Methodologies for Estimating Mean Wages for Occupational 

Employment Statistics (OES) Data 

Mallika Kasturirangan a, Shail Butani b, and Tamara Sue Zimmerman c

a One GEICO Plaza, Washington, DC 20076, Email: Mkasturirangan@GEICO.com

b,cBureau of Labor Statistics, Room 4985, 2 Massachusetts, N.E., Washington, DC 20212, 

Email: Butani.Shail@bls.gov and Zimmerman.Tamara@bls.gov

ABSTRACT 

The Occupational Employment Statistics (OES) is a joint Federal/State partnership program with a sample size of 1.2 million 

establishments over a 3-year period (six semi-annual panels each consisting of 200,000 establishments). The OES collects 

occupational employment and wage data for approximately 800 occupations at the MSA by 4-5 digit industrial (NAICS) 

level. Because of the burden on respondents, this survey is designed to collect wage data in intervals rather than exact wages 

for individual employees. In this paper, we will present the previous research work on the construction of lower and upper 

bounds of the intervals; alternative methods for estimating mean wages—arithmetic, geometric, and NCS mean wages; 

updating of wages from prior panels; and calculation of mean wages for the upper open-ended Interval L (i.e., employees 

making $70 or more per hour in the years 2003-2005). This study further examines several methods for approximating mean 

wages for Interval L for occupations that have significant employment (>5%) in Interval L and validates the OES 

methodology on independent data sets from the Current Population Survey for years 2003, 2004, and 2005. 

Key Words. Open-ended interval wage estimation, geometric mean, kernel density 

I. The Occupational Employment Statistics Survey

The Occupational Employment Statistics (OES) program is a Federal/State partnership program between the Bureau of Labor 

Statistics (BLS) and State Workforce Agencies (SWAs). OES collects data from approximately 1.2 million establishments 

over a three-year period. The data is collected in six semi-annual panels, with about 200,000 establishments surveyed per 

panel. Every effort is made to survey an establishment only once in each three-year period. 

The OES survey is designed to cover all full- and part-time salary workers in non-farm industries; it does not cover the selfemployed, owners and partners in unincorporated firms, or household workers. OES is designed to produce over 800 

occupational employment and wage estimates. Occupations are classified using the Office of Management and Budget 

(OMB) Standard Occupational Classification (SOC) system. OES is designed to produce these estimates by geographic 

area—National, State, and Metropolitan Area levels—and for over 450 industry classifications corresponding to the 3-, 4-

and 5-digit North American Classification System (NAICS). 

OES data are available for a wide variety of uses. One of the OES’s biggest clients is the Foreign Labor Certification 

program of the Employment Training Administration (ETA). OES data are also used in analysis of occupational employment 

and wages, development of occupational projections, vocational counseling and planning, industry skills and technology 

studies, and market analysis. 

II. OES Wage Intervals 

OES requests a large amount of data from respondents. In order to ease the burden on responding establishments, OES does 

not collect data on exact wages. Instead, establishments report the number of workers in a certain occupation earning within 

each of twelve wage intervals, denoted “A” through “L”. Figure 1 (all figures are at the end of this document) shows an 

example of the form given to respondents of the OES Survey. Each row represents a certain occupation: chief executives, 

general and operations managers, etc. Each column represents a wage interval. Interval A represents those earning less than 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

$6.75 an hour, and so on. All a respondent has to do is report the number of chief executives earning wages within Interval K 

($55.50-$69.99), for example. 

Extensive research was conducted as to how the upper and lower bounds of these wage intervals should be constructed. 

Several factors were considered prior to interval construction. Research was done by Dr. Sandra West on reported weekly 

wages from the Current Population Survey.1 Figure 2 shows some results of her research. Reported weekly earnings spiked 

at “clean” values like $200 ($5.00 per hour), $300, $400, etc. West concluded that this data does partially represent the true 

distribution of wages, but it also represents reporting error. Interval methodology could eliminate some of this error. 

Earlier simulations showed that mean squared errors were less when the lower bound of an interval was a factor of $0.25, 

rather than $0.25 plus a penny. The general method for determining the bounds of the intervals was to attempt to equalize the 

percent relative errors and coefficients of variation within each interval. This method is applied to Intervals B-K. 

Construction of Interval A is a function of the federal minimum wage, and Interval L is a function of inflation.2 Figure 3 

shows the OES interval bounds for 2003-2005, along with the percent relative errors and coefficients of variation. Notice the 

percent relative errors are similar for Intervals B-K (11.5-11.8%) as are the coefficients of variation (6.5-6.8%). Even Interval 

A is fairly close to these numbers. Interval L cannot be compared because it is an open-ended interval. 

