HomeMy WebLinkAboutU.S. Department of LaborDear Ms. Embleton:
Enclosed are the results of the recent National Compensation Survey of wages
for the Billings, MT area. Additional results are available for this area on our
website at hftp://www.bls.q6v/ncs/ocs/compub.htm
We are including a CD containing a collection of NCS publications from June
2007 to July 2008. The publications cover a broad range of compensation
information in over 150 areas.
The Bureau of Labor Statistics (BLS) appreciates the continued assistance of
firms like yours that provide current wage information. Your information makes an
important contribution to the measurement of compensation costs in our
economy and makes these survey results possible.
I invite you to use BLS as your source for business economic information. The
BLS programs provide a wide variety of information on such topics as wages and
benefits, job growth, consumer and producer prices, unemployment, and other
economic statistics for your industry and area. You may access this information
on our BLS web site at www.bls.gov.
If you have any questions about the National Compensation Survey or other
information available from BLS, please contact our Program Manager, Jerry
Shirley, at (800) 499-2597.
Sincerely,
FONDA IVY
Assistant Regional Commissioner
I _
Billings, MT
National Compensation Survey
State and Local Government
August 2008
U.S. Department of Labor
U.S. Bureau of Labor Statistics
January 2009
This summary provides results of an August 2008 sur-
vey of occupational pay in the Billings, MT, Metro-
politan Statistical Area (MSA). The MSA includes Carbon
and Yellowstone Counties. Tabulations in this publication
are limited to State and local government; future publica-
tions will include private industry.
Data shown in this summary were collected as part of
the Bureau of Labor Statistics (BLS) National Compensa=
lion -Survey- (NC-S). The NCS provides comprehensive
measures of occupational earnings, compensation cost
trends, benefit-incidence, and detailed plan-provisions.
This summary is limited to data on occupational wages and
salaries.
Table 1 presents mean hourly earnings data by work
level for occupational major groups and for detailed occu-
pations. Work level is a ranking based on knowledge, job
controls and complexity, contacts, and physical environ-
ment. Separate data are also shown for full-time and part-
time workers.
-Table 2 presents hourly wage percentiles that describe
the distribution of hourly earnings for individual workers
within eat publislied`accupation:-Data' aie provided for
the 10th, 25th, 50th, 75th, and 90th percentiles for detailed
occupations.
Table 3 presents mean and median hourly, weekly, and
annual earnings, and the associated hours, for major occu-
pational groups and detailed occupations for full-time
workers.
The survey could not have been conducted without the
cooperation of the many government agencies that pro-
FEB 1 7 2009
CITY OF LAUREL
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vided pay data included in this summary. The Bureau
thanks these respondents for their cooperation-. Field
economists of the Bureau of Labor Statistics collected and
reviewed the survey data. The Office of Compensation and
Working Conditions, in cooperation with the Office of
Field Operations and the Office of Technology and Survey
Processing in the BLS National Office, designed the sur-
vey, processed the data and the
prepared survey for publi-
cation. -----
Where to find more information
The data contained in this summary are available at
http://www.bis.gov/ncs/ocs/compub.htm, the BLS Inter-
net site. Data are presented in a Portable Document Format
(PDF) file, and in an ASCII file containing the published
table formats.
For additional information regarding this survey, includ-
ing a list of occupational classifications, please contact any
BLS regional office at the address and telephone number
listed on the back cover of this summary. You may also
write to the Bureau of Labor Statistics at: Division of
Compensation Data Analysis and Planning, 2 Massachu-
setts Avenue, NE., Room 4175, Washington, DC 20212-
0001, telephone (202) 691-6199, or send an e-mail to
NCSinfo@bls.gov.
. Material in this summary is in the public domain and,
with appropriate credit, may be reproduced without permis-
sion. This information will be made available to sensory
impaired individuals upon request. Voice phone: (202)
691-5200; Federal Relay Service 1--800-877-8339.
Table 1. State and local government workers: Mean hourly earnings' for full-time and part-time worker52 by work
levels3, Billings, MT, August 2008
Total Full-time workers Part-time workers
0ccupatlon4 and level Relative Relative Relative
Mean errors Mean errors Mean errors
(percent) (percent) (percent)
All woPkers ..................... ................................................... $24.71 5.6 $24.71 5.0 $24.67 39.3
Education, training, and library. occupations .................. 33.09 6.0 34.00 4.3 - -
Level9 ...................... :....:.......... :........... ........... 34.28 4.4 34.36 4.6 - -
Primary, secondary, and special education school
teachers - .......... :.:.:................ ....................................... 33.34 1.1 33.40 1.2 - -
Level9 .........................i.:...:...,,........................ 34.60 4.2 34.68 4.4 - -
Elementary and middle school teachers ...................... 37.26 3.9 37,64. 4.1 - -
Level9 .................. ..............:
.... ........................
