Weathe r i zat ion As s i s tance Prof i l e
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R e s e a r c h & E c o n o m i c A n a l y s i s
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Generally defined, weatherization protects a building from sunlight, precipitation and wind, reducing the overall
level of energy use required to keep the building’s inhabitants comfortable. Common weatherization projects
include replacing doors and windows, sealing gaps and upgrading insulation. As defined here in this brief, the
weatherization industry in Oklahoma is a relatively small but potentially growing player in the regional economy.
INDUSTRY EMPLOYMENT
In 2002, Oklahoma had 49,580 jobs in the weatherization industry according to EMSI.1 The heaviest concentration
of weatherization employment is found in the construction industry and common jobs include electrical, plumbing,
drywall, and heating and air contractors; gypsum product manufacturers; boiler and heat exchanger manufacturers;
sheet metal workers; and plastics film and sheet manufacturing, to name a few.
EMSI projects that by 2019, Oklahoma’s
weatherization industry related jobs will exceed
67,625. The addition of more than 18,000 jobs
between 2002 and 2019 represents a 36%
increase in employment over 17 years. That
equals approximately an average 2% increase
year-over-year, which is slightly better job
growth than is projected for the economy as a
whole during that time span.2
Roughly one quarter of Oklahoma’s
weatherization workers are self-employed.
Among the self-employed weatherization
workers, most are drywall and insulation
contractors, followed closely by electrical
contractors and plumbing and HVAC contractors.
The following charts provide more detail.
1 Economic Modeling Specialists, Inc. (EMSI), Complete Employment 1st Quarter 2010, as accessed on March 17, 2010
2 Economic Modeling Specialists, Inc. (EMSI), Complete Employment 1st Quarter 2010, as accessed on March 17, 2010
Weatherization Industry Employment in Oklahoma
2002-2008 (Actual and Estimated)
2009-2019 (Projected)
38,188 in 2002
11,392 in 2002 51,689 in 2019
15,936 in 2019
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
Contract or self-employed
Employed by another
OKLAHOMA'S WEATHERIZATION
INDUSTRY EMPLOYMENT 2002
38,188 ,
77%
1,891 ,
4%
2,508 ,
5%
3,929 ,
8%
3,064 ,
6%
11,392 ,
23%
employer establishment
Electrical contractors
Plumbing and HVAC contractors
Drywall and insulation contractors
Other
OKLAHOMA'S WEATHERIZATION
INDUSTRY EMPLOYMENT 2019
51,689 ,
76%
2,371 ,
4%
4,556 ,
7%
5,705 ,
8%
3,304 ,
5%
15,936 ,
24%
employer establishment
Electrical contractors
Plumbing and HVAC contractors
Drywall and insulation contractors
Other
wwwwwwwww
.okcommerce.gov Research & Economic Analysis
O
klahoma’s Weatherization Assistance Profile
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April 2010
Oklahoma’s weatherization workforce generated an estimated $2.7 billion in statewide earnings in 2009, based on EMSI’s earnings per worker and 2009 employment estimate.3 Almost half came from those working as plumbing and HVAC contractors (23%) and electrical contractors (22%).4
The 2002 Economic Census reports Oklahoma had 15 establishments manufacturing metal windows and doors at that time. Collectively, they employed almost 1,300 workers, generated almost $39 million in payroll, and produced over $208 million in shipments.5 A complete detailing of the value of weatherization products is not provided here as Economic Census data does not go to the appropriate level of detail necessary. Data from the 2007 Economic Census is not yet available at the time of the writing of this brief.
HOUSING STOCK
The 2000 Census defines housing units to include houses, apartments, houseboats, trailers, vans and mobile homes. Any individual housing unit with nine or more residents is considered group quarters and not part of the overall housing stock. At the time of the 2000 Census Oklahoma had 1.5 million housing units. Half were built before 1972 and one-third were built prior to 1960.6 Older homes, due to design or deterioration, are more likely to require weatherization assistance so that the structures will be more energy efficient.