There have been several proposed methods for estimating mean wages within each of these intervals, including the arithmetic 

mean (midpoint), geometric mean, and National Compensation Survey (NCS) mean. 

Arithmetic: (Lower Bound + Upper Bound) / 2 

Geometric: (Lower Bound x Upper Bound) 1/2 

The NCS mean is calculated using point data from the National Compensation Survey, weighted by number of workers 

earning that wage. The arithmetic mean was the method used previously. The geometric mean was never used, but suggested 

by a participating state office. The NCS mean is the method currently used to estimate mean wages within intervals. Research 

showed that the arithmetic mean worked well, the geometric was better, and the NCS mean performed best of the three.3 

Figure 4 shows a comparison of these three methods as well as the weighted mean using Current Population Survey (CPS) 

point data for 2004. For Intervals B-K, the interval means are very similar across all methods, which is why all three methods 

performed well in testing. The NCS Mean is generally lower than the arithmetic mean (the midpoint) suggesting that the data 

are not uniformly distributed within each interval, but tend to be slightly more concentrated in the lower half of the interval. 

It is also important to examine the data across years. Figure 5 shows interval means using NCS and CPS data across the years 

2003-2005. The interval means do not seem to change across years, yet the overall means do increase about 2-3% each year. 

Figure 6 gives us the reason for that 2-3% increase in overall mean wages. In all three surveys, NCS, CPS, and OES, we see a 

shift in percent of employment from the lower Intervals A-D to the upper Intervals E-L. It is also important to notice in 

Figure 5, there is a $60 difference between the mean wages for Interval L in CPS and NCS, with CPS being higher. If we 

consider that Interval L makes up a little over 1% of employment in CPS (Figure 6), this would create about a $0.60 

difference in the overall means between NCS and CPS, which we can also see in Figure 5. 

III. OES Mean Wage Estimation 

OES does not publish estimates for interval means. These are simply used in calculations of overall mean wages for 

occupations. Currently, to determine occupational mean wages, exact data from NCS are used to determine a wage for each 

interval. This interval mean is then applied to the OES sample. For Intervals A and B, if the State-specific minimum wage is 

higher than the calculated NCS mean for that interval, then the State minimum wage is applied. Otherwise, the NCS mean 

will be applied as with the other intervals. Interval L, the open-ended interval ($70 per hour or more), has a special procedure. 

Because this interval makes up only about 1% of the population, data in Interval L has little or no impact on mean wages for 

most occupations. The interval means are then used to compute an overall mean wage for each occupation. To take into 

account the 3-year period over which data are collected, previous panels’ data are updated using the employment cost index 

1 West, Sandra A. “Standard Measures of Central Tendency for Censored Earnings Data from the Current Population Survey” 

2

 Tou, Albert, Christina Chiu, and Kenneth Robertson. “An Evaluation of the Occupational Staffing Pattern and Mean Wage 

Rates of State Government Workers” 

3 “Occupational Employment Statistics Survey: Analysis of Alternative Procedures for Interval Mean Wage Rates, 

Supplement II”. December 2000 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

(ECI) by nine major occupational groups. The results of a study conducted by Kirk Wolter and Rashna Ghadialy of National 

Opinion Research Corporation (NORC) found this procedure performed the best of all the alternative methods used for 

updating prior year wage data.4 

Recently, a Wage Comparison Study was done using 2003 data.5 When comparing occupational wages between the two 

surveys it was found that about 70% of the detailed occupations did not have statistically significant differences at the 10% 

significance level. About one-third of the other 30% of occupations did not have economically meaningful differences 

between mean wages in each survey. This left about 20% of occupations that had both statistically significant differences and 

economically meaningful differences. These differences could arise from a number of factors including: small sample size in 

either survey; conceptual differences regarding definitions of occupations; occupational coding differences; and differences 

in methods of measurement of mean wages in open-ended Interval L for high paying occupations (the focus of this research), 

etc. When OES interval methodologies were applied to the NCS data, the above results did not change, suggesting it is 

appropriate to use NCS point data to estimate mean wages for OES. 

