green jobs: a special issue

7/28/2019 Green jobs: a special issue

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January 2013

M O N T H L Y L A B O R

U.S. Department of Labor U.S. Bureau of Labor Statistics


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U.S. Dparmn Labr

Sh D. Harris, Acing ScraryU.S. Burau Labr SaisicsErica L. Grshn, Cmmissinr

TheMonthly Labor Review is published monthly by the Bureau

of Labor Statistics of the U.S. Department of Labor. The

Review welcomes articles on employment and unemployment,

compensation and working conditions, the labor force,

labor-management relations, productivity and technology,

occupational safety and health, demographic trends, and other

economic developments.

TheReviewsaudience includes economists, statisticians, labor

relations practitioners (lawyers, arbitrators, etc.), sociologists,

and other professionals concerned with labor-related issues.

Because the Revie w presents topics in labor economics in

less forbidding formats than some social science journals,

its audience also includes laypersons who are interested inthe topics, but are not professionally trained economists,

statisticians, and so forth.

In writing articles for the Review, authors should aim at the

generalist s in the audience on the assumption that the specialist

will understand. Authors should use the simplest expositionof the subject consonant with accuracy and adherence to

scientic methods of data collection, analysis, and drawings

of conclusions. Papers should be factual and analytical, not

polemical in tone. Potential articles, as well as communicat ions

on editorial matters, should be submitted to:

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Monthly Labor Revie w

U.S. Bureau of Labor Statistics

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Washington, DC 20212

Telephone: (202) 6917911

Fax: (202) 6915908

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The Secretary of Labor has determined that the publication

of this periodical is necessary i n the transaction of the public

business requi red by law of thi s Depar tment .

The opinions, analysis, and conclusions put forth in articles

written by non-BLS staff are solely the authors and do not

necessarily reect those of the Bu reau of Labor Statistics or

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Schedule of Economic News Releases, February 2013

Date Time ReleaseFriday,Fbruary 01, 2013

8:30 AM Emplymn Siuain r January 2013

Tursday,Fbruary 07, 2013

8:30 AM Prduciviy and Css r Furh Quarr2012

Friday,Fbruary 08, 2013

10:00 AM Majr Wrk Sppags r 2012

usday,Fbruary 12, 2013

10:00 AM Jb Opnings and Labr urnvr Survy rDcmbr 2012

Wdnsday,Fbruary 13, 2013

8:30 AM U.S. Impr and Expr Pric Indxs rJanuary 2013


10:00 AM Exndd Mass Lays r Furh Quarr2012

Wdnsday,Fbruary 20, 2013

8:30 AM Prducr Pric Indx r January 2013


8:30 AM Cnsumr Pric Indx r January 2013


8:30 AM Ral Earnings r January 2013

Friday,Fbruary 22, 2013

10:00 AM Vlunring in h Unid Sas r 2012

usday,Fbruary 26, 2013

10:00 AM Mass Lays r January 2013

Subscribe to the BLS Online Calendar

Online calendar subscriptionautomatically updated:

I yu us a rcn vrsin an lcrnic calndar, yu may b abl sub-scrib h BLS Onlin Calndar.

S dails blw r usrs dirn yps calndars.

Insrucins r Oulk 2007 and Appl iCal Usrs:Click n his link:webcal://www.bls.gov/schedule/news_release/bls.ics(N: Link may sm b brkn i yu d n hav Oulk 2007 rAppl iCal insalld.)

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T BLS calndar cnains publicain das r ms nws rlass schduld b issud by h BLS nainal fc in upcming mnhs. I is updad

as ndd wih addiinal nws rlass, usually a las a wk br hirschduld publicain da.
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M O N T H L Y L A B O R

Volume 136, Number 1

January 2013

Green jobs: a special issue

BLS green jobs overview 3

BLS presents three new data collection activities: the Green Goods and Services (GGS) survey,GGS occupations (GGS-OCC) data, and Green Technologies and Practices (GTP) survey

Dixie Sommers

Te Green Goods and Services Occupational survey: initial results 26

GGS-OCC data provides employment and wage information on occupations in greenestablishments providing green goods or services

Zack Warren

Green technologies and practices: a visual essay 36

Audrey Watson

Workplace saety and health profles o occupations with green technology jobs 49

GTP survey data are used to examine industries and occupations that contain green jobs to deter-

mine the prevalence and details of workplace injuries for all jobs in those industries and occupations

Aaron Parrott and William Wiatrowski

Departments

Labor month in review 2Prcis 57Book review 59Current labor statistics 61

R E V I E W

Editor-in-ChieMichael D. Levi

Executive EditorEmily Liddel

Managing EditorTerry L. Schau

EditorsBrian I. BakerCharlotte M. IrbyCarol Boyd Leon

Book Review EditorJames C. Titkemeyer

Design and LayoutEdith W. Peters

ContributorsMonica R. GaborSerah A. HydeJames C. Titkemeyer


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Monthly Labor Review January 2013 3

Green Jobs Overview

BLS green jobs overview

Trough its green jobs initiative, BLShas developed its green jobsdenition and published inormation on green careers and results

rom three new data collection activities that measure the number ogreen jobs that produce green goods and services and the number ojobs related to the use o green technologies and practices

Dixie Sommers

Th c h cuy ww u -w y, y -

c c, wm-. T xc h cmy wu m cc . My uc c m, w u- h, m , uch C-

h G J Ac 2007.1T Amc Rcy RmAc 2009 c c u y c .2

A h m m, hw, c w u hum y , h h x u y . h h m, h Buu L Sc (BLS) -qu c u -c y (FY) 2010 .

I u qu, BLS wk wh h c kyz h uc u h . BLS - uc w mu m-ym w u whmy c c uc m h ccu- , wh ,

cmc c.3 I , BLS - cuc c my uy m h ccu w m c m .

Sc FY 2010, BLS h mmh , whch u h BLS uh c c

u m h w ccc: h G G Sc(GGS) uy, GGS ccu (GGS-OCC), G ch Pcc(GP) uy.

T GGS uy c h 2010,h U S h 3.1 m c (GGS) . GGS c-cu 2.4 c U.S. w y mym.4 T ch 2.3 m GGS , h ucc h 860,000 GGS . A

u 2011 w hcmMonthly Labor Review c.

GGS-OCC c h h-m h c h u mGGS h u 540,000 m m , u 208,000 -uc , 194,000 c m- u Nm 2011. Ih c h u, Zchy W

Dixie Sommers is Assistant

Commissioner in the Ofce o

Occupational Statistics and Em-ployment Projections, Bureau ofLabor Statistics. Email: [email protected].
mailto:sommers.dixie%40bls.gov?subject=mailto:sommers.dixie%40bls.gov?subject=mailto:sommers.dixie%40bls.gov?subject=mailto:sommers.dixie%40bls.gov?subject=


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Green Jobs Overview

4 Monthly Labor Review January 2013

cu GGS-OCC .T GP uy hw h, Auu 2011, u

h-qu u hm u chy cc. Axmy854,700 w h y wk wh m h

h h m ch cc (GP). Auy W uh hh-h m h GP uy h u u y.

T P Wwk c h u - y hh m ccu hcm h um GP .

T m h w c c hwBLS hw ch h h cc c w , , mm, wh h m. T c

w u y y cu h c m.

How BLS developed its green jobs defnition

T h BLS w - . BLS h hc h : mu c, m-u, u cc. A c wu cy um ccy,c wh h BLS m c cy. Amu wu wk wh u c-c: wu c uy m uy h

w BLS. Fy, h u cc wu m Oc Mm Bu c , w m cm h u h . T cc u cu h Nh AmcIuy Cc Sym (NAICS) h SOccu Cc (SOC).

T c wh w- h y x u y-c uy , ch uy z, h c, z. P h FY 2010 u

qu, BLS c wh S WkcAc h Emym Am- h G J Suy Gu. T Suy Guxm h x uy c u h u h um mum, y h qu u-u mu , m .5 Ahuhh my h Suy Gu wk w hS Wkc Ac, my whm w

c u h Am-c Rcy Rm Ac 2009, BLS u cc u. G

u y cuc C, Mch,O, Wh w uu xm.6

BLS xm uwy y hO*NE Ruc C; Bk Iu; h U.S.Dm Cmmc Ecmc Sc A-m; h Pw Ch u; G Ih,Ic.; h z.7 T Em G Sc Sc Hk m Eu, h -c cy h Eu U, y huccu mwk m mc cmc mum.8BLS cy xm hSuy Em G Sc cucy Sc C cu wh m hcy cc h cc xc.9

Du h ch c, BLS cu whh cy h U.S. Dm Ey, h Em Pc Acy, h Ec-mc Sc Am, h Cuc Em Quy ck y ch. Smy, BLS cu wh - uy u, c y h w- y u.

BLS w xc mc mh h c cy c cymk h

u, my, hh-ch . T wk w cuc h y 1980 h u m,m cy 2005.10 A wh , um mh y hh-ch , u - hh-ch u. A wh ,BLS h w c, w mu-, u cc (muy w u x , cu w cc- w cuc).

I 2004 cy m hh-ch u,u c cu h hh-ch u uy w . T c u,

uu (uc c), uc c:(1) hh c, , ch-c; (2) hh ch mmym; (3) uc hh-ch uc; (4) u hh-ch uc mh.11 T uu c c m h uu cch h BLS , cu h uqu h.

Fm h ch xm x -, BLS u h


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h wy cc. Ahuh h c c m, cm, h ucmmuy, u u h m y.

A cmm h huh h u cu-, hw, h -

h m. S c cmc cy w y uy c:w y, y ccy, u cu, u uc c.

A y h wk, BLS m h h m h c cu y my c ccu hmh m . BLS u h whh c hu h mc huc, c, wk cy h m, h u h wk m, .., h ccu.

BLS uh uc cmm h Federal Register Mch 2010.12BLS wch y m cmc c-y cu h c , whch wu uc u ccu. T w -ch (1) h uu ch, whch -hm h uc GGS cu h c

, (2) h c ch, whch -hm h u my y ucc cc cu h c .

T Federal Register c c h w -ch: I h uu ch, BLS cc wh

uc cc -c cc wh h m mc h uc c. T uu ch ,hw, wu c m c c

h y mc h m, huh huc c uc . T -c ch h c

. I h c ch, BLS cc whwhh h uc c h mc h m, u wh wh c -uc. T c ch y uy.Ech ch qu mum

w cu , wh m u h uc c.13

T c cc wm h Eu Em G ScSc Hk c NAICSu whch BLS c GGS c.

