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    News Release Information

    20-663-ATL
    Thursday, April 23, 2020

    Contacts

    Technical information:
    Media contact:
    • (404) 893-4220

    Occupational Employment and Wages in Charlotte-Concord-Gastonia — May 2019

    Workers in the Charlotte-Concord-Gastonia, NC-SC?Metropolitan Statistical Area had an average (mean) hourly wage of $25.07 in May 2019, about 3 percent below the nationwide average of $25.72, the U.S. Bureau of Labor Statistics reported today. Regional Commissioner Janet S. Rankin noted that, after testing for statistical significance,?3 of the 22 major occupational groups had average wages in the local area that were significantly higher than their respective national averages: sales and related, management, and business and financial operations. Thirteen groups had significantly lower wages than their respective national averages, including construction and extraction, architecture and engineering, and healthcare practitioners and technical.

    When compared to the nationwide distribution, Charlotte area?employment was more highly concentrated in 6 of the 22 occupational groups, including transportation and material moving, sales and related, and business and financial operations. Twelve groups had employment shares significantly below their national representation, including healthcare support, educational instruction and library, and healthcare practitioners and technical. (See table A and box note at end of release.)

    Table A. Occupational employment and wages by major occupational group, United States and the Charlotte-Concord-Gastonia, NC-SC?Metropolitan Statistical Area, and measures of statistical significance, May 2019?
    Major occupational groupPercent of total employmentMean hourly wage
    United StatesCharlotteUnited StatesCharlottePercent difference (1)

    Total, all occupations

    100.0100.0$25.72$25.07*-3

    Management

    5.55.558.8862.69*6

    Business and financial operations

    5.66.8*37.5639.03*4

    Computer and mathematical

    3.14.1*45.0844.46-1

    Architecture and engineering

    1.81.6*42.6938.52*-10

    Life, physical, and social science

    0.90.5*37.2833.26*-11

    Community and social service

    1.51.1*24.2722.72*-6

    Legal

    0.80.7*52.7149.86-5

    Educational instruction and library

    6.15.0*27.7521.69*-22

    Arts, design, entertainment, sports, and media

    1.41.1*29.7928.95-3

    Healthcare practitioners and technical

    5.95.0*40.2136.53*-9

    Healthcare support

    4.43.1*14.9114.23*-5

    Protective service

    2.42.2*23.9819.88*-17

    Food preparation and serving related

    9.29.112.8211.66*-9

    Building and grounds cleaning and maintenance

    3.02.6*15.0313.38*-11

    Personal care and service

    2.22.215.0313.51*-10

    Sales and related

    9.811.3*20.7023.02*11

    Office and administrative support

    13.312.7*19.7319.58-1

    Farming, fishing, and forestry

    0.30.1*15.0714.22-6

    Construction and extraction

    4.24.4*25.2820.97*-17

    Installation, maintenance, and repair

    3.94.1*24.1024.100

    Production

    6.26.519.3018.45*-4

    Transportation and material moving

    8.510.3*18.2316.94*-7

    Footnotes:
    ?(1) A positive percent difference measures how much the mean wage in the Charlotte-Concord-Gastonia, NC-SC?Metropolitan Statistical Area is above the national mean wage, while a negative difference reflects a lower wage.
    ? * The mean hourly wage or percent share of?employment?for this area is significantly different from the national average of all areas at the 90-percent confidence level.

    One occupational group—transportation and material moving—was chosen to illustrate the diversity of data available for any of the 22 major occupational categories. Charlotte had 128,790 jobs in transportation and material moving occupations, accounting for 10.3 percent of local area employment, significantly higher than the 8.5-percent share nationally. The local?average hourly wage for this occupational group was $16.94, significantly lower than the national wage of $18.23.

    Some of the larger detailed occupations within the transportation and material moving group included laborers and hand freight, stock, and material movers (32,970); stockers and order fillers (21,170); and heavy and tractor-trailer truck?drivers (18,430). Among the higher paying jobs were crane and tower operators, and heavy and tractor-trailer truck drivers,?with mean hourly wages of $23.83 and $21.92, respectively. At the lower end of the wage scale were parking attendants ($10.97) and cleaners of vehicles and equipment ($11.63). (Detailed data for the?transportation and material moving occupations?are presented in table 1; for a complete listing of detailed occupations available go to www.digitalmonojit.com/oes/current/oes_16740.htm.)