Homes in Oklahoma’s western counties are more likely to be older while homes in eastern counties are more likely to be newer (see map below). This trend is partially explained by the fact that most western counties in Oklahoma experienced peak population before World War II, reducing demand for newer housing. Yet many southeastern Oklahoma counties also experienced peak population before World War II and the median year of construction for homes in that part of the state is firmly set in the 1970s.
3 Economic Modeling Specialists, Inc. (EMSI), Complete Employment 1st Quarter 2010, as accessed on March 17, 2010
4 Economic Modeling Specialists, Inc. (EMSI), Complete Employment 1st Quarter 2010, as accessed on March 17, 2010
5 US Census Bureau, 2002 Economic Census, Sector 31: Manufacturing: Industry Series: NAICS 332321, as accessed on April 5, 2010
6 US Census Bureau, 2000 Census, Table HCT23, Tenure by year structure built by units in structure
Oklahoma's Weatherization Industry2009 Earnings Estimates$254$35$41$44$52$71$84$100$260$279$287$596$636$0$100$200$300$400$500$600$700Other weatherization sub-industriesMetal window and door manufacturingGlass and glazing contractorsSheet metal work manufacturingNonpackaging plastics film and sheet mfg.Industrial process variable instrumentsOther building equipment contractorsMasonry contractorsDrywall and insulation contractorsPower boiler and heat exchanger manufacturingAC, refrigeration, and forced air heatingElectrical contractorsPlumbing and HVAC contractorsIn MillionsMedian Age of Housing Units by Counties Source: Census 2000 Summary File 3: Table H35 Median year structure built Map created by: Oklahoma Department of Commerce Date: April 8, 2010 TexasOsageEllisBeaverKayCimarronLe FloreCaddoMcCurtainWoodsGradyGrantAtokaMajorKiowaCreekBryanPittsburgHarperCusterBlaineDeweyCraigAlfalfaLincolnGarfieldCarterNobeWashitaGarvinTillmanLoganWoodwardPushmatahaCoalGreerAdairPayneLoveTulsaHughesMayesRoger MillsComancheRogersLatimerJacksonCottonBeckhamCanadianStephensChoctawKingfisherHaskellJeffersonDelawarePontotocMuskogeeCherokeeWashingtonTexasOsageEllisBeaverKayCimarronLe FloreCaddoMcCurtainWoodsGradyGrantAtokaMajorKiowaCreekBryanPittsburgHarperCusterBlaineDeweyCraigAlfalfaLincolnGarfieldCarterNobeWashitaGarvinTillmanLoganWoodwardPushmatahaCoalGreerAdairPayneLoveTulsaHughesMayesRoger MillsComancheRogersLatimerJacksonCottonBeckhamCanadianStephensChoctawKingfisherHaskellJeffersonDelawarePontotocMuskogeeCherokeecIntoshNowataPawneeJohnstonSequoyahOklahomaOkmulgeeOttawaOkfuskeeWagonerMurrayMarshallMcClainSeminoleHarmonPottawatomieClevelanWashingtonMedian Home AgeBy County1946 - 19641965 - 19701971 - 19741975 - 1979Median Home AgeBy County1946 - 19641965 - 19701971 - 19741975 - 1979Oklahoma Housing Counts by CountiesWashingtonMarshallClevelandPottawatomieMurrayHarmonOkfuskeeSeminoleOkmulgeeMcClainNowataPawneeCherokeeDelawareTulsaWagoerOttawaOklahomaSequoyahJohnstonMcIntoshPontotocMuskogeeJeffersonHaskellKingfisherChoctawCottonLatimerStephensCanadianBeckhamJaksonRogersComancheRoger