T h u wy c-z uc uy cy uh GGS m m -GGS. Such wu h BLS cmmuc cy -

wh c hu uy h u u h u .Exm uch U S D-m Acuu (USDA) C Oc, EyS, h Lh Ey Em

D (LEED) G Bu R Sym.T u Sc C

u h mh mu mym uc GGS. I h u h mh, h u-

y wu k wh h h u m c. T c

wu h h mym h -hm m h um uc h c. Sc C h mh cu cc x-c hw h u w y cy m h um GGS -uc. BLS ccu h h u h - xy h h mym, um hh u mu m -w c h cuc wh h hm.

BLS c 156 cmm h .T cmm w ummz - Sm 2010 Federal Register c h u h BLS .14 T - h uu c ch,h u cz uy y

GGS, h u h mh mu GGSmym. BLS m h Eu cc my h cu h uc m c h . BLS GGS y cmm u cyw h c h y xcu hu .

T BLS w: BLS h h u c-c w uy. G h:

A. J u h uc c h h m c

u uc.B. J whch wk u mkh hm uc c mmy y u w u -uc.

BLS h cc . I w c mw cu m c.


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Green Jobs Overview


T BLS h uu -ch (A) h c ch (B). Bcu hw ch mu y cu h u mukw x, hy . I

, BLS c GGS u m-u h uu ch c GP u mu hc ch. T c hw h -cu h uy h w.

S u h BLS my m u. T BLS c quy c, uch w, ummh, , cm huh c. S cmm h uBLS u uch c. Hw, BLS c cu h wu cy h c cy. BLS wu h u, xm, wh wk y wu hh uh h cu . Hw, u my um wk y, w, h c c m h BLS h m h w c h c. A xm u h -m u h P Wwk c h u, whch y hh m ccu h cm h um GP

.T BLS umcy cu

u u uu w c huh h uy ch. I, u uu u whh hy y -c h m. T u BLS cu c uc y h uy whchhy uc (cuu) whch h -m h ccu u whch c uc c, , (mucu, c, wh- ).

Sm c uc, uc c -cyc u c y h uy whch

h u uc. F xm, ccyc c uc h uy, cu h m ccu cyc u uc wh h uc. Bu h mucu, , c uc m c cycu cu uc, cu uh m m h cyc cccu.

T u xcu m h

GGS. cy h m cm wh y h .

Ecc w u c xcu c, m h c xcu u-

. G c mh ccy h cc w , cu SmG ch, cu h y ccycy, hw. Nuc w cu c h w hu m h m uc cc w. T cy-c w uc cy GGS cu u,mucu, cm, h c w m.

T 2007 NAICS u whch GGS c w uh wh h -.15 BLS h y w (x-) NAICS uy uc .Exh 1 hw h c GGS: y mw uc; y ccy; u uc m, hu uc, cyc u; u uc c; -m cmc, uc , ucw. T uy c whch c c c ch u-y xm. Wh h uc h2012 NAICS, h w c h w uycc w cu 325 u.

F ch 2007 NAICS c, 1 hw h um u c c c m h um h hm mym u c ch c. I-c uccu 23.7 c hm 20.0c w y mym 2011. Tc wh h h hm m-ym c GGS cuc (97.4 c hm 90.0 c mym); -w y cuu, y, h, hu (93.0 84.6 c); mm cm

(82.2 95.7 c). Fu c h h 10 c hm c (h h h h 10 c mym c):

wh (1.4 c hm 2.1c mym); whu(4.3 10.7 c); , m, c(5.5 8.8 c); (6.4 2.7 -c). A u c y c.N h h y h x whchh GGS uy c h c; hy -


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cu hm cuy uc GGS h um uch uc.

T BLS ch mu h c m, m whch w u cmm h :

I mu uc GGS,h BLS ch m GGS uc y -hm c u h BLS u wh GGS c. I hm uc m h y

c, c y uy cc h my uu u. I hm uy h BLS h c my uu,

uc h -c cu.

T c GGS , h cGP h c ch. F xm, hm mc my cu

h uc hu cy ccy. Bcu h , BLS h m cc m h um

ch cy GGS ch c-y GP.

Bcu BLS cc GGS GP huh w uy, h cu yh w uy my hm huc GGS u GP. T x h ukw.

T u u h mh m m-ym uc GGS, ySc C, qu c um, cu .

D cc cu y w y wk- xcu h -my h c wk. T m u m u h BLSu h m u uy.

Exhibit 1. Categories o green goods and services

G c cum cu ch m, , mcc. G c m u:

1. Energy rom renewable sources. Exm cu ccy, h, u m w uc. Ty uc cu w, m, hm, , c, hyw, muc

w.

2. Energy efciency. G c h u m y ccy. Icu y-cqum, c, u, hc, w uc c h m h y ccy u h ccy y u, uch Sm G ch.

3. Pollution reduction and removal, greenhouse gas reduction, and recycling and reuse. T uc ch

uc m h c u xc cmu m u hzu w m h m;

uc hu m huh mh h h w y y

ccy, uch ccy m uc uc; uc m h c w m cc, u, mucu, cyc, cm

w m ww.

4. Natural resources conservation. G c h u c u uc. Icu uc c c cuu u y; mm; , w, wc; mw mm.

5. Environmental compliance, education and training, and public awareness. T c h

c m u uc ch cc c uc w m u.


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Green Jobs Overview


C cuu cm. T BLSu m umym u-c x h , h c cuu m . BLS h x-m h cuu c u, hw, m h h cmh uh cc .

The GGS survey

mu h uu ch,BLS h GGS uy. T uy uc h um c wh uc GGSy uy h , , h Dc C-um. Cc h ccu GGS

2007 NAICS industry sectors and 2011 annual average number o establishments and employment, in and not inscope or the Green Goods and Services survey

2007NAICScode

Sector

Number odetailed industries

Number o establishments, 2011 Employment, 2011

In scopeNot inscope

In scope Not in scopePercentin scope

In scope Not in scopePercentin scope

Total, all industries 333 861 2,112,134 6,788,107 23.7 25,861,335 103,449,745 20.0

Sectors in scope

11 Agriculture, forestr y,shing, and hunting 56 8 89,170 6,711 93.0 985,293 179,206 84.6

22 Utilities 6 4 14,315 11,016 56.5 289,045 516,943 35.9

23 Construction 48 2 749,211 20,250 97.4 5,087,631 563,949 90.0

3133 Manufacturing 127 345 81,997 259,955 24.0 3,495,456 8,550,659 29.0

42 Wholesale trade 1 70 8,694 605,226 1.4 117,298 5,428,579 2.1

45 Retail trade 1 74 16,623 243,944 6.4 133,247 4,788,874 2.7

4849 Transportation andwarehousing 10 47 10,769 241,686 4.3 534,698 4,440,242 10.7

51 Inormation 15 17 77,136 71,474 51.9 1,377,956 1,309,756 51.3

52 Finance and insurance 3 38 3,468 460,875 .7 33,258 5,499,322 .6

54 Professional, scientic, andtechnical services 21 27 628,903 409,833 60.5 5,055,118 2,724,229 65.0

55 Management of companiesand enterprises 1 2 44,146 9,530 82.2 1,832,345 82,198 95.7

56 Administrative and supportand waste management andremediation services 13 31 126,278 348,817 26.6 1,042,011 6,738,414 13.4

61 Educational services 5 12 27,946 139,670 16.7 3,704,528 8,387,156 30.6

71 Ar ts, enter tainment, andrecreation 3 22 7,211 123,438 5.5 202,388 2,107,575 8.8

81 Other services (except public

administration) 16 33 184,127 1,134,645 14.0 1,027,015 3,414,913 23.1

92 Public administration 7 22 42,140 95,557 30.6 944,048 6,361,627 12.9

Sectors entirely not in scope

21 Mining, quarrying, and oil andgas extraction 29 32,560 730,047

53 Real estate and rentaland leasing 24 346,185 1,954,964

62 Health care and socialassistance 39 826,075 18,362,350

72 Accommodation andfood services 15 632,006 11,447,468

NOTE: Dash indicates data not applicable.SOURCES: Green goods and services industry list and establishment

and employment data from the BLS Quarterly Census of Employmentand Wages.

Table 1.


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cu h x uc.

Overall survey design. T GGS uy m:

GGS uc c u h

c h NAICS c uc .

T x whch hm hu uc GGS c y hh h hm u c m uch c.

Ru h xy h h hhm mym h c whuc GGS.

A u, h GGS uy cc m

mym h u m GGSm m hm h u-. N, m u, u u

whu u k h c- mym uc GGS. Tu,h uy u c h h mym h u , ccy cy.

GGS mym m cu h u u h hm. F xm, - u mh h u m h GGS. I h c, cu,

cu , m, c, c.

Survey scope. T c h GGS uy y h uy uh wh h BLS

, c ummz 1. B wh h cc 2011, h2012 NAICS u w u.

Questionnaire design and testing. Dm h u-y qu qu h -c h y c h qu h h u. Qu-

m cu - m whh my h h m w w , m whh h qu- cy cy h m GGS -, m h m h cm h uy. T cm h - cu u h m u -y h mym uc GGS.

T GGS uy m c 14 qu-, ch uy c u

u. F ch y c, hu qu h xm xc uc h u c y h qu.F xm, h cuc c qu

whz c u

uc USDA c c c, whch - y h cuu c qu.16

R k whh h hmuc c h m h GGS c h qu. T c- m h BLS hw xh 1, wh m cy cc.F ch cy, h qu xm u h cc y c. T xm cu -c uy , uch Cuc ISO21930:2007cm u CucLEED c u hw h cucc qu h y ccy cy.

T cy cu h cy h y h c hy -uc h my . I h c hyuc y c, hy k cm h u qu.

T u qu cu y h h hm c y h cu

A 15 h c y. T k whh h hm h y u u

h c y m h c h qu. I y, h h u m h qu. Oy h h c u m GGS qu, h u. I h hm h u, m, , -u -hm, k h c

wk my wh my wk uc h uc c .

Sample design. T GGS uy m c -my m h BLS Quy Cu Emym

W (QCEW) u m m. P m hm cu, yhm wh mym h c 12mh xcu. T QCEWcm m um-ym uc x c h my whu c, w c uc Umym Cm F Emy.

T QCEW cu c chhm, uch m, , mhy my-m, uy cc, hc m.


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Green Jobs Overview


Bcu h x uc GGS mu h GGS uy w ukw y -qu, BLS u u h cuhm kw uc m k c, ccy uc h -

m. T u , h m- hm , cu u 13,000 -chm cm xmy mmy. BLS h hm (u) y huh ch h I u m m y -

m uh m. Sm u m h w c wh hh y h h hu.

