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The U.S. Bureau of Labor Statistics (BLS) first introduced Modeled Wage Estimates (MWE) in the 2013 article, “Wage estimates by job characteristic: NCS and OES program data,” and the first set of estimates were produced in 2016.1 Since then, MWE data have been published annually and provide average hourly wage estimates for occupations by job characteristics and geographical locations. These estimates are produced by combining data from two BLS programs—the Occupational Employment and Wage Statistics (OEWS) and the National Compensation Survey (NCS).2
The occupational and geographic wage data from the OEWS are combined with the job characteristics: bargaining status (union and nonunion), work status (part-time and full-time), basis of pay (incentive-based and time-based), and work level wage data from the NCS.3 By drawing on the strengths of each of the surveys, the MWE provide more information on occupational wages in geographic areas by job characteristics than each survey can provide individually. This article introduces grouped level estimates by providing the methodology used. The full set of experimental grouped work-level estimates including the relative standard errors and a listing of grouped work levels for each occupation and associated break level are available for download. (See source data.)
The “Guide for Evaluating Your Firm's Jobs and Pay” provides an explanation of how the BLS determines work levels in the NCS.4 Work levels provide insight into differences in compensation due, in part, to four job factors—the knowledge necessary, job controls and complexity, nature and purpose of contacts, and the physical environment for or of the job. Each factor consists of several levels, with an associated description and assigned points. The total points from the four factors are used to determine the work level for occupations. With the exception of the knowledge factor, a common scale is used for all occupations.
Points for job controls and complexity range from 100 to 1,950 points.5 Work performed at 100 points includes jobs where employees do not deviate from established procedures or direction provided by the supervisor. Tasks are clearly identified and related with little to no choice necessary to perform them. Work consists of simple and repetitive tasks, and the work has minimal impact outside the immediate organizational unit. Work performed at 1,950 points includes jobs where employees work with only administrative and policy direction and must define objectives, plan work, and develop new methods that influence workplace activities.
Points for the nature and purpose of contacts range from 30 to 280 points.6 Work performed at 30 points includes jobs where employees’ contacts are primarily with coworkers inside the organization unit or visitors to the work area (such as the public), and straightforward information is exchanged. Work performed at 280 points includes jobs where employees’ contacts are somewhat unstructured and primarily with technical individuals (such as scientists and engineers) as well as influential individuals inside and outside of the employing organization (such as elected officials, managers, media representatives, judges, or attorneys), and the nature of the contacts includes defending, negotiating, or resolving long-range issues and problems.
Points for the physical environment range from 10 to 100 points.7 Work performed at 10 points includes nonstrenuous jobs with low risk. This includes jobs that are primarily sedentary where workers may also walk, stand, or carry light objects. Work performed at 100 points includes strenuous jobs with high risk. This includes jobs required to lift more than 50 pounds or that involve climbing or running. These jobs may also include extreme temperatures, have a likelihood of physical attack, or potential exposure to smoke or fire.
As previously mentioned, points for knowledge do not use a common scale as the other factors, but points are assigned based on job families. The explanation of job guide factors in the “Guide for Evaluating Your Firm’s Jobs and Pay” provides an overview of the job families and a summary of the occupations covered.8 The occupations within the same job family use a common point scale based on the knowledge and the skill necessary for the job. For example, the knowledge point scale for service jobs, which include cashiers, dishwashers, and concierges, begins at 50 points and corresponds to knowledge of simple, routine, or repetitive tasks, which typically includes following step-by-step instructions.9 Workers in this job family may also need the skill to operate simple equipment or equipment that requires little or no prior training or experience in food, health, or janitorial occupations. Service jobs have a maximum of 1,250 knowledge points. This includes knowledge of many concepts, principles, and practices in a field. Comprehensive, intensive, and practical knowledge of the job or skill to develop new methods, approaches, or procedures to tailor the goods produced or services provided are necessary. Some executive chefs may match these knowledge criteria for the maximum knowledge points.