    Location quotients allow us to explore the occupational make-up of a metropolitan area by comparing the composition of jobs in an area relative to the national average. (See table 1.) For example, a location quotient of 2.0 indicates that an occupation accounts for twice the share of employment in the area than it does nationally. In the Charlotte Area, above-average concentrations of employment were found in some of the occupations within the transportation and material moving group. For instance, flight attendants were employed at 3.8 times the national rate in Charlotte, and commercial pilots, at 2.4 times the U.S. average.?Light truck drivers had a location quotient of 1.0 in Charlotte, indicating that this particular occupation’s local and national employment shares were similar.

    These statistics are from the Occupational Employment Statistics (OES) survey, a federal-state cooperative program between BLS and State Workforce Agencies, in this case, the North?Carolina Department of Commerce.

    Changes to the Occupational Employment Statistics (OES) Data

    With the May 2019 estimates, the OES program has begun implementing the 2018 Standard Occupational Classification (SOC) system. Each set of OES estimates is calculated from six panels of survey data collected over three years. Because the May 2019 estimates are based on a combination of survey data collected using the 2010 SOC and survey data collected using the 2018 SOC, these estimates use a hybrid of the two classification systems that contains some combinations of occupations that are not found in either the 2010 or 2018 SOC. These combinations may include occupations from more than one 2018 SOC minor group or broad occupation. Therefore, OES will not publish data for some 2018 SOC minor groups and broad occupations in the May 2019 estimates. The May 2021 estimates, to be published in Spring 2022, will be the first OES estimates based entirely on survey data collected using the 2018 SOC.

    In addition, the OES program has replaced some 2018 SOC detailed occupations with SOC broad occupations or OES-specific aggregations. These include home health aides and personal care aides, for which OES will publish only the 2018 SOC broad occupation 31-1120 Home Health and Personal Care Aides.

    For more information on the occupational classification system used in the May 2019 OES estimates, please see www.digitalmonojit.com/oes/soc_2018.htm and www.digitalmonojit.com/oes/oes_ques.htm#qf10.

    The May 2019 OES estimates use the metropolitan area definitions delineated in Office of Management and Budget (OMB) Bulletin 17-01, which add a new Metropolitan Statistical Area (MSA) for Twin Falls, Idaho. For more information on the area definitions used in the May 2019 estimates, please see www.digitalmonojit.com/oes/current/msa_def.htm.


    Technical Note

    The Occupational Employment Statistics (OES) survey is a semiannual survey measuring occupational employment and wage rates for wage and salary workers in nonfarm establishments in the United States. The OES data available from BLS include cross-industry occupational employment and wage estimates for the nation; over 580 areas, including states and the District of Columbia, metropolitan statistical areas (MSAs), nonmetropolitan areas, and territories; national industry-specific estimates at the NAICS sector, 3-digit, most 4-digit, and selected 5- and 6-digit industry levels, and national estimates by ownership across all industries and for schools and hospitals. OES data are available at www.digitalmonojit.com/oes/tables.htm.

    The OES survey is a cooperative effort between BLS and the State Workforce Agencies (SWAs). BLS funds the survey and provides the procedures and technical support, while the State Workforce Agencies collect most of the data. OES estimates are constructed from a sample of about 1.1 million establishments. Each year, two semiannual panels of approximately 180,000 to 200,000 sampled establishments are contacted, one panel in May and the other in November. Responses are obtained by mail, Internet or other electronic means, email, telephone, or personal visit. The May 2019 estimates are based on responses from six semiannual panels collected over a 3-year period: May 2019, November 2018, May 2018, November 2017, May 2017, and November 2016. The unweighted sampled employment of 83 million across all six semiannual panels represents approximately 57 percent of total national employment. The overall national response rate for the six panels, based on the 50 states and the District of Columbia, is 71 percent based on establishments and 68 percent based on weighted sampled employment. The sample in the Charlotte-Concord-Gastonia, NC-SC Metropolitan Statistical Area included?6,809 establishments with a response rate of?72 percent. For more information about OES concepts and methodology, go to www.digitalmonojit.com/oes/current/oes_tec.htm.

    A value that is statistically different from another does not necessarily mean that the difference has economic or practical significance. Statistical significance is concerned with the ability to make confident statements about a universe based on a sample. It is entirely possible that a large difference between two values is not significantly different statistically, while a small difference is, since both the size and heterogeneity of the sample affect the relative error of the data being tested.