T GGS uy m u 120,000 h-m. F h 2011 uy, h m cu x-my 116,000 hm c m h cqu 2010 QCEWm xmy 4,000 w-y c hm c m h uh qum w u c c h qu. T m c y uy. B- wh h 2012 uy, h GGS m h , ch c xmy 40,000m u. w h h m whh u y m uc m ch mym. D h m h GGS uy chc N.17

I h m c u m,

w k mxmz h w hGGS uy m h x Occu Em-ym Sc (OES) uy m. Sccy, cu w c GGSm u wh m OES m u.18 T -cm cu w u m GGS mym w y ccu, c h x uc.

Data collection.BLS cuc h GGS uy 2011 m uy, wh h w-u. F h 2012uy, I w . R

70.6 c 74.1 c w ch h 2010 2011 uy, cy.

Estimation. Fm h GGS uy , BLS ucm y y h u mymh y hm m-ym h hm. Em cu

w h u uc h um uc GGS h um h , y -uy, , uc wh. D

h m cu h GGS uychc N.19

Publication. T GGS uy uh u-y, wh 2010 uh Mch 2012 2011

hcm y 2013. T cu GGSmym y uy y u-c wh h y uy c h Dc Cum. GGS mym h mym . A ch w h BLS uc w, mu m . Hhh u w cu hcmMonthly Labor Review c.

Limitations. Ph h m c m h GGS uy h u u h

xy mu mym ucGGS. A y , h c c cmm h Federal Registerc h

.Bcu m hm h m h

uc c, m whch hh , BLS mh cuy h mym wh h -hm. Sm h xc Sc C-, u , BLS u h hmh uc h ch c cuy mym c- wh y uc c.20 F xm,hm h my wh wk hy uc m u

wh c cc uc c. BLSu u h m m y - um h .

T u h u mym h y -c hm uc h GGS -GGS.I hm y uc c-, u mym h wu 100 c h hm wu cu

GGS . U m h 2010 GGS uy, ch 1 m y h h cy (u mym) uc GGS.21 Au 5.6 -c -c hm 100 c h cy w GGS. T hmh 7.2 c mym m -c -hm 59.0 c GGS mym.

M hm cy, c-cu 81.6 c -c hm 69.9 c mym. T hm,


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Monthly Labor Review Januar y 2013 11

cu, h GGS mym. Bw h 0 c 100 c cy hm h m h cy w ucGGS. T hm huhu h

c, wh h cc 7.3 c wh 1 20 c h cy GGS, ccu 15.5 c mym -c hm 6.9 c GGS mym.

Oh m h GGS uy h xcu -my u my wk, cmc cuu, ck y wh h GPuy u. T m w cu .

GGS occupational data

I h GGS uy u y uy, BLS

uc h ccu w - uc GGS. BLS ccmh h y x- h x OES uy cc ccumym w m my h -hm h GGS uy m cu h . T u, GGS-OCC, mym

w y ccu hm wh hcy GGS. GGS-OCC cu hm wh m cy GGS

cy. T c c hw w c-c h m uc, wh w h OES uy.

T OES uy mu m uy h c-

c w y wk m -hm, uc mym w m u 800 ccu. T m y hc y uy wh. Tuy cu xmy 200,000 hm ch x mu k 3 y uycc h m 1.2 m hm. D cc c mh My Nm, mym m chmk h My Nm mym .

Survey scope and questionnaires. T GGS-OCC h

h m c h GGS uy, whch cmy c h OES uy, wh h xc -cuu. OES cu h cuu c-, u h h cu h GGSuy c. T um h OES uy m,cu h w uc, cu h - cuu u.22

T uc GGS-OCC w - h x OES uy . Tu, h m OESuy m u cc u OES , w

Chart 1. Percent distribution o in-scope establishments and employment and green goods and servicesemployment by share o activity in green goods and services, 2010

Percent

Percent of activity in green goods and services

Percent

90

80

70

60

50

40

30

20

10

0

90

80

70

60

50

40

30

20

10

00 120 2140 4160 6180 9199 100

SOURCE: U.S. Bureau of Labor Statistics.

All in-scope establishments

Employment in all in-scope establishments

Green goods and services employment


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12 Monthly Labor Review Januar y 2013

u h um m. Aw m w u h cu-u c u.

Sample design. T GGS-OCC u

hm h h h GGS uy m h h u OES m h OES u-m. T u m h m GGS-OCC (1) c h OES m, (2) c hGGS m, (3) mxmz h w h OES GGS m, (4) um h OES m

wh hm GGS u OES. S 3 wc , whch cm cu wuc h GGS m c mxmz h wh h OES m.

S 4 cy cu, wh h mxmz, um m

uc c, cu h cuuc u, cc hm- c m. T um m um h GGS m u.

I , h m h OES m c wch m mu u. T ch qu h cm u h c h mu ccu w u c- uqu h m m c .

T u m u m GGS-OCC cu y 90,000 u, whch u 64,700

w h u OES m u 25,000 c-u h um m. Sm cu cu h GGS-OCC chc N.23

Data collection. BLS cc h umm h u OES uy. Suy m y m, wh x h w-u. R- cu m, I, h, m, cc y . D c h SOC.24 F h uy cu h GGS-OCC , 66.4 c h-m , 59.9 c wh

mym. T c w h h 78 80c hm uuy ch h u OES uy. T c h GGS-OCC w, cu c- whh h OES hGGS uy, c h uc h w.

Estimation. Dm GGS-OCC m h qu hw ccu mym whu m hm h h y

h u mym GGS. BLSxm w . T w ucm h c u mymh: , m , cy. Tc w u h mh m h GGS u-

y, h , y h cy h my-m y ccu ch hm.

BLS c h h c wy - h ccu wk ucGGS. T m h cy hw hum y ccu kw uc GGS. U h c , h-m uc h GGS -GGS, mu -um h h ccu mx wk uc hGGS h m h uc h -

c. T wu m u h mhm cuu. F xm, m ccuh u my c y , uch hc , m mym wu hw hm wh h ccu h 100 c u m GGS.

cmu m, BLS mch ch u h GGS-OCC m m h GGSuy h u mym h. Txc u h c 48.6 -c h h hm h h h GGS OES uy. uc , BLS u mu wh c u-

m.

25

I , OES chmk w u- m cu w GGS-OCC m.

Publication. BLS uh h GGS-OCC Sm 2012. T cu ccumym w h cyc ( , m , ). A ch w h BLS uc w, mu m . Hhh u hc h u y Zchy W. D cc

cu, wh Nm 2012 uc h 2013.

Limitations. Ahuh BLS h uh u h cy c, h u ccu hGGS uy. A , BLS m h -y h u mym h ccumym wu uc u h my cu u. Ahuh c m,


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ccu y u cy mwh cm-x qu cu y.

T y w c 48.6 c uc h mu m h m quy cy c uc.

The GTP survey

mu h c ch,BLS h GP uy. T c my u-

y uc hm u GP h ccu wk wh m h hh m GP.

Overall survey design. T c ch cu whch wk u mk h hm uc c mmy y u w u uc.

cc m u h , BLS uy h c my yuc c wy h w h y u h u c h ch- cc .

Bcu h um uch ch c-c y cc ym xh um hm, BLS u h Eu cc

c ch cc xm. T c hw xh2: y m w uc; y ccy; -u uc m, hu uc, cyc u; u uc c-

. Ahuh h c m h c- GGS, hy ch u cm wh hm, h uc c uc. F xm, chy cc, y m w uc h y my u wh h -hm, uch u ym ccy w h qum cy. I h GGS cx, h y m wuc cy y my cum.

Wk c GP hy -ch, , m, u, ch cc h m mc h -hm hy h hm wk h GP. T GP mym m cu yh whch h wk m h hh m GP. BLS u h m c cu whch h c c- h wk u, uch whch wkc c cyc.

Categories o green technologies and practices

G ch cc u h m mc hm. T ch cc m u u:

1. Energy rom renewable sources. Exm cu ccy, h, u m w uc my u wh h hm. T y uc cu w, m, hm, , c, hyw, muc w.

2. Energy efciency. ch cc u m y ccy wh h hm. Icu h u c (cm h w).

3. Pollution reduction and removal, greenhouse gas reduction, and recycling and reuse. ch cc uwh h hm

uc m h c u xc cmu, m u hzuw m h m;

uc hu m huh mh h h w y yccy;

uc m h c w m; cc, u, mucu, cyc, cm wm ww.

4. Natural resources conservation. ch cc u wh h hm c uuc. Icu h u ch cc c cuu uy; mm; , w, w c; mw mm.

Exhibit 2.


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Green Jobs Overview

14 Monthly Labor Review Januar y 2013

Sm u my mm GP y cc h wk . T GP uy cu y

whch h my h wk xcucc. Cc h mm GP -

GGS, h wu

h GGS uy.

Survey scope. C wh h BLS c ch , whch h cu h uc- c h uc c uc,h c h GP uy cu u xc huh. T uy c cc y, whch h GP uy h y h cu Auu 12, 2011.

Questionnaire design and testing. Dm huy qu qu h

c h y GP h c whh hm u y hch cc, whh hy h my- h ch cc, ,

whh y h my h hm . F h my, h qu cc h um wk y c-cu h w.

c h y GP, BLS c m h c hw xh2 cu xm ch cy. T c- xm m h w h

c whh h chy cc u whh y wk . T -m qu c h my wh my . T qu k h c whh my y h mch, , m, u ch cc h m m-c h hm h hm

wk h ch cc.A uqu qu w h mym -

quy h um wk m h hh m GP. F h wk, - w h k , -c, h um wk, y ccu y w , u m m h u h OES uy.

T GP uy uw u - . u mmy c, BLS cuc cw wh hm huh h GP. Ay uy w cuc h h -

u h uy u hy h qu . F wcuc h uy cu ccum h m (m, x,m, I). uh u

c h uy qu h , BLS cuc y uy m um - ch h .26

Sample design. T GP uy w m h QCEWu , u . T

w y U.S. Cu 2007 NAICSw- uy c, hm wh zmym h c 12 mh w xcu.

A h GGS uy m , h x u GP w ukw y qu. T,

ccy uc h m, BLS u hm kw u ch cc. BLS cm h huh

w ch m h u z, u c u 31,000 h-m, whch BLS h mch h QCEW u c . T w m

wh mwh hh y h h QCEW .T m cu u 35,000 hm, whu 33,000 u m h QCEW u 2,000u m h .

Data collection. T GP uy m uy m, h, m, x, I -. Ex h w-u w cuc, 70.0 c w ch. D c h 2010 SOC. Ex w uy ccu c w cuc.

Estimation. BLS GP uy m u- m wh um chmk mym c. I , OES wu m cu w

GP m.27

Publication. T GP w uh Ju2012, wh c Auu 2011. T cu h cc cc GP h um- whch wk m h h hm GP. T w uh -u cm h U.S. Cu uy c h . I -, ccu mym w


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w uh whch wk m hh h m GP. A ch w h BLS uc

w, mu m .Auy W hhh u h u

y h u.Cc c GP uy h

2012, wh Sm 2012 uc- h umm 2013. Whh h uy w cuc h m h y m.

