Response Rates for the Pre-Production Test of 

the Occupational Requirements Survey 

Alice Yu1, Chester H. Ponikowski1, & Erin McNulty1

1U.S. Bureau of Labor Statistics, 

2 Massachusetts Ave., NE, Room 3160 Washington, DC 20212 

Abstract

The Occupational Requirements Survey (ORS) is an establishment survey conducted by 

the Bureau of Labor Statistics (BLS) for the Social Security Administration (SSA). The 

survey collects information on the vocational preparation and the cognitive and physical 

requirements of occupations in the U.S. economy, as well as the environmental conditions 

in which those occupations are performed. In fiscal year (FY) 2015, the BLS completed 

data collection for the ORS pre-production test. This paper focuses on the process for 

computing and analyzing the response rates from the ORS pre-production test, utilizing 

Office of Management and Budget (OMB) approved methods and formulas to produce 

detail statistics –weighted and unweighted at the establishment, occupation, and item 

levels. The results from this process will be used to help identify important auxiliary 

variables for use in estimation processes to reduce potential bias due to non-response in 

future samples. 

Key Words: response rates, efficiency rates, completion rates, non-response bias 

1. Introduction 

In the summer of 2012, the Social Security Administration (SSA) and the Bureau of Labor 

Statistics (BLS) signed an interagency agreement to begin the process of testing the 

collection of data on occupations. As a result, the Occupational Requirements Survey 

(ORS) [1] was established as a test survey in late 2012. The goal of ORS is to collect and 

publish occupational information that will replace outdated data currently used by SSA. 

All outputs generated from ORS data will be made public for use by non-profits, 

employment agencies, state or federal agencies, the disability community, and other 

stakeholders. 

The ORS data are collected by field economists. The field economists are required to 

collect close to 70 data elements related to the occupational requirements of a job. The 

following four groups of data are being collected: 

 Physical demands of work such as keyboarding and lifting 

 Environmental conditions such as extreme heat and cold 

 Vocational preparation including education, prior work experience, and training 

 Mental and cognitive demands of work including decision making and communication 

Response rates are one of the most important indicators of a survey’s quality since they 

can be used as a method to gauge the potential for non-response bias. Although most 

surveys have procedures to adjust for non-response, a low response rate may have an 

impact on accuracy of a survey estimate of the population value. Therefore, it is important 

to monitor response rates and keep them as high as possible. The purpose of this paper is 

JSM 2016 - Government Statistics Section

1622
to document the methods for analyzing response rates in ORS samples. This paper will 

describe the results from the pre-production test as an example of the method to be used 

for future production analyses. Section 2 of this paper provides additional background 

information on the ORS, including description of response status codes used by the survey. 

Section 3 describes calculation of response rates at the establishment, occupation, and ORS 

element level. Section 4 presents analysis of response rates at the three levels. Section 5 

presents our conclusion and suggestions for future work. 

2. Background Information on ORS 

In addition to providing Social Security benefits to retirees and survivors, the Social 

Security Administration (SSA) administers two large disability programs, which provide 

benefit payments to millions of beneficiaries each year. Determinations for adult disability 

applicants are based on a five-step process that evaluates the capabilities of workers, the 

requirements of their past work, and their ability to perform other work in the U.S. 

economy. In some cases, if an applicant is denied disability benefits, SSA policy requires 

adjudicators to document the decision by citing examples of jobs the claimant can still 

perform despite restrictions (such as limited ability to balance, stand, or carry objects) [2]. 

For over 50 years, the Social Security Administration has turned to the Department of 

Labor's Dictionary of Occupational Titles (DOT) [3] as its primary source of occupational 

information to process the disability claims [4]. SSA has incorporated many DOT 

conventions into their disability regulations. However, the DOT was last updated in its 

entirety in the late 1970’s, although a partial update was completed in 1991. Consequently, 

the SSA adjudicators who make the disability decisions must continue to refer to an 

increasingly outdated resource because it remains the most compatible with their statutory 

mandate and is the best source of data at this time. 

When an applicant is denied SSA benefits, SSA must sometimes document the decision by 

citing examples of jobs that the claimant can still perform, despite their functional 

limitations. However, since the DOT has not been updated for so long, there are some jobs 

in the American economy that are not even represented in the DOT, and other jobs, in fact 

many often-cited jobs, no longer exist in large numbers in the American economy. For 

example, a job that is often cited is “envelope addressor,” because it is an example of a 

low-skilled job from the DOT with very low physical demands. There are serious doubts 

about whether or not this job still exists in the economy. 

SSA has investigated numerous alternative data sources for the DOT such as adapting the 

Employment and Training Administration’s Occupational Information Network (O*NET) 

[5], using the BLS Occupational Employment Statistics program (OES) [6], and 

developing their own survey. But SSA was not successful with any of these potential data 

sources and turned to the National Compensation Survey program at the Bureau of Labor 

Statistics. 