MillsAdairMayesHughesLoveGreerCoalPaynePushmatahaTillmanWoodwardLoganGarvinNobleWashitaCarterGarfieldLincolnAlfalfaCraigDeweyBlineHarperCusterPittsburgBryanCreekMajorAtokaKiowaGrantGradyMcCurtainWoodsCimarronCaddoLe FloreKayBeaverEllisTexasOsageWashingtonMarshallClevelandPottawatomieMurrayHarmonOkfuskeeSeminoleOkmulgeeMcClainNowataPawneeCherkeeDelawareTulsaWagonerOttawaOklahomaSequoyahJohnstonMcIntoshPontotocMuskogeeJeffersonHaskellKingfisherChoctawCottonLatimerStepensCanadianBeckhamJacksonRogersComancheRoger MillsAdairMayesHughesLoveGreerCoalPaynePushmatahaTillmanWoodwardLoganGarvinNobleWashitaCarterGarfieldLincolnAlfalfaCraigDeweyBlineHarperCusterPittsburgBryanCreekMajorAtokaKiowaGrantGradyMcCurtainWoodsCimarronCaddoLe FloreKayBeaverEllisTexasOsageSource: H34. YEAR STRUCTURE BUILT [10] Data Set: Census 2000 Summary File 3 (SF 3) - Sample Data Map created by Oklahoma Department of Commerce April 8, 2010Housing CountsBy CountyLess than 5,0005,000 to 10,00010,001 to 20,00020,001 to 50,000More than 50,000Housing CountsBy CountyLess than 5,0005,000 to 10,00010,001 to 20,00020,001 to 50,000More than 50,000ww ww ww . o k c o m m e r c e . g o v R e s e a r c h & E c o n o m i c A n a l y s i s
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This indicates the time of peak population has not been the only driver for home construction across the state.
Mobile homes (including trailers, RVs, vans, houseboats, and similar structures) are often targeted for weatherization improvements due to a variety of factors including deterioration over time and improvements in housing design. Mobile homes represent 10% of the state’s housing stock and also influence the median year of home construction.
There are 14 counties in Oklahoma where mobile homes make up more than 20% of the housing stock. In 12 of those counties, the median year of home construction is in the 1970s. In the other two, the median year of construction is in the late 1960s.
Weatherization funding is based in part on a composite housing quality index designed to assess the overall condition of properties within each county. The method used to calculate the index is explained in Appendix A. The higher a county’s score, the more substandard housing exists within that county. Data indicates a higher prevalence of substandard housing in the Oklahoma panhandle area and in the southeastern part of the state.
POVERTY
Weatherization projects under the US federal government’s Weatherization Assistance Program (WAP) save low-income families an average of $350 in reduced first-year energy costs at current prices.7 The reductions are particularly relevant in light of the fact that energy spending typically consumes $1 out of every $6 of total earnings in low-income households. Energy spending by other households typically consumes $1 of every $25 earned.8
Poverty figures are defined at the national level and do not take into account local cost of living. Due to cost of living differences, a person living at poverty level in Oklahoma is likely to be better off than a person living at poverty level in New York City or Los Angeles.
