nation’s new array of regional 

development and green cluster offerings remains valuable 

but modest in scale—and frequently oversubscribed.72 More 

importantly, the nation’s chief energy-sector agency—the 

DOE—has until recently lacked a strong economic or regional 

development mission and still contends with a culture of 

insularity and aloofness from the marketplace that derives 

from the security mindset of its work in nuclear weapons 

development.73

At the state level, clean economy strategies do not always 

apply a well-focused regional emphasis—even when they 

adopt cluster concepts and terminology. Along these lines, 

state approaches to clean economy development—while 

well intentioned and frequently impressive—remain at times 

generic or ill-defi ned; insuffi ciently grounded in top-quality 

data analysis; or insuffi ciently “bottom-up.”74

And then, while more and more regions are mounting 

their own increasingly strategic, locally specifi c initiatives to 

accelerate clean economy growth, not enough are. 

On the positive side, regional self-assertion has emerged 

as a bright spot in the United States, with dozens of 

regionally-based intermediaries now moving to execute 

sophisticated growth strategies. 

However, the fact remains that too few local clean 

economy growth campaigns are employing truly disciplined, 

data-rich, analytic approaches to ascertaining local 

specialization and accelerating home-grown growth. 

As at the state level, too few regions—given the limited 

cross-region data that has been available—have been able 

to assemble adequate information to really understand 

their clusters’ market position and growth potential. 

Consequently, too many regional clean economy strategies 

focus on overly broad categories like “renewable energy” or 

“energy effi ciency” rather than more distinctive sub-niches 

and developing strategy at that level. 

Probably the most visible consequences of all of this 

inconsistent attention to cluster dynamics and locallyspecifi c data, meanwhile, are workforce problems. On the 

one hand, concern has been mounting in some quarters 

about shortages of qualifi ed workers, especially in the utility 

sector, to meet near- and long-term demand.75 By contrast, 

though, more recent news and other reports—following on 

the investment of some $600 million of stimulus money 

in “green” training programs—have described situations 

in which the supply of trained clean economy workers 

has exceeded the regional market’s need for them.76 What 

links these seemingly opposite labor supply problems, it 

turns out, are widely recognized disjunctions between U.S. 

regions’ workforce training systems and the local clean 

economy. Several studies note, after all, that clean economy 

worker training programs have neither been suffi ciently 

data-driven nor informed by adequate partnerships 

between educational and training organizations, on the 

one hand, and employers, on the other.77 These reports 

note that the multifariousness of the clean economy and its 

newness in some segments add to the usual challenges 

of securing suffi cient communication and coordination 

among stakeholders to link industries’ demands to the 

supply of workers. 

Along these lines, it is plain that the inconsistent 

availability of objective, timely data about the size and 

growth of regional clean economy clusters has complicated 

the design of smart, realistic training and economic 

development systems at the regional level. 

The strategy: Build the clean economy “bottom 

up,” region by region

And so a broad strategy for all parties must be to place 

regional growth strategies specifi cally near the center of 

efforts to advance the clean economy.

At the federal level, the growing recognition in Congress 

of the value of regional strategies and local innovation 

clusters—as evidenced by the inclusion of a new “regional 

innovation program” in last year’s America COMPETES 

reauthorization—encourages hopes that Congress will 

support increased investment in new regional innovation 

and industry cluster programs.

78 Competitive awards 

like the EDA’s i6 Green Challenge for the establishment or 

expansion of regional proof of concept centers in various 

green technology fi elds has the power to further catalyze 

the “bottom up” clean economy development work that has 

broken out in numerous regions. Scaling such offerings up 

would accelerate growth. Funding options, while complicated 

in the current budgetary environment, do exist as noted in 

the fi nancing discussion. 

Visualizing the Clean Economy: The Metropolitan Policy Program’s Interactive Mapping Tool 

Far more data underlies this study of the clean economy than can be conveyed in the pages of this report. Yet, one of 

the core goals of this undertaking has been to provide detailed, actionable data to national, and especially regional, 

actors who have mostly lacked such information on the size, shape, and nature of the clean economy in U.S. regions. To 

that end, the Metropolitan Policy Program at Brookings has developed an interactive web-based mapping and downloads 

tool designed to provide in-depth access to the Brookings-Battelle Clean Economy Database that provides the basis for 

the analyses in this report. 

Both map- and spreadsheet-oriented, the new tool allows users to visualize, or simply download data on, the 

geography of the clean economy at the state and metropolitan levels with an unprecedented richness of detail. Available 

on the site are jobs data—totals, shares, and growth—for the aggregate clean economy, fi ve broad clean economy 

categories, and 39 narrower industry segments. Among the many possibilities users of the tool can disaggregate and 

study clean economy segments of interest, see where particular segment specializations exist, or fi nd out where the 

clean economy is fastest growing (with the important 

caveat that the growth fi gures do not incorporate job 

losses from establishments that closed prior to 2010). 

Furthermore, the tool allows users to visualize the 

education profi le of the clean economy’s workforce as well 

as to probe wage characteristics, export orientations, and 

explore typical establishment ages. In all of this, the goal is 

to make the vast majority of the new information as widely 

available as possible while providing the greatest possible 

fl exibility to users in its output and display. To explore the 

online application please visit the Brookings site at: 

www.brookings.edu/metro/clean_economy/map.aspx
SIZING THE CLEAN ECONOMY | V. ADVANCING THE CLEAN ECONOMY 43

States, for their part, need to make regions and 

metropolitan areas central to clean economy growth 

strategies. State leaders need to understand and embrace 

the fact that the clean economy is signifi cantly region- and 

metro-led.79 What does that mean? By and large, it means 

that more states should empower regional clean economy 

cluster initiatives. States, to begin with, should work with 

the federal government and their regions—as many now 

are—to improve the information base about local industry 

clusters, with an emphasis on pulling together objective 

market analysis on their size, growth, market positioning, 

and challenges.80 Too little is as yet known about these 

industries at the crucial regional level, and that has impeded 

good strategymaking.

Beyond improving the data, states can also play a 

critical role in advancing U.S. clean economy growth by 

making sure their clean economy activities fi rmly support 

regionally crafted cluster strategies. One way states can 

achieve this is through the provision of dedicated, modestscaled resources—perhaps from state energy funds—to 

well-designed regional cluster initiatives.81 For example, 

New York state has since 2009 invested nearly $9 million 

in six regionally-based and -oriented cleantech incubators 

through its Clean Energy Business Incubator program. Yet 

specifi cally titled formal “cluster” programs are only part 

of the picture. Equal or more value may in fact come from 

swinging other, more generally relevant, programs behind 

the regions’ cluster strategies, whether it be related marketmaking procurement or utility initiatives; export promotion; 

particular fi nance interventions; various R&D, tech transfer, 

or other innovation initiatives; or workforce training policy. 

Such an alignment of multiple state activities with the needs 

of local clean economy clusters represents a low-profi le but 

essential element of fostering growth

All of which leads to the critical role of regional actors 

themselves in accelerating the emergence of a dynamic 

clean economy in America. At this level, the needed 

development work will frequently be facilitative and 

focused especially on analysis and coordination: identifying 

promising local clusters, identifying the constraints they 

face, and facilitating joint regional action to address them.82

The fi rst step for regions must be to use data and 

analysis to understand the local clean economy in detail. 

Currently, very few regions have access to the kind of 

rigorous, fi ne-grained information needed to make objective 

assessments about the nature, prospects, and needs of their 

local clean economies. Such data has simply not been widely 

available, given the diffi culties of defi ning the clean economy 

and then of collecting the relevant information across 

diverse industries. And yet such statistical intelligence is 

absolutely essential to allow regions to defi ne the terms; sort 

out fact from fi ction; and focus regional strategy on truly 

viable, distinctive, and competitive networks of fi rms and 

establishments. 

The data provided in this report, its appendices, and on 

an accompanying project website make a start. (See sidebar 

on visualizing the clean economy). Using this information, 

regions can obtain initial guidance on the relative size of 

their clean economy industry segments; the numbers of 

establishments and fi rms they contain; their growth; and 

their strength relative to those in other regions. In that way 

regions can begin to assemble what they in many cases do 

not have now: a basic empirical platform on which to base 

strategic clean economy development efforts. 

With such a basic platform in place, regions should move 

to rigorously identify clusters’ binding constraints and 

then move to formulate strong, “bottom up” action to 

address them. To the fi rst point, a top priority of regional 

cluster participants and intermediaries should be to tease 

out the specifi c hurdles to the further growth of an area’s 

most extensive, concentrated clusters. In this connection, 

rigorously identifying the most promising clusters on which 

to focus development efforts is part of the work but equal 

effort must drill down on isolating the specifi c impediments 

to future growth. 

Are there local procurement sources that have not been 

exploited that could drive growth? Are there regulatory 

impediments that are precluding the siting of critical capital 

Carving a Niche in the Clean Economy: The Puget Sound’s Regional Business Plan

One region that has taken bottom-up cluster development to a rigorous new level is the Puget Sound area, which 

has devised a hard-edged action plan to make itself a world center for a particular sub-area of the massive energy 

effi ciency (EE) industry. 

Working through a disciplined regional “business planning” process conducted in collaboration with the Metropolitan 

Policy Program at Brookings and RW Ventures LLC, Seattle’s move has been to employ detailed data and analysis to 

reveal and begin to seize on its strong positioning for exporting building systems software and technology to the world. 

The market opportunity is huge. McKinsey & Company estimates that $520 billion in investment is required to 

fully capitalize on the U.S. economy’s energy savings potential through 2020. HSBC projects that the global building 

effi ciency market will grow to $245 billion a year by then. Within this large market, the Puget Sound has targeted the 

building systems niche, which is projected to grow to $14 billion globally. In this niche, as it happens, the region already 

enjoys signifi cant competitive advantage, ranging from a world-class array of large and small software and IT fi rms 

(arrayed around Microsoft); a signifi cant EE consulting and services cluster anchored by McKinstry; a world-beating 

international business infrastructure; and the presence of progressive utilities and numerous military bases that are 

serving as early adopters for technology demonstration and deployment. 

And so the region has devised a catalytic, bottom-up strategy to achieve its goal of world export preeminence: the 

creation of the Building Energy Effi ciency Testing and Integration (BETI) Center and Demonstration Network. BETI will 

allow EE IT innovators in the region to test, integrate, and verify promising products and services before launching them 

to market, providing a potentially game-changing boost. BETI would be a self-fi nancing entity whose real-world facilities 

fi rms and entrepreneurs would pay to access and whose validation would become industry standard, establishing the 

region as a global EE IT hub. 

BETI’s ambition and grounding in rigorous market analytics are exemplary in their own right. Even more signifi cant, 

however, is what the region’s complete business planning effort represents: a region coming together, taking the initiative 

to fundamentally understand its economy, and acting intentionally on the fi ndings. While too many other states and 

regions fritter away money chasing the next hot cleantech fad, the Puget Sound is assiduously carving itself a niche in 

the next economy. 

Source: “Innovation Meets Demonstration: A Prospectus for Catalyzing Growth in the Puget Sound’s Energy Effi ciency Cluster” (Brookings Institution, 2011); 

and Puget Sound Regional Council and Prosperity Partnership, “Business Plan for BETI” (2011), available at www.psrc.org/econdev/beti. 
44 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM

investments? Do businesses in the cluster lack access to 

fi nancing owing, for example, to their distance from VC 

networks in Boston, New York, or Silicon Valley? 

Such a drill-down will require fi ne-grained, often 

qualitative but still precise local information, including 

proprietary company data, detailed survey information, 

real-time market intelligence, and other forms of fi rst-hand 

insight. For that reason such work to pinpoint local clusters’ 

binding constraints will always be an inherently regional 

responsibility.

Why is such work so important? Such work is important 

because it represents the essential basis for “bottom 

up” regional action to address cluster needs and seize 

opportunities. Such regional assertiveness is critical, 

meanwhile, because it represents the best available source 

of locally grounded, cluster-specifi c information, prioritysetting, and implementation.

And as it happens, numerous regions are engaged in this 

sort of disciplined, data-informed work to develop smart, 

place-specifi c development strategies. 

Industry and economic development leaders in the 

Puget Sound area, for example, have collaborated with 

the Brookings Institution and RW Ventures LLC to craft a 

regional “business plan” refl ecting that region’s specifi c 

clean economy specialties, with a view to strengthening the 

global positioning of the region’s EE technology cluster.83

(See sidebar on the previous page). Similarly, the Climate 

Prosperity Project, a non-profi t focused on the clean 

economy, has been working with four regions—San Jose, St. 

Louis, Denver, and Portland, OR—to develop locally tailored, 

empirically based clean economy “greenprints” to guide 

clean economy development in those metros.84 (For more 

on Climate Prosperity and on regional networking in the 

Sacramento region see sidebar above). And for that matter, 

some 15 regions are now working together to forge common 

cause as they develop clean energy “innovation consortium” 

initiatives aimed at addressing innovation pipeline gaps and 

accelerating regional cluster growth in areas ranging from 

New England and Michigan to San Diego. In these ways, 

U.S. regions are moving assertively to defi ne the needed 

interventions, implement them, and share their learning, 

whether through local initiative or through the targeting and 

tuning of various federal and state efforts.

Regional implementation steps can, should, and do 

vary widely. Backed by all kinds of entities, regional 

actions to advance the clean economy run the gamut of 

market-making, fi nance-oriented, innovation, and cluster 

development activities.85 On market-making, for example, 

Climate Prosperity’s efforts in Silicon Valley, Denver, 

Portland, OR, and St. Louis focus on expanding the demand 

for clean economy good and services by promoting use 

of local products, aggregating public procurement, and 

branding and marketing regional specializations.86 To 

address fi nance issues in its region, the Clean Tech Center 

at the Syracuse-based Tech Garden offers technical 

and fi nancial assistance—by facilitating access to angel 

investments and venture capital—to entrepreneurs and 

early stage companies to foster clean technology business 

development.87 In Wisconsin, meanwhile, the Milwaukee 

Water Council is working to catalyze water-tech innovation 

in a cluster that includes more than 100 scientists and 

130 water technology companies.88 And for that matter, 

CleanTECH San Diego in California, a non-profi t membership 

organization, has developed a comprehensive one-stop-shop 

to advance the region’s clean economy by helping companies 

coordinate with established research facilities to identify 

both synergies and gaps and network through an online 

registry of the region’s growing cluster of clean technology 

companies.89

Among all these activities two more stand out. Given the 

prominence regional leaders retain on land use, regional 

and local offi cials have special power to manage the zoning 

and permitting issues that can determine how quickly and 

where key clean economy infrastructure or installations are 

sited within the demographic and workforce contexts of their 

communities. 

Likewise, regional leaders’ sensitivity to local population 

and business dynamics argues that they should lead 

efforts to improve regional clean economy workforce 

development. And here, too, regional cluster knowledge and 

the collection of detailed cluster data allow for improved 

outcomes. Too often in U.S. regions workforce training for 

Metro ’Greenprints’ in Four Metropolitan Areas: The Climate Prosperity Network

Four very different metro regions—Silicon Valley, Denver, Portland, OR, and St. Louis—are pursuing assertive, 

bottom-up regional development strategies to move to a carbon-free future. These metros are partners in the 

Climate Prosperity Network, a national coalition of regions that share a common belief that they can simultaneously 

expand economic opportunities and reduce greenhouse gas emissions through practical strategies involving business, 

government, education, and other community partners. 

Established in 2009, the network fosters the development of tailored “climate prosperity” strategies within 

the context of a shared commitment to the use of good economic information to identify regions’ clean industry 

specializations; an effective collaborative process that focuses diverse partners on a few major strategic priorities; and 

visionary leadership—particularly from the business community. 

Along these lines, while each region seeks to hone its unique comparative advantages, each is employing a common 

analytic framework that focuses on expanding market demand for clean economy products and services, as well as 

building the regional base of clean economy companies. The four metro areas are pursuing common market and business 

development strategies—including promoting use of local products, aggregating public procurement, branding and 

marketing regional specializations, expanding clean economy fi nancing, growing regional supply chains, training a skilled 

workforce, and promoting commercialization, innovation, and entrepreneurship. They have also published strategies 

(“Greenprints”) and established outcome metrics to track regional progress.

And yet, notwithstanding the common analytic framework, each region’s greenprint capitalizes on its unique strengths 

and priorities. Silicon Valley is engaged in accelerating the “third revolution” clean technologies—with focus on renewable 

energy—by standardizing procurement and permitting for solar projects and promoting smart grid infrastructure. Metro 

Denver represents an integrated economic development strategy encompassing education and marketing of green 

products and services, building and documenting the cleantech value chain, and leveraging and commercializing the 

region’s R&D assets. Metro Portland is using the greenprint process as a “call to action” to aggressively move itself along 

the clean economy pathway by expanding project fi nance, commercializing green technologies, cultivating the cleantech, 

sustainable forestry and agriculture clusters, and developing a skilled workforce. And St. Louis' fi rst step in the process 

of developing its strategy has been to conduct a Green Economic Profi le study that provides detailed metrics on the 

region’s green economy.