Limitations. T GP uy c h mym ch chy cc. Emy w k c h m-y wh cc ch cc, my cu mu ch- cc.28

T GGS GP uy w ccc cm. A , cu y h w uy my hm h uc GGS u GP. Bcu h ccu c h , uhu um h m cu mym c h w m h um . U hu c whch h ch u h yc . GP GGS uy m c cm wh chh mu h ch m-ym m.29

BLS cu u u cm h GP c-cu wh m h OES uy. T w uc h c c, c , mhy. T GP uy cu cuu

u cu h OES uy. Iuy-cc m h GP uy cu mhm, m uy m h OESuy . T c mh GP Auu2011, h My 2011 OES m chmk

h h My 2011 Nm 2010 -c .30

Inormation on green careers

T BLS Emym Pc m u-h m c wh C

W Ey Sm 2010. N m ch uh huh Juy 2013, cuc c w, cuc,cc hc, cyc, y u, u-y, m m, hm y,

u. Ech c cu hw h cu ch-y wk h m ccu. F h ccu, h u h wk,c qu, w .31

BLS developed a green jobs definition huh x- ch cu h hw cc ch GGS uy, GGS-OCC, GP uy c m. R-u m h GGS-OCC GP cc c uh h u c y Zch-y W Auy W. I , P

Wwk x m y hh ccu h cm h umGP . Ru m h GGS uy w - hcmMonthly Labor Review c.

Notes

1 Ey Ic Scuy Ac, X, Pu. L. N. 110-140 (2007), http://www.gpo.gov/fdsys/pkg/BILLS-110hr6enr/pdf/BILLS-110hr6enr.pdf.

2 Amc Rcy Rm Ac, Pu. L. N. 111-5 (2009),http://www.gpo.gov/fdsys/pkg/BILLS-111hr1enr/pdf/BILLS-

111hr1enr.pdf.3 U.S. Dm L, FY 2010 u , . 50, http://www.dol.gov/dol/budget/2010/PDF/bib.pdf.

4 D cu m uc; hw, h w u hcmMonthly Labor Review c. Pc w y mym c y umymuc, mu y h BLS Quy Cu Emym W m, http://www.bls.gov/cew/.

5 Measurement and analysis o employment in the green economy(Wkc Im Cuc G J Suy Gu FR, Oc 2009), http://www.workforceinfocouncil.org/

Documents//WICGreenJobsStudyGroupReport-2009-10-01t.pdf.

6 F m m h u, C cmy: ummy uy u (C Emy-m Dm Dm, Oc 2010), http://www.energy.ca.gov/cleanenergyjobs/GrSurveyRpt_1115.pdf; Mch

2009 (Mch Dm Ey, L Ec-mc Gwh, My 2009), http://www.michigan.gov/documents/nwlb/GJC_GreenReport_Print_277833_7.pdf; T O wkc: , w, (O EmymDm, Wkc Ecmc Rch D, Auu2009), http://www.qualityinfo.org/pubs/green/greening.pdf; 2008 cmy Wh S (Wh Em-ym Scuy Dm, Juy 2009), http://www.energy.wsu.edu/documents/Green_Jobs_Report_2008_WEXVersion.pdf.

7 Ech C. D, J J. N, D W. Dw, ChM. Ku, D Rk, Ph Lw, G hw wk: mc O*NE-SOC w m
http://www.gpo.gov/fdsys/pkg/BILLS-110hr6enr/pdf/BILLS-110hr6enr.pdfhttp://www.gpo.gov/fdsys/pkg/BILLS-110hr6enr/pdf/BILLS-110hr6enr.pdfhttp://www.gpo.gov/fdsys/pkg/BILLS-111hr1enr/pdf/BILLS-111hr1enr.pdfhttp://www.gpo.gov/fdsys/pkg/BILLS-111hr1enr/pdf/BILLS-111hr1enr.pdfhttp://www.dol.gov/dol/budget/2010/PDF/bib.pdfhttp://www.dol.gov/dol/budget/2010/PDF/bib.pdfhttp://www.bls.gov/cew/http://www.workforceinfocouncil.org/Documents//WICGreenJobsStudyGroupReport-2009-10-01t.pdfhttp://www.workforceinfocouncil.org/Documents//WICGreenJobsStudyGroupReport-2009-10-01t.pdfhttp://www.energy.ca.gov/cleanenergyjobs/GrSurveyRpt_1115.pdfhttp://www.energy.ca.gov/cleanenergyjobs/GrSurveyRpt_1115.pdfhttp://www.michigan.gov/documents/nwlb/GJC_GreenReport_Print_277833_7.pdfhttp://www.michigan.gov/documents/nwlb/GJC_GreenReport_Print_277833_7.pdfhttp://www.qualityinfo.org/pubs/green/greening.pdfhttp://www.energy.wsu.edu/documents/Green_Jobs_Report_2008_WEXVersion.pdfhttp://www.energy.wsu.edu/documents/Green_Jobs_Report_2008_WEXVersion.pdfhttp://www.energy.wsu.edu/documents/Green_Jobs_Report_2008_WEXVersion.pdfhttp://www.energy.wsu.edu/documents/Green_Jobs_Report_2008_WEXVersion.pdfhttp://www.qualityinfo.org/pubs/green/greening.pdfhttp://www.michigan.gov/documents/nwlb/GJC_GreenReport_Print_277833_7.pdfhttp://www.michigan.gov/documents/nwlb/GJC_GreenReport_Print_277833_7.pdfhttp://www.energy.ca.gov/cleanenergyjobs/GrSurveyRpt_1115.pdfhttp://www.energy.ca.gov/cleanenergyjobs/GrSurveyRpt_1115.pdfhttp://www.workforceinfocouncil.org/Documents//WICGreenJobsStudyGroupReport-2009-10-01t.pdfhttp://www.workforceinfocouncil.org/Documents//WICGreenJobsStudyGroupReport-2009-10-01t.pdfhttp://www.bls.gov/cew/http://www.dol.gov/dol/budget/2010/PDF/bib.pdfhttp://www.dol.gov/dol/budget/2010/PDF/bib.pdfhttp://www.gpo.gov/fdsys/pkg/BILLS-111hr1enr/pdf/BILLS-111hr1enr.pdfhttp://www.gpo.gov/fdsys/pkg/BILLS-111hr1enr/pdf/BILLS-111hr1enr.pdfhttp://www.gpo.gov/fdsys/pkg/BILLS-110hr6enr/pdf/BILLS-110hr6enr.pdfhttp://www.gpo.gov/fdsys/pkg/BILLS-110hr6enr/pdf/BILLS-110hr6enr.pdf


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ccu (N C O*NE Dm, Fuy2009), http://www.onetcenter.org/reports/Green.html; Mk Mu,Jh Rhw, Dh Sh, Sizing the clean economy: anational and regional green jobs assessment (Bk Iu, Juy13, 2011),http://www.brookings.edu/research/reports/2011/07/13-clean-economy; Mu h cmy (U.S. Dm

Cmmc, Ecmc Sc Am, A 2010),http://www.esa.doc.gov/sites/default/files/reports/documents/greeneconomyreport_0.pdf; Te clean energy economy: repowering jobs,businesses and investments across America (T Pw Ch u,Ju 2009),http://www.pewenvironment.org/uploadedFiles/PEG/Publications/Report/Clean%20Energy%20Economy.pdf; Cu h U.S. cmy, U.S. MetroEconomies (Whm, MA: G Ih Ic., T U SCc My, Oc 2008), http://www.usmayors.org/pressreleases/uploads/GreenJobsReport.pdf.

8Te Environmental Goods and Services Sector: A Data Collection Hand-book (Luxmu: Oc Oc Puc h EuCmmu, Eu, Sm 2009), http://epp.eurostat.ec.europa.eu/portal/page/portal/product_details/publication?p_product_code=ks-ra-09-012.

9 Suy m c (Sc C, Ju2008), http://www23.statcan.gc.ca/imdb/p2SV.pl?Function=getSurvey&SDDS=1209&lang=en&db=imdb&adm=8&dis=2.

10 D E. Hck, Hh-chy mym: NAICS-u,Monthly Labor Review, Juy 2005, . 5772.

11 I, . 58.

12Federal Register, Mch 16, 2010, . 75, . 50, . 12,57112,573.

13 I.

14Federal Register, Sm 21, 2010, . 75, . 182, . 57,50657,514.

15 S h 2007 NAICS u h BLS http://www.bls.gov/ggs/ggsfaq.htm#3.

16 T 14 GGS uy m qu NAICS c 11 -cuu; 23 cuc; mucu (3 qu, ch NAICS c 31, 32, 33); 42 wh ; 48 ;51 m 71 , m, c; 61 uc- c 813 u, mk, cc, , m z; 92 uc m; 811 m-c; 2211 cc w , m, u;2213 w, w, h ym; cm qu 5112 w uh; 52 c uc; 54 -

, cc chc c; 55 mm cm ; 561 m u c. S http://www.bls.gov/respondents/ggs/forms.htm.

17 F h m , GGS uy chc N http://www.bls.gov/ggs/ggs_technote_extended.pdf.

18

T cm cu c h GGS-OCC chcN, IV, http://www.bls.gov/ggsocc/survey_methods.pdf.

19 F m m, GGS uy chc N http://www.bls.gov/ggs/ggs_technote_extended.pdf.

20 R V, K Fm, D Huh, RchCy, Mu uy mym (U.S. Buu L Sc, 2012), . 2,000-2,001, http://www.amstat.org/sec-tions/srms/proceedings/y2011/Files/301278_66470.pdf.

21 D cu m uc; hw, h w u hcmMonthly Labor Review c.

22 T OES uy w x y uc GGS-OCC m.T u h u OES m.

23 F m m m, GGS-OCC uy chc

N, IV, http://www.bls.gov/ggsocc/survey_methods.pdf.24 T GGS-OCC m cc 3-y cu cc u h h 2000 SOC h2010 SOC. T m h cc ym c GGS-OCC Fquy Ak Qu (FAQ) 8 http://www.bls.gov/ggsocc/faq.htm#8.