38.42
4.8
-
-
-
Elementary school teachers, except special
education ......................................:........ ............. 37.90 4.4 - - - -
Secondary school teachers ..................... 33.16 348 33.16 3.8
Level9 ...................... ................. ..................... 33.16 3.8 33.16 3.8 - -
Secondary school teachers, except special and
vocational education ........................................... 33.16 3.8 33.16 3.8 - -
..........................
. Level9
..........................................
33.16
3.8
33.18
3.8
-
-
Protective service occupations ......................................... 21.19 5.7 22.03 6.7 - -
Offlce. and administrative support occupations .............. 13.64 7.3 13.59 7.6 - -
Office clerks, general ........................................................ 11.74 2.1 - - - -
Construction and extraction occupations ....................... 18.19 10.8 18.19 1018 - -
.r Earnings are the straight-time hourly wages or salaries paid to employees.
They include incentive pay, cost-of-living adjustments, and hazard pay. Excluded
are premium pay for overtime, vacations, holidays, nonproduction bonuses, and
lips. The mean is computed by totaling the pay of all workers and dividing by the
number of workers, weighted by hours. See appendix A for more information.
Employees are classified as working either a full-time or a part-time
schedule. based on the definition used by each establishment. Therefore, a
worker with a 35-hour-per-week schedule might be considered a full-time
employee In one establishment, but classified as pan-rime in another firm, where
a 40-hour week is the minimum full-time schedule.
33 Each occupation for which data are collected in an establishment is
evaluated based an four factors, Including knowledge, job controls and
complexity, contacts, and physical environment. The knowledge factor is tailored
to 24 families of dosely related jobs. Points are assigned based on the
occupation's rank within each factor. The points are summed to determine the
overall level of the occupation. See appendix A for more Information.
. 4 Workers are classified by occupation using the 2000 Standard
Ocoicpafional Classification (SOC) system, See appendix B ror more information.
6 The relative standard error (RSE) Is the standard error expressed as a
percent of the estimate. It can be used to calculate a "confidence interval" around
a sample estimate. For more information about RSEs, see appendix A.
SOURCE: Bureau of Labor Statistics, National Compensation Survey.
NOTE: Dashes Indicate that no data were reported or that data did not meet
publication criteria. Overall occupational groups may include data for categories
not shown separately
A
Table 2. State and local government workers: Hourly wage percentiles', Billings, MT, August 2008
Occupation2 10 25 M Dian 75 90
All workers .............................................................................. $12.49 $16.24 $20.86 $31.80 $45.09
Education, training, and library occupations .................. 16.78 24.82 33.98 43.22 45.81
Primary, secondary, and special education school
teachers ...................................................................... 19.40 27.43 32.73 40.80 45.09
Elementary and middle school teachers ....................... 24.05 32.73 40.80 45.09 45.09
Elementary school teachers, except special
education ............................................................ 24.05 34.92 40.80 45.09 45.09
Secondary schoolteachers .......................................... 22.$7 29.23 30.92 4t,51 45.09
Secondary school teachers, except special and
vocational education ........................................... 22.57 29.23 30,92 41.51 45.09
Protective service occupations ......................................... 16.04 18.47 20.88 24.63 26.83
Office and administrative support occupations .............. 11.00 11.18 12.50 1;5.20 20.00
Office clerks, general ........................................................ 10.69 11.00 11.13 12.89 13.20
Construction and extraction occupations ....................... 13.24 13.24 18.63 22.37 23.61
I percentiles designate position in the eamings distribution and are
calculated from individual-worker earnings and the hours they are
scheduled to work. At the 50th percentile, the median, half of the hours
are paid the some as or more than the rate shown, and half are paid the
same as or less than the rate shown, At the 25th percentile, one-fourth
of the hours are paid the same as or less than the rate shown, At the
75th percentile, one-fourth are paid the same as or more than the rate
shown. The 10th and 90th percentiles follow, the same logic. Hourly
wages are the straight-time wages or salaries paid to employees. They
Include incentive pay, cost-cf-living adjustments, and hazard pay.