7 US Department of Energy, Weatherization Assistance Program Overview, as accessed on March 17, 2010 at
http://www.waptac.org/sp.asp?id=1437/
8 Greg Reamy and Carole Gates, Weatherization for Newcomers, presented at the 2009 Weatherization Training Conference, as accessed
on March 17, 2010 at http://207.188.207.153/doclib/openfile.asp?id=1105
Oklahoma Counties With Highest Rate of Mobile Homes as Percentage of Overall Housing Stock
Geographic Area
Peak Population Census Year
Median Year of Construction for All Housing Structures
Mobile Homes As Percent of Housing Stock As Mobile Homes
Oklahoma Statewide
2000
1972
10%
Delaware
2000
1979
32%
Marshall
1920
1977
28%
McIntosh
1920
1979
28%
Pawnee
1930
1973
26%
Texas
2000
1969
23%
Nowata
1920
1967
23%
Creek
2000
1974
22%
Lincoln
1910
1974
22%
Cherokee
2000
1978
22%
Mayes
2000
1974
22%
Adair
2000
1975
22%
Logan
2000
1974
22%
Haskell
1920
1974
21%
Love
1920
1975
20%
Sources: 2000 Census, Summary File 4, Table H35 and HCT23
Peak Population of Oklahoma Counties by Decennial Census WashingtonMarshallClevelandPottawatomieOkfuskeeHarmonSeminoleOkmulgeeMcClainCherokeeDelawareMurrayWagonerOttawaOklahomaSequoyahohnstonPawneeNowataMcIntoshMuskogeePontotocJeffersonHaskellKingfisherChoctawStephensCanadianBeckhamCottonJacksonLatimerRogersCoancheRoger MillsMayesHughesTulsaLovePayneAdairGreerCoalPushmatahaWoodwardLoganTillmanGarvinWashitaNobleCarterGarfieldLincolnAlfalfaCraigDeeyBlaineCusterHarperPittsburgBryanCreekKiowaMajorAtokaGrantGradyWoodsMcCurtainCaddoLe FloreCimarronKayBeaverEllisOsageTexasWashingtonMarshallClevelandPottawatomieOkfuskeeHarmonSeminoleOkmulgeeMcClainCherokeeDelawaeMurrayWagonerOttawaOklahomaSequoyahJohnstonPawneeNowataMcIntoshMuskogeePontotocJeffersonHaskellKingfisherChoctawStephensCanadinBeckhamCottonJacksonLatimerRogersComancheRoger MillsMayesHughesTulsaLovePayneAdairGreerCoalPushmatahaWoodwardLoganTillmanGarvinWashitaNobleCarterGarfieldLincolnAlfalfaCraigDeeyBlaineCusterHarperPittsburgBryanCreekKiowaMajorAtokaGrantGradyWoodsMcCurtainCaddoLe FloreCimarronKayBeaverEllisOsageTexasSource: U.S. Census Bureau, Decennial Census Programs Map created by Oklahoma Department of Commerce April 8, 2010 Decade of Peak PopulationBy County1900 to 19301940 to 19601970 to 19801990 to 2000Decade of Peak PopulationBy County1900 to 19301940 to 19601970 to 19801990 to 2000ww ww ww . o k c o m m e r c e . g o v R e s e a r c h & E c o n o m i c A n a l y s i s
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Similar differences exist, though on a much smaller scale, when comparing locations within the state. National poverty figures do make some differentiation based on size of family and age.
WAP provides weatherization services for persons living below 200% of the poverty line as defined by the US Census Bureau. The 2000 Census reports 37% of Oklahoma’s population live below the 200% poverty line. In particular, counties in southern Oklahoma show higher population percentages living below the 200% poverty level.
SUMMARY
Between 2000 and 2007, Weatherization and Low-Income Energy Programs administered by the Oklahoma Department of Commerce weatherized an average of 821 homes a year, at an average cost of $2,860 per home9. But that represents a fraction of the potential for weatherization services. Oklahoma has, on average, about 60 days below freezing in the southeast increasing to 140 days in the western panhandle. Oklahoma also has anywhere from 60-65 days over 90 degrees in the panhandle to 115 days over that temperature in the southwest10. In 2008, Oklahoma ranked 17th in the nation for the summer use of electric utilities11 despite ranking 28th in population.12
Oklahoma businesses also benefit from efforts to weatherize Oklahoma households. With over 3,600 establishments working in Oklahoma’s weatherization related industries,13 it is possible to keep money spent on replacement doors, windows, and insulation products in the state. Installation too creates jobs, supporting local contractors.