Once points have been assigned for each job factor, they are summed. The work level is determined as shown in exhibit 1.10 Suppose a job in the janitors and cleaners’ occupation was assigned 100 points for job controls and complexity, 75 points for contacts, 40 points for physical environment, and 200 points for knowledge. The 415 points correspond to work level 2. The 2020 MWE publication provided estimates for janitors and cleaners at the national level, 48 states, the District of Columbia, as well as 474 metropolitan and nonmetropolitan areas.11 These estimates show that the wages for the janitors and cleaners occupation ranged from $10.26 in Monroe, Louisiana to $21.69 in the San Francisco-Oakland-Hayward, California metropolitan area.
|Work level||Minimum points||Maximum points|
|4,055||4,055 or more|
Source: U.S. Bureau of Labor Statistics, National Compensation Survey.
The MWE work levels provide information about compensation in the national economy by accounting for differences in the knowledge, job controls and complexity, contacts, and the physical environment of occupations. There are 347 estimates available for work level 1 janitors and cleaners, 527 for work level 2, 526 for work level 3, 379 for work level 4, and a single estimate for work level 5. As human resources professionals evaluate their firm’s pay, workers and employers engage in wage negotiations and workers assess differences in pay across the country. When that is done, it is necessary to compare average hourly wages by controlling for attributes that affect pay. Evaluating pay for janitors and cleaners can be reliably performed for work levels 2 and 3; the lack of data for other work levels and characteristics complicates the analysis. Over the years, the NCS program has looked for better ways to present leveling data to help users understand how job factors affect pay.
As wages tend to increase along with the progression in work level, stakeholders have expressed interest in understanding the differences in pay for entry, intermediate, and experienced work levels. In the labor market, wage progression resulting from more experience, credentials, or complexity of tasks differs by occupation. Using the individual work levels does not allow for comparison of entry level, intermediate level, and experienced level across occupations. But grouping the work levels and allowing them to vary by occupation allows for these broad comparisons. Even though it is possible for data to be available for 15 levels for a given occupation, it generally does not occur as illustrated by the knowledge point differences by occupational family. That is, work levels may be clustered; for example, leveling data for food preparation workers are concentrated within the 1–5 level range. For electro-mechanical technicians, an occupation that typically requires an associate degree or a postsecondary certificate, leveling data are available in the 4–9 range, and for chief executives the 11–15 range. Given the difference in work-level ranges, the NCS program evaluated grouping work levels to allow for additional evaluation of compensation differences.
The Jenks optimization method is an algorithm that identifies the optimal number of groups from a domain (in this case occupations).12 To do this, the sum of squared deviations from the average (mean) wages is calculated for grouped work levels based on the cluster that minimize the sum of within-group deviations. To simplify the evaluation of work-level clusters, two (to represent entry and experienced levels) and three groups (to represent entry, intermediate and experienced levels) were generated for each detailed occupation (six-digit 2010 Standard Occupational Classification code). In addition to the Jenks natural breaks, the NCS program evaluated the difference in log wages between groups and share of employment. These additional criteria identified occupations that should not be leveled, as meaningful distinctions between groups could not be determined. It also identified occupations that should be estimated using two or three work-level groups. Occupations like food preparation workers, waiters and waitresses, or nursing assistants could only be grouped into the entry and experienced levels, as additional meaningful wage differences were not found beyond these two groupings. For occupations such as loan officers, meaningful wage distinctions were found when using three groups. In 2019, work levels were available for loan officers from level 6 to level 12. As shown in table 1, the wages for levels 6–8 were very similar as were wages for levels 9 and 10. By grouping the work levels using the Jenks optimization method, users can understand the compensation progression of occupations. The associated relative standard errors provide an indication about the reliability of the estimates.13 Although comparing the individual work levels would provide more granular information, this is not always possible, especially in more detailed areas. The NCS sample is not sufficiently large to provide wage estimates for each work level. By grouping the work levels, more data are available to produce the estimates.
|Variable||Estimate (in dollars)||RSE|
NCS work levels
Note: RSE = relative standard error.
Source: U.S. Bureau of Labor Statistics, Modeled Wage Estimates.