25 F m m cu BLS u uc - , http://www.bls.gov/ggsocc/survey_methods.pdf.

26 F m m m, GP uy chc N, V, http://www.bls.gov/gtp/survey_methods.pdf.

27 Fuh m cu h GPchc N, III, http://www.bls.gov/gtp/survey_methods.pdf.

28 F m m, GP FAQ8, http://www.bls.gov/gtp/faq.htm#q8.

29 F m m, GPFAQ11, http://www.bls.gov/gtp/faq.htm#q11.

30 F m m, GPFAQ12, http://www.bls.gov/gtp/faq.htm#q12.

31 T c c http://www.bls.gov/green/greencareers.htm.
http://www.onetcenter.org/reports/Green.htmlhttp://www.brookings.edu/research/reports/2011/07/13-clean-economyhttp://www.brookings.edu/research/reports/2011/07/13-clean-economyhttp://www.esa.doc.gov/sites/default/files/reports/documents/greeneconomyreport_0.pdfhttp://www.esa.doc.gov/sites/default/files/reports/documents/greeneconomyreport_0.pdfhttp://www.pewenvironment.org/uploadedFiles/PEG/Publications/Report/Clean%20Energy%20Economy.pdfhttp://www.pewenvironment.org/uploadedFiles/PEG/Publications/Report/Clean%20Energy%20Economy.pdfhttp://ttp//usmayors.org/pressreleases/uploads/GreenJobsReport.pdfhttp://ttp//usmayors.org/pressreleases/uploads/GreenJobsReport.pdfhttp://epp.eurostat.ec.europa.eu/portal/page/portal/product_details/publication?p_product_code=ks-ra-09-012http://epp.eurostat.ec.europa.eu/portal/page/portal/product_details/publication?p_product_code=ks-ra-09-012http://epp.eurostat.ec.europa.eu/portal/page/portal/product_details/publication?p_product_code=ks-ra-09-012http://www.bls.gov/ggs/ggsfaq.htm#3http://www.bls.gov/respondents/ggs/forms.htmhttp://www.bls.gov/respondents/ggs/forms.htmhttp://www.bls.gov/ggs/ggs_technote_extended.pdfhttp://ttp//www.bls.gov/ggsocc/survey_methods.htm#coordinationhttp://ttp//www.bls.gov/ggsocc/survey_methods.htm#coordinationhttp://www.bls.gov/ggs/ggs_technote_extended.pdfhttp://www.bls.gov/ggs/ggs_technote_extended.pdfhttp://www.amstat.org/sections/srms/proceedings/y2011/Files/301278_66470.pdfhttp://www.amstat.org/sections/srms/proceedings/y2011/Files/301278_66470.pdfhttp://www.bls.gov/ggsocc/faq.htm#8http://www.bls.gov/ggsocc/faq.htm#8http://www.bls.gov/ggsocc/faq.htm#8http://www.bls.gov/gtp/survey_methods.pdfhttp://www.bls.gov/gtp/survey_methods.pdfhttp://www.bls.gov/gtp/survey_methods.pdfhttp://www.bls.gov/gtp/survey_methods.pdfhttp://www.bls.gov/gtp/faq.htm#q8http://www.bls.gov/gtp/faq.htm#q8http://www.bls.gov/gtp/faq.htm#q11http://www.bls.gov/gtp/faq.htm#q11http://www.bls.gov/gtp/faq.htm#q12http://www.bls.gov/gtp/faq.htm#q12http://www.bls.gov/green/greencareers.htmhttp://www.bls.gov/green/greencareers.htmhttp://www.bls.gov/green/greencareers.htmhttp://www.bls.gov/green/greencareers.htmhttp://www.bls.gov/gtp/faq.htm#q12http://www.bls.gov/gtp/faq.htm#q12http://www.bls.gov/gtp/faq.htm#q11http://www.bls.gov/gtp/faq.htm#q11http://www.bls.gov/gtp/faq.htm#q8http://www.bls.gov/gtp/faq.htm#q8http://www.bls.gov/gtp/survey_methods.pdfhttp://www.bls.gov/gtp/survey_methods.pdfhttp://www.bls.gov/gtp/survey_methods.pdfhttp://www.bls.gov/ggsocc/faq.htm#8http://www.bls.gov/ggsocc/faq.htm#8http://www.amstat.org/sections/srms/proceedings/y2011/Files/301278_66470.pdfhttp://www.amstat.org/sections/srms/proceedings/y2011/Files/301278_66470.pdfhttp://www.bls.gov/ggs/ggs_technote_extended.pdfhttp://www.bls.gov/ggs/ggs_technote_extended.pdfhttp://ttp//www.bls.gov/ggsocc/survey_methods.htm#coordinationhttp://www.bls.gov/ggs/ggs_technote_extended.pdfhttp://www.bls.gov/respondents/ggs/forms.htmhttp://www.bls.gov/respondents/ggs/forms.htmhttp://www.bls.gov/ggs/ggsfaq.htm#3http://epp.eurostat.ec.europa.eu/portal/page/portal/product_details/publication?p_product_code=ks-ra-09-012http://epp.eurostat.ec.europa.eu/portal/page/portal/product_details/publication?p_product_code=ks-ra-09-012http://epp.eurostat.ec.europa.eu/portal/page/portal/product_details/publication?p_product_code=ks-ra-09-012http://ttp//usmayors.org/pressreleases/uploads/GreenJobsReport.pdfhttp://ttp//usmayors.org/pressreleases/uploads/GreenJobsReport.pdfhttp://www.pewenvironment.org/uploadedFiles/PEG/Publications/Report/Clean%20Energy%20Economy.pdfhttp://www.pewenvironment.org/uploadedFiles/PEG/Publications/Report/Clean%20Energy%20Economy.pdfhttp://www.esa.doc.gov/sites/default/files/reports/documents/greeneconomyreport_0.pdfhttp://www.esa.doc.gov/sites/default/files/reports/documents/greeneconomyreport_0.pdfhttp://www.brookings.edu/research/reports/2011/07/13-clean-economyhttp://www.brookings.edu/research/reports/2011/07/13-clean-economyhttp://www.onetcenter.org/reports/Green.html


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Green Goods and Services

The Green Goods and ServicesOccupational survey: initial results

A new BLSsurvey provides data on occupations and wagesin green establishments; a wage gap between green and nongreenestablishments is traced to the occupational mix

Zack Warren

Zack Warren is an economistin the Ofce o Employmentand Unemployment Statis-tics, Division of OccupationalEmployment Statistics, Bu-reau of Labor Statistics. Email:[email protected].

In 2012, the Bureau o Labor Statistics

(BLS, the Bureau) published data onthe green economy rom three new

data collection eorts. Te results thatollow come rom one o these eorts: theGreen Goods and Services Occupationalsurvey (also known as the GGS-OCCsurvey), whose data were rst releasedin September 2012. Integrating greenrevenue data rom one BLS surveytheGreen Goods and Services (GGS) sur-

veywith occupational stafng patternsrom another BLS surveythe Occu-pational Employment Statistics (OES)surveythe GGS-OCC survey providesinormation on occupational employmentand earnings in GGS industries. Ater giv-ing some background on the GGS-OCCmethodology, this article presents a num-ber o high-level ndings on occupationalemployment and wages in establishmentsproviding green goods or services. Tearticle concludes by demonstrating how

wages in green establishments are largely

a result o the industrial and occupationalcomposition o those establishments.

The GGS-OCC survey

As noted in the previous section, GGS-OCC data do not come rom a dedicatedsurvey; rather, the estimates are calculatedrom the aorementioned GGS and OESsurveys. o acilitate the calculation, the

GGS survey was designed rom the ground up

to allow or the creation o the GGS-OCC esti-mates, while the OES survey was modied byaltering sampling procedures and supplement-ing data collection with additional units.1

Te GGS survey is comprised o 120,000units selected rom 333 o the roughly 1,200detailed industries listed in the 2007 North

American Industrial Classication System(NAICS).2 Te Bureau identied these 333 in-dustries as industries that could produce greengoods and services. Tis subset o industriescollectively represents approximately 23 per-cent o all establishments, and 20 percent o allemployment, in the U.S. economy. Te numbero industries included within the scope o thesurvey varies by industry sector; or example,nearly all the industries in the construction sec-tor are in scope, whereas none o the healthcareand social assistance industries are.3 An impor-tant act to recall is that NAICS industries areassigned a code only by the primary activityo the establishment; thus, it is likely that someestablishments which produce green goods and

services as a secondary activity, and hence theemployees rom those establishments, are notincluded in the GGS survey. Because the GGS-OCC and GGS surveys share the same scope,all GGS-OCC data are restricted to this poten-tially green sector o the economy based on theprimary activity o the establishment.

Te GGS survey orm asks each establish-ment sampled or the percentage o its revenuegenerated by the sale o goods and services that

Note 2 and corresponding text (page 26) were updated on February 6, 2013.
mailto:warren.zachary%40bls.gov?subject=mailto:warren.zachary%40bls.gov?subject=mailto:warren.zachary%40bls.gov?subject=


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benet the environment or conserve natural resources, ac-cording to the BLS denition o a green job.4 Alternatively,and in the case o establishments that do not generaterevenue, such as government or nonprot establishments,respondents are asked or the percentage o employment

associated with green goods and services. Te revenue oremployment percentage reported is then reerred to as theestablishmentsgreen percentage.

Te other source o data or the GGS-OCC estimates,the OES survey, is a longtime BLS program that surveysestablishments or their stang patterns: lists o employ-ees classied by their occupations,5 along with the wageso those employees. Te OES sample o 1.2 million es-tablishments is drawn rom a list o U.S. establishmentsmaintained by the BLS Quarterly Census o Employmentand Wages (QCEW) and is the same rame used to selectthe 120,000-unit GGS sample. Te OES sample is collect-ed in six semiannual panels, rather than in single annualpanels as is the GGS sample. o acilitate the GGS-OCCestimates, the GGS and OES samples are drawn simulta-neously in a manner that maximizes the number o OESunits that are also sampled by the GGS survey. Wheneverpossible, in addition to the units that naturally overlapthe two surveys, GGS units are replaced with similar unitsalready sampled by the OES survey. A 25,000-unit samplesupplement also is added to the OES sample in order tocollect data rom industries that are not within the scopeo the OES survey, as well as to improve the GGS-OCCs

coverage o existing industries. All these modicationsserve to maximize the number o available units or theGGS-OCC estimates.

Finally, to create the GGS-OCC estimates, the OESstang patterns are matched to the GGS green percent-ages or each o the establishments that responded to theGGS survey. For units that did not respond to the OESsurvey, stang patterns are imputed according to a near-est neighbor method. A nonresponse adjustment actoris used to adjust or nonresponding GGS units, and theemployment estimate is benchmarked to the QCEWem-ployment levels. Te last step o estimation leads to the

most important distinction between the GGS and GGS-OCC surveys: the manner in which the green percent-age is used to derive green employment. o get the GGSestimate o green employment, the Bureau multiplies thegreen percentage by the establishments employment g-ure to estimate the establishments GGS employment.By contrast, the GGS-OCC estimates o green employ-ment are based ongroupingestablishments by their greenpercentage rather than prorating employment by it.