IV. Purpose of Research

It is important to note that while OES uses interval mean methodology, the program is not designed to make occupational 

estimates for any specific interval. This study is not exploring differences in wage rates by area occupation. We assume a 

priori that wages do, in fact, differ by area and occupation. The assumption that occupational mean wage rates vary by these 

factors does not imply, however, that wage rates vary within a wage interval. Virtually all occupations are reported across a 

subset of the complete set of wage intervals, low paying occupations concentrated in the lower intervals, and high paying 

occupations in the higher intervals. Because of this fact, this study will concentrate only on mean wages for occupations 

overall. The following research has two goals: 1) Evaluate the effectiveness of the OES estimation procedures used in 

occupational mean wage rates, across all intervals, on an independent data set. For this study we used data from the Current 

Population Survey (CPS) for 2003-2005 as our independent sample. 2) Develop alternative procedures for estimating mean 

wages for Interval L, specifically for those occupations having significant employment in this open-ended wage interval. 

V. Validation of OES Methodology

To check the accuracy and effectiveness of the OES methods, data from CPS was tabulated and used to compute mean wages 

using the OES methodology as described previously. CPS and OES use the same occupational coding system, which allows 

for some comparison. However, the CPS only offers data at the major occupational group level. In each year, about one-third 

of the 22 major occupational groups had statistically significant differences between the actual mean computed using CPS 

reported data, and the mean computed using OES methodology at the 10% significance level. Also consistently from 2003 to 

2005 only one major occupational group or 5% of the groups had an economically meaningful difference of more than 10%. 

Figure 7 displays the results of this validation procedure of OES methodology on CPS data for 2005. The table shows first 

the mean wages computed using CPS data weighted by employment, followed by the unweighted sample size for a point of 

reference as to relative sample size of each occupational group. For each occupational group, a 90% confidence interval was 

computed using standard errors produced from CPS replicate weights. Notice that the confidence intervals around the CPS 

computed mean are very tight. This suggests that there is very small sampling error in CPS. Next on this table is the mean 

wage using OES methodology. That is, CPS data were dropped into the OES wage intervals. The wage values were then 

replaced with mean wages for each interval computed from NCS data. State-specific minimum wages were applied when 

applicable for Intervals A and B. The overall mean wage for each occupation group was then calculated from the CPS 

sample. Means using OES methodology tended to be lower than those using CPS reported data. Some of this difference is 

attributable to the difference in mean wages between NCS and CPS within Interval L. As mentioned before, CPS wages in 

Interval L were about $60 higher than those in NCS for 2003-2005. However, only one group, as mentioned before, had an 

economically meaningful difference in this study. For 2005, as shown in Figure 7, this group is arts, design, entertainment, 

sports and media occupations. Results for the years 2003 and 2004 were generally similar, leading to the conclusion that the 

OES methodology is fairly accurate, with a portion of the bias being attributable to Interval L. 

4

“Occupational Employment Statistics Survey: Analysis of Alternative Procedures for Interval Mean Wage Rates, 

Supplement II”. December 2000 

5 Barkume, Tony. Matt Dey, Larry Ernst, Maury Gittleman, Anne Polivka. “Comparing OES and NCS Wage Estimates. 

Phase I: Comparison of National Estimates.” May 2006. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

VI. Wage Interval L

OES Interval L accounts for those earning at least $70 per hour. A relatively small portion of the OES sample falls within this 

interval. For the years 2003-2005 less than 1.5% of the OES sample was in Interval L. What complicates OES mean wage

estimation the most is the open-ended nature of this interval. An observation in Interval L could make $72 per hour or $5000 

per hour, but this cannot be discerned from the collected data. This leads to hard-to-answer questions. Is it possible that OES 

is currently underestimating or overestimating the mean wage within Interval L? About 40 occupations have significant 

employment (over 5%) in the Interval L range. This is just a handful of the 800 detailed occupations dealt with in OES, but it 

is for these occupations that Interval L estimation has a meaningful effect. It is therefore necessary, especially for these 

specific occupations, to create a special methodology for accurately estimating mean wages in Interval L. 

Figures 8, 9, and 10 show occupations that have employment of 5% or more in Interval L for 2003-2005. Notice that most of 

these occupations consist of physicians, managers, sales occupations, and postsecondary teachers. These are the groups of 

high-paying occupations that are most effected by Interval L. Also of note here is the difference between percent employment 

in Interval L and employment level in Interval L. It is important to be aware of both numbers as each has its own merit. For 

example, in Figure 9, podiatrists have 27% of their employment in Interval L, compared to 25% for lawyers. However, actual 

employment in L is only 2,200 for podiatrists, compared to 134,000 for lawyers. Which of the two measures is more 

important depends on the question we are attempting to answer. 

Computing Mean Wages for Interval L for Detailed Occupations

For this study it was necessary to examine several different data sources and assess the appropriateness of each to this topic. 

