Clinton County, IA 

National Compensation Survey 

Private Industry 

August 2008 

__________________________________________________________________________________________________ 

U.S. Department of Labor 

U.S. Bureau of Labor Statistics 

February 2009

his summary provides results of an August 2008 survey of occupational pay in Clinton County, IA. Tabulations in this publication are limited to private industry; 

data were not collected for State and local government. 

 Data shown in this summary were collected as part of 

the Bureau of Labor Statistics (BLS) National Compensation Survey (NCS). 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 occupations. Work level is a ranking based on knowledge, job 

controls and complexity, contacts, and physical environment. Separate data are also shown for full-time and parttime workers. 

 Table 2 presents hourly wage percentiles that describe 

the distribution of hourly earnings for individual workers 

within each published occupation. Data are 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 occupational groups and detailed occupations for full-time 

workers. 

 The survey could not have been conducted without the 

cooperation of the many private establishments that provided 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 survey, processed the data, and prepared the survey for publication. 

Where to find more information

The data contained in this summary are available at 

http://www.bls.gov/ncs/ocs/compub.htm, the BLS Internet 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, including 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 Massachusetts 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 permission. This information will be made available to sensory 

impaired individuals upon request. Voice phone: (202) 

691–5200; Federal Relay Service 1–800–877–8339. 

T 
Table 1. Private industry workers: Mean hourly earnings1 for full-time and part-time workers2 by work levels3, Clinton

County, IA, August 2008

Occupation4 and level

Total Full-time workers Part-time workers

Mean

Relative

error5

(percent)

Mean

Relative

error5

(percent)

Mean

Relative

error5

(percent)

All workers .............................................................................. $15.12 4.8 $16.28 2.9 $8.53 7.6

Management occupations ................................................. 35.30 9.1 35.30 9.1 – –

Healthcare support occupations ....................................... 11.83 12.5 12.08 12.1 – –

Nursing, psychiatric, and home health aides .................... 10.08 6.8 – – – –

Food preparation and serving related occupations ........ 7.84 2.0 – – 7.48 .9

Fast food and counter workers ......................................... 7.74 .5 – – – –

Sales and related occupations .......................................... 10.45 6.4 – – – –

Office and administrative support occupations .............. 12.46 3.7 12.81 3.7 – –

Level 4 ............................................................. 12.29 6.5 12.61 7.3 – –

Financial clerks ................................................................. 12.70 12.6 12.70 12.6 – –

Production occupations .................................................... 15.41 8.2 15.41 8.2 – –

Level 3 ............................................................. 14.37 10.5 14.37 10.5 – –

Level 4 ............................................................. 18.01 3.2 18.01 3.2 – –

Level 5 ............................................................. 19.83 4.2 19.83 4.2 – –

Transportation and material moving occupations .......... 14.04 8.7 15.89 3.9 – –

Level 3 ............................................................. 14.45 14.7 15.87 2.1 – –

1 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

tips. 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. 2 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 part-time in another firm, where

a 40-hour week is the minimum full-time schedule. 3 Each occupation for which data are collected in an establishment is

evaluated based on four factors, including knowledge, job controls and

complexity, contacts, and physical environment. The knowledge factor is tailored

to 24 families of closely 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

Occupational Classification (SOC) system. See appendix B for more information. 5 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

3
Table 2. Private industry workers: Hourly wage percentiles1, Clinton County, IA, August 2008

Occupation2 10 25 Median

50 75 90

All workers .............................................................................. $8.15 $9.84 $13.00 $18.53 $23.56

Management occupations ................................................. 22.50 23.56 32.92 41.27 46.70

Healthcare support occupations ....................................... 8.80 9.36 11.49 13.54 15.50

Nursing, psychiatric, and home health aides .................... 8.50 9.00 9.49 11.23 12.09

Food preparation and serving related occupations ........ 6.58 6.58 7.68 8.54 9.69

Fast food and counter workers ......................................... 6.58 6.58 7.42 8.54 9.69

Sales and related occupations .......................................... 7.77 8.55 10.20 11.30 15.06

Office and administrative support occupations .............. 9.02 10.00 11.43 14.21 17.82

Financial clerks ................................................................. 9.20 9.75 11.12 16.60 18.53

Production occupations .................................................... 10.76 12.29 14.46 18.29 21.43

Transportation and material moving occupations .......... 8.00 11.00 14.10 17.00 20.49

1 Percentiles designate position in the earnings 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 same 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-of-living adjustments, and hazard pay.