Te Bureau ound prorating to be a good proxy or

determining totalgreen employment by industry, but themethod would not provide as useul an estimate o greenoccupational employment. Te employment estimatesrom the GGS survey, which use prorating, rely on the as-sumption that the ratio o green revenue to total revenue

is directly proportional to the ratio o green employmentto total employment. However, in establishments withrevenue rom the sale o green goods and services, one

would expect certain occupations to be more closely re-lated to producing those green goods and services thanothers. Under that expectation, prorating all employmentby the green percentage would result in parto every oc-cupation in such an establishment becoming a green job,rather than the entirety o a subset o occupations.

Consequently, to preclude such a possibility, establish-ments were categorized into three groups, based on theirreported percentages o greenness and named or theirdegree o greenness: those which derive allo their rev-enue rom green sources; those which derive some, but notall, o their revenue rom green sources; and those with nogreen revenue. Te three groups are dened strictly; thatis, the all-green category comprises all establishments thatreported a green revenue or employment o 100 percent;the some-green category comprises those which reportedgreater than zero percent but less than 100 percent; andthe no-green category comprises those reporting exactlyzero percent. Because o the dierent estimation meth-ods, even though the GGS and GGS-OCC surveys share a

common data source, there is no single green employmentestimate that is directly comparable between the two sur-veys. GGS data oer more detailed industry estimatesdown to the six-digit NAICS level or some industriesas

well as estimates by state, but lack occupational detail,making GGS estimates generally most useul or analysesin which occupational detail is not required. By contrast,although the GGS-OCC estimates are national only andprovide industry data just to the sector NAICS level, theyinclude occupational detail.

Tree key actors to bear in mind in reviewing theGGS-OCC data in the rest o this article are (1) that the

estimates are created rom the green percentages col-lected by the GGS survey and stang patterns collectedby the OES survey; (2) that the green categories are basedon establishments reported green percentages, so that allemployment in an establishment contributes to the samegreen category, regardless o whether those occupationsare or are not related to the green activity at the establish-ment; and (3) that the GGS-OCC survey is restricted toa subset o the entire economy: the 333 industries thatcould produce green goods and services.


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Overall GGS-OCC estimates

At their highest level o aggregation, the GGS-OCC esti-mates show that employment is overwhelmingly concen-trated in no-green establishments. In all, more than 1.9

million jobs are in all-green establishments, 6.1 millionare in some-green establishments, and almost 18.3 mil-lionnearly 70 percent o all in-scope employmentarein no-green establishments, as shown in the ollowingtabulation:

Green revenue Total Average annualcategory employment wage

otal, all in-scopeestablishments ......................... 26,326,990 $56,540All-green establishments ....... 1,949,520 48,210Some-green establishments .... 6,110,380 54,440No-green establishments ........ 18,267,090 58,130

able 1 shows how employment, even when classied intooccupational groups, is nearly always greatest in no-greenestablishments, compared with the other two green cat-egories: in only 4 o the 22 major occupational groupslie, physical, and social science; education, training, andlibrary; ood preparation and serving related occupations;and transportation and material movingis the majorityo employment ound in all-green or some-green estab-lishments (or both combined).

Te largest occupations in all-green establishments,

shown in table 2, include school bus drivers (174,450 em-ployees), transit bus drivers (111,760), collectors o reuseand recyclable materials (56,930), and orest and conserva-tion technicians (56,620). Te largest occupations in no-green establishments are general oce clerks (530,180 em-ployees), secretaries and administrative assistants (417,780),general and operations managers (408,080), and construc-tion laborers (405,880). All o these no-green occupationsare among the largest in the economy overall.6

Another interesting way to look at the occupationalcomposition oGGS employment is to examine the dis-tribution o occupations across the three categories o rev-

enuein particular, the occupations that are most heavilyconcentrated in each category. Te occupations that arealmost entirely ound in all-green establishments includesubway and street car operators, school bus drivers, nucle-ar reactor operators, orest and conservations technicians,and transportation attendants. In all o these occupations,more than 75 percent o in-scope employment is oundin the all-green category. A ar greater number o occupa-tions are ound exclusively in no-green establishments, anunsurprising act given the much greater employment in

that category. Some o the largest occupations that are atleast 99 percent concentrated in the no-green category areair trac controllers, insurance underwriters, transporta-tion security screeners, insurance sales agents, actuaries,actors, and law clerks.

Te bulk o this article treats the all-green and no-green categories, because the two extremes provide themost interesting comparisons. Still, the some-green cate-gory is not without interesting results. Te category tendsto be dominated by large, nonspecialized institutions thatmight have a particular department or subunit whichocuses on green products and services. Tis structure isnoticeable in the occupations most heavily concentratedin the some-green category: sociologists, locker room at-tendants, psychiatrists, musical instrument repairers, andamily and general practitioners. Tese occupations arethe ve most concentrated, and all ve have the majorityo their in-scope GGS-OCC employment in universitiesand colleges.7

Te other noteworthy nding rom the some-greencategory is that the establishments in the constructionindustry that conduct any green activity are almost en-tirely in that category. In other words, very ew construc-tion establishments provide green construction servicesexclusively. Rather, such services are provided mostly bytraditional construction establishments, either specializ-ing temporarily in green construction or dedicating onlya small part o their activities to it while continuing with

traditional activities. Tis nding is apparent in GGS-OCCestimates in several ways. First, the some-green categorycomprises roughly 25 percent o employment withinthe construction occupational group, while the all-greencategory comprises only 4 percent. Second, 7 o the 10largest occupations in the some-green category are spe-cic to construction: carpenters, electricians, plumbers,general managers, construction laborers, civil engineers,and construction supervisors. (Te other 3 occupationsare oce clerks, the catchall grouping all other postsec-ondary teachers, and secretaries.) Finally, as shown later,employment in the construction industry as a whole is 24

percent in the some-green category and only 2 percent inthe all-green category.8

In the development o the green surveys at the Bureau,an early research avenue was to examine the occupationscollected by the OES survey to see i analysts could con-sider any o them as green by denition; or example, thedenition o environmental engineers says that theyresearch, design, plan, or perorm engineering duties inthe prevention, control, and remediation o environmentalhazards using various engineering disciplines.9 Because


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Employment and wages in the largest occupations in the all-green and no-green categories, November 2011

Occupation Employment Mean annual wage

All green

Bus drivers, school or special client 174,450 $30,460

Bus drivers, transit and intercity 111,760 41,580

Refuse and recyclable materials collectors 56,930 34,670

Forest and conservation technicians 56,620 40,110

Laborers and freight, stock, and material movers, hand 54,890 26,270

No green

Oce clerks, general 530,180 29,730

Secretaries and administrative assistants, except legal, medical, and executive 417,780 33,770

General and operations managers 408,080 133,890

Construction laborers 405,880 35,340

Landscaping and groundskeeping workers 403,440 25,350


Table 2.

Employment and wages, by occupational group and green category, November 2011

Occupational group

All green Some green No green

EmploymentMean annual

wageEmployment

Mean annualwage

EmploymentMean annual

wage

Total, all occupations 1,949,520 $48,210 6,110,380 $54,440 18,267,090 $58,130

Management 95,360 110,220 428,390 108,450 1,428,280 124,230

Business and nancial operations 83,740 71,250 279,960 64,750 1,216,160 69,530

Computer and mathematical 25,540 77,270 196,340 68,280 1,422,100 78,940

Architecture and engineering 105,670 77,130 404,910 70,900 822,600 75,920

Life, physical, and social science 174,930 57,660 185,160 57,510 324,850 68,670

Community and social service 3,030 47,170 44,870 45,780 75,790 44,500

Legal 6,670 115,150 39,350 144,720 562,080 116,020

Education, training, and library 13,090 53,440 941,770 66,810 918,970 58,650

Arts, design, entertainment, sports, and media 22,200 50,750 155,910 52,520 647,880 73,260

Healthcare practitioners and technical 7,900 66,640 57,830 57,740 113,510 67,310

Healthcare support 70 35,260 9,270 31,760 26,400 34,350

Protective service 26,320 44,090 54,190 40,350 106,880 39,930

Food preparation and serving related 2,160 27,190 26,790 27,620 27,550 25,040

Building and grounds cleaning and maintenance 35,620 29,080 186,050 28,900 627,090 27,520

Personal care and service 18,780 2 4,320 45,730 27,130 71,440 31,210

Sales and related 84,560 38,020 180,010 46,920 629,940 61,200

Oce and administrative support 194,440 37,260 877,470 35,970 2,918,530 37,850

Farming, shing, and forestry 29,260 25,670 86,420 25,150 625,000 23,690

Construction and extraction 137,060 44,910 895,310 47,000 2,539,890 45,270

Installation, maintenance, and repair 135,470 49,140 278,480 44,580 1,000,620 42,210

Production 208,180 39,240 462,710 36,780 1,520,970 36,150

Transportation and material moving 539,470 35,390 273,450 34,570 640,560 36,720


Table 1.


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one o the conditions listed in the BLS denition o agreen job is that the job reduce or eliminate the creationor release o pollutants or toxic compounds, or removepollutants or hazardous waste rom the environment, the

job o any worker who perormed, or example, the du-

ties that meet the denition o environmental engineerswould also meet the denition o a green job.10 Eight oc-cupations whose duties were ound to be directly linkedto green activities were examined in an OES publication

while the GGS survey was rst being collected;11 chart 1shows the GGS-OCC data or those eight occupations.

Because the eight occupations in the chart seem inher-ently green, one might expect the no-green employmentin those occupations to be vanishingly small. Yet it isnt:the eight occupations have rom 8 percent to 40 percent otheir employment in the no-green category. Such a rangeillustrates how the dierent BLS approaches to measur-ing green jobs capture dierent workers: the inherentlygreen workers may still be ound in establishments withno green revenue, because those workers are developinggreen products or services that are not yet generating rev-enue or they could be perorming activities to make theestablishments production processes greener, rather thanproducing a green product or service. Activities that make

the establishments production processes greener wouldbe captured by the BLS Green echnologies and Practicessurvey.12

Te GGS-OCC data include mean (or average) and me-dian (or 50th-percentile) wage estimates in addition to

the employment gures. Te wage estimates are availableboth as hourly wage rates and as annual wages based ona 2,080-hour standard work year.13 Te latter is used inthis article. Across all occupations, the average wage o thethree categories decreases rom the no-green to the all-green category. As shown in the text tabulation on page28, the no-green category has an average annual wage o$58,130. Te some-green category is lower, at $54,440,

while the all-green category is still lower, at $48,210. Al-though this appears to be a stark result, the analysis willsubsequently demonstrate that these dierences refectmainly the occupational composition o the three catego-ries o revenue.

Te employment and wage gures cited in the previ-ous several paragraphs highlight the broadest estimatesin the rst publication o the GGS-OCC survey, as wellas some o the more noteworthy occupational estimates.