Using these estimates, chart 1 demonstrates the wage variation by state for entry, intermediate, and experienced levels for accountants and auditors. In 2019, the average hourly wages for entry level accountants and auditors ranged from $21.14 in Indiana to $30.76 in North Carolina. For experienced accountants and auditors, average hourly wages ranged from $44.22 in Florida to $62.27 in New York.14
Although wages generally increase with work-level progression, there are instances when this does not occur. This is illustrated in North Carolina between entry and intermediate grouped work levels. Other job characteristics (e.g., work status, basis of pay, and bargaining status) may contribute more to the wage difference than the work levels. To produce uniform grouped work levels across geographic areas, the grouped work levels were determined at the national level. It is also possible that there are differences in job requirements, such as education, training, and experience requirements, within different geographic areas that may also contribute to the pay factors.15 Another way of evaluating the inversion between entry level and intermediate grouped levels is to use the standard error to assess the reliability of the estimates. The entry group level relative standard error (RSE) was 12.96, whereas the intermediate group level one was 5.91 percent. Though the RSE indicates almost twice as much variability in the entry group level as compared with the intermediate level, users can also construct confidence intervals to evaluate whether the estimates are reliable for their intended purpose.
A 90-percent level of confidence interval for each grouped work level published for North Carolina accountants and auditors is calculated as follows:
$30.76 x 0.1296 = 3.99
Lower bound estimate = $30.76 - (3.99 x 1.645) = $24.20
Upper bound estimate = $30.76 + (3.99 x 1.645) = $37.32
$29.79 x 0.0591 = 1.76
Lower bound estimate = $29.79 – (1.76 x 1.645) = $26.89
Upper bound estimate = $29.79 + (1.76 x 1.645) = $32.67
Even though the differences between the estimates are not statistically significant, users may evaluate these estimates and their corresponding confidence intervals to engage in salary negotiations and align compensation packages based on geographic area.16
Accountants and auditors as well as loan officers are part of the business and financial occupational group. The entry level for these occupations includes work levels 1 to 7, the intermediate level consists of levels 8 and 9, and experienced includes levels 10 to 15. Entry-level wages for accountants and auditors were $25.21, and wages for loan officers were $25.01. Intermediate-level wages for accountants and auditors were $34.98 and wages for loan offices were $36.82, and at the experienced level, wages were $52.83 and $52.72, respectively. (See chart 2.)
Additional occupations within the business and financial occupational group with the same work-level groupings as accountants and auditors include appraisers and assessors of real estate, credit analysts, personal financial advisors, insurance underwriters, financial examiners, loan officers, and all other financial specialists. The grouped levels provide an easier approach for comparing wages across these related occupations and also facilitate comparisons with occupations in other occupational groups. Civil engineers are part of the architecture and engineering occupational group; child, family and school social workers are part of the community and social service group; public relation specialists are part of the arts, design, entertainment, sport, and media occupational groups. All have the same grouping of work levels for entry, intermediate, and experienced levels. (See table 2.)
|Occupational code||Occupation||Entry level average hourly wage||Entry level RSE||Intermediate average hourly wage||Intermediate RSE||Experienced average hourly wage||Experienced RSE|
|Claims adjusters, examiners, and investigators||23.36||0.92||34.86||0.79||50.49||0.95|
|Human resources specialists||21.09||3.56||32.16||2.65||51.25||3.91|
|Child, family, and school social workers||18.22||2.37||28.3||2.35||32.44||5.53|
|Public relations specialists||20.33||3.11||33.06||3.44||45.68||4.94|
Note: RSE = relative standard error.
Source: U.S. Bureau of Labor Statistics, Modeled Wage Estimates.
For production occupations, the grouped work levels may be considered analogous to the apprentice (entry), journey (intermediate), and master (experienced) levels. In conjunction with the four factors used to determine the work levels, production occupations may include on-the-job training, which further contributes to the knowledge and skills of workers. As indicated in the Occupational Outlook Handbook, moderate-term on-the-job-training is needed for assemblers17 and long-term on-the-job training is needed for power plant operators.18
Chart 3 shows the average hourly wages for production occupations, where the average hourly wages for machinists were $18.90 and for aircraft structure, surfaces, rigging, and systems assemblers, wages were $25.48 at the apprentice (entry) grouped levels. 19 These two occupations have the same grouped work levels for apprentice (entry: levels 1 to 4), journey level (intermediate: levels 5 to 6), and master (experienced: levels 7 to 15).
The grouped work levels for machinists, tool die makers, and power plant operators are slightly different, since apprentice includes levels 1 to 5, journeyman is level 6, and master includes levels 7 to 15.
BLS provides a variety of wage data through programs such as the OEWS, Current Population Survey (CPS), the Current Employment Statistics survey (CES), and the NCS.20 The average hourly wages by work levels provided by the MWE further allows users to examine the compensation factors of workers in the U.S. economy. The addition of grouped work levels helps compare average hourly wages by facilitating the identification of occupations with similar factors. The NCS program continues to evaluate the usefulness and availability of the MWE. These grouped work levels represent an initial attempt to provide grouped work levels based on the Jenks optimization method.