Source: Climate Prosperity Network website; e-mail correspondence with Andre Pettigrew, Climate Prosperity Project Inc. 
SIZING THE CLEAN ECONOMY | V. ADVANCING THE CLEAN ECONOMY 45

so-called “green jobs” (as well as other occupations) has 

proceeded on its own track, aspirational about what job 

placements training might yield and divorced from the latest 

market trends and real industry demand in local places.90

The result has been disturbing shortages and surpluses 

of particular types of workers. However, the availability of 

improved data and more assertive cluster initiatives points 

to a better way—and one of the most important future 

roles of metropolitan and rural regions in advancing the 

clean economy. Along these lines, the use of fi ne-grained 

segment data and better communication in the design and 

management of worker training efforts should make possible 

a much more accurate tuning of training efforts to true 

private sector needs—and better connection of workers to 

opportunities. Proving that it can be done, some community 

colleges and other regional intermediary organizations 

have successfully linked training to cluster-specifi c industry 

needs with considerable success. For instance, the Los 

Angeles Trade-Technical College grounds all of its work on 

“green jobs” with careful research and industry engagement 

to inventory “real” employment opportunities and future 

demand.91 Likewise, the Workforce Development Council 

of Seattle/King County (WDC) has gone to great lengths 

to aligning its workforce development efforts with private 

sector needs. First, the WDC convened an industry panel to 

explore market dynamics and employer needs in the area 

of green design and construction. Then the WDC partnered 

with the City of Seattle and other organizations to launch a 

new industry-led project to understand and meet employer 

needs in the residential and commercial building energy 

effi ciency sectors.92

 

* * *

The takeaway is clear: While private enterprise ultimately 

will deliver a robust clean economy, federal, state, and local 

governments all have roles to play in co-producing a clear, 

supportive, and stable growth environment for it.

In that role, government must work to structure a vibrant 

domestic market, ensure the availability of fi nance, and keep 

the innovation pipeline charged. Throughout, regions and 

clean economy industry clusters must move to the center of 

development efforts.

Ultimately, by pursuing this course, the nation can and 

will build the domestic clean economy, fi rm by fi rm, and 

region by region. ●

Advancing the Clean Economy in California’s Capital Region: 

Sacramento’s Clean Technology Story 

Regional networking—and using it to devise a regional investment strategy—has brought new focus to the Sacramento 

region’s efforts to become a hub for clean energy technology. Leading the way has been the Green Capital Alliance 

(GCA). The GCA unites public and private partners, including the regional economic development organizations, 

workforce development organizations, non-profi ts, the regional council of governments, and academic institutions, in 

common cause to make clean technology a defi ning feature of Sacramento region’s economy.

GCA is working to develop an investment strategy for the clean energy sector that will become the central plan 

guiding the clean energy-related work of its partners. As part of that, GCA holds Clean Energy Technology (CET) Business 

Roundtables to assess opportunities in the cleantech industry, stay in tune with market realities, and make sure regional 

education and workforce training programs meet the industry’s needs. The roundtables are also helping shape the 

high-level strategies emerging from Mayor Kevin Johnson’s “Greenwise Sacramento” initiative, which aims to transform 

Sacramento into the greenest region in the country. 

Sacramento has enjoyed considerable success of late in securing state and federal investment, which leaders credit 

in part to its now renowned collaborative approach and ability to articulate a clear regional vision. The region has 

also witnessed signifi cant private investment, with the Bank of America playing a pivotal role in GCA’s CET Business 

Roundtables by providing fi nancial insight into the region’s clean technology cluster expansion. The Sacramento Area 

Regional Technology Alliance (SARTA) has been chosen as one of the state’s six Innovation Hubs (iHubs) with an 

emphasis on clean technologies. Meanwhile, University of California, Davis—a GCA partner and home to the nation’s 

fi rst university-based Energy Effi ciency Center—supports the region’s commercialization of clean energy through major 

research initiatives in lighting and cooling effi ciency, clean transportation, and renewable energy.

The region’s efforts are already producing signifi cant results. The clean economy in the Sacramento-Arden-ArcadeRoseville metro area grew 59 percent from 2003 to 2010. Although much of this growth was driven by large state 

agencies, the presence of the electric vehicle technologies, solar thermal, and solar photovoltaic segments increased 

markedly and signals a building out of Sacramento’s cleantech economy that is gaining momentum. 

Sources: Green Capital Alliance website; Sacramento Area Commerce & Trade Organization website.

While private enterprise ultimately will deliver 

a robust clean economy, federal, state, and 

local governments all have roles to play

in co-producing a clear, supportive, and stable 

growth environment for it.
46 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM
VI

SIZING THE CLEAN ECONOMY | VI. CONCLUSION 47

CONCLUSION

In many respects, the analysis warrants optimism.

As the nation continues to search for new sources 

of high-quality growth, the present fi ndings depict a sizable 

and diverse array of industry segments—in key privatesector areas—expanding rapidly at a time of sluggish 

national growth.

Already the aggregate clean economy employs 

more people than the fossil fuels and biotech industries. 

More importantly, a dozen or so “hot” segments—mostly 

dynamic renewable energy categories like wind energy, 

solar photovoltaic, and smart grid—doubled and tripled 

in size in the last decade, answering the hype that has 

surrounded them despite extremely diffi cult recent market 

and fi nance conditions.

What is more, the analysis suggests that the clean 

economy is producing jobs relevant to the nation’s need to 

renew its economic base. Clean economy jobs are inordinately 

oriented toward manufacturing and exporting. Likewise, the 

segments of the clean economy encompass a balanced array 

of jobs and occupations, with substantially more opportunities 

and better pay for lower-skilled workers along with other 

positions in higher-end “innovation” fi elds. Having more 

clean economy jobs as the sector’s younger, more innovative 

segments advance in technology, deployment, and marketpenetration would be good for the nation.

Yet, the information here also underscores several 

challenges. 

For one thing, the data counsel against excessive hopes 

for large-scale, near-term job-creation from the sector. After 

all, the U.S. clean economy remains small where it is fastgrowing and relatively slow-growing on balance, as defi ned 

here. That means that while key clean economy growth 

segments appear of critical importance to America’s future, 

their status as major employers remains a few years off.

Beyond that, what is more concerning about the future 

outlook is that the growth of the clean economy has almost 

certainly been depressed in recent years by signifi cant policy 

problems and uncertainties.

America, its industries, and its regions are in many places 

making solid progress on clean economy development, 

especially at the early-stages of the technology commercialization pathway, where new ideas, business plans, and fi rms 

come into being. However, much evidence suggests that 

the scale-up of these ideas has not been maximized, due in 

part to policies that have left domestic demand weaker than 

it might be, fi nancing harder to obtain, and the innovation 

pipeline unsecured for the future, even as too little attention 

is paid to the regional underpinnings of growth. 

In that sense, what is most challenging here is the 

fundamental question raised by the dynamic growth but 

modest size of the most vibrant and promising segments of 

the clean economy. 

That question is: Will the nation marshal the will to make 

the most of those industries?

In the end, it is a question raised frequently by these 

pages. ●

The measurements and trends reviewed here 

offer an encouraging but also challenging assessment of the ongoing development of the clean 

economy in the United States and its regions.
48 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM

APPENDIX Appendix A. The U.S. Clean Economy by Category and Segment Share of Annual jobs held Share Share of average Clean Median by workers of jobs traded sector change economy age of with a jobs that establishments in jobs, share of all establishment Exports high school are green Average that are Jobs, Jobs, 2003–2010 U.S. jobs, (in years) per job, diploma or collar, annual clustered, Category/Segment 2003 2010 (%) 2010 (%) 2010 2009 less, 2010 (%) 2010 (%) wage, 2009 2010 (%) Agricultural and Natural Resources Conservation 374,120 505,993 4.4 0.4 15 $13,239 39.4 58.5 $42,721 10.5 Conservation 193,836 314,983 7.2 0.2 14 $466 27.1 50.6 $47,121 8.0 Organic Food and Farming 114,931 129,956 1.8 0.1 23 $29,677 59.5 65.1 $35,946 17.9 Sustainable Forestry Products 65,353 61,054 -1.0 0.0 18 $44,146 60.1 83.7 $34,442 6.2 Education and Compliance 95,064 142,156 5.9 0.1 15 $233 29.0 59.1 $45,865 18.6

 Regulation and Compliance 95,064 141,890 5.9 0.1 15 $232 29.0 59.1 $45,879 19.8 Training 0 266 N/A 0.0 21 $768 40.2 50.3 $38,345 7.0Energy and Resource Effi ciency 675,391 830,146 3.0 0.6 16 $21,167 49.3 75.0 $38,073 11.3

 Appliances 45,671 36,608 -3.1 0.0 21 $56,838 54.0 77.8 $37,980 8.3 Battery Technologies 14,605 16,129 1.4 0.0 8 $81,867 44.9 64.0 $43,011 13.1 Electric Vehicle Technologies 10,264 15,711 6.3 0.0 8.5 $124,825 53.7 78.1 $38,324 18.2 Energy-saving Building Materials 135,911 161,896 2.5 0.1 17 $20,788 58.7 81.6 $36,786 3.4 Energy-saving Consumer Products 23,615 19,210 -2.9 0.0 17 $56,040 49.2 71.4 $40,725 16.9 Fuel Cells 3,542 7,041 10.3 0.0 10 $74,746 33.9 46.1 $50,287 29.6 Green Architecture and Construction Services 36,512 56,190 6.4 0.0 21 $4,908 26.0 32.9 $56,487 32.7 HVAC and Building Control Systems 58,654 73,600 3.3 0.1 17 $46,776 45.0 65.2 $42,806 8.3 Lighting 16,269 14,298 -1.8 0.0 18 $47,922 49.6 71.4 $39,469 24.2 Professional Energy Services 31,161 49,863 6.9 0.0 9 $30,207 20.5 26.2 $56,063 21.8 Public Mass Transit 267,946 350,547 3.9 0.3 21 $53 54.4 90.3 $30,947 11.8 Smart Grid 8,986 15,987 8.6 0.0 10.5 $35,108 33.4 48.2 $48,758 12.8 Water Effi cient Products 22,255 13,066 -7.3 0.0 18 $57,487 50.2 72.9 $39,479 17.2
SIZING THE CLEAN ECONOMY | APPENDIX 49

Appendix A. The U.S. Clean Economy by Category and Segment (continued)  Share of Annual jobs held Share Share of average Clean Median by workers of jobs traded sector change economy age of with a jobs that establishments in jobs, share of all establishment Exports high school are green Average that are Jobs, Jobs, 2003–2010 U.S. jobs, (in years) per job, diploma or collar, annual clustered,Category/Segment 2003 2010 (%) 2010 (%) 2010 2009 less, 2010 (%) 2010 (%) wage, 2009 2010 (%) Greenhouse Gas Reduction, Environmental Management, and Recycling 854,247 1,058,886 3.1 0.8 16 $19,432 45.5 69.6 $40,644 10.3 Air and Water Purifi cation Technologies 18,072 24,930 4.7 0.0 17 $63,028 47.6 67.9 $39,136 19.6 Carbon Storage and Management 163 391 13.3 0.0 8 $25,678 38.4 55.3 $47,462 14.3 Green Building Materials 69,496 76,577 1.4 0.1 20.5 $32,714 61.1 85.3 $34,191 13.4 Green Chemical Products 28,795 22,622 -3.4 0.0 18 $178,861 48.9 72.8 $39,061 8.1 Green Consumer Products 77,032 77,264 0.0 0.1 18 $48,205 55.4 78.9 $36,069 19.1 Nuclear Energy 66,936 74,749 1.6 0.1 16 $10,733 36.7 66.0 $45,843 12.6 Pollution Reduction 11,024 9,986 -1.4 0.0 18 $27,431 31.0 41.4 $48,133 16.0 Professional Environmental Services 89,253 141,046 6.8 0.1 14 $16,104 20.2 26.7 $55,235 15.7 Recycled-Content Products 56,475 59,712 0.8 0.0 18 $62,637 58.1 85.0 $35,316 11.4 Recycling and Reuse 89,584 129,252 5.4 0.1 17 $1,805 51.3 75.4 $36,463 10.0 Remediation 40,702 56,241 4.7 0.0 14 $1,316 52.9 78.7 $40,101 9.2 Waste Management and Treatment 306,715 386,116 3.3 0.3 16 $3,428 46.6 76.4 $38,795 6.3Renewable Energy 111,386 138,364 3.1 0.1 6 $64,884 43.3 69.4 $43,070 14.6 Biofuels/Biomass 11,384 20,680 8.9 0.0 6 $189,088 45.3 67.1 $41,010 7.9 Geothermal 1,722 2,720 6.7 0.0 12 $8,131 46.8 73.6 $42,772 17.1 Hydropower 71,625 55,467 -3.6 0.0 20 $300 37.5 68.8 $45,226 10.0 Renewable Energy Services 1,294 1,981 6.3 0.0 8 $17,650 40.5 63.6 $46,884 19.6 Solar Photovoltaic 11,866 24,152 10.7 0.0 5 $80,464 45.0 66.7 $43,858 29.4 Solar Thermal 1,647 5,379 18.4 0.0 9 $36,801 53.3 70.8 $35,652 19.6 Waste-to-Energy 2,566 3,320 3.7 0.0 20 $513 49.4 76.6 $40,466 25.9 Wave/Ocean Power 98 371 20.9 0.0 4.5 $11,291 19.6 23.0 $59,368 20.0 Wind 9,184 24,294 14.9 0.0 6 $117,164 49.8 75.1 $40,588 12.0Aggregate Clean Economy 2,110,208 2,675,545 3.4 2.0 15 $20,129 44.6 68.7 $43,773 10.9Source: Brookings-Battelle Clean Economy Database; exports: Brookings analysis of U.S. International Trade Commission, Bureau of Economic Analysis, Internal Revenue Service, Institute of International Education, and Moody’s Analytics data; educational attainment: U.S. Bureau of Labor Statistics Employment Projections Program; green collar jobs: U.S. Bureau of Labor Statistics Occupational Employment Statistics and Employment Projections Program; wages: U.S. Bureau of Labor Statistics Occupational Employment Statistics; clusters: Brookings analysis (see external methods appendix for details). 
50 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM Appendix B. The Aggregate Clean Economy by State Share of Annual jobs held Share Share of average Clean Median by workers of jobs traded sector change economy age of with a jobs that establishments in jobs, share of all establishment Exports high school are green Average that are Jobs, Jobs, 2003–2010 state jobs, (in years) per job, diploma or collar, annual clustered, State 2003 2010 (%) 2010 (%) 2010 2009 less, 2010 (%) 2010 (%) wage, 2009 2010 (%) Alabama 32,592 38,182 2.3 1.9 14 $23,684 47.7 72.8 $36,260 1.6 Alaska 8,439 16,682 10.2 4.7 12 $2,294 33.2 56.5 $48,778 1.3 Arizona 29,896 37,257 3.2 1.5 14 $13,504 43.6 68.2 $38,831 14.1 Arkansas 27,920 32,450 2.2 2.6 15 $42,450 49.9 73.7 $32,116 6.6 California 239,064 318,156 4.2 2.1 16 $16,314 43.1 64.2 $46,400 41.0 Colorado 34,787 51,036 5.6 2.2 14 $23,165 38.2 59.7 $45,973 5.5 Connecticut 22,541 29,751 4.0 1.8 16 $11,793 42.5 67.6 $45,802 8.7 Delaware 4,873 6,917 5.1 1.6 15 $13,830 38.7 57.6 $46,607 5.5 District of Columbia 20,302 22,462 1.5 3.1 14 $2,454 38.4 65.4 $52,608 37.5 Florida 74,669 102,967 4.7 1.4 13 $9,386 41.5 65.6 $38,085 2.1 Georgia 64,709 83,707 3.7 2.1 13 $20,216 48.1 72.3 $36,764 10.6 Hawaii 7,144 11,113 6.5 1.7 13 $4,913 42.0 66.1 $42,235 4.7 Idaho 12,992 17,543 4.4 2.7 15 $10,514 42.3 65.2 $36,359 0.7 Illinois 86,084 106,375 3.1 1.8 17 $25,917 45.5 70.7 $41,357 22.4 Indiana 48,352 53,684 1.5 1.9 16 $29,777 48.2 73.0 $37,162 5.5