9 US Department of Energy, Weatherization Assistance Program – State Activities, as accessed on April 9, 2010 at
http://apps1.eere.energy.gov/weatherization/state_activities_detail.cfm/state_abbr=OK
10 Derek Arndt, Oklahoma Climatological Survey; Norman, Oklahoma; January 2003, as accessed on April 9, 2010 at
http://cig.mesonet.org/climateatlas/doc60.html
11 US Energy Information Administration, Oklahoma Electric Profile, Table 1 2008 Summary Statistics, as obtained April 9, 2010 at http://www.eia.doe.gov/cneaf/electricity/st_profiles/oklahoma.html
12 US Census Bureau, Population Estimates Division, Annual Estimates of the Resident Population for the United States, Regions, States, and Puerto Rico: April 1, 2000 to July 1, 2009 (NST-EST2009-01)
13 Economic Modeling Specialists, Inc. (EMSI), Complete Employment 1st Quarter 2010, as accessed on March 17, 2010
WashingtonClevelandPottawatomieHarmonSeminoleMcClainMarshallMurrayWagonerOkfuskeeOttawaOkmulgeeOklahomaSequoyahJohnstonPawneeNoataMcIntoshCherokeeMuskogeePontotocDelawareJeffersonHaskellKingfisherChoctawStephensCanadianBeckhamCottonJacksonLatimerRogersCoancheRoger MillsMayesHughesTulsaLovePayneAdairGreerCoalPushmatahaWoodwardLoganTillmanGarvinWashitaNobleCarterGarfieldLincolnAlfalfaCraigDeeyBlaineCusterHarperPittsburgBryanCreekKiowaMajorAtokaGrantGradyWoodsMcCurtainCaddoLe FloreCimarronKayBeaverEllisOsageTexasWashingtonClevelandPottawatomieHarmonSeminoleMcClainMarshallMurrayWagonerOkfuskeeOttawaOkmlgeeOklahomaSequoyahJohnstonPawneeNowataMcIntoshCherokeeMuskogeePontotocDelawareJeffersonHaskellKingfisherChoctawStephensCanadinBeckhamCottonJacksonLatimerRogersComancheRoger MillsMayesHughesTulsaLovePayneAdairGreerCoalPushmatahaWoodwardLoganTillmanGarvinWashitaNobleCarterGarfieldLincolnAlfalfaCraigDeeyBlaineCusterHarperPittsburgBryanCreekKiowaMajorAtokaGrantGradyWoodsMcCurtainCaddoLe FloreCimarronKayBeaverEllisOsageTexasWashingtonMarshallClevelandPottawatomieMurrayHarmonOkfuskeeSeminoleOkmulgeeMcClainNowataPaneeCherokeeDelawareTulsaWagonerOttawaOklahomaSequoyahJohnstonMcIntoshPontotocMuskogeeJeffersonHaskellKingfisherChoctawCottonLatmerStephensCanadianBeckhamJacksonRogersComancheRoger MillsAdairMayesHughesLoveGreerCoalPaynePushmatahaTillmanWoodwardLoganGarvinNobleWashitaCarterGarfieldLincolnAlfalfaCraigDeweyBlineHarperCusterPittsburgBryanCreekMajorAtokaKiowaGrantGradyMcCurtainWoodsCimarronCaddoLe FloreKayBeaverEllisTexasOsageWashingtonMarshallClevelandPottawatomieMurrayHarmonOkfuskeeSeminoleOkmulgeeMcClainNowataPawneeCherkeeDelawareTulsaWagonerOttawaOklahomaSequoyahJohnstonMcIntoshPontotocMuskogeeJeffersonHaskellKingfisherChoctawCottonLatimerStepensCanadianBeckhamJacksonRogersComancheRoger MillsAdairMayesHughesLoveGreerCoalPaynePushmatahaTillmanWoodwardLoganGarvinNobleWashitaCarterGarfieldLincolnAlfalfaCraigDeweyBlineHarperCusterPittsburgBryanCreekMajorAtokaKiowaGrantGradyMcCurtainWoodsCimarronCaddoLe FloreKayBeaverEllisTexasOsageQuality of Housing Units by Counties Source: Score based on Census 2000 Summary File 3: Tables H20 Tenure by occupants per room; H47 Plumbing facilities; H50 Kitchen facilities Blended score based on percentage of homes lacking complete plumbing facilities, percentage lacking complete kitchen facilities and percentage subject to overcrowding. Score of 1.3 is considered average. Higher scores represent increasingly substandard conditions. Map created by: Oklahoma Department of Commerce Date: April 8, 2010 Percent of Population Below 200% of Poverty by Counties Source: Census 2000 Summary File 3: Table PCT50 Age by ratio of income in 1999 to poverty level Map Created by: Oklahoma Department of Commerce Date: April 8, 2010 Housing QualityBy County1.8 to 3.21.3 to 1.71.0 to 1.20.5 to 0.9Housing QualityBy County1.8 to 3.21.3 to 1.71.0 to 1.20.5 to 0.9Percent In PovertyBy County46% to 56%42% to 45%38% to 41%24% to 37%Percent In PovertyBy County46% to 56%42% to 45%38% to 41%24% to 37%ww ww ww . o k c o m m e r c e . g o v R e s e a r c h & E c o n o m i c A n a l y s i s