Mean and median wages from the NCS were examined for OES occupations with significant employment in Interval L. It 

was found that NCS data tended to be quite variable, and that the percent employment within Interval L by occupation was 

often quite different between the NCS and OES surveys. For example, in OES about 45% of pilots earn wages in Interval L, 

while in NCS about 70% of pilots fall in Interval L. Also overall pilots comprise about 2% of the total employment in 

Interval L for OES, compared to about 10% in NCS. 

CPS data were also examined, but the lack of detailed occupational coding and large difference in mean wages for Interval L 

between CPS and NCS were flagged as possible issues. Data from the American Community Survey were also considered, 

but issues with quality of data and mean wages similar to CPS eliminated this option. 

There is a methodology already in place for computing mean wages in Interval L. Currently, NCS data are used to compute a 

mean wage across all occupations excluding pilots for each of the years or panels in the sample. This mean wage across 

occupations excludes pilots because they have very high hourly wages (NCS data shows $145 per hour) and work a relatively 

low number of hours per year (1100 per year compared to the average 2080). Then the simple average of the yearly or panels 

estimates is computed. The mean wage is not updated using ECI because it is difficult to justify updating wages in this group 

when the Interval L mean wages for both all occupations and that excluding pilots are trending downwards or possibly 

fluctuating around a true mean. 

Pilots 

Figure 11 shows the Interval L mean wages for 1999-2002. For each of the four years, the mean wage excluding pilots is 

lower than the mean for all occupations. Taking a simple average of the four years’ data shows still a $10 difference between 

the two means; pilots’ data tend to bias the Interval L data upwards. 

Figure 12 examines pilots mean wages more closely. NCS publishes a mean hourly wage for pilots as shown in this table, 

close to $100 for each year (notice the variability across years). OES used a fairly conservative hourly estimate of about $95 

per hour according to the above methodology for the 2003-2005 years, yet the OES published annual wage for pilots is still 

higher than that calculated using NCS wages and mean annual hours for each year. Some of this difference could be 

explained by the fact that, in OES about 45% of pilots earn wages in Interval L, while in NCS about 70% of pilots fall in 

Interval L. However, most of this difference is arising from the number of hours worked by pilots. In NCS, the number of 

hours worked in a year by pilots is approximately 1100, whereas, in OES the assumption is 2080 hours. 

Options for Estimating Mean Wages in Interval L 

Along with the current methodology, four other options have been proposed for computing mean wages for Interval L. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1. Compute mean wages across all occupations 

2. Compute mean wages for NCS major occupational groups (see Figure 13) 

3. Compute mean wages for two major groupings: sales and non-sales occupations 

4. Compute mean wages for a combination of specific occupations and major occupational groups 

Options 1 and 2 are fairly straightforward. When looking at results for Option 2 in Figure 14, it is apparent that, within 

Interval L, Occupational Groups D-K are negligible. These are groups that do not tend to have high employment in Interval 

L. It is also apparent that Occupational Groups A and B are very similar in both size and mean wages in Interval L. The most 

noticeable of these occupational groups is Group C, sales occupations. It is then reasonable to collapse Groups A, B, and D-K 

into a major grouping of non-sales and compare to the sales occupations, resulting in Option 3. 

Option 4 can also be considered in this light. The occupational groups with the most employment in Interval L are Groups A, 

B, and C. These are professional and technical occupations, executive, administrative, and managerial occupations, and sales 

occupations. In other words, these are comparable to the handful of detailed occupations with significant employment in 

Interval L shown in Figures 8, 9, and 10. Ideally, these detailed occupations could be handled individually, to compute the 

most accurate overall mean wage for each occupation. Option 4, consequently, would compute a mean wage in Interval L for 

specific occupations—physicians, post-secondary teachers, lawyers & judges, and pilots; and major groups—managers, sales 

occupations, and all others. The specific occupations chosen are all in Occupational Group A, while managers is Group B, 

sales Group C, and the rest of Group A and D-K are grouped in “all others.” 

The current options, as well as the three new options, were tested. (Note: option 2 is equivalent to option 3) Figure 15 details 

those occupations that failed tests for each of the options. For an occupation to fail when tested with each option, it had to 

have at least 1000 employed (weighted) in Interval L and the given option had to produce a relative error on mean wages per 

hour of 10% or more for at least 2 of the 3 years of 2003-2005. All options worked fairly well. In total, 25 occupations had at 

least 1000 employed in Interval L. Out of this only three occupations (or about 12%) failed for the current option and Options 

3 and 4, while in Option 1 five occupations (or about 20%) failed. 