Excluded are premium pay for overtime, vacations, and holidays;

nonproduction bonuses; and tips. 2 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 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

4
Table 3. Full-time1 private industry workers: Mean and median hourly, weekly, and annual earnings and mean

weekly and annual hours, Clinton County, IA, August 2008

Occupation2

Hourly earnings3 Weekly earnings4 Annual earnings5

Mean Median Mean Median

Mean

weekly

hours

Mean Median

Mean

annual

hours

All workers ................................................ $16.28 $14.21 $650 $561 39.9 $33,607 $29,120 2,065

Management occupations ................... 35.30 32.92 1,462 1,564 41.4 76,031 81,305 2,154

Healthcare support occupations ......... 12.08 12.09 452 446 37.4 23,529 23,213 1,947

Office and administrative support

occupations .................................... 12.81 11.97 505 479 39.4 26,245 24,898 2,049

Financial clerks ................................... 12.70 11.12 497 445 39.2 25,851 23,130 2,036

Production occupations ...................... 15.41 14.46 616 578 40.0 32,044 30,077 2,080

Transportation and material moving

occupations .................................... 15.89 14.60 683 604 43.0 35,499 31,408 2,235

1 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 part-time in another firm,

where a 40-hour week is the minimum full-time 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 tips. 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 are the straight-time weekly wages or salaries

paid to employees. Median weekly earnings designates position - one-half of

the hours are paid the same 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 were reported or that data did not meet

publication criteria. Overall occupational groups may include data for

categories not shown separately

5
 7

Appendix: Technical Note 

Survey scope 

This survey of Clinton County, IA, covered establishments 

employing one worker or more in private goods-producing 

industries (mining, construction, and manufacturing) and 

private service-providing industries (trade, transportation, 

and utilities, information, financial activities, professional 

and business services, education and health services, leisure 

and hospitality, and other services). Agriculture, forestry, 

fishing and hunting, private households, the Federal Government, and State and local governments were excluded 

from the scope of the survey. For purposes of this survey, 

an establishment is an economic unit that produces goods 

or services, a central administrative office, or an auxiliary 

unit providing support services to a company. For private 

industries in this survey, the establishment is usually at a 

single physical location. 

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 available at the time the sample was selected. 

Sample design

The sample for this survey area was selected using a twostage stratified design with probability proportional to employment 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 establishment 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 occupation, they were classified in the occupation that required the 

higher skill level. When there was no perceptible difference in skill level, the workers were classified in the occupation that described their primary activity. 

 Each occupational classification is an element of a 

broader classification known as a major group. Occupations 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 identified 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 assigned 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 
 8

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 knowledge guide for 24 families of closely related occupations 

contains short definitions of the point levels of knowledge 

expected for the occupations and presents relevant examples. 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 publishes data for up to 15 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 supervise. 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 establishment in the survey, the data reflect the establishment’s 

most recent information at the time of collection. The payroll reference month shown in the tables reflects the average date of this information for all sample units. 

Earnings

Earnings were defined as regular payments from the employer to the employee as compensation for straight-time 

hourly work, or for any salaried work performed. The following 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 transportation 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 relative size of the occupation within the establishment and of 

the establishment within the sample universe. Weights 

were used to aggregate data for the individual establishments 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 establishments were classified into these cells according to industry 

and employment size. Responding and nonresponding occupations within responding establishments were classified 

into cells that were additionally defined by major occupation 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 average hourly earnings of respondents. The regression model 
 9

that takes into account available establishment characteristics is used to derive the rate of change in the average 

hourly earnings. 

 Establishments that were determined to be out of business or outside the scope of the survey had their weights 

changed to zero. 

Survey response 

Establish- 

 ments 

Total in sampling frame 1,021 

Total in sample 51 

 Responding 36 

 Refused or unable to provide data 8 

 Out of business or not in survey scope 7 

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 number of workers; the sample weight, adjusted for nonresponding establishments and other factors; and the occupation’s scheduled 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 employment totals to the current counts of employment by industry. 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 sufficient. This review prevented the publication of a series 

that could have revealed information about a specific establishment. 

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 using 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 sample approximates the average result of all possible samples. 

The relative standard error (RSE) is the standard error divided by the estimate. RSE data are provided alongside the 

earnings data in the summary tables. 

 The standard error can be used to calculate a “confidence 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 confidence interval for this estimate is from $17.46 to $18.04 

($17.75 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 population 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 survey definitions, inability of the respondents to provide correct information, or mistakes in recording or coding the 

data obtained. Although they were not specifically measured, 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.