Excluded, are premium pay for overtime, vacations, and holidays;
nonoraduotion bonuses; and tips.
22 Workers are classified by occupation using the 2000 Standard
Occupational Classification (SOC) system. See appendix B for more
Information.
SOURCE; Bureau of Labor Statistics, National Compensation Survay.
NOTE; Dashes Indicate that no data were reported or that data did not
meet publication criteria. Overall occupational groups may include data
for categories not shown separately
r
4
Table 3. Full-timer State and local government workers: Mean and median hourly, weekly, and annual earnings
and mean weekly and annual hours, Billings, MT, August 2008
Hourly eamings3 Weekly earnings4 Annual eamings5
Occupation
Mean Mean
Mean Median Mean Median weekly Mean Median, annual
hours hours
All workers ................................. .......... $24.71 $20.86 $971 $863 39.3 $43,418 $43,029 1,757
Education, training, and library
occupations .................................... 34.00 35.13 1,298 1,318 38.2 49,501 49,578 1,456
Primary, secondary, and special
education school teachers ............ 33.40 33.06 1,267 1,241 37.9 47,400 46,406 1,419
Elementary and middle school
teachers ............ :.................... ... 37.64 40.80 1,427 1,530 37.9 53,375 57221 1,418
Secondary school teachers ............ 33.16 30.92 1,253 1,159 37.8 46,879 43,360 1,414
Secondary school teachers,
except special and vocational
education .............................. 33.16 30.92 1,253 1,159 37.8 46,879 43,360 1,414
Protective service occupations .........., 22.03 21.09 897 910 40.7 46;668 47,323 2,119
Office and administrative support
occupations .................................... 13.59 12.50 544 500 40.0 27,485 26,000 21022
Construction and extraction
occupations .................................... 18.19 18.63 727 745 40.0 37,829 38,750 2,080
' Employees are classified as working either a full4me or a part-time
schedule based on the definition used by each establishment. Therefore, a
worker with a 35-hour-per-week schedule might be considered a full-time
employee In one establishment, but classified as part-time in another firm,
where a 40-hour week is the minimum full-lime schedule,
2 Workers are classified by occupation using the 2000 Standard
Occupational Classification (SOC) system. See appendix B for more
information.
3 Earnings are the straight-time hourly wages or salaries paid to
employees. They include incentive pay, cost-of-living adjustments, and
hazard pay. Excluded are premium pay for overtime, vacations, holidays,
nonproduction bonuses, and Ups. The mean is computed by totaling the pay
of all workers and dividing by the number of workers, weighted by hours. See
appendix A for more information.
4 Mean weekly earnings ere the straight-lime weekly wages or salaries
paid to employees. Median weekly earnings designates position - one-half of
the hours are paid the some as or more than the rate shown. Mean weekly
hours are the hours an employee is scheduled to work in a week, exclusive of
overtime.
5 Mean annual earnings are the straight-time annual wages or salaries
paid to employees. Median annual earnings designates position - one-half of
the hours are paid the same as or more than the-'rate shown. Mean annual
hours are the hours an employee is scheduled to work in a year, exclusive of
overtime.
SOURCE: Bureau of Labor Statistics; National Compensation Survey.
NOTE: Dashes Indicate that no data ware reported or that data did not meet
publication criteria. Overall occupational `groups' may include data for
categories not shown separately
Appendix: Technical Note
Survey scope
This survey of the Billings, MT, Metropolitan Statistical
Area (MSA) covered establishments employing one worker
or more in State and local governments. Future publica-
tions for this area will include private goods-producing
industries and private service-providing industries. Agri-
culture, forestry, fishing and hunting, private households,
and the Federal Government were excluded from the scope
of the survey. For purposes of this survey, an establish-
ment is an economic unit that produces goods or services, a
central administrative office, or an auxiliary unit providing
support services to a company. For State and local gov-
ernments, an establishment is defined as all locations of a
government agency within the sampled area.
Sampling frame
The list of establishments from which the survey sample
was selected (sampling frame) was developed from State
unemployment insurance reports. Due to the volatility of
industries within the private sector, sampling frames were
developed using the most recent month of reference avail-
able at the time the sample was selected.
Sample design
The sample for this survey area was selected using a two-
stage stratified design with probability proportional to em-
ployment sampling at each stage. The first stage of sample
selection was a probability-proportional-to-size sample of
establishments. Use of this technique means that the larger
an establishment's employment, the greater its chance of
selection. The second stage of sample selection, detailed
below, was a probability sample of occupations within a
sampled establishment.