    The May 2019 OES estimates are the first set of OES estimates to be based in part on survey data collected using the 2018 SOC. These estimates use a hybrid of the 2010 and 2018 SOC systems. More information on the hybrid classification system is available at www.digitalmonojit.com/oes/soc_2018.htm.

    The May 2019 OES estimates are based on the 2017 North American Industry Classification System (NAICS). More information about the 2017 NAICS is available at www.digitalmonojit.com/bls/naics.htm.

    Metropolitan Area definitions

    The substate area data published in this release reflect the standards and definitions established by the U.S. Office of Management and Budget.

    The Charlotte-Concord-Gastonia, NC-SC Metropolitan Statistical Area includes Cabarrus, Gaston, Iredell, Lincoln, Mecklenburg, Rowan, and Union Counties in North Carolina and?Chester, Lancaster, and York Counties in South Carolina.

    For more information

    Answers to frequently asked questions about the OES data are available at www.digitalmonojit.com/oes/oes_ques.htm. Detailed information about the OES program is available at www.digitalmonojit.com/oes/oes_doc.htm.

    Information in this release will be made available to sensory impaired individuals upon request. Voice phone: (202) 691-5200; Federal Relay Service: (800) 877-8339.

    Table 1. Employment and wage data for transportation and material moving occupations, Charlotte-Concord-Gastonia,?NC-SC Metropolitan Statistical Area, May 2019??
    Occupation (1)EmploymentMean wages
    Level (2)Location quotient (3)HourlyAnnual (4)

    Transportation and material moving occupations

    128,7901.2$16.94$35,240

    First-line supervisors of transportation and material moving workers, except aircraft cargo handling supervisors

    5,7101.525.6853,410

    Airline pilots, copilots, and flight engineers

    (5)(5)(6)104,100

    Commercial pilots

    7602.4(6)81,100

    Airfield operations specialists

    901.018.9339,380

    Flight attendants

    3,9003.8(6)56,190

    Driver/sales workers

    4,7601.312.2725,520

    Heavy and tractor-trailer truck drivers

    18,4301.221.9245,590

    Light truck drivers

    8,0501.016.7234,770

    Bus drivers, transit and intercity

    9200.618.2037,860

    Passenger vehicle drivers, except bus drivers, transit and intercity

    4,0600.713.4627,990

    Motor vehicle operators, all other

    9101.910.9722,820

    Parking attendants

    1,2101.010.9722,830

    Automotive and watercraft service attendants

    9601.012.6126,240

    Traffic technicians

    (5)(5)18.8939,300

    Transportation inspectors

    500.239.6982,550

    Passenger attendants

    (5)(5)12.4425,880

    Aircraft service attendants and transportation workers, all other

    3001.013.2927,640

    Conveyor operators and tenders

    1500.717.2135,800

    Crane and tower operators

    3801.023.8349,560

    Industrial truck and tractor operators

    7,1601.316.9635,280

    Cleaners of vehicles and equipment

    3,5601.111.6324,190

    Laborers and freight, stock, and material movers, hand

    32,9701.314.1429,410

    Machine feeders and offbearers

    3200.612.2325,430

    Packers and packagers, hand

    8,1501.512.2225,410

    Stockers and order fillers

    21,1701.213.7028,500

    Refuse and recyclable material collectors

    2,2202.215.7532,750

    Material moving workers, all other

    300.115.0731,360

    Footnotes:
    ?(1) For a complete listing of all detailed occupations in the Charlotte-Concord-Gastonia, NC-SC, see www.digitalmonojit.com/oes/current/oes_16740.htm.
    ?(2) Estimates for detailed occupations do not sum to the totals because the totals include occupations not shown separately. Estimates do not include self-employed workers.
    ?(3) The location quotient is the ratio of the area concentration of occupational employment to the national average concentration. A location quotient greater than one indicates the occupation has a higher share of employment than average, and a location quotient less than one indicates the occupation is less prevalent in the area than average.
    ?(4) Annual wages have been calculated by multiplying the hourly mean wage by a "year-round, full-time" hours figure of 2,080 hours; for those occupations where there is not an hourly mean wage published, the annual wage has been directly calculated from the reported survey data.
    ?(5) Estimate not released.
    ?(6) Wages for some occupations that do not generally work year-round, full time, are reported either as hourly wages or annual salaries depending on how they are typically paid.

     

    Last Modified Date: Thursday, April 23, 2020

    光棍天堂影院1111
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