Any option chosen would still need to be tested on OES data. For example, let us choose Option 4. In testing on NCS data, 

Option 4 forces pilots to pass because a separate mean wage for Interval L is computed for pilots using NCS data. If the 

interval hourly mean wage for pilots from NCS ($145 per hour) is applied to the OES sample, it would further increase the 

OES published as $95 per hour for Interval L and 2080 hours are used for annual wages. However, when we adjust NCS 

mean wages for Interval L to take into account the NCS annual hours worked and OES annual hours worked assumption (i.e. 

Interval L mean wages in OES context are equal to about $77 or $145×1100 ÷2080), then this brings the OES annual wages 

close to the NCS calculated annual wages, as shown in Figure 16. This suggests that even for specific occupations, special 

methods may need to be applied. 

VII. Future Research 

More research on this topic is definitely required. As mentioned before, each proposed option for estimating mean wages in 

Interval L should be tested further. This should include testing the options on NCS data after it has changed to using the 

Standard Occupational Coding system currently used by OES. This should also include testing the options on OES data with 

the new Interval L lower bound of $80 per hour. It would also be beneficial to test the use of special procedures for certain 

occupations, as in the case of pilots as well as post-secondary teachers, who often earn wages on an annual basis rather than 

hourly (as a result of unusual annual hours). In question is whether this procedure should utilize one year’s data in NCS or 

the average of three years. 

To even further examine the distribution of wages within intervals, it may be useful to explore a kernel density model.6 A 

non-parametric kernel density function could be used to estimate mean wages for wage intervals by occupation. This 

approach is particularly suitable for wage data collected from the NCS because the point data are available. It can also be 

useful in estimating percentiles from OES data. 

6

 Lehman. Elements of Large Sample Theory, Springer 1999, pp. 406-417 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

References 

1. Butani, Shail. “Mean OES Wages--$60.00”. October 17, 1990. Electronic message with attachment 

2. Butani, Shail J., and Michael McElroy. “Managing Various Customer Needs for Occupational Employment Statistics

Survey” 

3. Butani, Shail, Kenneth Robertson, and George Werking. “Alternative Methods for Updating Wage Data from the 

Occupational Employment Statistics Survey” 

4. Echols, Carrae, Albert Tou, and Kenneth W. Robertson. “Comparing Alternative Median Wage Rate Estimates for the 

Occupational Employment Statistics Survey” 

5. Robertson, Kenneth W., Albert Tou, and Larry Huff. “A Study of Donor Pools and Imputation Methods for Missing 

Employment Data” 

6. Robertson, Kenneth W., and Pamela L. Frugoli. “Statistical Issues for the Redesigned Occupational Employment Statistics 

Survey” 

7. Tou, Albert, Christina Chiu, and Kenneth Robertson. “An Evaluation of the Occupational Staffing Pattern and Mean Wage 

Rates of State Government Workers”. 

8. West, Sandra A. “Estimation of the Mean from Censored Income Data”. 

9. West, Sandra A. “Standard Measures of Central Tendency for Censored Earnings Data from the Current Population 

Survey”. 

10. West, Sandra A., Shail Butani, and Michael Witt. “Alternative Imputation Methods for Wage Data” 

11. West, Sandra, Diem-Tran Kratzke, and Shail Butani. “Measures of Central Tendency for Censored Wage Data” 

12. West, Sandra, Diem-Tran Kratzke, and Kenneth Robertson. “Alternative Procedures for Item Non-response from New 

Establishments in the Universe” 

13. Wolter, Kirk, and Rashna Ghadialy. “Preliminary Report on Evaluation of the Occupational Employment Statistics 

Estimation and Alternative Methods of Updating Wage Estimates” 

14. “Occupational Employment Statistics Survey: Analysis of Alternative Procedures for Interval Mean Wage Rates”. 

October 2000 

15. “Occupational Employment Statistics Survey: Analysis of Alternative Procedures for Interval Mean Wage Rates, 

Supplement II”. December 2000 

16. Lehman. Elements of Large Sample Theory, Springer 1999, pp. 406-417 
Figure 1: Example of OES Survey Form 
Figure 2: Reported Weekly Earnings from CPS Measures of Central Tendency-Dr. Sandra West. 
 