Occupational selection and classification
Identification of the occupations for which wage data were
to be collected was a multistep process:
1. Probability-proportional-to-size selection of estab-
lishment jobs
2. Classification of jobs into occupations based on the
2000 Standard Occupational Classification (SOC)
system
3. Characterization of jobs as full-time or part-time,
union or nonunion, and time or incentive
4. Determination of the level of work of each job
For each occupation, wage data were collected for those
workers whose jobs could be characterized by the criteria
identified in the last three steps. In step one, the jobs to be
sampled were selected at each establishment by the BLS
field economist. A complete list of employees was used for
sampling, with each selected worker representing a job
within the establishment. The greater the number of people
working in a job in the establishment, the greater its chance
of selection.
The second step of the process entailed classifying the
selected jobs into occupations based on their duties. NCS
uses the 2000 Standard Occupational Classification (SOC)
system. A selected job may fall into any one of about 800
occupational classifications, from accountant to zoologist.
When workers could be classified in more than one occupa-
tion, they were classified in the occupation that required the
higher skill level. When there was no perceptible differ-
ence in skill level, the workers were classified in the occu-
pation that de§cribcd their primary activity.
.Each occupational classification is an element of a
broader classification known as a major group. Occupa-
tions can fall into any of 22 major groups. A complete list
of all individual occupations, classified by the major group
to which they belong, is available from BLS.
In step three, certain other job characteristics of the
chosen worker were identified. First, the worker was iden-
tified as holding either a full-time or part-time job, based
on the establishment's definition of those terms. Then, the
.worker was classified as having a time versus incentive job
and also identified as being in a union or a nonunion job.
Occupational leveling
In the last step before wage data were collected, the work
level of each selected job was determined using a "point
factor leveling" process. Point factor leveling matches
certain aspects of a job to specific levels of work with as-
signed point values. Points for each factor are then totaled
to determine the overall work level for the job.
The NCS program is in the process of converting from a
nine-factor to a four-factor occupational leveling system.
The conversion is being phased in via annual NCS sample
replenishment groups and will require several years for full
implementation. The four occupational leveling factors
are:
• Knowledge
• Job controls and complexity
• Contacts (nature and purpose)
• Physical environment
Each factor consists of several levels, and each level has
an associated description and assigned points. A knowl-
edge guide for 24 families of closely related occupations
contains short definitions of the point levels of knowledge
expected for the occupations and presents relevant exam=
ples. The other three factors use identical descriptions for
all occupational categories and contain a definition of each
point level within each factor.
The description within each factor best matching the job
is chosen. The point levels within each factor are designed
to describe the thresholds of distinct levels of work. When
a job does not meet the full description of a point level, the
next lowest point level is used. Points for the four factors
are totaled to determine the overall work level. NCS pub-
lishes data for up to IS work levels.
Most supervisory occupations are evaluated based on
their duties and responsibilities. A modified approach is
used for professional and administrative supervisors when
they direct professional work and are paid primarily to su-
pervise. - -Such supervisory occupations are leveled based
on the work level of the highest position reporting to them.
For a complete description of point factor leveling, refer
to the publication "National Compensation Survey: Guide
for Evaluating Your Firm's Jobs and Pay," available at the
BLS National Compensation Survey Internet site at
http://www.bls.gov/ncs/ocs/sp/ncbr0004.pdf.
Collection period
Survey data were collected over a 13-month period for the
86 largest areas in the NCS program. For 66 smaller areas,
data were collected over a 4-month period. For each estab-
lishment in the survey, the data reflect the establishment's
most recent information at the time of collection. The pay-
roll reference month shown in the tables reflects the aver-
age date of this information for all sample units.
Earnings
Earnings were defined as regular payments from the em-
ployer to the employee as compensation for straight-time
hourly work, or for any salaried work performed. The fol-
lowing components were included as part of earnings:
• Incentive pay, including commissions, production
bonuses, and piece rates
• Cost-of-living allowances
• Hazard pay
• Payments of income deferred due to participation
in a salary reduction plan
• Deadhead pay, defined as pay given to transporta-
tion workers returning in a vehicle without freight
or passengers
.The following forms of payments were not considered
part of straight-time earnings:
• Shift differentials, defined as extra payment for
working a schedule that varies from the norm, such
as night or weekend work
• Premium pay for overtime, holidays, and weekends
• Bonuses not directly tied to production (such as
Christmas and profit-sharing bonuses)
• Uniform and tool allowances
• Free or subsidized room and board
• Payments made by third parties (for example, tips)
• On-call pay
To calculate earnings for various periods (hourly,
weekly, and annual), data on work schedules also were
collected. For hourly workers, scheduled hours worked per
day and per week, exclusive of overtime, were recorded.