Iowa 24,574 30,835 3.3 2.0 17 $44,942 51.4 77.0 $35,237 0.8Kansas 22,179 27,199 3.0 1.9 16 $26,853 43.2 65.4 $38,733 2.0Kentucky 32,011 36,963 2.1 1.9 16 $39,948 48.1 72.8 $35,585 3.5Louisiana 28,468 28,673 0.1 1.5 15 $19,443 45.2 70.3 $36,493 2.3Maine 9,298 12,212 4.0 2.0 18 $14,158 44.1 69.3 $36,460 0.8Maryland 34,837 43,207 3.1 1.7 15 $9,143 41.3 65.2 $44,790 0.3Massachusetts 50,598 63,523 3.3 2.0 17 $16,166 42.4 65.4 $47,815 23.1Michigan 78,537 76,941 -0.3 1.9 17 $26,589 48.6 73.3 $40,558 5.3Minnesota 41,752 58,232 4.9 2.1 16 $21,868 46.7 70.7 $41,240 10.3Mississippi 17,730 20,905 2.4 1.8 13 $25,010 50.2 75.1 $31,053 3.5Missouri 36,496 43,736 2.6 1.6 15 $27,868 44.7 69.4 $38,401 5.4Montana 11,850 14,235 2.7 3.1 15 $8,970 33.3 54.0 $37,860 0.0Nebraska 10,286 15,311 5.8 1.5 18 $20,940 45.1 67.6 $36,323 5.8Nevada 11,167 16,578 5.8 1.5 13 $7,872 39.4 60.3 $44,545 10.9New Hampshire 8,971 12,886 5.3 2.0 16.5 $14,449 42.8 67.6 $40,773 0.8New Jersey 68,127 94,241 4.7 2.4 18 $13,639 45.8 72.6 $43,809 4.3New Mexico 11,818 17,725 6.0 2.1 14 $10,380 37.5 61.6 $39,327 4.2New York 124,848 185,038 5.8 2.1 18 $13,149 44.6 71.6 $44,056 10.2
SIZING THE CLEAN ECONOMY | APPENDIX 51

Appendix B. The Aggregate Clean Economy by State (continued)

 Share of Annual jobs held Share Share of average Clean Median by workers of jobs traded sector change economy age of with a jobs that establishments in jobs, share of all establishment Exports high school are green Average that are Jobs, Jobs, 2003–2010 state jobs, (in years) per job, diploma or collar, annual clustered,State 2003 2010 (%) 2010 (%) 2010 2009 less, 2010 (%) 2010 (%) wage, 2009 2010 (%) North Carolina 52,780 78,881 5.9 1.9 14 $25,774 45.7 70.3 $37,348 9.1North Dakota 4,537 7,146 6.7 1.7 14 $61,299 47.0 72.4 $35,547 2.7Ohio 88,513 105,306 2.5 2.0 17 $25,067 45.5 69.9 $39,275 5.1Oklahoma 13,903 19,297 4.8 1.2 16 $10,491 43.6 71.0 $33,673 0.0Oregon 50,482 58,735 2.2 3.4 18 $13,484 46.0 68.2 $40,072 6.0Pennsylvania 99,334 118,686 2.6 2.1 17 $15,709 46.0 71.7 $39,266 10.4Rhode Island 9,017 9,563 0.8 2.0 14.5 $32,274 45.0 68.9 $41,442 0.0South Carolina 46,659 50,424 1.1 2.7 15 $38,172 47.0 71.5 $36,373 1.3South Dakota 5,459 6,659 2.9 1.5 15 $42,092 42.7 69.2 $33,880 0.0Tennessee 58,456 76,031 3.8 2.8 13 $50,939 42.8 65.5 $37,347 3.4Texas 115,194 144,081 3.2 1.3 13 $16,703 45.0 68.7 $37,926 28.2Utah 14,312 18,261 3.5 1.5 14 $10,699 45.2 70.3 $36,637 3.6Vermont 8,295 9,425 1.8 3.0 15 $22,377 48.2 71.5 $37,681 0.0Virginia 48,423 66,772 4.7 1.7 14 $11,034 40.6 65.8 $43,400 11.4Washington 69,106 83,676 2.8 2.8 16 $14,363 44.0 64.9 $46,457 26.0West Virginia 10,587 12,659 2.6 1.6 17 $12,835 44.0 70.5 $33,805 0.0Wisconsin 73,093 76,858 0.7 2.7 18 $27,674 50.2 75.3 $37,931 7.5Wyoming 4,147 6,363 6.3 2.1 14 $5,612 33.3 57.1 $41,603 0.0United States 2,110,208 2,675,545 3.4 2.0 15 $20,129 44.6 68.7 $43,773 14.2Source: Brookings-Battelle Clean Economy Database; exports: Brookings analysis of U.S. International Trade Commission, Bureau of Economic Analysis, Internal Revenue Service, Institute of International Education, and Moody's Analytics data; educational attainment: U.S. Bureau of Labor Statistics Employment Projections Program; green collar jobs: U.S. Bureau of Labor Statistics Occupational Employment Statistics and Employment Projections Program; wages: U.S. Bureau of Labor Statistics Occupational Employment Statistics; clusters: Brookings analysis (see methods external appendix for details). *State and metro clustering fi gures exclude non-exporting segments, defi ned as those with less than $4000 in exports per job. This is why the clustering fi gure for the United States seen here does not match the fi gure in Appendix A. 
52 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM Appendix C. The Aggregate Clean Economy in the 100 Largest Metropolitan Areas Share of Annual jobs held Share Share of average Clean Median by workers of jobs traded sector change economy age of with a jobs that establishments in jobs, share of all establishment Exports high school are green Average that are Jobs, Jobs, 2003–2010 metro jobs, (in years) per job, diploma or collar, annual clustered, Metropolitan Area 2003 2010 (%) 2010 (%) 2010 2009 less, 2010 (%) 2010 (%) wage, 2009 2010 (%) Akron, OH 4,355 5,445 3.2 1.7 16 $11,788 46.4 72.9 $38,120 0.0 Albany-Schenectady-Troy, NY 15,557 28,087 8.8 6.3 15.5 $44,114 34.3 56.6 $48,087 9.1 Albuquerque, NM 5,851 9,912 7.8 2.6 16 $14,180 38.1 61.8 $40,145 6.9 Allentown-Bethlehem-Easton, PA-NJ 5,509 6,770 3.0 2.0 18 $11,992 47.0 74.4 $37,766 0.0 Atlanta-Sandy Springs-Marietta, GA 28,922 43,060 5.9 1.9 12 $15,089 43.2 66.3 $40,602 8.6 Augusta-Richmond County, GA-SC 9,110 6,106 -5.6 2.7 16 $9,331 50.5 77.9 $37,758 0.0 Austin-Round Rock-San Marcos, TX 10,107 14,554 5.3 1.9 12 $10,414 38.9 65.3 $40,441 1.2 Bakersfi eld-Delano, CA 2,536 3,097 2.9 1.1 18 $6,226 47.1 65.6 $44,005 0.0 Baltimore-Towson, MD 18,927 22,619 2.6 1.7 16 $6,869 40.7 64.1 $44,569 0.5 Baton Rouge, LA 6,695 8,167 2.9 2.2 14 $29,918 40.2 63.0 $39,427 7.4 Birmingham-Hoover, AL 5,296 8,317 6.7 1.7 13 $16,609 47.8 71.0 $37,655 2.6 Boise City-Nampa, ID 5,433 7,456 4.6 2.8 17 $16,815 44.7 69.4 $36,139 1.6 Boston-Cambridge-Quincy, MA-NH 34,032 41,825 3.0 1.7 17 $17,184 42.6 63.8 $51,271 28.9 Bridgeport-Stamford-Norwalk, CT 5,196 6,266 2.7 1.5 19 $16,142 47.6 73.8 $44,251 4.7 Buffalo-Niagara Falls, NY 13,952 14,452 0.5 2.7 16 $5,831 46.8 73.9 $38,017 0.0 Cape Coral-Fort Myers, FL 1,496 2,235 5.9 1.1 10 $23,291 43.1 65.3 $37,131 0.0 Charleston-North Charleston-Summerville, SC 3,014 4,369 5.4 1.5 15 $34,605 45.1 67.8 $37,534 2.3 Charlotte-Gastonia-Rock Hill, NC-SC 11,217 15,485 4.7 1.9 13 $21,303 45.0 69.9 $40,858 10.1

Chattanooga, TN-GA 5,654 6,688 2.4 2.9 11.5 $18,776 49.4 75.8 $35,000 2.4Chicago-Joliet-Naperville, IL-IN-WI 61,659 79,388 3.7 1.8 16 $25,002 45.3 70.1 $42,816 28.3Cincinnati-Middletown, OH-KY-IN 14,804 18,525 3.3 1.9 16 $29,922 47.9 74.9 $37,991 2.6Cleveland-Elyria-Mentor, OH 18,224 24,664 4.4 2.5 18 $33,682 48.1 74.2 $39,213 8.0Colorado Springs, CO 1,287 1,934 6.0 0.7 16 $2,770 50.3 75.6 $37,605 0.0Columbia, SC 8,099 8,568 0.8 2.4 16 $5,779 38.5 62.5 $38,621 0.0Columbus, OH 11,231 15,498 4.7 1.7 18 $22,935 40.0 64.3 $42,340 10.3Dallas-Fort Worth-Arlington, TX 30,658 38,562 3.3 1.3 14 $23,416 46.3 69.1 $40,105 28.1Dayton, OH 4,263 6,232 5.6 1.6 16 $20,193 49.0 76.8 $37,574 0.0Denver-Aurora-Broomfi eld, CO 20,214 27,929 4.7 2.3 13 $14,279 36.5 59.9 $47,602 8.0Des Moines-West Des Moines, IA 2,472 5,256 11.4 1.6 15 $9,683 40.9 69.9 $38,671 0.0Detroit-Warren-Livonia, MI 14,741 20,323 4.7 1.2 17 $21,218 45.0 69.2 $45,642 4.1El Paso, TX 2,570 2,695 0.7 0.9 12.5 $13,915 46.7 72.2 $29,828 0.0Fresno, CA 8,308 9,301 1.6 2.8 18 $12,041 47.8 65.0 $38,031 51.1Grand Rapids-Wyoming, MI 17,232 8,812 -9.1 2.4 18 $39,631 52.4 74.4 $38,203 13.0Greensboro-High Point, NC 5,086 5,725 1.7 1.7 15 $23,679 50.8 73.9 $35,381 7.6Greenville-Mauldin-Easley, SC 7,247 10,127 4.9 3.4 14 $86,143 46.0 68.3 $38,193 1.7Harrisburg-Carlisle, PA 9,091 13,025 5.3 4.0 12 $19,621 34.0 62.7 $43,224 0.0Hartford-West Hartford-East Hartford, CT 8,812 13,712 6.5 2.2 14 $8,016 37.1 61.1 $48,757 10.8Honolulu, HI 6,270 9,269 5.7 1.9 12.5 $5,161 42.7 68.1 $42,140 6.8Houston-Sugar Land-Baytown, TX 27,855 39,986 5.3 1.6 13 $16,926 41.9 63.1 $42,779 74.0
SIZING THE CLEAN ECONOMY | APPENDIX 53

Appendix C. The Aggregate Clean Economy in the 100 Largest Metropolitan Areas (continued) Share of Annual jobs held Share  average Clean Median by workers of jobs Share of change economy age of with a jobs that establishments in jobs, share of all establishment Exports high school are green Average that are Jobs, Jobs, 2003–2010 metro jobs, (in years) per job, diploma or collar, annual clustered,Metropolitan Area 2003 2010 (%) 2010 (%) 2010 2009 less, 2010 (%) 2010 (%) wage, 2009 2010 (%) Indianapolis-Carmel, IN 13,574 15,183 1.6 1.7 15.5 $9,362 37.4 61.5 $41,245 0.0Jackson, MS 3,370 4,298 3.5 1.7 14 $7,304 43.8 69.5 $32,888 0.0Jacksonville, FL 5,940 7,679 3.7 1.3 13 $13,928 47.0 68.7 $37,040 4.2Kansas City, MO-KS 19,832 25,039 3.4 2.5 18 $15,879 41.5 62.9 $42,870 6.8Knoxville, TN 6,206 16,135 14.6 4.9 11 $20,107 28.1 37.7 $45,184 2.6Lakeland-Winter Haven, FL 1,985 2,290 2.1 1.1 13 $25,218 48.8 71.9 $34,981 0.0Las Vegas-Paradise, NV 6,672 9,797 5.6 1.2 9 $5,937 38.0 57.6 $46,590 13.8Little Rock-North Little Rock-Conway, AR 5,916 11,934 10.5 3.4 14.5 $57,514 47.7 72.1 $33,857 13.2Los Angeles-Long Beach-Santa Ana, CA 62,807 89,592 5.2 1.7 16 $18,449 46.7 70.9 $40,910 72.8Louisville-Jefferson County, KY-IN 12,779 14,447 1.8 2.4 17 $36,817 51.5 76.1 $37,317 5.1Madison, WI 9,215 12,337 4.3 3.5 17 $16,544 39.4 64.8 $43,466 12.2McAllen-Edinburg-Mission, TX 1,243 2,203 8.5 1.0 11 $5,759 49.5 70.6 $27,981 0.0Memphis, TN-MS-AR 8,719 11,515 4.1 1.9 13 $40,621 49.5 74.6 $36,138 7.5Miami-Fort Lauderdale-Pompano Beach, FL 19,688 24,194 3.0 1.1 12 $9,155 42.2 66.6 $38,500 6.7Milwaukee-Waukesha-West Allis, WI 13,516 13,471 0.0 1.6 19 $29,252 48.1 71.9 $41,031 3.9Minneapolis-St. Paul-Bloomington, MN-WI 26,519 37,750 5.2 2.2 17 $15,608 45.0 69.5 $44,388 15.8Modesto, CA 2,974 2,688 -1.4 1.7 18 $10,017 53.9 61.4 $39,279 0.0Nashville-Davidson--Murfreesboro--Franklin, TN 11,211 17,913 6.9 2.4 13 $17,026 41.3 67.9 $37,705 0.0New Haven-Milford, CT 4,711 5,636 2.6 1.6 19 $17,974 47.4 72.2 $42,985 13.8New Orleans-Metairie-Kenner, LA 8,385 7,298 -2.0 1.4 15 $5,604 43.5 70.9 $38,183 0.0New York-Northern New Jersey-Long Island, NY-NJ-PA 104,185 152,034 5.5 1.8 18 $10,251 47.0 74.4 $45,586 10.8North Port-Bradenton-Sarasota, FL 2,095 2,409 2.0 1.0 14 $22,719 45.7 70.9 $36,499 0.0Ogden-Clearfi eld, UT 1,184 2,111 8.6 1.0 13 $4,657 40.7 62.3 $39,615 0.0Oklahoma City, OK 4,835 6,854 5.1 1.2 17 $6,716 40.5 67.2 $35,559 0.0Omaha-Council Bluffs, NE-IA 4,954 7,406 5.9 1.6 18 $11,663 45.0 67.8 $38,057 10.4Orlando-Kissimmee-Sanford, FL 7,132 11,033 6.4 1.1 14 $11,654 45.3 69.7 $36,408 0.0Oxnard-Thousand Oaks-Ventura, CA 4,344 5,246 2.7 1.7 18 $21,007 46.6 59.8 $44,449 14.3Palm Bay-Melbourne-Titusville, FL 6,204 3,446 -8.1 1.7 14 $5,568 42.8 71.0 $37,931 0.0Philadelphia-Camden-Wilmington, PA-NJ-DE-MD 47,752 54,325 1.9 2.0 17 $15,693 45.5 70.3 $43,913 7.6Phoenix-Mesa-Glendale, AZ 18,814 22,904 2.9 1.3 13 $14,390 45.1 71.1 $38,980 18.6Pittsburgh, PA 17,025 21,963 3.7 1.9 17 $13,257 46.7 71.9 $37,906 35.9Portland-South Portland-Biddeford, ME 2,692 3,591 4.2 1.3 18 $12,662 46.8 69.8 $37,612 0.0Portland-Vancouver-Hillsboro, OR-WA 20,792 27,489 4.1 2.7 18 $13,952 45.0 69.0 $42,548 7.5Poughkeepsie-Newburgh-Middletown, NY 2,139 2,951 4.7 1.1 17 $6,096 46.0 70.2 $41,635 0.0Providence-New Bedford-Fall River, RI-MA 11,709 12,904 1.4 1.9 14 $24,971 46.2 71.1 $40,036 0.0Provo-Orem, UT 1,406 1,587 1.7 0.8 14.5 $18,767 43.4 66.7 $33,374 0.0Raleigh-Cary, NC 6,788 16,677 13.7 3.3 13 $5,867 37.0 64.0 $40,795 21.9Richmond, VA 7,723 10,630 4.7 1.7 15 $20,896 45.1 72.8 $40,365 2.6
54 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM Appendix C. The Aggregate Clean Economy in the 100 Largest Metropolitan Areas (continued) Share of Annual jobs held Share Share of average Clean Median by workers of jobs traded sector change economy age of with a jobs that establishments in jobs, share of all establishment Exports high school are green Average that are Jobs, Jobs, 2003–2010 metro jobs, (in years) per job, diploma or collar, annual clustered, Metropolitan Area 2003 2010 (%) 2010 (%) 2010 2009 less, 2010 (%) 2010 (%) wage, 2009 2010 (%) Riverside-San Bernardino-Ontario, CA 17,172 22,532 4.0 1.9 16 $14,924 45.3 65.2 $41,248 15.1 Rochester, NY 7,061 8,385 2.5 1.6 15 $17,289 50.1 75.3 $36,699 0.0 Sacramento--Arden-Arcade--Roseville, CA 23,462 37,319 6.9 4.5 14 $4,975 34.4 62.0 $49,589 34.7 Salt Lake City, UT 7,412 10,539 5.2 1.7 15.5 $13,374 47.6 75.3 $36,251 6.5 San Antonio-New Braunfels, TX 7,938 10,634 4.3 1.2 14 $6,764 47.1 72.4 $34,195 0.0 San Diego-Carlsbad-San Marcos, CA 14,337 22,862 6.9 1.7 15 $17,114 43.3 66.0 $45,016 56.5 San Francisco-Oakland-Fremont, CA 36,027 51,811 5.3 2.7 15 $20,705 37.1 54.7 $59,856 23.3 San Jose-Sunnyvale-Santa Clara, CA 19,360 18,868 -0.4 2.2 12.5 $38,521 44.9 66.6 $55,827 37.1 Scranton--Wilkes-Barre, PA 3,464 4,437 3.6 1.7 18 $10,094 47.6 71.6 $34,780 0.0 Seattle-Tacoma-Bellevue, WA 21,760 31,340 5.3 1.8 16 $10,389 44.1 65.3 $49,128 44.8 Springfi eld, MA 7,235 10,443 5.4 3.5 17 $4,079 39.1 68.1 $42,657 0.0 St. Louis, MO-IL 15,836 17,553 1.5 1.3 17 $29,792 45.8 68.5 $41,968 3.8 Stockton, CA 3,390 4,642 4.6 2.2 16 $17,374 49.4 75.0 $40,437 0.0 Syracuse, NY 8,272 9,648 2.2 3.0 15 $10,317 46.7 74.4 $39,254 8.5 Tampa-St. Petersburg-Clearwater, FL 10,733 15,347 5.2 1.3 14.5 $11,603 44.3 68.6 $37,300 0.0 Toledo, OH 6,873 11,831 8.1 3.9 16 $25,371 41.7 61.0 $40,276 11.5 Tucson, AZ 3,556 5,327 5.9 1.5 18 $12,627 40.2 63.1 $38,838 9.5 Tulsa, OK 4,076 7,130 8.3 1.7 16 $9,457 43.8 72.6 $34,079 0.0