Te remainder o the article will continue to clariy thesignicance o these high-level GGS-OCC estimates by

Chart 1.

Numberemployed Numberemployed

70,000

60,000

50,000

40,000

30,000

20,000

10,000

0

Employment in eight occupations with duties expected to be directly linked to green activities, bygreen category, November 2011

Foresters Environmentalscientists and

specialists

Environmentalengineers

Environmentalengineeringtechnicians

Conservationscientists

Environmental

science and

protection

technicians

Forest and

conservation

workers

Forest andconservationtechnicians

Some green

All green

No green

70,000

60,000

50,000

40,000

30,000

20,000

10,000

0



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illustrating what the detailed GGS-OCC estimates canreveal about them.

Industry efects and employment

Chart 2 introduces a new level o detail in the GGS-OCCestimates. Te chart shows how the total in-scope em-ployment in each o the 16 NAICS industry sectors (as

well as the cross-industry total) is divided among thethree green revenue categories. Across all industries, 69percent o employment is ound in establishments withno green revenue (or employment), 23 percent is ound inthose with some, and just 7 percent is ound in establish-ments in which all the revenue comes rom green revenuestreams. Tat pattern does not hold in many individualindustries, however: all-green employment ranges rom79 percent in transportation and warehousing to less than1 percent in management o companies and enterprisesand in educational services.

Te distribution o green employment in each sector isuseul or any overall or cross-industry analysis that usesGGS-OCC data because it lays bare some o the industrialeects behind the estimates. Any employment estimatesinvolving multiple industries will be heavily infuenced

by industry dierences, but the GGS-OCC estimates areespecially so because they are based on a limited industryscope. Chart 2 helps to illustrate how the largest occu-pations in each green category appear there, given thatthe occupations naturally ollow rom the industrial mix

o the category. Te reason is that industry is by ar themost important determinant o which occupations an es-tablishment will employ. It is clear rom this act why busdrivers and reuse and recyclable material collectors areamong the largest all-green occupations. Aside rom the

wholesale and retail trade industries, which are very smallin the scope o the GGS survey, the transportation and

warehousing industry and the utilities industry are thegreenest o all the industries in the chart. Tus, it comes asno surprise that many o the largest all-green occupationsare ound primarily in those industries.

Although there is a considerable amount o shading indi-cating all-green and some-green employment in industriesshown in the chart, those industries tend to be the smallerones within the scope o the GGS survey. Te industries

with the most all-green employmenttransportation andwarehousing, wholesale trade, utilities, and retail tradeare4 o the 6 smallest industry sectors within the scope o thesurvey. O course, the retail trade sector is very large in the

Chart 2. Percentage o industry sector employed, by green category, November 2011

Some greenAll green No green

All in-scope Industries

Agriculture, forestry, shing, and hunting

Utilities

Construction

Manufacturing

Wholesale trade

Retail trade

Transportation and warehousing

Information

Finance and insurance

Professional and technical services

Management of companies and enterprises

Administrative and waste services

Educational services

Arts, entertainment, and recreation

Other services (except public administration)

Public administration

0 20 40 60 80 100Percent

NOTE: Complete data for nance and insurance are not available.



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overall economy, while the wholesale trade and transporta-tion sectors are midsized; but in each o those three sectors,only a small portion o the total industry is within the scopeo the GGS survey. Te utilities sector, by contrast, is mostly

within the surveys scope, but it is small overall.

In addition to estimates at the levels o aggregationalready mentioned, detailed occupational estimates oreach o the 16 industry sectors are included in the GGS-OCC data. Tus, industry-specic comparisons betweenthe green categories can help isolate industry eects. Asnoted beore, an establishments industry is the majordeterminant o the occupations that establishment willemploy. Te GGS-OCC data show that, within an industry,an establishments greenness is also a determinant o theoccupations that establishment employs. For example, inthe construction sector, while both all-green and no-greenestablishments employ many basic construction occupa-tions, such as construction supervisors, carpenters, elec-tricians, and construction laborers, establishments in the

two categories also have specialized occupations that areheavily avored by one category over the other. One way toshow these dierences, given the large employment sizedierence between the all-green and no-green categories,is to compare the relative concentrations o all the occupa-

tions in those categories. able 3 lists selected occupationsin construction that are more prevalent in all-green estab-lishments, those which appear in both categories in nearlyequal proportions, and those which are more prevalent inno-green establishments.

able 3 shows that there are more insulation workersworking in no-green establishments than in all-green es-tablishments. Te reason, however, is primarily becausethere are more than 30 no-green establishments or everyall-green establishment in the construction sector. In or-der to control or that size discrepancy, table 3 also showsthe relative concentration o each occupation in the all-green and no-green categories. Te relative concentrationo an occupation in all-green establishments is calculated

Relative concentrations o selected occupations in the construction industry, November 2011

OccupationAll-green

employmentNo-green

employment

Concentration in allgreen relative to no

green

Concentrated in all-green establishments

Insulation workers, oor, ceiling, and wall 8,210 13,210 25.7

Electrical engineers 460 1,300 14.7

Helpers, construction trades, all other 1,420 9,310 6.3

Electrical power-line installers and repairers 1,690 21,440 3.3

Heating, air conditioning, and refrigeration mechanics and installers 5,190 93,760 2.3

Heavy and tractortrailer truck drivers 2,430 52,590 1.9

Welders, cutters, solderers, and brazers 1,020 24,870 1.7

Similarly concentrated

Construction managers 2,610 103,530 1.0

First-line supervisors of construction trades and extraction workers 5,830 232,610 1.0

Carpenters 7,860 319,090 1.0

Electricians 5,390 256,320 .9

Construction laborers 7,680 390,060 .8

Concentrated in no-green establishments

Sheet metal workers 51,750 .3

Cement masons and concrete nishers 92,540 .3

Roofers 70,180 .2

Painters, construction and maintenance 105,800 .0

Telecommunications equipment installers and repairers, except lineinstallers 0 21,190 .0

Telecommunications line installers and repairers 0 23,140 .0

Brickmasons and blockmasons 0 61,500 .0

NOTE: Dash indicates data do not meet BLS publication standards. SOURCE: U.S. Bureau of Labor Statistics.

Table 3.


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by dividing the share o all-green construction employ-ment in all-green establishments by the share o no-greenconstruction employment in no-green establishments.

Tat is, the relative concentration is

where Nc

= no-green total employment in industryc,

ncj

= no-green employment in industrycandoccupation j,

Ac= all-green total employment in industryc,

and

acj

= all-green employment in industrycandoccupationj.

Tus, although there are 5,000 more insulation workers

in no-green establishments than in all-green establish-ments, insulation workers are relatively more importantin the latter establishments. In act, a worker in an all-green construction establishment is 25 times more likelythan a worker in a no-green establishment to be an in-sulation worker. In contrast, no-green establishments usepainters heavily, whereas all-green establishments do not.Both types o establishments employ carpenters, electri-cians, and construction laborers in approximately similarproportions. From these data, an analyst can identiy theoccupations that are relatively more important to green

employers and, in some cases, such as the appearance oinsulation workers and heating, air conditioning, and re-rigeration mechanics and installers in the all-green cat-egory, get an indication o the type o green activities thegreen establishments engage in.

Occupational composition and wages

In the same manner that occupational dierences be-tween the green categories shown in the overall numbersare largely a result o the specic industries that make upthose categories, the rather large wage dierences between

categories can be illuminated with the use o the moredetailed occupational estimates. For example, a data usermay be immediately struck by the relatively large wagegap o nearly $10,000 in annual mean wages between theall-green and no-green categories. However, the overall

wage o $48,210 in the all-green category, compared withthe $58,130 mean or the no-green category, does not nec-essarily indicate that all workers in green establishmentsare paid signicantly less than those producing nongreenproducts and services. In act, as o November 2011, wages

in all-green establishments and in some-green establish-ments were still higher than the U.S. average o $45,230measured 6 months earlier.

A workers wage rates can be infuenced by many ac-tors, including the workers experience, education, or union

participation; the industry, size, or location o the workersemployer; and, most importantly when groups with manyoccupations are compared, the workers occupation. A sim-ple analysis shows how the wage dierence between theall-green and no-green categories can be attributed largelyto the occupational composition o employment in thosecategories. o illustrate, the 22 major occupational groupsare divided into 3 categories according to the mean wageo the occupational group in the May 2011 OES estimates.

Te 8 occupational groups with an average below the 33rdpercentile o the wage distribution are considered lowestpaying, the 7 occupational groups between the 33rd and66th percentiles are considered middle paying, and the 7

with an average wage above the 66th percentile are consid-ered highest paying.14 Chart 3 shows the resulting share oemployment in the lowest, middle, and highest paying oc-cupational groups in the all-green and no-green categories

when those wage classications are applied to the majorgroups in the GGS-OCC data. Te chart shows that theno-green category has roughly equal employment amongthe lowest, middle, and highest paying occupational groups

while the all-green category has relatively more employ-ment in the lowest paying occupational groups.

A more sophisticated technique called shift-shareanalysiscan be used to isolate one source o the wage di-erence. In the June 2009 issue o the Review, BLS econo-mist Rebecca Keller used the technique to break downchanges in the U.S. real wage, and in the May 2003 issueo Occupational Employment and Wages, BLS economistPatrick Kilcoyne used it to compare the average wages othe 50 States and the District o Columbia.15 Te tech-nique is useul in the analysis presented here because oc-cupation is one o the largest determinants o wages oran individual worker. Te mix o occupations that makeup an entity such as a State, an industry, a snapshot in

time o the economy, or, in this case, a green category,plays a large part in determining the average wage o thatentity. I the large wage dierence between all-green andno-green workers is real, then it should persist across oc-cupations; i it is misleading, then it is most likely becauseall-green workers are ound more in the lowest payingoccupations than are no-green workers. Te shit-sharetechnique is used to separate the $9,920 wage dierencebetween the two groups o workers into a portion dueto dierences in pay, a portion due to the occupations in


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Chart 3.

Middle payingoccupations

Highest payingoccupations

Lowest payingoccupations

Percentage

employedPercentage

employed

100

90

80

70

60

50

40

30

20

10

0

All green No green

25.6

52.7

21.6

32.2

35.4

32.4

100

90

80

70

60

50

40

30

20

10

0

Distribution o employment in lowest, middle, and highest paying occupations, by green category,November 2011


which those workers are employed, and a portion due toall other reasons.

Te shit-share technique works in this instance byswapping data between the two green categories and re-

cording the eect on the estimates in order to estimatethe size o each portion. Tis is done, in simple terms, bymultiplying the all-green employment by the no-green

wage, and vice versa, or each occupation. Te sum o alloccupations or the ormer is used to estimate the portiono the wage gap due to real dierences in pay. Te sumo all occupations or the latter is used to estimate theportion o the wage gap due to occupational composition.