Looking ahead, the NCS program will reevaluate the grouped work levels for each occupation, in particular because of the Modeled-Based Estimation Methodology (referred to as MB3) and 2018 SOC implementation by the OEWS and MWE.21 In addition, another set of experimental estimates will be published through a factsheet on the MWE website before adding them into the annual production process. This will allow users to provide feedback on the grouped work levels and allow the NCS to consider approaches to publish more data.
ACKNOWLEDGMENT: We are grateful to Nathan F. Modica, David H. Oh, and Jesus Ranon for their contributions to this project. We also thank Laura Train for her helpful comments.
Joana Allamani, Michael Hudak, and Adam Issan, "Introducing Modeled Wage Estimates by grouped work levels," Monthly Labor Review, U.S. Bureau of Labor Statistics, September 2022, https://doi.org/10.21916/mlr.2022.23
1 For more information about the MWE program, see www.bls.gov/mwe; the published estimates were for the 2014 and 2015 reference years, see www.bls.gov/mwe/#tables; see Michael K. Lettau and Dee A. Zamora, “Wage estimates by job characteristics: NCS and OES program data,” Monthly Labor Review, August 2013, www.bls.gov/opub/mlr/2013/article/lettau-zamora.htm.
2 For more information on the OEWS and NCS programs, see www.bls.gov/oes and www.bls.gov/ncs.
3 Work levels are determined by assigning points to four job factors. The leveling guide provides information on the basis for assigning points to the knowledge, job controls and complexity, contacts, as well as the physical environment of selected occupations, see the “National Compensation Survey: Guide for Evaluating Your Firm's Jobs and Pay,” May 2013, www.bls.gov/ncs/ocs/sp/ncbr0004.pdf.
5 Ibid., p. 63.
6 Ibid., p. 65.
7 Ibid., p. 67.
8 Ibid., p. 9.
9 Ibid., p. 49.
10 Ibid., p. 67.
11 The 2020 MWE complete dataset can be downloaded by visiting, www.bls.gov/mwe/mwe-2020complete.xlsx and is found within the MWE Tables page, www.bls.gov/mwe/tables.htm.
12 See George Jenks, “The Data Model Concept in Statistical Mapping,” 1967, www.semanticscholar.org/paper/The-Data-Model-Concept-in-Statistical-Mapping-Jenks/9551c4531a87b4ab01931bf5b68dac945ef3f9ab; this work discussed in further detail in this article, support.esri.com/en/technical-article/000006743.
13 See “Relative standard errors for Modeled Wage Estimates” for an explanation of how to use them to assess estimate reliability, www.bls.gov/mwe/mwe-rse.htm.
14 The industry composition for occupations may inform differences in average hourly wages. The OEWS provides research estimates by state and industry which may assist with this analysis at the state level. See www.bls.gov/oes/2020/may/oes_research_estimates.htm.
15 Future research is necessary to evaluate state-wide or more detailed area variation in grouped work levels. The outcome of this research may be used to inform enhancements to the grouped work-level approach.
16 See “Relative standard errors for Modeled Wage Estimates” for more information on how to interpret, build, and compare confidence intervals, www.bls.gov/mwe/mwe-rse.htm.
17 See the Occupational Outlook Handbook for information on assemblers and fabricators, www.bls.gov/ooh/production/assemblers-and-fabricators.htm#tab-1.
18 See the Occupational Outlook Handbook for information on power plant operators, distributors, and dispatchers, www.bls.gov/ooh/production/power-plant-operators-distributors-and-dispatchers.htm.
19 The grouped level estimates for apprentice tool and die makers and power plant operators did not pass publication criteria.
20 For information on the various BLS compensation measures see the Compensation Matrix tool, beta.bls.gov/comparison-matrix/.
21 With the May 2021 estimates, the OEWS program now uses a new estimation methodology as described in the following MLR article. See Matthew Dey, Stephen M. Miller, and David S. Piccone Jr, “Model-Based Estimates for the Occupational Employment Statistics program,” Monthly Labor Review, August 2019, www.bls.gov/opub/mlr/2019/article/model-based-estimates-for-the-occupational-employment-statistics-program.htm.