 

Figure 3: OES Wage Interval Boundaries 2003-2005 

OES Wage Interval Boundaries

Interval

Lower

Bound

Upper

Bound

Interval

Width

% 

Relative % CV

A $5.15 $6.74 $1.60 13.4 7.8 

B $6.75 $8.49 $1.75 11.5 6.6 

C $8.50 $10.74 $2.25 11.7 6.7 

D $10.75 $13.49 $2.75 11.3 6.5 

E $13.50 $16.99 $3.50 11.5 6.6 

F $17.00 $21.49 $4.50 11.7 6.7 

G $21.50 $27.24 $5.75 11.8 6.8 

H $27.25 $34.49 $7.25 11.7 6.8 

I $34.50 $43.74 $9.25 11.8 6.8 

J $43.75 $55.49 $11.75 11.8 6.8 

K $55.50 $69.99 $14.50 11.6 6.7 

L $70.00 ∞ 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 4: Interval mean Wages using Proposed Methods 

Mean Wages within OES wage intervals A through L 

CPS, NCS, and OES data 

Year OES Wage Interval Lower Bound

Upper

Bound Arithmetic Mean Geometric Mean NCS Mean CPS Mean 

2004 A 5.15 6.74 5.95 5.89 5.79 5.37 

B 6.75 8.49 7.62 7.57 7.52 7.54 

C 8.50 10.74 9.62 9.55 9.55 9.56 

D 10.75 13.49 12.12 12.04 12.03 12.06 

E 13.50 16.99 15.25 15.14 15.11 15.10 

F 17.00 21.49 19.25 19.11 19.06 19.01 

G 21.50 27.24 24.37 24.20 24.27 24.05 

H 27.25 34.49 30.87 30.66 30.42 30.39 

I 34.50 43.74 39.12 38.85 38.60 38.30 

J 43.75 55.49 49.62 49.27 48.54 48.46 

K 55.50 69.99 62.75 62.33 61.39 61.29 

L 70.00 103.91 161.43 

Total 17.59 18.32 
 

 

 

 

Figure 5: Interval Means 2003-2005 

NCS and CPS Interval Means Across Years

Intervals NCS Interval Means $ CPS Interval Means $

2003 2004 2005 2003 2004 2005

A 5.78 5.79 5.82 5.37 5.37 5.41 

B 7.51 7.52 7.54 7.54 7.54 7.55 

C 9.57 9.55 9.55 9.57 9.56 9.56 

D 12.03 12.03 12.03 12.05 12.06 12.05 

E 15.11 15.11 15.10 15.10 15.10 15.12 

F 19.04 19.06 19.06 19.01 19.01 18.99 

G 24.23 24.27 24.27 24.06 24.05 24.10 

H 30.40 30.42 30.43 30.35 30.39 30.38 

I 38.49 38.60 38.57 38.32 38.30 38.41 

J 48.75 48.54 48.68 48.54 48.46 48.63 

K 61.20 61.39 61.36 61.20 61.29 61.16 

L 107.43 103.91 103.09 163.82 161.43 163.95 

Overall 17.22 17.59 18.07 17.78 18.32 18.82 

• Means Wages in each interval for the three years are about the same.

Yearly Percentage Change

NCS% CPS%

2004 2.15 3.04

2005 2.73 2.73
 

Figure 6: Distribution of Employment Across Years 

NCS, CPS, and OES Employment Distribution 

2003 - 2005

Intervals NCS % CPS % OES %

2003 2004 2005 2003 2004 2005 2003 2004 2005

A 8.6 8.1 7.5 8.0 7.2 6.7 7.7 7.3 6.8 

B 12.4 11.7 11.3 12.1 12.0 11.1 13.0 12.3 12.2 

C 15.1 14.7 14.4 15.1 14.7 14.6 14.6 14.3 14.3 

D 14.0 14.2 13.8 14.4 13.9 14.0 14.2 14.0 14.0 

E 13.2 13.4 13.7 13.8 14.0 14.0 13.5 13.6 13.7 

F 11.7 12.0 12.2 12.7 13.0 13.0 12.4 12.4 12.5 

G 10.1 10.2 10.2 10.1 10.4 10.6 9.8 10.3 10.4 

H 6.9 7.4 7.7 6.4 6.5 7.0 6.4 6.7 7.0 

I 4.1 4.4 4.7 4.0 4.4 4.5 3.9 4.2 4.4 

J 2.2 2.3 2.7 1.9 2.1 2.4 2.1 2.3 2.4 

K 1.0 1.0 1.1 0.8 0.9 1.1 1.0 1.1 1.2 

L 0.6 0.7 0.7 0.9 1.0 1.1 1.3 1.4 1.4 

Totals 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 7: Validation of OES Methodologies for 2005 

Comparison of CPS mean wages to means calculated using NCS Interval means, state minimum wages and a proposed option

Interval L methodology *

Year Occupational Group

CPS

Mean

Wage

Unweighted

Sample Size

90%Confidence 

Intervals About the

CPS Mean Wage

Mean Wage using 

OES Interval

Methodology Error

%

Relative

Error

2005 Management Occupations $29.96 15,758 (29.51,30.42) $28.77 -1.20 (4.00%) 

Business and financial operations occupations $25.15 7,131 (24.53,25.77) $24.76 -0.39 (1.56%)