Virginia Beach-Norfolk-Newport News, VA-NC 8,065 9,594 2.5 1.1 13 $4,883 46.2 72.3 $38,171 0.0Washington-Arlington-Alexandria, DC-VA-MD-WV 50,425 70,828 5.0 2.3 13 $6,183 37.2 62.3 $51,651 19.8Wichita, KS 2,811 3,913 4.8 1.3 16 $27,177 47.6 71.6 $36,124 8.3Worcester, MA 4,914 6,537 4.2 2.0 18 $24,177 47.3 74.0 $41,788 3.2Youngstown-Warren-Boardman, OH-PA 2,192 2,977 4.5 1.3 15 $4,402 48.3 75.1 $34,923 0.0100 Largest Metro Areas 1,276,388 1,705,897 4.2 1.9 15 $17,255 43.6 67.7 $43,133 18.8Source: Brookings-Battelle Clean Economy Database; exports: Brookings analysis of U.S. International Trade Commission, Bureau of Economic Analysis, Internal Revenue Service, Institute of International Education, and Moody's Analytics data; educational attainment: U.S. Bureau of Labor Statistics Employment Projections Program; green collar jobs: U.S. Bureau of Labor Statistics Occupational Employment Statistics and Employment Projections Program; wages: U.S. Bureau of Labor Statistics Occupational Employment Statistics; clusters: Brookings analysis (see methods external appendix for details). *State and metro clustering fi gures exclude non-exporting segments, defi ned as those with less than $4000 in exports per job. 
SIZING THE CLEAN ECONOMY | APPENDIX 55

Appendix E. Occupations of the Clean Economy 

 Share of all Share of Share of workers in

 Median clean economy all U.S. occupation with

 annual wage, occupations occupations with high school

Occupational Title 2009 (%) (%) diploma or less (%)

High-wage occupations 

Management $89,330 5.7 4.7 4.7

Legal $74,030 0.7 0.8 2.7

Computer & math $72,900 2.1 2.5 1.2

Architecture & engineering $68,790 5.7 1.8 2.4

Business & fi nancial $58,910 5.8 4.6 2.1

Life, physical, & social science $58,300 2.3 1.0 3.3

Healthcare practitioner & technical $57,690 1.2 5.5 1.2

Education, training, & library $45,210 0.4 6.5 2.0

Arts, design, entertainment, sports, & media $42,450 0.6 1.3 4.8

All high-wage occupations $63,068 24.4 28.8 2.8

Middle-wage occupations 

Installation, maintenance, and repair occupations $39,600 6.2 3.9 27.6

Community and social services occupations $38,970 1.4 1.4 3.3

Construction and extraction occupations $38,770 7.2 4.4 51.9

Protective service occupations $36,170 4.5 2.4 10.5

Offi ce and administrative support occupations $30,410 14.1 17.1 10.2

Production occupations $29,970 15.9 6.8 44.2

Transportation and material moving occupations $28,010 19.3 6.8 43.3

All middle-wage occupations $34,557 68.7 42.9 26.5

Low-wage occupations 

Healthcare support occupations $24,720 0.3 3.0 23.2

Sales and related occupations $23,940 3.4 10.5 17.7

Building and grounds cleaning and maintenance occupations $22,350 0.9 3.3 66.6

Personal care and service occupations $20,770 1.2 2.6 23.7

Farming, fi shing, and forestry occupations $19,610 0.7 0.3 18.2

Food preparation and serving related occupations $18,490 0.4 8.6 49.6

All low-wage occupations $21,647 6.9 28.3 34.2

Source: Brookings analysis of the Brookings-Battelle Clean Economy Database and industry-occupation estimates from the U.S. Bureau of Labor Statistics' 

Occupational Employment Statistics (OES) and Employment Projections programs. Occupations were estimated based on 4-digit NAICS codes. Missing 

data (for the public sector and agricultural workers) were supplemented using the 2009 American Community Survey--accessed through Integrated Public 

Use Microdata Series (IPUMS) Version 4.0. The rows with category totals display the sum of the percentages and the average of the median wages and 

educational requirements. See external methods appendix for more details. 

Appendix D. The Clean Economy by Industry (NAICS-Based) 

 

NAICS Share of all clean

Code Industry Title Jobs, 2010 economy jobs, 2010 (%)

11 Agriculture, Forestry, Fishing and Hunting 31,373 1.2

21 Mining, Quarrying, and Oil and Gas Extraction 1,091 0.0

22 Utilities 155,875 5.8

23 Construction 106,109 4.0

31-33 Manufacturing 687,116 25.7

42 Wholesale Trade 157,476 5.9

44-45 Retail Trade 15,977 0.6

48-49 Transportation and Warehousing 341,041 12.7

51 Information 657 0.0

52 Finance and Insurance 565 0.0

53 Real Estate and Rental and Leasing 718 0.0

54 Professional, Scientifi c, and Technical Services 278,621 10.4

55 Management of Companies and Enterprises 453 0.0

56 Administrative and Support and Waste Management and Remediation Services 299,409 11.2

61 Educational Services 520 0.0

62 Health Care and Social Assistance 2,115 0.1

71 Arts, Entertainment, and Recreation 253 0.0

72 Accommodation and Food Services 314 0.0

81 Other Services (except Public Administration) 21,067 0.8

92 Public Administration 574,795 21.5

Source: Brookings-Battelle Clean Economy Database 
56 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM

ENDNOTES

CHAPTER 1

1. See Allison Hannon and others, “Delivering Low Carbon Growth: 

A Guide to China’s 12th Five-Year Plan” (London: Climate Group and 

HSBC, 2011).

2. Chico Harlan, “Japan Takes a Shine to Renewable Energy.” 

The Washington Post, May 27, 2011.

3. “UK Outlines Plans for Green Bank.” The Associated Press, May 23, 2011.

4. Data here and in the following passage on world clean energy 

investments come from Bloomberg New Energy Finance. For background 

on the international clean energy “race” see Pew Charitable Trusts, 

“Who’s Winning the Clean Energy Race? 2010 Edition: G-2- Investment 

Powering Forward” (Washington: 2011).

5. Andrew Liveris, Make It in America: The Case for Re-Inventing the 

Economy (Hoboken: John Wiley & Sons, 2011).

6. The most notable and comprehensive cross-sectional study to date 

remains the 50-state comparative research Collaborative Economics 

performed for the Pew Charitable Trusts. See The Pew Charitable 

Trusts, “The Clean Energy Economy: Repowering Jobs, Businesses, and 

Investments Across America” (Washington: 2009).

CHAPTER 2

1. For important reviews of the environmental, security, and economic 

challenges associated with the world’s present development path, with 

a focus on the energy portion of the “green” concern, see Michael 

Greenstone and Adam Looney, “A Strategy for America’s Energy 

Future: Illuminating Energy’s Full Costs” (Washington: Hamilton Project/

Brookings Institution, 2011) and Jason Furman and others, “An Economic 

Strategy to Address Climate Change and Promote Energy Security” 

(Washington: Hamilton Project/Brookings Institution, 2007).

2. United Nations Environment Program, “Global Environmental Outlook 

4” (New York: 2007). United Nations Environment Program, “Towards a 

Green Economy” (Paris: 2011). Deutsche Bank Climate Change Advisors, 

“Investing in Climate Change 2010: A Strategic Asset Allocation 

Perspective” (New York: January 2010).

3. United Nations Department of Economic and Social Affairs, “World 

Population Prospects: The 2010 Revision” (New York: 2011).

4. United Nations Environment Programme, “Global Environmental Outlook 

4.” United Nations Water, “World Water Development Report: Water for a 

Changing World” (New York: 2009). Available at www.unesco.org/water/

wwap/wwdr/wwdr3/ 

5. Deutsche Bank Research, “World Water Markets 2010” (Frankfurt, 2010).

6. McKinsey & Company, “Charting Our Water Future” (2009). Available 

at http://www.mckinsey.com/App_Media/Reports/Water/Charting_Our_

Water_Future_Full_Report_001.pdf . 

7. On the growing world energy demand see Energy Information 

Administration, “International Energy Outlook 2010” (Washington: 2010). 

In its “World Energy Outlook 2010,” the International Energy Agency 

predicts that energy demand will increase more slowly, by 36 percent 

from 2008 to 2035, if countries act on their Copenhagen commitments. 

8. National Academy of Sciences, “Advancing the Science of Climate 

Change” (Washington: National Academies Press, 2010). National 

Academy of Sciences, “America’s Climate Choices” (Washington: 

National Academies Press, 2011). There remains broad-based scientifi c 

and political consensus that climate change is occurring and that 

increases in atmospheric greenhouse gas (GHG) concentrations are 

driving it. 

9. Emissions targets submitted to the United Nations Framework 

Convention on Climate Change (UNFCCC) for industrialized (Annex 

I countries) countries can be found here: http://unfccc.int/home/

items/5264.php; nationally appropriate mitigation actions committed to 

by developing (non-Annex I) countries can be found here: http://unfccc.

int/home/items/5265.php. See also William Antholis, “International 

global energy diplomacy built on domestic action: A” in William 

Antholis and Charles Ebinger, “The Status Report: Obama and Energy 

Security,” Up Front Blog, Brookings Institution, January 5, 2011. For 

background on the diffi culty of comparing the often ambiguous national 

emissions reduction commitments made in the Copenhagen Accord 

see Warwick McKibben, Adele Morris, and Peter Wilcoxen, “Comparing 

Climate Commitments: A Model-Based Analysis of the Copenhagen 

Accord” (Washington: Brookings Institution, 2010). To be sure these 

commitments are insuffi cient by themselves to reduce global emissions 

by the 50 to 80 percent from 2005 levels estimated to be needed to 

limit global average temperature increase to an acceptable 2.4 degrees 

Celsius. For an analysis of the pledges’ insuffi cient contributions to 

needed long-term emissions reductions see United Nations Environment 

Programme, “The Emissions Gap Report: Are the Copenhagen Accord 

Pledges Suffi cient to Limit Global Warming to 2°C or 1.5°C?” (2010). 

10. Deutsche Bank Climate Change Advisors, “Investing in Climate Change 

2011” (Frankfurt am Main, 2011). See also Deutsche Bank Climate Change 

Advisors, “Investing in Climate Change 2010” which notes that though 

while the Copenhagen meeting did not deliver a legally binding global 

deal to curb emissions it “shifted the focus to countries taking action 

and reporting it individually.”

11. Bernard Sinclair-Desgagné, “The Environmental Goods and Services 

Industry” (Montreal: HEC Montréal, CIRANO, CIRAIG, 2008). See also: 

Pew Charitable Trusts, “Global Clean Power: A$2.3 Trillion Opportunity” 

(Washington, 2010).

12. Sarah Ladislav and others, “A Roadmap for a Secure, Low Carbon 

Energy Future” (Washington: World Resources Institute and Center for 

Strategic and International Studies, 2010).

13. Energy Information Administration, “Monthly Energy Review April 2011” 

available at (May 2011) www.eia.gov/petroleum/data.cfm#summary. 

14. Michael Greenstone and Adam Looney, “A Strategy for America’s Energy 

Future.” 

15. See also, on energy security challenges more generally, Sarah Ladislaw, 

Kathryn Zyla, and Britt Childs, “Managing the Transition to a Secure, 

low-Carbon Energy Future” (Washington: Center for Strategic and 

International Studies and World Resources Institute, 2008). 

16. A large body of economics research fi nds that oil price shocks and 

higher electricity prices each have large and negative effects on U.S. 

gross domestic product. See Jason Furman and others, “An Economic 

Strategy to Address Climate Change and Promote Energy Security” as 

well as James D. Hamilton, “Oil and the Microeconomy.” (La Jolla, CA: 

University of California, San Diego, August 2005) and Donald W. Jones, 

Paul Leiby, and Inja Paik, “Oil Price Shocks and the Macroeconomy: What 

Has Been Learned Since 1996,” The Energy Journal 25 (2) (2004): 1–32.

17. CNA Corporation, “National Security and the Threat of Climate Change” 

(Alexandria, Virginia: 2007). Dennis Blair, “Annual Threat Assessment 

of the U.S. Intelligence Community” (Testimony before the U.S. Senate 

Select Committee on Intelligence: February 2, 2010). 

18. For background on the demand for water treatment technologies and 

services being driven by shale gas mining in Pennsylvania see Maria 

Gallucci, “Water Treatment Firms See Boom in Business as Gas Drilling 

Spreads.” SolveClimate News, May 23, 2011.

19. CNA Corporation, “National Security and the Threat of Climate Change.” 

The United Nations projects that developing countries, where access to 

clean water and basic sanitation are already poor, will shelter 90 percent 

of the 3 billion people the planet will add through 2050. For additional 

information see: UN Water, “World Water Development Report 3.”

20. UN Water, “World Water Development Report 3.”

21. McKinsey & Company, “Charting Our Water Future.” 

22. Mia Javier, “The Promise of Water Innovation” Cleantech Investment 

Insights, a blog of the Cleantech Group, May 13, 2011, available at http://

blog.cleantech.com/cleantech-investments/the-promise-of-waterinnovation/. See also DB Climate Change Advisors, “Investing in Climate 

Change 2011” and McKinsey & Company, “Charting Our Water Future.”

23. Some conventional economists still view capital accumulation as the key 

to growth. However, in recent years, a growing number of economists 

have come to conclude that it is not so much the accumulation of more 

savings or capital that is the key to improving standards of living in 

developed countries; rather it is innovation. For such views see: Robert 

Solow, “Technical Change and the Aggregate Production Function,” The 

Review of Economics and Statistics 39 (3) (1957): 312-320; Paul Romer, 

“Endogenous Technological Change,” Journal of Political Economy 98 

(5) (1990). 71-102; Gregory N. Mankiw, David Romer, and David N. Weil, “A 

Contribution to the Empirics of Economic Growth,” Quarterly Journal of 

Economics 107 (2) (1992): 407-437; Robert E. Hall and Charles I. Jones, 

“Why do Some Countries Produce So Much More Output per Worker 

than Others?” The Quarterly Journal of Economics 114 (1) (1999): 83-116; 

and Elhanan Helpman, The Mystery of Economic Growth (Cambridge, 

MA: Belknap Press, 2004.

24. World Economic Forum, “Green Investing 2011” (Geneva: 2011).

25. Ernst & Young, “Cleantech Matters: Global Cleantech Insights and 

Trends, 2011” (London: 2011).

26. Mia Javier, “State of Water Innovation” (San Francisco: Cleantech Group, 

2010) and Deutsche Bank Research, “World Water Markets 2010.”

27. Stuart J.H. Graham, Robert Merges, Pam Samuelson, and Ted Sichelman 

“High Technology Entrepreneurs and the Patent System: Results of the 

2008 Berkeley Patent Survey,” Berkeley Technology Law Journal 24 

(4) (2010): 1248-1318; Bronwyn H. Hall and Josh Lerner, “The Financing 

of R&D and Innovation.” In B. Hall and N. Rosenberg eds., Handbook of 

the Economics of Innovation, (Elsevier-North Holland: 2010). The reason 

for the patent intensity of VC-backed fi rms appears to be the fact that 

venture-capitalists screen fi rms and their technologies very carefully 

and then closely monitor and try to improve their performance as the 

fi rm develops its product.