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NAICS
Industry
NAICS
Industry
23814
Masonry contractors
32615
Urethane and other foam product manufacturing
23815
Glass and glazing contractors
326199
All other plastics product manufacturing
23821
Electrical contractors
32742
Gypsum product manufacturing
23822
Plumbing and HVAC contractors
327992
Ground or treated minerals and earths mfg.
23829
Other building equipment contractors
327993
Mineral wool manufacturing
23831
Drywall and insulation contractors
332321
Metal window and door manufacturing
23839
Other building finishing contractors
332322
Sheet metal work manufacturing
313221
Narrow fabric mills
33241
Power boiler and heat exchanger manufacturing
314912
Canvas and related product mills
332812
Metal coating and nonprecious engraving
314999
All other miscellaneous textile product mills
333414
Heating equipment, except warm air furnaces
321219
Reconstituted wood product manufacturing
333415
AC, refrigeration, and forced air heating
321911
Wood window and door manufacturing
334512
Automatic environmental control manufacturing
322222
Coated and laminated paper manufacturing
334513
Industrial process variable instruments
322299
All other converted paper product mfg.
334515
Electricity and signal testing instruments
325211
Plastics material and resin manufacturing
33511
Electric lamp bulb and part manufacturing
325212
Synthetic rubber manufacturing
335211
Electric housewares and household fan mfg.
325222
Noncellulosic organic fiber manufacturing
335222
Household refrigerator and home freezer mfg.
32552
Adhesive manufacturing
335228
Other major household appliance manufacturing
326113
Nonpackaging plastics film and sheet mfg.
33792
Blind and shade manufacturing
32614
Polystyrene foam product manufacturing
339991
Gasket, packing, and sealing device mfg.
APPENDICES
A.
The index is based on the percent of housing units in each county lacking complete plumbing facilities, lacking complete kitchen facilities, having between 1.01 and 1.5 persons per room (overcrowded), and having more than 1.5 persons per room (severely overcrowded). Data was obtained from the following tables in Summary File 3 of the 2000 Census.
H20. TENURE BY OCCUPANTS PER ROOM [13] - Universe: Occupied housing units
H47. PLUMBING FACILITIES [3] - Universe: Housing units
H50. KITCHEN FACILITIES [3] - Universe: Housing units
Severely overcrowded housing units received a doubled weighting as a more significant measure of housing inadequacy. The resulting numbers for each county were added together to achieve a gross composite score of housing conditions, then gross composite scores were added together for a grand total. The final composite score for each county is the county’s gross composite score as a percentage of the grand total.
While this is not an absolute expression of the quality of housing overall, it is considered a fair proxy measure to evaluate the existence of substandard housing relative to surrounding areas and relative to the overall housing quality with a given county. Lower scores represent increasingly better conditions while higher scores represent increasingly substandard conditions.
B.
NAICS industries considered to be part of the overall Weatherization Industry for purposes of this report.
If you have any questions regarding this profile, please contact Deidre Myers at deidre_myers@okcommerce.gov or Steve Barker at steven_barker@okcommerce.gov.
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