Computer and mathematical science occupations $30.64 4,166 (29.67,31.60) $29.16 -1.47 (4.81%)

Architecture and engineering occupations $28.90 3,656 (27.95,29.87) $28.19 -0.72 (2.50%)

Life, physical, and social science occupations $26.74 1,959 (25.92,27.55) $26.16 -0.58 (2.18%)

Community and social service occupations $19.96 3,096 (19.03,20.90) $19.35 -0.62 (3.09%)

Legal occupations $32.71 1,872 (31.51,33.92) $30.05 -2.67 (8.15%)

Education, training, and library occupations $22.40 11,546 (21.83,22.98) $21.14 -1.27 (5.65%)

Arts, design, entertainment, sports, andmedia occupations $25.52 2,711 (24.80,26.24) $22.10 -3.42 (13.4%)

Healthcare practitioner and technical occupations $25.77 8,999 (25.39,26.16) $25.30 -0.47 (1.84%)

Healthcare support occupations $11.44 4,234 (11.17,11.71) $11.41 -0.03 (0.24%)

Protective service occupations $17.80 3,891 (17.43,18.16) $17.71 -0.08 (0.46%)

Food preparation and serving related occupations $9.68 10,489 ( 9.58, 9.79) $9.83 0.15 1.53%

Building and grounds cleaning and maintenance occupations $10.91 6,377 (10.76,11.06) $11.02 0.11 1.04%

Personal care and service occupations $11.36 4,755 (11.12,11.60) $11.44 0.08 0.75%

Sales and related occupations $17.90 19,043 (17.52,18.28) $17.23 -0.67 (3.76%)

Office and administrative support occupations $14.76 27,053 (14.59,14.92) $14.54 -0.21 (1.44%)

Farming, fishing, and forestry occupations $9.98 1,355 ( 9.58,10.37) $10.19 0.21 2.11%

Construction and extraction occupations $16.95 10,037 (16.55,17.34) $16.68 -0.27 (1.59%)

Installation, maintenance, and repair occupations $18.65 6,651 (18.01,19.29) $18.16 -0.49 (2.65%)

Production occupations $14.95 12,487 (14.79,15.12) $14.79 -0.16 (1.09%)

Transportation and material moving occupations $14.73 11,153 (14.49,14.97) $14.35 -0.38 (2.56%)

2005 All Occupations $18.80 178,419 (18.69,18.91) $18.27 -0.53 (2.81%)
 

 

 

 

 

 

 

 

 

 

 

Figure 8 

Group I - OES Occupations with 40% Employment in Interval L

Weighted Interval L

Employment

No. SOC Occ # Occupation % Emp in L Emp in L

1 29-1067 84 Surgeons 82 44,000 

2 29-1061 84 Anesthesiologists 78 22,000 

3 29-1064 84 OBGyn 77 17,000 

4 29-1063 84 Internists, general 59 29,000 

5 29-1066 84 Psychiatrists 50 12,000 

6 29-1069 84 Physicians/Surgeons 49 88,000 

7 11-1011 4 Chief Executives 49 156,000 

8 29-1062 84 Family/Gen. practition 46 52,000 

9 53-2011 226 Pilot/Copilot/Fl.engin. 46 35,000 

10 29-1065 84 Pediatricians, gen. 43 12,000 

Figure 9 

Group II - OES Occupations with 15 - 30% Employment in Interval L

Weighted Interval L

Employment

No. SOC Occ # Occupation % Emp in L Emp in L

11 29-1081 88 Podiatrists 27 2,200 

12 23-1011 178 Lawyers 25 134,000 

13 29-1199 84 Health Dia/Treat Prac 24 14,000 

14 27-2021 199 Athletes andSports 21 2,600 

15 41-3031 255 Secur./Comm./Finance. 19 48,000 

16 11-1021 22 General/Operation Mgr. 18 304,000 

17 11-2022 243 Sales Managers 18 57,000 

18 11-2021 13 Mkt. Managers 17 29,000 

19 13-2052 25 Personal Financial Ad. 16 18,000 

20 13-2051 7 Financial Managers 15 70,000 

21 41-9021 254 Real Estate Brokers 15 6,100 

22 25-1112 145 Lawteachers, postsec. 15 2,000 
 

 

 

 

 

 

 

 