Annual-weeks worked were.-determined. Because salaried
workers who are exempt from overtime provisions often
work beyond the assigned work schedule, their typical
number of hours actually worked was collected.
Weighting and nonresponse
Sample weights were calculated for each establishment and
occupation in the survey. These weights reflected the rela-
tive size of the occupation within the establishment and of
the establishment within the sample universe. Weights
were used to aggregate data for the individual establish-
ments or occupations into the various data. series.
If data were not provided by a sample member during
the initial interview, the weights of responding sample
members in the same or similar "cells" were adjusted to
account for the missing data. This technique assumes that
the mean value of data for the nonrespondents equals the
mean value of data for the respondents at some detailed
"cell" level. Responding and nonresponding establish-
ments were classified into these cells according to industry
and employment size. Responding and nonresponding oc-
cupations within responding establishments were classified
into cells that were additionally defined by major occupa-
tion group.
If average hourly earnings data were not provided by a
sample member during the update interview, then missing
average hourly earnings were imputed by multiplying prior
average hourly earnings by the rate of change in the aver-
age hourly earnings of respondents. The regression model
that takes into account available establishment characteris-
tics is used to derive the rate of change in the average
hourly earnings.
Establishments that were determined to be out of busi-
ness or outside the scope of the survey had their weights
changed to zero.
Survey response
Establish-
ments
Total in sampling frame 64
Total in sample 17
Responding 15
Refused-or-unable to provide data 2
Out of business or not in survey scope 0
Estimation
The wage series in the tables are computed by combining
the wages for each sampled occupation. Before being
combined, individual wage rates are weighted by the num-
ber of workers; the sample weight, adjusted for nonre-
s otion'nsto scheduled establishments and other, factors; and the occupa-
hours of work.
The sample weight reflects the inverse of each unit's
probability of selection at each sample selection stage and
four weight adjustment factors. The first factor adjusts for
establishment nonresponse and the second factor adjusts
for occupational nonresponse. The third factor adjusts for
any special situations that may have occurred ,during data
collection. The fourth factor, post-stratification, also called
benchmarking, is introduced to adjust estimated employ-
ment totals to the current counts of employment by indus-
try. The latest available employment counts were used to
derive average hourly earnings in this publication.
Not all calculated series met the criteria for publication.
Before any series was published, it was reviewed to make
sure that the number of observations underlying it was suf-
ficient. This review prevented the publication of a series
that could have revealed information about a specific estab-
lishment.
Data reliability
The data in this summary are estimates from a scientifically
selected probability sample. There are two types of errors
possible in an estimate based on a sample survey, sampling
and nonsampling.
Sampling errors occur because observations come only
from a sample and not from an entire population. The
sample used for this survey is one of a number of possible
samples of the same size that could have been selected us-
ing the sample design. Estimates derived from the different
samples would differ from each other.
A measure of variation among these differing estimates
is called the standard error or sampling error. It indicates
the precision with which an estimate from a particular sam-
ple approximates the average result of all possible samples.
The relative standard error (RSE) is the standard error di-
vided by the estimate. RSE data are provided alongside the
earnings data in the summary tables.
The standard error can be used to calculate a "confi-
dence interval" around a sample estimate. As an example,
suppose a table shows that mean hourly earnings for all
workers were $17.75, with a relative standard error of 1.0
percent for this estimate. At the 90-,percent level, the con-
fidence.-interval for-this estimate _is-from .$17.46 to $18.04
($17775 minus and.plus $0.29, where $0.29 is the product
of 1.645 times 1.0 percent times $17.75). If all possible
samples were selected to estimate the population value, the
interval from each sample would include the true popula-
tion value approximately 90 percent of the time.
Nonsampling errors also affect survey results. They
can stem from many sources, such as inability to obtain
information for some establishments, difficulties with sur-
vey definitions, inability of the respondents to provide cor-
rect information, or mistakes in recording or coding the
data obtained. Although they were not specifically meas-
ured, the nonsampling errors were expected to be minimal
due to the extensive training of the field economists who
gathered the survey data, computer edits of the data, and
detailed data review.