28. PricewaterhouseCoopers / National Venture Capital Association 

MoneyTree Report, Data: Thomson Reuters, available at www.nvca.org/

29. Ernst and Young, “From Survival to Growth: Global Venture Capital 

Insights and Trends Report 2009” (2009). Deloitte and National Venture 
SIZING THE CLEAN ECONOMY | ENDNOTES 57

Capital Association, “2010 Global Trends in Venture Capital: Outlook for 

the Future” (2010).

30. OECD, “Indicator of environmental technologies (ENV-tech)” (2010), 

available at www.oecd.org/environment/innovation.

31. For discussions of nations’ efforts to establish competitive advantage 

in clean economy manufacturing capacity, the deployment of clean 

energy technologies, and enabling infrastructure see Rob Atkinson and 

others, “Rising Tigers, Sleeping Giant: Asian Nations Set To Dominate 

the Clean Energy Race by Out-Investing the United States” (Washington 

and Oakland: Information Technology and Innovation Foundation and 

Breakthrough Institute, 2009) and Pew Charitable Trusts, “Who’s 

Winning the Clean Energy Race? 2010 Edition.”

32. Alan Berube and others, “MetroNation: How U.S. Metropolitan Areas Fuel 

American Prosperity” (Washington: Brookings Institution, 2007).

33. Mark Muro and others, “MetroPolicy: Shaping a New Federal Partnership 

for a Metropolitan Nation” (Washington: Brookings Institution, 2008).

34. Brookings analysis of Census Bureau American Community Survey 

data (2009); Brookings analysis of U.S. Geological Survey data 

(2005); Brookings analysis of Department of Transportation Highway 

Performance Monitoring System data (2006); Marilyn Brown and others, 

“Shrinking the Carbon Footprint of Metropolitan America.” (Washington: 

Brookings Institution, 2008).

35. Brookings analysis of data from the U.S. Green Building Council.

36. National Research Council Committee on an Assessment of Research 

Doctorate Programs, "A Data-Based Assessment of Research-Doctorate 

Programs in the United States" (Washington: The National Academy of 

Sciences, 2010), available at http://www.nap.edu/rdp. Brookings analysis 

of U.S. Census Bureau American Community Survey 2009 data.

37. Brookings analysis of data from ARPA-E.

38. The three programs administered by the Department of Energy Offi ce of 

Loans are Section 1703, which guarantees loans for projects that employ 

new or signifi cantly improved energy technologies to avoid, reduce, or 

sequester air pollutants or greenhouse gases; Section 1705, part of the 

Recovery Act, which guarantees loans for certain clean energy projects 

that commence construction on or before September 30, 2011; and the 

Advanced Technology Vehicles Manufacturing program, which provides 

direct loans to fi nance advanced vehicle technologies. See https://lpo.

energy.gov/?page_id=2. 

39. Alan Berube and others, “MetroNation.” Research from the Federal 

Reserve Bank of Philadelphia, for instance, notes that patents not only 

proliferate markedly with increased employment density but tend to be 

cited within the same metropolitan area. See Gerald Carlino, Satyajit 

Chatterjee, and Robert Hunt, “Urban Density and the Rate of Invention.” 

Working Paper 04-16/R (Federal Reserve Bank of Philadelphia, 2006). 

For more on the association of clusters with innovation, see Maryann 

Feldman, The Geography of Innovation (Dordrecht: Kluwer Academic 

Publishers, 1994) and David Audretsch and Maryann Feldman, “The 

New Economics of Innovation, Spillovers, and Agglomeration: A Review 

of Empirical Studies.” In Gordon L. Clark, Maryann Feldman, and Meric 

Gertner, eds., The Oxford Handbook of Economic Geography (New York: 

Oxford University Press, 2002).

40. For background on the relationship between fi rm growth and regional 

character see Zoltan Acs and Pamela Mueller, “Employment effects 

of business dynamics: Mice, Gazelles and Elephants,” Small Business 

Economics 30 (2008): 85-100. For the Global Cleantech 100 list see www.

guardian.co.uk/globalcleantech100/cleantech-100-2010-list?CMP=twt_gu 

For a dot map of the world location of the 100 Cleantech 100 fi rms 

go here: http://www.guardian.co.uk/globalcleantech100/interactive/

world-map For two blogs on the metropolitan clustering of U.S. Global 

Cleantech 100 fi rms see Jonathan Rothwell and Mark Muro, “Where the 

Cleantech Companies Are,” The Avenue, a blog of The New Republic, 

February 23, 2011 and Jonathan Rothwell and Mark Muro, “Top of the 

Class: The Role of Leading Academic Programs in Cleantech Innovation,’’ 

The Avenue, a blog of The New Republic, February 24, 2011.

41. Alan Berube and others, “MetroNation.”

CHAPTER 3

1. Index to the Digest of Green Reports and Studies, available at 

www.labormarketinfo.edd.ca.gov/contentpub/GreenDigest/GreenDigest-Index.pdf (February 2011).

2. “Global Metro Summit 2010: Delivering the Next Economy,” available 

at www.brookings.edu/events/2010/1208_metro_summit.aspx. Emilia 

Istrate, Jonathan Rothwell, and Bruce Katz, “Export Nation: How U.S. 

Metros Lead National Export Growth and Boost Competitiveness” 

(Washington: Brookings Institution, 2010).

3. Eurostat, “Handbook on the Environmental Goods and Services Sector” 

(Luxembourg, 2009); U.S. Census Bureau, “Survey of Environmental 

Products and Services” (Washington: Environmental Protection Agency, 

1998); Organization for Economic Cooperation and Development, “The 

Environmental Goods and Services Industry: Manual for Data Collection 

and Analysis” (Paris, 1999); U.S. Bureau of Labor Statistics Federal 

Register Notice 75 (182) (September 21, 2010) www.bls.gov/green/

frn_2010_09_21.pdf

4. Readers interested in these jobs can look forward to the Bureau of Labor 

Statistics survey, which will aim to measure the clean economy and 

clean process economy in two separate surveys.

5. Eurostat, ”Handbook on the Environmental Goods and Services Sector“; 

U.S. Census Bureau, "Survey of Environmental Products and Services"; 

OECD, ”The Environmental Goods and Services Industry“; BLS, Federal 

Register Notice 75.

6. Since 1990, the fi rm Dun & Bradstreet has aimed to create a census of 

U.S. establishments and their employees. They used the SIC system to 

classify fi rms, and found that they needed to expand the number of 

digits from six to eight to account for new industries. In 1997, the federal 

government moved to the NAICS, but Dun & Bradstreet kept the older 

system that they had developed. Walls & Associates has developed a 

“cross-walk” between D&B’s SIC and the contemporary NAICS, which was 

used in this report.

7. Karen Chapple and Malo Hutson, “Innovating the Green Economy 

in California Regions” (Berkeley: University of California Center for 

Community Innovation, 2010). Available at http://communityinnovation.

berkeley.edu/publications.html

8. Some industries—such as urban planning and bicycle repair—were not 

included in this study because the environmental benefi t was unclear. 

Likewise, some companies appeared to have been mis-classifi ed, and so 

they were excluded.

9. The Pew Charitable Trusts, “The Clean Energy Economy.” Pew found 

that 60 percent of clean economy jobs are in establishments from these 

industries. 

10. The following changes were made to the BLS categories: Public 

awareness was dropped from the category “Education and Compliance” 

(and considered here as a clean economy “process job” rather than a 

production job); “Energy Effi ciency” was broadened to include resource 

effi ciency (e.g. water); Agriculture was added to “Natural Resources 

Conservation;” and “Pollution Reduction and Removal” was changed to 

“Environmental Management.”

11. For example, if a company was listed by the American Wind Energy 

Association, it was placed in “Wind Energy.” All USDA certifi ed farmers 

were classifi ed in “Organic Farms and Organic Food Production.” In 

other cases, the product—such as vehicle batteries—was used to make 

the classifi cation.

12. BLS Business Employment Dynamics, available at www.bls.gov/bdm/

home.htm (2011).

13 Istrate, Rothwell, and Katz, “Export Nation.”

14. See www.bls.gov/oes/oes_dl.htm#2009; http://www.bls.gov/emp/

ep_table_111.htm#1

15. Elliot Martin and others, “Impact of Carsharing on Household Vehicle 

Holdings: Results from North American Shared-Use Vehicle Survey,” 

Transportation Research Record 2143 (2010): 150-158.

16. Ibid.

17. Tai Stillwater and others, “Carsharing and the Built Environment: A 

Geographic Information System–Based Study of One U.S. Operator,” 

Transportation Research Record 2110 (2009): 27-34.

18. Oregon Employment Department, “The Greening of Oregon’s Workforce: 

Jobs, Wages, and Training” (2009); California Employment Development 

Department, “California’s Green Economy” (2010); Nicholas Jolly, “How 

Green is Connecticut’s Economy?” The Connecticut Economic Digest

13 (12) (2008): 1-3. The green jobs number in California refers to the 

number of employees who report spending most of their time on green 

aspects of job (263,000). 

19. Washington State Employment Security Department, “2008 Washington 

State Green Economy Jobs” (2009); Washington State Employment 

Security Department, “2009 Washington State Green Economy Jobs” 

(2010).

20. Missouri Economic Research and Information Center, “The Missouri 

Green Jobs Report” (2009); Kansas Department of Labor, “2009 Kansas 

Green Jobs Report” (2010).

21. Michigan Department of Energy, Labor & Economic Growth, “Michigan 

Green Jobs Report: Occupations & Employment in the New Green 

Economy” (2009).

22. The Pew Charitable Trusts, “The Clean Energy Economy”; U.S. 

Department of Commerce, Economics and Statistics Administration, 

”Measuring the Green Economy“ (Washington, 2010) U.S. International 

Trade Administration, Offi ce of Energy and Environmental Industries, 

“Environmental Technologies Industries: 2010 Industry Assessment” 

(2010); U.S. Conference of Mayors, “U.S. Metro Economies: Current 

and Potential Green Jobs in the U.S. Economy” (2009); The Center for 

Community Innovation, “Innovating the Green Economy in California 

Regions” (2010).

23. See the Solar Energy Industries Association website, available at 

http://seia.org/galleries/default-fi le/2009%20Solar%20Industry%

20Year%20in%20Review.pdf
58 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM

24. See the Solar Foundation website, available at 

http://www.thesolarfoundation.org/sites/thesolarfoundation.org/fi les/

Final%20TSF%20National%20Solar%20Jobs%20Census%202010%

20Web%20Version.pdf

25. See the National Hydropower Association website, available at 

http://hydro.org/wp-content/uploads/2011/02/NHA-Annual-ConfFrantzis-pres-Final-7.pdf

26. See the American Wind Industry Association website, available at 

www.awea.org/_cs_upload/learnabout/publications/5094_1.pdf

27. See the Geothermal Energy Association website, available at 

http://geo-energy.org/geo_basics_employement.aspx

28. “Global Cleantech 100,” The Guardian, available at 

http://www.guardian.co.uk/globalcleantech100/cleantech-100-2010-

list?CMP=twt_gu (January 2011).

CHAPTER 4

1. The fi gure is for 2010, and the source is Moody’s Economy.com. NAICS 

621, 622, and 623 were included. Social assistance was excluded.

2. Brookings analysis of 2009 Census County Business Patterns data 

shows that jobs associated with producing fossil fuel based energy, 

derivative products, and machinery make up roughly one percent of the 

U.S. economy. If one adds distribution, gas stations, fuel transportation, 

and wholesalers—peripheral activities excluded from the clean economy 

estimates—the fossil fuel economy still employs only 1.8 percent of U.S. 

workers or 2.4 million workers. A 2009 report from Pricewaterhouse 

Coopers estimated that the number of jobs directly involved in the 

fossil fuel industry was 2.1 million; that report was commissioned by 

the American Petroleum Institute. (See Pricewaterhouse Coopers, 

“The Economic Impacts of the Oil and Natural Gas Industry on the U.S. 

Economy: Employment, Labor Income and Value Added” (2009).

3. Battelle and Biotechnology Industry Organization, “State Bioscience 

Initiatives 2010” (2010).

4. The source of these data is Moody’s Economy.com special aggregates, 

IT-Producing Industries. Estimates are for 2010.

5. See the GoodGuide, available at www.goodguide.com/about/

methodology. GoodGuide is a “for benefi t” corporation, or B 

Corporation.

6. Growth data here refer to job gains from openings and expansions, 

as well as job losses from contractions. They exclude job losses from 

the closing of establishments, because that data was not available 

for the clean economy. The national data also excludes jobs lost from 

closings to create a comparable set of businesses. This can be done 

by subtracting the number of deaths over the period (2003 to 2010) 

from the base year (2003). This creates a universe of survivors. The 

underlying national data is from the Bureau of Labor Statistics’ Business 

Employment Dynamics series.

7. John C. Haltiwanger, Ron S. Jarmin, and Javier Miranda, “Who Creates 

Jobs? Small Vs. Large Vs. Young.” Working Paper 16300 (National 

Bureau of Economic Research, 2009).

8. The median year of establishment birth in the clean economy is 1995. 

Analysis of Business Dynamics Statistics and the Bureau of Employment 

Dynamics data show that the average year of establishment birth 

is between 1994 and 1997 for the U.S. economy. Start years for the 

hydropower segment were missing for all but three observations out 

of 1400 establishments. The median start year for those three was 

1990. Caution should be used in interpreting these fi gures. The true 

median start year is probably earlier. However, the Federal Energy 

Regulatory Commission database reports the date of licenses issued to 

hydroelectric producers. The median year for these licenses is also 1990. 

See www.ferc.gov/industries/hydropower.asp

9. See the external methods appendix for details. These fi gures refl ect 

Brookings analysis of data from the BLS’s Business Employment 

Dynamics series. All subsequent deaths were subtracted from the 

base year to account for job losses due to closings and make the data 

comparable to the clean economy. Nationally, old establishments—

born before 2003—lost jobs at a rate of -0.5 percent per establishment 

per year. 

10. Data on U.S. manufacturing from Moody’s Economy.com. This number 

is the sum of manufacturing employment in the 50 states, not for the 

United States and its territories.

11. These data are from the BLS Business Employment Dynamics program. 

The 3.3 million fi gure is net of openings, expansions, contractions, and 

closings. The comparable number to the clean economy would be 1.3 

million looses—that excludes job losses from establishments that closed.

12. These data are estimated based on a technique described in the 

methods section and external methods appendix. It estimates exports 

at the establishment level based on the establishment’s industry. 

However, the use of an alternative method to estimate exports yields 

similar results. Evidence from the International Trade Administration 

(ITA) paints an encouraging picture on exports in the clean economy—

which is associated with environmental technologies. According to 

a Brookings analysis of an ITA list of 228 products deemed to be 

environmental technologies, the United States exports 60 percent 

more in environmental goods than it imports. Moreover, the share of 

U.S. manufacturing exports from environmental technologies increased 

from 2.9 in 1996 to 4.5 in 2009. Overall, the defi nition used by the ITA is 

very similar to the Brookings defi nition used here. Employing the ITA’s 

product codes, the value of environmental exports—excluding services—

comes to almost $40 billion in 2010. 

13. Randy A. Becker and Ronald J. Shadbegian, “Environmental Products 

Manufacturing: A Look Inside the Green Industry,” The B.E. Journal of 

Economic Analysis and Policy 9 (1) (2009): 1–23.

14. All the growth fi gures here exclude establishments that may have closed 

between 2003 and 2010.

15. Gilles Duranton and Diego Puga, “Nursery Cities: Urban Diversity, 

Process Innovation, and the Life Cycle of Products,” American Economic 

Review 91 (5) (2001): 1454–1477.

16. This excludes establishments that may have closed in intervening years.

17. Exporting establishments are defi ned as those with above average 

exports per worker, meaning above $20,000. 

18. Details describing how this result was obtained are discussed in 

the external methods appendix. To summarize, establishment level 

employment growth was regressed on establishment characteristics 

including age, headquarters status, branch status, three-digit industry, 

county level employment, company level employment, the number of 

establishments in the company, and county level segment employment 

in other establishments. Errors were allowed to cluster at the county 

level.

19. Methodologically, establishments were defi ned as concentrated in 

clusters if other establishments in the same county comprised at least 

1 percent of all U.S. employment for the given segment in the base year 

of 2003. By this standard, 47.3 percent of all establishments were in 

clusters. The results are not substantially changed if the defi nition is 

relaxed or made more discriminating. Using a threshold of 0.01 percent 

for the county share of U.S. employment, which includes 73 percent 

of all establishments, clustered establishments grew at 4.6 percent on 

average, compared to 3.2 percent for isolated establishments. Using 

a stricter threshold of 1 percent, which applies to just 11 percent of 

establishments in the clean economy, those that were clustered grew 

at a rate of 5.3 percent, compared to 3.4 percent for non-clustered 

establishments. In other words, using any reasonable defi nition of 

concentration, clean economy establishments benefi tted from being 

located in concentrated clusters of peer establishments in the same 

segment.