Figure 10 

Group III - OES Occupations with 5 - 14% Employment in Interval L

Weighted Interval L Employment

No. SOC Occ # Occupation % Emp in L Emp in L

23 29-1041 87 Optometrists 14 3,000 

24 29-1011 84 Chiropractors 13 3,000 

25 11-3021 64 Computer/Info Sys Mgr 13 34,000 

26 11-9121 22 Natural Sciences Mgr. 13 5,000 

27 11-9041 59 Engineering Managers 12 23,000 

28 15-2011 66 Actuaries 12 1,900 

29 29-1199 134 Health Spec. teachers 11 12,000 

30 13-1011 22 Agents/Business Mgr. 11 1,200 

31 11-2011 13 Ad. & Promo. Mgr. 11 5,000 

32 25-1042 114 Bio. Teacher, Postsec. 11 6,000 

33 11-2031 13 PR Managers 10 4,000 

34 27-2012 187 Producers/Directors 9 5,000 

35 41-1012 22 First-line Supv./Mgr. 8 22,000 

36 29-1131 86 Veterinarians 7 3,000 

37 19-3011 166 Economists 6 800 

38 13-2051 25 Financial Analysts 6 11,000 

39 19-2042 75 Geoscientists 6 1,700 
 

 

 

 

 

 

Figure 11. Mean Wages for Interval L 

All data Excluding Pilots

1999 $124.55 $109.44 

2000 107.33 100.76 

2001 107.37 101.35 

2002 101.14 94.23 

Avg 110.10 101.44

Figure 12. Airline Pilots Mean Wages 

NCS Published NCS Calculated OES Published 

2003 $ 98.47 / hr $ 111,800 / yr $ 129,900 / yr 

2004 113.82 / hr 121,100 / yr 129,600 / yr 

2005 95.50 / hr 116,300 / yr 135,000 / yr 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 13 

NCS Occupational Groups

Group Occupational Description

A Professional and Technical Occupations 

B Executive, Administrative, and Managerial Occupations 

C Sales Occupations 

D Administrative Support Occupations, Including Clerical 

E Precision Production, Craft, and Repair Occupations 

F Machine Operators, Assemblers, and Inspectors 

G Transportations and Material Moving Occupations 

H Handlers, Equipment Cleaners, Helper, and Labors 

K Service Occupations, Expert Private Household 

Figure 14 

Options ΙΙ and ΙΙΙ- - NCS Major Occupational Groups

Mean 2004

NCS

Group Occupations

Weighted

Employment

in Interval L

% 

Employment

in Interval L

Mean

Wage for

Interval L

A Professional and Technical Occupations 288,800 2.002 $101.38 

B Executive, Administrative, and Managerial Occupations 210,500 3.584 101.99 

C Sales Occupations 50,100 0.628 127.34 

D Administrative Support Occupations, Including Clerical 500 0.004 116.73 

E Precision Production, Craft, and Repair Occupations 200 0.003 91.59 

F Machine Operators, Assemblers, and Inspectors 0 0.000 . 

G Transportations and Material Moving Occupations 0 0.000 72.43 

H Handlers, Equipment Cleaners, Helper, and Labors 0 0.000 . 

K Service Occupations, Expert Private Household 1,900 0.011 80.99 

Overall All Occupations 552,100 0.681 103.91 
 

 

 

 

 

Figure 15 

RESULTS 

Fail Criteria: Weighted employment in interval L > 1000 and 

 Relative error on mean wages per hour > 10% for 2 or 3 years 

Occ 

Code Title 

Average 

Weighted 

employment in 

interval L 

Average %

employment in 

interval L 

Current 

Method 

Overall 

Mean 

Option I

Sales vs. 

Non-Sales 

Option III 

Combination of 

Occupation 

Option IV 

119 College & University, Teachers 6,000 45 Pass Failed Failed Pass 

127 College & University, Teachers 6,000 33 Pass Failed Borderline Pass 

179 Judges 3,000 30 Failed Failed Failed Pass 

226 Pilots 62,000 70 Failed Failed Failed N/A 

255 Financial Service Sales 19,000 12 Failed Failed Pass Pass 

166 Economists 4,000 6 Pass Pass Pass Failed 

186 Musicians & Composers 4,000 15 Pass Pass Pass Failed 

198 Announcers 6,000 10 Pass Pass Pass Failed 
 

 

 

 

 

 

Figure 16: Pilots Mean Wages

NCS Published NCS Calculated OES Published

OES Calculated w/NCS 

Pilots yearly mean for 

interval L (Approximation)

2003 $ 98.47 / hr $ 111,800 / yr $ 129,900 / yr $ 114,600 / yr 

2004 113.82 / hr 121,100 / yr 129,600 / yr 114,300 / yr 

2005 95.50 / hr 116,300 / yr 135,000 / yr 119,700 / yr