Te ormula used to compare wages in the all-green andno-green categories is

A = all-green total employment,

aj

= all-green employment in occupationj,

WN

= no-green total wage,

wnj = no-green wage in occupationj, w

aj= all-green wage in occupationj, and

wa w

n= dierence o all-green and no-green

average annual wages.

When shit-share analysis is used on the GGS-OCCestimates to compare the all-green average wage with theno-green average wage, the hypothesis that the nearly$10,000 wage gap is due more to the variety o occupa-tions employed in each category than to the various wagesis conrmed, as the ollowing tabulation shows:

Dollar amountCategory or percentage

Annual wage, no-green establishments ........... $58,130Annual wage, all-green establishments ........... $48,210Dierence (all green minus no green)............. $9,920

Wage-rate component. ................................... $3,080Occupational component................................ $10,310Residual .......................................................... $3,470

Percentage due to wages ................................. 31Percentage due to occupational composition. . 104Percentage due to other actors. ...................... 35

=

Wageportion

Occupationalportion

Residual

,

=1

where N = no-green total employment,

nj

= no-green employment in occupationj,


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Te idea to take away rom this tabulation is not somuch the specic dollar values or each component as theact that the occupational composition has roughly 3 timesthe explanatory power as the wage values. Similar to theearlier analysis, this one shows that the wage gap between

green categories is due mostly to the types o jobs the estab-lishment employs and not because no-green establishmentsalways pay better. Still, there is a $3,000 wage-rate-basedcomponent in the analysis, suggesting that there is somedierence in pay between the categories even when isolatedrom the occupational mix. Tis wage-rate component ismatched and canceled by a component attributable to un-known actors. In addition to the much more sizable oc-

cupational component, the act that the residual is as largeas the wage-rate component suggests that the wage-ratecomponent is a minor actor in the wage gap. Even thoughthe ull $10,000 wage gap is misleading, the analysis is notmeant to suggest that the wage estimates are not inorma-

tive: it is still worthwhile to know that, in the aggregate, theall-green jobs tend to be lower paying. Te all-green work-ers may be close to equally compensated or their jobs rela-tive to the other categories, but the act remains that those

jobs tend to be lower paying. Te intent o the analysis issimply to illustrate the meaning behind the estimates andto show how the detailed estimates can clariy the higherlevel aggregates.16

Notes

1 For a thorough discussion o the survey methodology, see GreenGoods and Services Occupations: Survey Methods and ReliabilityStatement or Occupational Employment and Wages in Green Goodsand Services (U.S. Bureau o Labor Statistics, Oct. 3, 2012), http://www.bls.gov/ggsocc/survey_methods.htm.

2 An article on the Green Goods and Services survey will be pub-lished in a orthcoming issue oftheMonthly Labor Review.

3 For the ull list o included and excluded industries, see GreenGoods and Services Occupations: Green Goods and Services Occupa-tions (GGS-OCC) FAQs, question 7, What industries are within scopeor the GGS-OCC estimates? (U.S. Bureau o Labor Statistics, Oct. 3,2012), http://www.bls.gov/ggsocc/aq.htm#7.

4 For the ull BLS denition o a green job, see Te BLS Green JobsDenition, in Green Jobs: Measuring Green Jobs(U.S. Bureau o Labor

Statistics), http://www.bls.gov/green/#defnition.5 Te GSS-OCC classies occupations in accordance with the Standard

Occupational Classication system; see Standard Occupational Classi-cation (U.S. Bureau o Labor Statistics), http://www.bls.gov/soc .

6 According to May 2011 OES data, general ofce clerks, secretariesand administrative assistants, and general and operations managers areamong the 15 largest occupations in the U.S. economy while construc-tion laborers are among the 40 largest. Te OES estimates, unlike thoseo the GGS-OCC, include data rom all nonarm establishments.

7 Other than sociologists, these occupations are not normally con-centrated in universities, but because the GGS-OCC survey excludesmany industries, colleges and universities make up the largest remain-ing industry to employ these workers.

8 In the case o construction, it can be easy to conuse occupationsand industries because the construction occupations make up the bulko the construction industry. However, construction occupations can beound in many industries, while the construction industry also employsmany nonconstruction workers, such as secretaries and accountants.

9 SeeStandard Occupational Classifcation(U.S. Bureau o Labor Statis-

tics, Mar. 11, 2010) p. 27, http://www.bls.gov/soc/2010/soc172081.htm .10 See Te BLS Green Jobs Denition.11 See Occupational Employment Statistics: Occupational Em-

ployment Statistics (OES) Highlights: Jobs or the Environment(U.S. Bureau o Labor Statistics, June 2009), http://www.bls.gov/oes/high light_environment.htm.

12 See Green echnologies and Practices (U.S. Bureau o LaborStatistics), http://www.bls.gov/gtp .

13 In the GGS-OCC survey, a standard work year is 40 hours o worka week or 52 weeks.

14 Te lowest paying occupational groups are healthcare sup-port; ood preparation and serving; building and grounds cleaning;personal care and service; ofce and administrative support; arming,

shing, and orestry; production; and transportation and materialmoving. Te middle-paying groups are community and social service;education, training, and library; arts, design, entertainment, sports,and media; protective service; sales; construction; and installation,maintenance, and repair. Te highest paying occupational groupsare management; business and nancial occupations; computer andmathematical occupations; architecture and engineering; lie, physi-cal, and social science; legal occupations; and healthcare practitionersand technical occupations.

15 See Rebecca Keller, How shiting occupational compositionhas aected the real average wage,Monthly Labor Review, June 2009,pp. 2638, http://www.bls.gov/opub/mlr/2009/06/art2ull.pd; andPatrick Kilcoyne, Te role o occupational composition in state wagedierentials,Occupational Employment and Wages, September 2004, pp.813, http://www.bls.gov/oes/2003/may/composition.pd.

16 Te entirety o the November 2011 GGS-OCC data, which con-sists o more than 10,000 distinct green categoryindustryoccupationcells, is available on the BLS GGS-OCC program page; see Green Goodsand Services Occupations: Green Goods and Services Occupations(GGS-OCC),www.bls.gov/ggsocc.
http://www.bls.gov/ggsocc/survey_methods.htmhttp://www.bls.gov/ggsocc/survey_methods.htmhttp://www.bls.gov/ggsocc/faq.htm#7http://www.bls.gov/green/#definitionhttp://www.bls.gov/sochttp://www.bls.gov/soc/2010/soc172081.htmhttp://www.bls.gov/oes/highlight_environment.htmhttp://www.bls.gov/oes/highlight_environment.htmhttp://www.bls.gov/opub/mlr/2009/06/art2full.pdfhttp://www.bls.gov/oes/2003/may/composition.pdfhttp://www.bls.gov/oes/2003/may/composition.pdfhttp://www.bls.gov/ggsocchttp://www.bls.gov/ggsocchttp://www.bls.gov/oes/2003/may/composition.pdfhttp://www.bls.gov/opub/mlr/2009/06/art2full.pdfhttp://www.bls.gov/oes/highlight_environment.htmhttp://www.bls.gov/oes/highlight_environment.htmhttp://www.bls.gov/soc/2010/soc172081.htmhttp://www.bls.gov/sochttp://www.bls.gov/green/#definitionhttp://www.bls.gov/ggsocc/faq.htm#7http://www.bls.gov/ggsocc/survey_methods.htmhttp://www.bls.gov/ggsocc/survey_methods.htm


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Visual Essay: Green Technologies and Practices

Green technologies and practices:

a visual essay

Audrey Watson

Three-quarters o business establishments during

August 2011 used at least one green technologyor practice to make their production processes

more environmentally riendly. More than hal tooksteps to reduce or eliminate the creation o waste ma-terials as a result o their operations, and approximately1 in 5 used technologies or practices to conserve naturalresources such as soil, water, or wildlie. Inormation andeducational services were among the industries with thehighest incidence o green technologies and practices,

with more than 4 in 5 such establishments reporting theuse o at least one green technology or practice.

Green technologies and practices accounted or morethan hal o the time workers spent at more than 850,000

jobs; this represents about 0.7 percent o total U.S. jobs

and included, or example, 56,700 janitors, 22,000 land-scaping and groundskeeping workers, and 13,300 auto-motive service technicians and mechanics.

Tese are some o the results rom the rst Bureau oLabor Statistics (BLS) Green echnologies and Practices(GP) survey, released in June 2012. Te GP survey isa sample survey o 35,000 business establishments thatcollects inormation on the use o green technologies andpractices, along with inormation about employment and

wages or workers who spend more than hal their timeinvolved in these technologies and practices. Te GPsurvey uses the BLS process approach to measuring green

jobs. (A separate BLS survey, the Green Goods and Ser-vices (GGS) survey, uses the output approach to measuringgreen jobs by collecting data on jobs that are associated

with producing goods or providing services that benetthe environment or conserve natural resources. Data onGGS jobs are available atwww.bls.gov/ggs.)

For the purposes o the GP survey, green technolo-gies and practices are dened as those which make anestablishments production processes more environ-mentally riendly. GP survey respondents were asked

whether they had used each o the ollowing types ogreen technologies and practices during the survey re-erence period, the pay period that included August 12,2011:

Generation o electricity, heat, or uel rom renewablesources primarily or use within the establishment

Use o technologies or practices to improve energyeciency within the establishment

Use o technologies or practices in operations toreduce greenhouse gas emissions through methodsother than renewable energy generation and energyeciency

Use o technologies or practices either to reduce the

creation or release o pollutants or toxic compoundsas a result o operations or to remove pollutants orhazardous waste rom the environment

Use o technologies or practices to reduce or elimi-nate the creation o waste materials as a result ooperations

Use o technologies or practices in operations toconserve natural resources, excluding the use o re-cycled inputs in production processes

Respondents also were asked to provide employment

and wage inormation, by occupation, or workers whospent more than hal their time involved in green tech-nologies and practices during the survey reerence period.

Workers were considered to be involved in green tech-nologies and practices i they were researching, develop-ing, maintaining, using, or installing green technologiesand practices or were training the establishments work-ers in these technologies and practices.

Tis visual essay presents highlights rom the GPsurvey. Te rst 7 charts ocus on business establish-
http://www.bls.gov/ggshttp://www.bls.gov/ggs


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ments use o green technologies and practices. Charts 1and 2 show the percentage o establishments, nationallyand by census region, that used at least one green technol-ogy or practice and that used specic types o technologiesor practices during the survey reerence period. Charts 3

through 7 present data on green technologies and practicesuse by industry.

Te second part o the visual essay presents data on GPemployment, or employment o workers who spent morethan hal their time involved in green technologies andpractices during the