20. See, among others, J. Vernon Henderson, “Marshall’s Scale Economies,” 

Journal of Urban Economics 53 (2003): 1–28; Stuart Rosenthal and 

William Strange, “Evidence on the Nature and Sources of Agglomeration 

Economies.” In J.V. Henderson and J. F. Thisse, eds., Handbook of 

Regional and Urban Economics, vol. 4 (Amsterdam: North-Holland, 

2004); Gilles Duranton, Philippe Martin, Thierry Mayer and Florian 

Mayneris, The Economics of Clusters: Lessons from the French 

Experience (Oxford: Oxford University Press, 2010). Clusters benefi t 

economic performance through three mechanisms, according to the 

work of Giles Duranton and colleagues: sharing, learning, and matching. 

Sharing is facilitated in clusters in that proximity allows fi rms to share 

things like facilities, transportation infrastructure, and even institutions 

(like universities or federal labs). Clusters may reduce the costs of 

establishing or maintaining these valuable resources. Learning is 

facilitated in clusters through knowledge diffusion, which has proven 

to be easier over short distances, whether it be via teaching, casual 

conversation, or employees transferring to rival fi rms or starting-up 

their own. Finally, clusters can improve matching between workers and 

employers or suppliers and buyers. (For details see: Peter Thompson, 

“Patent Citations and the Geography of Knowledge Spillovers: What do 

Patent Examiners Know?” The Review of Economics and Statistics 88 (2) 

(2006): 383–388; Matt Marx, Deborah Strumsky, Lee Fleming, “Mobility, 

Skills, and the Michigan Non-Compete Experiment,” Management 

Science 55 (6) (2009): 875–889; Toby Stuart and Olav Sorenson, 

“Liquidity Events, Noncompete Covenants, and the Geographic 

Distribution of Entrepreneurial Activity,” Administrative Science 

Quarterly 48 (2003): 175–201.

21. That calculation takes (1130/190)^0.03, where 0.03 is the coeffi cient on 

cluster size for a regression of the log of 2003 jobs at an establishment 

on the log of county level employment of other establishments in the 

same segment. See the external methods appendix for details.

22. Zoltan J. Acs and Pamela Mueller, “Employment Effects of Business 

Dynamics: Mice, Gazelles and Elephants,” Small Business Economics 30 

(2008): 85–100.

23. The numbers reported are the collective growth rates of all clustered 

and all isolated establishments. At the level of the individual 

establishment, the average annual compound growth rate was 

4.2 percent versus 3.4 percent in favor of clustered establishments. This 

difference was statistically signifi cant with a p-value of less than 0.01.

24. These low-exporting segments were as follows: waste management and 

treatment, recycling and reuse, remediation, training, waste-to-energy, 

conservation, hydropower, regulation and compliance, and public mass 

transit. It was deemed that clustering dynamics (or agglomeration 

economies in the technical jargon) are less relevant for these sectors 

because there is little private-sector competition and they are untraded. 

However, some of the advantages of clustering could still work to 

increase effi ciency and productivity in these segments.
SIZING THE CLEAN ECONOMY | ENDNOTES 59

CHAPTER 5

1. See Bloomberg New Energy Finance, “Weathering the Storm: Public 

Financing for Low-Carbon Energy in the Post-Financial Crisis Era” 

(Washington, 2010) and DBCCA, “Investing in Climate Change 2011.”

2. Bloomberg New Energy Finance data on U.S. and Chinese asset fi nance 

from 2004 to 2010 show that while fi nancings have grown in both 

nations, China has far outpaced the U.S. in the last few years. Chinese 

asset fi nancings increased from $1.5 billion in 2004 to $47.3 billion in 

2010. By contrast, U.S. asset investment grew much more slowly, rising 

from $2.8 billion in 2004 to $21.9 billion in 2008 before slipping to $20.7 

billion in 2010—a level less than half the Chinese amount.

3. Data through 2008. “Environmental Technologies Industries: FY2010 

Industry Assessment” (Washington: International Trade Administration, 

2010). U.S. Ron Senator Wyden’s much-referenced reports on U.S. trade 

in environmental goods, which track a basket of 43 climate-friendly 

environmental technology products, confi rm this broad trend through 

2009. See “U.S. Trade in Environmental Goods: Updated Report to Major 

Opportunities and Challenges to U.S. Exports of Environmental Goods” 

(Washington: Offi ce of Senator Ron Wyden, December 2010).

4. Google and Good Energies, an investment fi rm specializing in renewable 

energy, each agreed to take 37.5 percent of the equity portion of the 

transmission line project at a cost of $200 million each. Envision: 

Charlotte is a fi rst-of-a-kind collaborative partnership among major 

employers, building owners and managers along with municipal and 

technology leaders to create the most environmentally sustainable 

urban core in the nation. 

5. See, for example, Rebecca Henderson and Richard G. Newell, 

“Introduction and Summary.” in Rebecca Henderson and Richard G. 

Newell, eds., Accelerating Energy Innovation: Insights from Multiple 

Sectors. (Cambridge: National Bureau of Economic Research, 

forthcoming). Available at www.nber.org/books/hend09-1/. This sort of 

argument has also been made by Richard Kauffman in “Has China Won 

the U.S. Solar War? Huffi ngton Post, January 19, 2011. See also Richard 

Newell, “The Role of Markets and Policies in Delivering Innovation for 

Climate Change Mitigation,” Oxford Review of Economic Policy 26 (2010): 

253–269.

6. See, Michael Porter, The Competitive Advantage of Nations (New York: 

Free Press, 1990).

7. To be sure, narrow segments of the clean economy, such as energysaving consumer products, green building materials, or solar 

photovoltaic, face very specifi c market making challenges and it is 

beyond the scope of this report to go into detail for each of those. The 

report attempts to highlight some high level, salient problems that 

impede the growth of the entire clean economy or signifi cant chunks of 

it.

8. See, for example, Greenstone and Looney, “A Strategy for America’s 

Energy Future.”

9. See, for example, Newell, “The Role of Markets and Policies.” See also, 

Carolyn Fischer and Richard Newell, “Environmental and Technology 

Policies for Climate Mitigation,” Journal of Environmental Economics 

and Management 55 (2) (2008). And, Carolyn Fischer, “The Role 

of Technology Policies in Climate Mitigation.” Issue Brief #09-08 

(Washington: Resources for the Future, July 2009).

10. See Bloomberg New Energy Finance, “Crossing the Valley of Death” 

(New York, 2010) for a discussion on how governments, as fi rst adopters, 

can play a direct role in fostering clean technologies. 

11. Kate Manuel and L. Elaine Halchin, “Environmental Considerations in 

Federal Procurement: An Overview of the Legal Authorities and Their 

Implementation,” CRS Report for Congress (June 2010). There is also 

the problem that environmental objectives compete with other policy 

objectives and interests such as obtaining high quality goods at low 

prices through competition, protecting American manufacturing from 

foreign competition, and ensuring opportunities for small businesses. 

See also Eric Fischer, “Green Procurement: Overview and Issues for 

Congress,” (Washington: Congressional Research Service, April 2010). 

12. See Blair Hamilton, “Developing Effective and Sustainable Financing 

Approaches.” In Scaling Up Building Energy Retrofi tting in U.S. Cities 

(Montpelier, VT: Institute for Sustainable Communities, June 2009). 

See also, Merrian Fuller, “Enabling Investments in Energy Effi ciency: A 

Study of Programs that Eliminate First Cost Barriers for the Residential 

Sector” (Burlington, VT: Effi ciency Vermont, August 2008). See Derek 

Supple, “Financing Models for Energy Effi ciency and Renewable 

Energy in Existing Models” (Milwaukee: Institute for Building Effi ciency 

and Johnson Controls, September 2010). Johnson Controls and the 

international Facility Management association (iFMa) surveyed over 

1400 executives with budget responsibility for their company’s facilities 

during the spring of 2009. When asked what the top barrier for energy 

effi ciency was, the most frequent response amongst managers, 

consistent across a wide variety of industries, was capital availability. 

13. Deep energy retrofi t packages can cost anywhere from $6,000 to 

$20,000 per home and require longer fi nancing with terms of 10 to 

20 years. Direct cash incentives such as rebates and grants do not 

completely cover the full upfront cost of clean energy investment. In this 

regard, many states, municipalities and utilities are continuing to offer 

traditional fi nancing programs (e.g., revolving loan funds, energy savings 

performance contracting) and experiment with innovative fi nancing 

mechanisms (e.g., utility on-bill fi nancing, property assessed clean 

energy) that can operate in parallel with rebates and grants, lowering 

the cost of the project and shortening the payback period for fi nancing. 

However, these fi nancing programs have also not been widespread or 

designed to offer a large number of loans and come with their own 

specifi c challenges in design and implementation. For a review of various 

clean energy fi nancing mechanisms, see Devashree Saha, Sue Gander, 

Greg Dierkers, “State Clean Energy Financing Guidebook” (Washington: 

National Governors Association Center for Best Practices, January 2011).

14. ARRA represents a one-time historic infusion of funds that is expected 

to be temporary. For instance, DOE funded the State Energy Program 

(SEP) at $25 million each in FY 2009 and FY 2010 in SEP formula 

funding, and ARRA provided $3.1 billion for SEO formula grants. For 

FY 2011, SEP received $50 million, with $39 million of that amount 

in formula funding and the rest in technical assistance support. DOE 

funded the Weatherization Assistance Program (WAP) at $250 million 

in FY 2009, and ARRA provided $5 billion. For FY 2011, WAP received 

$174.3 million. See www.naseo.org/news/releases/2011-05-20.pdf.

15. For an overview of the characteristics of the water and wastewater 

sector and the challenges it faces see Haarmeyer and Coy, “An Overview 

of Private Sector Participation.” 

16. See, for instance, Marilyn Brown and Sharon Chandler, “Governing 

Confusion: How Statutes, Fiscal Policy, and Regulations Impede Clean 

Energy Technologies,” Stanford Law and Policy Review 472 (19) (2008). 

See also Benjamin Sovacool and Chistopher Cooper, “Congress Got 

It Wrong: The Case for a National Renewable Portfolio Standard and 

Implications for Policy,” Environmental and Energy Law and Policy 

Journal 85 (3) (2008); and Lincoln Davis, “Power Forward: The 

Argument for a National RPS,” Connecticut Law Review 42 (5) 

(July 2010).

17. Richard Lester and David Hart, “The Great Unlocking: A Comprehensive 

Energy Innovation Strategy for the U.S.” Discussion draft (Industrial 

Performance Center, Massachusetts Institute of Technology, 2011)

18. The Senate Committee on Energy and Natural Resources (ENR) released 

a Clean Energy Standard White Paper in March 2011 that lays out key 

questions and potential design elements of a CES. The white paper 

solicited inputs from stakeholders to inform the early consideration of a 

national CES by the ENR Committee. For more details, see www.energy.

senate.gov/public/_fi les/CESWhitePaper.pdf. However, it does not seem 

likely that a “clean energy standard” is forthcoming anytime soon. See, 

for example, “Outlook Bleak for Passing CES, Repealing Oil Subsidies – 

Bingaman.” Greenwire, May 16, 2011.

19. The Center for American Progress and the Coalition for Green Capital 

have advanced the concept of “races to the top” in the clean energy 

realm in Bracken Hendricks and others, “Cutting the Cost of Clean 

Energy 1.0” (Washington: Center for American Progress and the 

Coalition for Green Capital, 2011).

20. The greening of federal activities and the use of federal procurement to 

create stable market demand has been an object of bipartisan interest 

in both Congress and the executive, through both Republican and 

Democratic administrations. More recently, in response to Executive 

Order on Federal Leadership in Environmental, Energy, and Economic 

Performance (EO 13514) signed by President Obama in 2009, federal 

agencies have released Strategic Sustainability Performance Plans that 

outline how they will achieve the environmental, energy, and economic 

goals set forth in the executive order. This is the fi rst time that federal 

agencies have developed and submitted detailed sustainability plans. 

See www.whitehouse.gov/administration/eop/ceq/sustainability/plans. 

For a discussion of how energy and environmental innovation has 

been driven by Department of Defense procurement through both the 

Bush and Obama administrations, see Matthew Hourihan and Matthew 

Stepp, “Lean, Mean, and Clean: Energy Innovation and the Department 

of Defense” (Washington: Information Technology and Innovation 

Foundation, 2011). 

21. More ambitious reforms would make an even bigger difference. For 

instance, Congress should help strengthen FERC’s authority to promote 

these reforms and make electricity markets more competitive by 

revising the Federal Power Act.

22. States have taken action in several policy areas that are driving the 

demand for clean energy investment. 36 states have renewable portfolio 

standards or goals and 24 states have energy effi ciency resource 

standards or goals. 43 states have adopted a net metering policy and 

41 states have adopted an interconnection policy. 21 states have public 

benefi t funds (PBFs) supporting energy effi ciency and 16 have PBFs 

for renewable energy. 11 states have adopted the most recent building 

energy codes or more stringent codes in the residential sector (IECC 

2009); 15 have done so in the commercial sector (ASHRAE 90.1-2007). 

47 states have one or more tax incentives supporting renewable energy; 

24 states have one or more tax incentives directed at energy effi ciency. 

For more information, see Rachel Escobar and Sue Gander, “Clean and 

Secure State Energy Actions – 2010 Update” (Washington: National 

Governors Association, August 2010). See also the Database of State 

Incentives for Renewables and Effi ciency (DSIRE) Summary Maps, 

available at www.dsireusa.org/summarymaps/index.cfm.

23. As state RPS experience accumulates, studies have begun to evaluate 

RPS impact and effectiveness. See Langniss and Wiser, “The Renewable 

Portfolio Standard in Texas: An Early Assessment,” Energy Policy 31 (6) 

(2003). This study reports positive initial results from the establishment 

of RPS in Texas. See also Carley, “State Renewable Energy Electricity 

Policies: An Empirical Evaluation of Effectiveness,” Energy Policy 37 (8) 

(2009) and Powers and Yin, “Do State Renewable Portfolio Standards 

Promote In-State Renewable Generation?” Energy Policy 38 (5) (2010). 

Both studies credit RPS implementation with increasing total renewable 

energy generation across the nation. More recently, the implementation 

over time of RPS standards has been credited with signifi cantly 

expanding installed wind capacity in both Colorado and Texas. Installed 
60 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM

wind capacity grew by a factor of fi ve between 2004–2007 after 

Colorado’s RPS came into effect in 2004, and similarly Texas witnessed a 

quintupling of installed capacity in the four years following the passage 

of its RPS in 2005. See Joshua Freed, Elizabeth Horwitz, and Nicholas 

Cunningham, “A Clean Energy Standard: Getting the United States Back 

Into the Clean Energy Race” (Washington: Third Way, March 2011).

24. Examples of states that have ratcheted up their electricity sourcing 

targets include Colorado, which has twice updated its RPS, and 

Nevada, which increased its RPS target in 2009. Resource eligibility 

has expanded beyond traditional renewable energy resources to cover 

energy effi ciency and other supply-side technologies. For a more 

detailed discussion on state revisions of RPS, see Ryan Wiser and Galen 

Barbose, “Renewable Portfolio Standards in the United States: A Status 

Report with Data Through 2007” (Berkeley: Lawrence Berkeley National 

Laboratory, 2008). For background on state-by-state RPS coverage 

visit the Pew Center on Global Climate Change at www.pewclimate.org/

what_s_being_done/in_the_states/rps.cfm.

25. States have been leveraging their procurement power to drive the 

clean economy revolution through advanced energy effi ciency and 

renewable energy requirements for new and existing publicly funded 

buildings, facilities, and fl eets; energy effi cient and green product 

procurement (for instance, requiring all appliances and equipment 

purchases to meet the ENERGY STAR requirement); and using renewable 

energy either through generation at public facilities or on public 

lands, or by purchasing renewable energy directly from the electricity 

provider in what is popularly called green power purchasing. For more 

details on state best practices, see Maria Ellingson and Lesley Hunter, 

“Compendium of Best Practices: Sharing Local and State Successes 

in Energy Effi ciency and Renewable Energy from the United States” 

(Renewable Energy and Energy Effi ciency Partnership, Alliance to Save 

Energy, and American Council on Renewable Energy, May 2010). See 

also Alison Partin, “Greening State Government: ‘Lead by Example’ 

Initiatives” (Washington: National Governors Association, July 2008). 

For further details on how states can maximize their efforts by designing 

comprehensive programs, see U.S. Environmental Protection Agency, 

“Clean Energy Lead by Example Guide” (June 2009). Available at www.

epa.gov/statelocalclimate/documents/pdf/epa_lbe_full.pdf. See also 

ACEEE, “How State Governments can Lead by Example” at www.aceee.

org/fi les/pdf/fact-sheet/State%20Toolkit_Lead%20by%20Example.pdf.

26. See Saha and others, “State Clean Energy Financing Guidebook.” The 

Department of Energy’s Solution Center highlights nine particularly 

effective fi nancing mechanisms: state and municipal revolving loan 

funds, third party loans, energy savings performance contracting, 

property-assessed clean energy, on-bill repayment, energy effi cient 

mortgages, power purchase agreements, FHA Power Saver, and qualifi ed 

energy conservation bond programs. See www1.eere.energy.gov/wip/

solutioncenter/fi nancialproducts/fi nancingprograms.html.

27. American Wind Energy Association and Solar Energy Industry 

Association, “Green Power Superhighways Building a Path to America’s 

Clean Energy Future” (2009); William W. Hogan, “Electricity Wholesale 

Market Design in a Low Carbon Future.” In Jorge Padilla and Richard 

Schmalensee, eds., Harnessing Renewable Energy (Washington: 

Resources for the Future Press, 2010).

28. See, for instance, the IEA’s report providing guidance to local 

policymakers to enhance the deployment and use of renewable energy 

resources within their geographic boundaries. International Energy 

Agency, “Cities, Towns and Renewable Energy: Yes in my Front Yard,” 

(2009). 

29. See the Playbook for Green Buildings available at www.greenplaybook.

org/buildings/index.htm

30. For instance, the global C40 Cities Climate Leadership Group, chaired 

by New York City Mayor Bloomberg, recently released its fl agship 

report in which 36 global cities—including Austin, Chicago, Los Angeles, 

New Orleans, New York, Philadelphia, Portland, Seattle, and San 

Francisco—disclose their carbon emissions. The report will inform cities’ 

emissions-reduction efforts and establish a benchmark for judging the 

effectiveness of present and future policies. KPMG Advisory N.V., “CDP 

Cities 2011: Global Report on C40 Cities,” report prepared for C40 Cities 

Climate Leadership Group (2011).

31. See, for example, BNEF, “Crossing the Valley of Death.”

32. Ibid.

33. Clear analyses of the “commercialization Valley of Death” can be found 

in BNEF’s “Crossing the Valley of Death” and Eliot Jamison, “From 

Innovation to Infrastructure: Financing First Commercial Clean Energy 

Projects” (San Francisco: CalCEF, 2010).0.

34. The Solar Energy Industries Association, for one, has complained about 

long processing delays associated with the Loan Guarantee Program’s 

multi-agency review process as well as recent budget-related “holds” on 

pending applications. See Solar Energy Industries Association, www.seia.

org/galleries/FactSheets/Factsheet_DOE_LGP.pdf as well as www.seia.

org/galleries/pdf/SEIA_Letter_to_Congressional_Leaders_on_LGP_5.11.11.

pdf. 

35. Jamison, “From Innovation to Infrastructure.” See also Jenny Mandel, 

“Loan Guarantee Program’s Financial Rigor Slows it Down.” E&E News,

April 1, 2011. 

36. For a good discussion of these and other fl aws in the structure and 

nature of renewable energy subsidies see Nate Gorence and Sasha 

Mackler, “Reassessing Renewable Energy Subsidies” (Washington: 

Bipartisan Policy Center, 2011). 

37. Originally enacted in 1992, the PTC has been renewed and expanded 

numerous times, most recently through the Energy Improvement and 

Extension Act of 2008 and the American Recovery and Reinvestment 

Act (ARRA) of 2009. Through ARRA, Congress acted to provide a threeyear extension of the PTC through December 31, 2012. Wind projects 

must be in place before January 1, 2013 and other projects in general 

before January 1, 2014. For more details, see American Wind Energy 

Association, “What is the Current Status of the Production Tax Credit.” 

Available at www.americanwindenergyassociation.net/ei_policy_ptc.

cfm. The ITC similarly has gone through several revisions, most notably 

through the Energy Improvement and Extension Act of 2008 and 

subsequently under ARRA. Through ARRA, qualifying wind projects can, 

for a limited time, choose between a 30 percent ITC or a 30 percent cash 

grant in lieu of the PTC. 

38. For background on CEDA, see Senate Committee on Energy & Natural 

Resources, “The 21st Century Energy Technology Deployment Act” 

(April 2009). Available at www.energy.senate.gov/public/_fi les/

CEDAOnePageSummary.pdf. For more recent arguments in support 

of CEDA see the testimonies of Dan Reicher, Christopher Guith, 

and Kassia Yanosek before the Senate Energy & Natural Resources 

Committee on May 3, 2011. Available at www.energy.senate.gov/public/

index.cfm?FuseAction=Hearings.Hearing&Hearing_ID=929b04b3-

bbb7-c4d3-c14a-e477af7b1291. For discussion of the so-called Energy 

Independence Trust model see Hendricks and others, “Cutting the Cost 

of Clean Energy 1.0.” For discussions of capital repatriation schemes 

as sources of investment fi nance see Reed Hundt and Thomas Mann, 

”Rebuild American Infrastructure? Companies' Offshore Profi ts Can 

Help.“ Washington Post, June 16, 2011 and Elise Zoli and Peter Rothstein, 

”Repatriation to Accelerate Clean Energy (RACE): New Private 

Capital for Cleantech Investment and Deployment on a Pilot Scale.“ 

Presentation, April 22, 2011.

39. For discussions of the need to restructure renewable energy investment 

incentives see Steven Hayward and others, “Post-Partisan Power” 

(Oakland: The Breakthrough Institute, 2010) and Gorence and Mackler, 

“Reassessing Renewable Energy Subsidies,” which provides a rich 

discussion of the problems, potential solutions, and the political 

moment. 

40. Gorence and Mackler, “Reassessing Renewable Energy Subsidies” 

provides a detailed discussion of reverse auctions. 

41. For information on Connecticut’s programs see the CDA’s technology 

oriented expansion fi nance programs see www.ctcda.com/Financing/

Specialty_Programs/TECHNOLOGY_INTENSIVE. For more information 

on the California alternative vehicle program see the California Energy 

Commission website at www.energy.ca.gov/altfuels/index.html.

42. This concept is described in Jamison, “From Innovation to 

Infrastructure.” 

43. See BNEF, “Crossing the Valley of Death.”

44. On the general importance of innovation to economic growth see 

Robert Atkinson and Howard Wial, “Boosting Innovation, Productivity, 

and Growth Through a National Innovation Foundation” (Washington: 

Brookings Institution, 2008). See also, on the energy fi eld, and Richard 

Newell, “A U.S. Innovation Strategy for Climate Change Mitigation” 

(Washington: Brookings Institution / Hamilton Project, 2008). James 

Duderstadt and others, “Energy Discovery-Innovation Institutes: A Step 

Towards America’s Energy Future” (Washington: Brookings Institution, 

2009); and Hayward and others, “Post Partisan Power.” and Hourihan 

and Atkinson, “Inducing Innovation.” 

45. See, among many others, Duderstadt and others, “Energy DiscoveryInnovation Institutes” and Hayward and others, “Post Partisan Power.” 

In the energy fi eld, the “levelized” costs of new renewable electricity 

technologies remain substantially higher than conventional coal and 

natural gas-fi red fossil power plants, according to the U.S. Energy 

Information Administration. For plants entering service in 2016, 

these estimates suggest that while the costs of conventional coalfi red plants going online in 2016 would come in at about $95 per 

megawatt hour (MWh), those for onshore wind generation clock in at 

$97, for geothermal at $101, and for advanced nuclear at $113. Solar 

PV generation will run to $211, offshore wind $243, and solar thermal 

to $312. See U.S. Department of Energy, “2016 Levelized Cost of New 

Generation Resources from the Annual Energy Outlook 2010” (Energy 

Information Administration). Available at www.eia.doe.gov/oiaf/aeo/

electricity_generation.html. The International Energy Agency similarly 

writes that “a global revolution is needed in the ways that energy 

is supplied and used” and outlines detailed roadmaps for both the 

incremental and dramatic innovations necessary to enable “all countries 

to put in motion a transition to a more secure, lower-carbon energy 

[system], without undermining economic growth.” International Energy 

Agency, “Energy Technology Perspectives 2008” (Paris, 2011). 

46. For an early review of the literature see David Mowery and Nathan 

Rosenberg, “The Infl uence of Market Demand upon Innovation: A Critical 

Review of Some Recent Empirical Studies,” Research Policy 8 (2) (1979). 

More recent treatments of the interplay of “induced” and “pushed” 

innovation include: Adam Jaffe, Richard Newell, and Robert Stavins, 

“Environmental Policy and Technological Change,” Environmental 

and Resource Economics 22 (1-2) (2002); Adam Jaffe, Richard Newell, 

and Robert Stavins, “A Tale of Two Market Failures: Technology and 

Environmental Policy,” Ecological Economics 54 (2005): 164–174; Gregory 

Nemet, “Demand-Pull, Technology-Push, and Government-Led Incentives 

for Non-Incremental Technical Change,” Research Policy 38 (2009): 

700–709; and David Popp, Richard Newell, and Adam Jaffe, “Energy, the 

Environment, and Technological Change.” Working Paper. (Cambridge: 

National Bureau of Economic Research, 2009). See also Duderstadt 

and others, “Energy Discovery-Innovation Institutes;” Hayward 

and others, “Post Partisan Power;” and Matt Hourihan and Robert 
SIZING THE CLEAN ECONOMY | ENDNOTES 61

Atkinson, “Inducing Innovation: What a Carbon Price Can and Can’t Do” 

(Washington: Information Technology and Innovation Foundation, 2011).

47. Among the numerous market failures and barriers that prevent private 

fi rms from adequately investing in the development of new, high-risk 

energy and environmental technologies and business models are: 

the high relative price of new technologies; knowledge spillover risks; 

uncertainty about the present and future regulatory environment and 

prices; the heavy requirements of new infrastructure required by many 

new energy technologies; and the scale and long time-horizon of many 

projects. See Marilyn Brown, “Market Failures and Barriers as A Basis 

for Clean Energy Policies,” Energy Policy 29 (2001): 1197–1207; Jaffe and 

others., “A Tale of Two Market Failures;” Atkinson and Wial, “Boosting 

Productivity;” and Duderstadt and others, “Energy Discovery-Innovation 

Institutes.” 

48. See, for example, Newell, “A U.S. Innovation Strategy for Climate Change 

Mitigation” and Duderstadt and others, “Energy Discovery-Innovation 

Institutes.” See also American Energy Innovation Council, “A Business 

Plan for America’s Energy Future” (Washington, 2010); President’s 

Council of Advisors on Science and Technology, “Report to the President 

on Accelerating the Pace of Change in Energy Technologies Through an 

Integrated Federal Energy Policy” (The White House, November 2010); 

and Heyward and others, “Post Partisan Power.”

49. K.S. Gallagher and L.D. Anadon, “DOE Budget Authority for Energy 

Research, Development, and Demonstration Database,” Energy 

Technology Innovation Policy, John F. Kennedy School of Government, 

Harvard University, March 3, 2011. Figures reported are the sum total 

of the “Total Energy Technology RD&D” and “Basic Energy Sciences” 

budgets in 2005 dollars. The assessment here includes Basic Energy 

Sciences (BES) (while others do not) because BES funds some of the 

Department of Energy’s most innovative programs beyond ARPA-E like 

the Energy-Regional Innovation Clusters (E-RIC) and Energy Frontier 

Research Centers (EFRCs), in addition to energy-related fundamental 

research at institutions across the country. Other transparent and 

similarly legitimate tabulations choose to exclude BES and arrive at 

lower estimates of energy R&D accordingly. The Energy Innovation 

Tracker at http://energyinnovation.us/ is a particularly good resource. It 

should be noted too that the Recovery Act has already pumped over $22 

billion into the third and growing “D:” deployment. 

50. See Duderstadt and others, “Energy Discovery-Innovation Institutes” 

and American Energy Innovation Council, “A Business Plan for America’s 

Energy Future.” See also Mark Muro and Sarah Rahman, “$15 billion: The 

New Energy Target.” The Avenue, a blog of The New Republic, November 

2, 2009.

51. Organization for Economic Cooperation and Development iLibrary, 

“Government Budget Appropriations or Outlays for R&D by 

Socioeconomic Objective,” accessed May 11, 2011 and available at www.

oecd-ilibrary.org/statistics. Includes federal energy research and 

development (and excludes demonstration) spending as reported by 

member countries to the OECD. International comparison only available 

through 2009. 

52. The National Center for Science and the Environment’s “Handbook of 

Federal Funding for Environmental R&D – FY 2011” tallies $9.1 billion 

in total federal environmental R&D funding in 2010 spread across 11 

agencies—a considerable number. The largest sponsor of environmentrelated R&D is the Department of Energy, whose efforts encompass 

mainly renewable energy and energy effi ciency projects meant to reduce 

the environmental impact of energy production and consumption, which 

have been growing swiftly since 2006 but we categorize as energy R&D. 

Much of the R&D conducted by other signifi cant sponsors like NASA, 

NOAA, and NSF we consider basic research rather than applied R&D. 

The subtle distinction here is between invaluable basic research into 

how the climate is changing from NASA and NOAA, and more marketoriented applied research into and development of technologies that can 

mitigate change, for example. This report’s focus on the production of 

goods and services with an environmental purpose aligns closest with 

EPA’s R&D portfolio, though surely spillover benefi ts accrue from the 

Department of Defense’s efforts to reduce its environmental impact and 

the Department of Agriculture’s water management innovations, for 

example, as well. 

53. Organization for Economic Cooperation and Development iLibrary, 

“Government Budget Appropriations or Outlays for R&D by 

Socioeconomic Objective,” accessed May 11, 2011 and available at www.

oecd-ilibrary.org/statistics. Includes research and development spending 

with an environmental objective, as reported by countries to the OECD. 

International comparisons only available through 2009. 

54. See Dan Kammen, “The Case for State RD&D Programs,” presentation 

made at the National Governors Association State Workshop on Clean 

Energy Research, Development, and Demonstration (March 2008).

55. See Jim Duderstadt and others, “Energy Discovery-Innovation 

Institutes.”

56. In August 2009, the DOE established 46 Energy Frontier Research 

Centers comprising universities, national laboratories, non-profi t 

organizations, and for-profi t fi rms. These Centers were funded at $2-5 

million per year for a 5-year initial award period. For more information, 

see DOE’s Energy Frontier Research Centers website at www.er.doe.

gov/bes/EFRC/index.html. Modeled after the Department of Defense’s 

Defense Advanced Research Projects Agency (DARPA), the DOE’s 

ARPA-E program was created by H.R. 364 in 2007 but only allocated 

a budget of $400 million in April 2009 through ARRA. Like DARPA, 

ARPA-E identifi es game changing ideas and funds them. At least six 

ARPA-E projects, ranging from solar and wind to advanced batteries 

have gone on to win additional backing from venture capitalists. For 

more details, see www.arpa-e.energy.gov/. In FY 2010 budget, DOE 

requested fi nancing for Energy Innovation Hubs in eight areas: smart 

grid, solar electricity, carbon capture and storage, extreme materials, 

batteries and energy storage, energy effi ciency buildings, nuclear 

energy, and fuels from sunlight. Thus far, three hubs have been 

launched: the Energy-Effi cient Buildings System Design Hub run by 

the Greater Philadelphia Innovation Cluster (GPIC), led by Penn State 

University; the Fuels from Sunlight Energy Innovation Hub run by 

the Joint Center for Artifi cial Photosynthesis, led by Caltech; and the 

Nuclear Energy Modeling and Simulation Energy Innovation Hub run 

by the Oak Ridge National Laboratory. For details, see www.energy.gov/

hubs/index.htm.

57. For general information on the WITC, visit www.epa.gov/wtic/index.html. 

See also “Administrator Jackson, SBA Administrator Mills Announce 

launch of Water Technology Innovation Cluster” (U.S. Environmental 

Protection Agency Press Release, January 18, 2011).

58. See www.eesi.org/fy-2011-budget-compromise-cuts-fundingenvironmental-energy-programs-19-apr-2011.

59. The Obama administration’s FY 2012 budget request includes $100 

million to continue supporting the 46 Energy Frontier Research Centers; 

$550 million for ARPA-E; and $146 million to support the three existing 

Energy Innovation Hubs and to establish three new Hubs in the areas of 

batteries and energy storage, smart grid technologies and systems, and 

critical materials. See www.energy.gov/news/10064.htm.

60. For information on the Clean Energy Innovation Consortia proposal see 

www.energyinnovationconsortia.org/. 

61. For the concept of a Water Innovation Center, see G. Allen Burton and 

others, “Leveraging the Great Lakes Region’s Water Assets for Economic 

Growth” (Washington: Brookings Institution, 2010). 

62. For discussion of these and other revenue ideas see Hayward and 

others, “Post Partisan Power” and the President’s Council of Advisors on 

Science and Technology, “Report to the President on Accelerating the 

Pace of Change in Energy Technologies Through an Integrated Federal 

Energy Policy” (Washington: 2010). See also Hundt and Mann, ”Rebuild 

American Infrastructure?“ and Zoli and Rothstein, ”Repatriation to 

Accelerate Clean Energy.“

63. For background on state efforts in clean energy RD&D, see Daniel 

Kammen, “Opportunities for States in Clean Energy Research, 

Development & Demonstration,” (National Governors Association, 

2008). This report identifi ed nine states as having dedicated 

clean energy RD&D funds: California, Connecticut, Florida, Illinois, 

Massachusetts, Minnesota, New Jersey, New York, and Wisconsin. See 

also Escobar and Gander, “Clean and Secure State Energy Actions,” 

which lists state-by-state actions on clean energy RD&D between 

July 2008 and May 2010. State efforts in clean energy RD&D can be 

broadly categorized under direct investment in research; supporting 

incubators; establishing seed funds to bridge funding gap between 

lab research and venture funding; and supporting demonstration 

projects. States’ direct investment in research is mostly achieved 

through the creation and funding of research centers within state 

universities. Examples include the Florida Solar Energy Research 

Center, Oregon’s Built Environment & Sustainable Technologies Center 

(BEST), South Dakota’s 2010 Research Centers, and Virginia’s Coastal 

Energy Research Consortium (VCERC). States also provide support to 

cleantech incubators that provide guidance, technical assistance, and 

consultation to companies to help them develop and commercialize 

clean technologies. Examples of this include the Colorado Collaboratory 

and NYSERDA’s Clean Energy Business Incubator program. Moving along 

the cleantech RD&D continuum, states also provide seed funds to help 

companies develop and commercialize their products and services. 

Some state examples are: Iowa Power Fund supporting research, 

development, commercialization, and deployment of biofuels, renewable 

energy technologies, and energy effi ciency technologies; MassCEC’s 

Investments in the Advancement of Technology program that makes 

venture capital equity investments in promising early-stage clean energy 

companies that are developing and commercializing technologies; 

and the Edison Innovation Clean Energy Fund that helps New Jersey 

companies in demonstration projects and developmental and ancillary 

activities necessary to commercialize energy effi ciency and renewable 

energy technologies. Typical state awards in this category can range 

anywhere from $100,000 up to $500,000. Finally, some states can 

maintain dedicated grants and awards supporting demonstration 

projects. These include the Connecticut Clean Energy Fund’s Operational 

Demonstration Program; the Delaware Green Energy Fund’s Technology 

and Demonstration Program; Massachusetts’ Catalyst Program; and 

South Carolina’s Renewable Energy Grant program, which provides 

matching grants for demonstration projects. Awards for demonstration 

projects can range from $40,000, as in the Massachusetts example, to 

$500,000, as in the Connecticut example. 

64. For background on the state clean energy funds, see Lewis Milford 

and others, “Clean Energy and Economic Development: How Existing 

and New State Clean Energy Funds Could Become the Engines of 

Job Growth, Industry Creation, and Exports” (Washington: Brookings 

Institution, forthcoming).

65. Deutsche Bank Climate Change Advisors, in a similar discussion, 

argues that “`TLC’—transparency, longevity, and certainty—drives 

investment.” They say: “Investors need transparency in policies to create 

understanding and a level playing fi eld. Longevity means policy has to 

match the timeframe of the investment and stay the course. Certainty 

refers to knowing that incentives are fi nanceable and can be trusted 

in the fi nancial return calculation and again are likely to be maintained 

over the course of the investment. TLC should result in a lower cost of 

capital for projects while still delivering a fair and market-related return 

to capital.” See DBCCA, “Investing in Climate Change 2011.”
62 THE BROOKINGS INSTITUTION | METROPOLITAN POLICY PROGRAM

66. They do this by facilitating dense knowledge fl ows, the sharing of 

vital resources, and the matching of specialized workers to fi rms. In 

one infl uential discussion, the urban economist Gilles Duranton has 

identifi ed three mechanisms by which clusters work: learning, sharing, 

and matching. Learning is facilitated in clusters as workers share 

knowledge with one another, switch fi rms, or create start-ups after 

leaving an older fi rm. Clustered fi rms share a number of potentially 

vital resources like specialized suppliers or clients, organizations 

(e.g. university departments, research organizations, grant-making 

foundations), infrastructure (e.g. roads, ports, and even offi ce buildings), 

labor, training programs, and a favorable policy environment. Finally, in a 

clustered environment, it is easier for workers to match their specialized 

skills with the right fi rm or vice versa. See Gilles Duranton, Philippe 

Martin, Thierry Mayer, and Florian Mayneris, The Economics of Clusters: 

Evidence from France (Oxford: Oxford University Press, 2010).

67. For more extensive discussion of the signifi cance of regional industry 

clusters see, among other literature, Mark Muro and Bruce Katz, “The 

New `Cluster Moment:’ How Regional Innovation Clusters Can Foster the 

Next Economy” (Washington: Brookings Institution, 2010). 

68. For a discussion of the nature and economic importance of regional 

industry clusters see Muro and Katz, “The New `Cluster Moment.’”

69. For a review of recent federal cluster offerings see Muro and Katz, “The 

New `Cluster Moment.’” Note that “clean” and “green” initiatives have 

fi gured among the winners of several of these initial offerings. Three 

of the 10 “Innovation Economies” that received SBA Regional Cluster 

Initiative pilot grants last fall involved clean industries. These ranged 

from the Carolinas’ nuclear cluster to Connecticut’s hydrogen fuel cell 

coalition and the Illinois Smart Grid cluster. Likewise, the Oregon Built 

Environment and Sustainable Technologies Center is a partner in one of 

the six consortia that won EDA’s i6 Challenge.

70. For information on the Energy Regional Innovation Cluster for effi cient 

buildings systems, see www.energy.gov/hubs/eric.htm. For information 

on the i6 Green Challenge, see www.energy.gov/news/10169.htm.

71. For information on various cluster- or region-focused state clean 

economy development initiatives, see the following websites: Colorado: 

www.coloradocollaboratory.org/; New York: www.nyserda.org/

publications/2010_Strategic_Plan.pdf; Oregon: www.oregonbusinessplan.

org/Industry-Clusters/About-Oregons-Industry-Clusters.aspx. 

72. In FY 2010 the EDA, SBA, and USDA made available less than $150 

million in small grants for regional innovation clusters programming. 

In that year, the EDA received 83 applications for grants under the i6 

Challenge and made six awards. This spring, the agency had by early 

May received 140 letters of intent to apply for the i6 Green Challenge, 

which will also make just six awards. Correspondence with John 

Fernandez, EDA administrator, April 29, 2011 and May 2, 2011. 

73. Duderstadt and others, “Energy Discovery-Innovation Institutes.” 

74. For a view of these matters across multiple sectors see Mark Muro 

and Kenan Fikri, “Job Creation on a Budget: How Regional Industry 

Clusters Can Add Jobs, Bolster Entrepreneurship, and Spark Innovation” 

(Washington: Brookings Institution, 2011).

75. One-third of the current 400,000 jobs in the electric power industry will 

become vacant by 2013, following a wave of baby boomer retirements, 

and will need to be replaced with well-trained workers skilled in various 

clean energy technology operation. See the National Commission 

on Energy Policy, “Task Force on America’s Future Energy Jobs” 

(Washington: October 2009). A Lawrence Berkeley National Laboratory 

report projects a two- to four-fold increase in the size of the energy 

effi ciency sector between 2008-2020, with workforce need reaching 

a 220,000 person-year equivalent (PYE) in a low growth scenario to a 

380,000 PYE in a high growth scenario in 2020. See Charles Goldman, 

Jane Peters, Nathaniel Albers, Elizabeth Stuart, and Merrian Fuller, 

“Energy Effi ciency Services Sector: Workforce Education and Training 

Needs” (Berkeley Lawrence Berkeley National Laboratory, 2010). The 

American Solar Energy Society estimates that renewable energy and 

energy effi ciency sectors combined would grow from 9 million in 2007 

to 16.3 million jobs by 2030, assuming no new federal-level clean energy 

policy initiatives. See Roger Bezdek, “Green Collar Jobs in the U.S. and 

Colorado: Economic Drivers for the 21st Century” (Boulder: American 

Solar Energy Society, 2008). 

76. See Michael Fletcher, “Retrained for Green Jobs, but still waiting on 

work.” The Washington Post, November 22, 2010. See also, Abby Gruen, 

“NJ Green Jobs Creation Slow, Despite Grants.” The Newark Star-Ledger, 

April 7, 2010. According to a recent state-backed University of California, 

Berkeley report, California’s job market in the energy effi ciency sector 

will remain tight through 2020 and, rather than funding training 

programs for new workers, the focus should be on upgrading the 

energy effi ciency skills and knowledge of the incumbent workforce. See 

Carol Zabin and others., “California Workforce Education & Training 

Needs Assessment” (Donald Vial Center on Employment in the Green 

Economy, University of California, Berkeley, 2011). The concerns about 

“too many workers, too few jobs” seem especially troublesome in the 

backdrop of signifi cant infusion of ARRA dollars for purpose of job 

training and preparing workers for careers in clean economy. Through 

ARRA, the Department of Labor has allotted $500 million, across 

fi ve categories, for clean energy workforce training. The Department 

of Energy has provided up to $100 million for smart grid workforce 

training. In addition, many states are also using portions of their State 

Energy Program and Weatherization Assistance Program funding for 

clean energy workforce training. For more details, see Devashree Saha, 

“Enhancing State Clean Energy Workforce Training to Meet Demand” 

(Washington: National Governor’s Association Center for Best Practices, 

2010).

77. See, for example, National Commission on Energy Policy, “Task Force 

on America’s Future Energy Jobs” and Saha, “Enhancing State Clean 

Energy Workforce Training to Meet Demand.”

78. For background on the “regional innovation program’ included in the 

AmericaCOMPETES reauthorization act last year, see Mark Muro, 

“AmericaCOMPETES: Pass It, Nevertheless.” The Avenue, a blog of The 

New Republic, December 21, 2010. 

79. For broader discussions of the regional or metropolitan focus of the U.S. 

economy, see Bruce Katz, Jennifer Bradley, and Amy Liu, “Delivering the 

Next Economy: The States Step Up” (Washington: Brookings Institution, 

2010) and Bruce Katz and Jennifer Bradley, “Metro Connection.” 

Democracy 20, Spring 2011.

80. For more comprehensive discussions of federal, state, and regional 

cluster dynamics and policy see Muro and Katz, “The New `Cluster 

Moment,’” and Muro and Fikri, “Job Creation on Budget.” 

81. Muro and Fikri, “Job Creation on Budget” outlines one possible design 

for a competitive state cluster grant program. 

82. All of the discussion of the regional analysis and coordination agenda 

draws heavily on Muro and Katz, “The New `Cluster Moment.’”

83. Puget Sound Regional Council and Brookings Institution, “Innovation 

Meets Demonstration: A Prospectus for Catalyzing Growth in Puget 

Sound’s Energy Effi ciency Technology Cluster” (Washington, 2011).

84. See the Climate Prosperity Project, Inc. at www.climateprosperityproject.

org/pilot_regions.htm.

85. Depending on the region, clean economy development activities 

may be facilitated or led by entities as varied as a regional economic 

development entity, a metropolitan planning organization, a university 

or consortia of universities, a formal cluster organization, or trade 

association.

86. For an overview of Climate Prosperity’s activities in the four metro 

regions, see www.climateprosperityproject.org/.

87. For an overview of Syracuse Tech Garden’s activities, see www.

thetechgarden.com/cleantech.

88. For an overview of Milwaukee Water Council’s activities, see www.

thewatercouncil.com/.

89. For an overview of CleanTECH San Diego’s activities, see www.

cleantechsandiego.org/.

90. See, for instance, Zabin and others., “California Workforce Education & 

Training Needs Assessment.” 

91. See the Institute for Sustainable Communities’ Case Study on “Los 

Angeles Trade-Technical College: A Model of Workforce Development 

in the Energy/Utility Sector” (May 2010). In a more rural setting the 

Renewable Energy Technology Program at Columbia Gorge Community 

College in Oregon emerged out of a dialogue with the private sector 

after wind manufacturers began opening wind farms in the region and 

seeking trained workers. For more details see SEED Center, “Columbia 

Gorge Community College Leads Nation in Wind Training,” available at 

www.theseedcenter.org/Colleges-in-Action/Success-Stories/ColumbiaGorge-Community-College-Leads-Nation-in-W.

92. See the Institute for Sustainable Communities’ Case Study on “Going to 

the Source: Seattle Turns to Employers on Green Job Potential and Job 

Training” (April 2010). 
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PHOTOGRAPHS: © ISTOCKPHOTO AND GETTY IMAGES
Acknowledgments

About the Metropolitan Policy 

Program at Brookings

Created in 1996, the Brookings Institution’s Metropolitan 

Policy Program provides decision makers with cutting-edge 

research and policy ideas for improving the health and 

prosperity of cities and metropolitan areas including their 

component cities, suburbs, and rural areas. To learn more 

visit www.brookings.edu/metro.

For More Information

Mark Muro

Senior Fellow and Policy Director

Metropolitan Policy Program at Brookings

202.797.6315

mmuro@brookings.edu

Jonathan Rothwell

Senior Research Analyst

Metropolitan Policy Program at Brookings

202.797.6314

jrothwell@brookings.edu

Preparation of this paper and of the database that underlies 

it has been an unusually collaborative undertaking.

For expert analytic partnership the Brookings team is 

grateful to the dogged work of Mitchell Horowitz and Martin 

Grueber at Battelle, supported by John Vitou, Dawn Calvert 

and Ryan Helwig. 

For his pathbreaking work on clean economy measurement and for many contributions to this work the BrookingsBattelle team is also appreciative of Doug Henton of 

Collaborative Economics.

Otherwise, we would like to acknowledge several other 

invaluable contributions. For critical guidance, critiques, 

and nudges we are indebted to those who consulted with 

us on technical issues: Alan Baum, Randy Becker, Roger 

Bezdek, Karen Chappel, Jane Evenson, Grant Ferrier, Tracey 

Grose, David Karpinski, Jed Kolko, Andrew Reamer, Ronald 

Shadbegian, Greg Tassey, Grahm Toft, Don Walls, Gregg 

Weeks, and Bob Weissbourd. 

For conversations with the Bureau of Labor Statistics 

team working on these issues we would like to thank Dixie 

Sommers and Rick Clayton. For hosting useful discussions 

on various aspects of this work at various stages we want 

to thank Jeff Finkle, Dick Fleming, Jesse Jenkins, and 

Andre Pettigrew. 

In addition, we would like to thank the following people 

for their varied and generous contributions: Laurie Actman, 

William Antholis, Robert Atkinson, Rebecca Bagley, George 

Bilicic, Drew Bond, Bill Bonvillian, Tom Burke, Michael Carr, 

Dan Carol, Tom Clark, Will Coleman, John Cleveland, Marc 

Cummings, Charles Ebinger, Todd Foley, Christina Gabriel, 

Sue Gander, Jeffrey Genzer, William Harris, Matthew 

Hourihan, Reed Hundt, Jesse Jenkins, Mark Johnson, Janet 

Joseph, David Karpinski, Linda Katehi, Richard Kauffman, 

Kei Koizumi, Nate Lewis, Arun Majumdar, Kristine Mazzei, 

Lew Milford, Jessica Morey, Adele Morris, Ted Nordhaus, 

Brian Overington, Ron Pernick, Roberto Porzecanski, Sean 

Randolph, Elizabeth Redmond, Peter Rothstein, Brian Sager, 

David Sandalow, Dan Sarewitz, Eric Schinfeld, Rich Sedano, 

Ryan Sharp, Mike Schwenk, Michael Shellenberger, David 

Terry, Elizabeth Thorstensen, Alison Wise, and Ethan Zindler.

At Brookings, the project authors want to thank Kenan 

Fikri and Alec Friedhoff for their hard work and sense of 

purpose as well as David Jackson for his editorial touch. 

Other colleagues who have gone above and beyond to help 

include: Rahsheeda Ali, Alan Berube, Jennifer Bradley, 

Sue Burnett, Shyamali Choudhury, John Fairbanks, Jeanine 

Forsythe, Marek Gootman, Rachel Harvey, Carrie Kolasky, 

Amy Liu, Mariela Martinez, Ellen Ochs, Alicia Posner, Rob 

Puentes, Neil Ruiz, Chad Shearer, Barbara Semedo, Karen 

Slachetka, Adie Tomer, Malina Tran, Jennifer Vey, Owen 

Washburn, and Howard Wial. And as always we thank 

Bruce Katz for his visionary leadership.

More broadly, the Metropolitan Policy Program 

at Brookings wishes to thank the Nathan Cummings 

Foundation, the General Electric Foundation, Living Cities, 

Inc., and the Surdna Foundation for their support of the 

program’s clean economy work. The John D. and Catherine 

T. MacArthur Foundation, the Heinz Endowments, the 

George Gund Foundation, and the F.B. Heron Foundation 

provide general support for the program’s research and 

policy efforts, and we owe them a debt of gratitude as well.

Finally, we wish to thank the program’s Metropolitan 

Leadership Council, a bipartisan network of individual, 

corporate, and philanthropic investors that provide us 

financial support but, more importantly, are true intellectual 

and strategic partners. While many of these leaders act 

globally, they retain a commitment to the vitality of their 

local and regional communities, a rare blend that makes 

their engagement even more valuable. 

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and, based on that research, to provide innovative, practical recommendations for policymakers and the public. The conclusions and recommendations of any Brookings publication are solely those of its author(s), and do not reflect the views of the 

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