In fiscal years 2013 and 2014, several feasibility tests were performed to assess the viability 

of collecting data on occupational requirements using the platform currently used by the 

NCS. These tests provided evidence that the NCS platform could be adapted to ORS data 

collection, which led to the pre-production test in FY 2015.4 Unlike the earlier tests, which 

were small-scale and tested a subset of data elements or the viability of different collection 

methods, the pre-production test was designed as a relatively large-scale, nationally 

representative test of ORS data collection. ORS pre-production data collection began in 

October 2014 and continued until May 2015. The sampling, data collection, procedures, 

and review were designed to mimic what will occur during ORS production. [7]

JSM 2016 - Government Statistics Section

1623
The ORS sample is based on a complex two-stage stratified design with probability 

proportionate to employment size sampling at each stage. The first stage is a probability 

sample of establishments and the second stage is a probability sample of jobs (occupations) 

from sampled establishments. Stratification of establishments in the sampling frame is by 

industry and ownership, and also implicitly by region and establishment employment. The 

frame used for sampling is developed from the BLS Quarterly Census of Employment and 

Wages (QCEW) Database with railroads added in. Allocation of sample is proportional to 

employment size. ORS samples follow a three-year rotation. Nonresponse in ORS can 

occur at the establishment level, job level, and data items (elements) level. Adjustment to 

sample weights is done at the establishment and job levels. Imputation is used to account 

for missing item values. For more details on the ORS sample design, see the Ferguson and 

McNulty paper [8]. Under this design, it is possible for a job to be sampled more than once 

in a given establishment. When this occurs, the job is “collapsed” so that data for the job 

is only collected once. In reports about data collection, collapsed jobs are counted only 

once. In this response analysis, collapsed quotes are counted every time they were selected. 

2.1 Response Status Codes: Non-response Types and Outcome codes

Like any survey, the ORS does not receive responses from every establishment in its 

sample. Ideally, the sample establishment agrees to participate in the survey and gives the 

Field Economist (FE) quality data. However, sometimes the FE is unable to make contact 

with a sample establishment’s representative that is knowledgeable of the ORS data 

elements, or an establishment can simply refuse to participate. Also, sample establishments 

may go out of business or be out of the survey’s scope. A list of response status codes for 

establishments and occupations are provided below: 

Response Status 

(Code) Indications

Usable (USE)

Establishment data: When the establishment is coded with all of 

the following:

- description of establishment operations for the purpose of 

assigning North American Industry Classification System 

(NAICS)

- total employment

- eligible employment

- at least one usable occupational observation

Occupational data: When the occupation in the sample 

establishment is coded with all of the following:

- occupational employment

- worker characteristics (Full-time/Part-time, Union/Nonunion, and Time/Incentive)

- occupational work schedule

- worker type (Supervisory, Non-supervisory, Lead)

- job leveling

- job duties to code the eight-digit Standard Occupational 

Classification (SOC) code using Training 

Administration’s Occupational Information Network 

(O*NET)

- at least one ORS element data

JSM 2016 - Government Statistics Section

1624
Response Status 

(Code) Indications

Refusals (REF)

Refusals can take several forms:

- The establishment/occupation does not have the 

minimum required data to be usable.

- The respondent is unwilling or unable to provide data.

Out-of-Business 

(OOB)

For Establishment data only: When a sample establishment is 

no longer in business. Since the sample of establishments is 

chosen some months before the actual start of collection, it is 

possible that some sample units are no longer in business by the 

date scheduled for data collection.

Out-of-Scope 

(OOS)

For Establishment data only: A sample establishment can be 

out of scope for two reasons:

- Geography

When an establishment is located in or has moved to an 

area entirely outside of the United States, defined as the 

50 states and the District of Columbia.

- Industry

When an establishment falls into one of the following 

industry categories:

▪ Federal Government

▪ Private households

▪ Agriculture

▪ Quasi-Federal

▪ Foreign Government

▪ International Government

No-Matching-Job 

(NMJ)

(For establishment data: When all occupations...)

(For occupational data: When the occupation...)

( )...in the sample establishment are in one or more of the 

following categories:

- contractors

- corporate officers, trustees, and board members who do 

not hold a job at the firm

- employees on strike more than a year

- family members earning higher-than-market wages

- federal work-study students

- individuals on long-term disability (LTD) not expected to 

return

- leased employees

- non-working individuals with no guarantee to return

- owners of unincorporated firms

- temporary help employees

- volunteers and unpaid workers

- For occupational data only: employees outside the 

assigned area (except for situations where worker lives 

outside the area, but all work performed via email and 

phone)

JSM 2016 - Government Statistics Section

1625
Even if the sample establishment agrees to participate in the survey and gives the FE data, 

it would be ideal to capture all of the data for the survey, but this is not always the case. A 

list of response status codes for ORS element data are provided below: 

Response Status 

(Code) Indications

Known (KN) Respondent provided the ORS element data.

Present, but 

unknown (PU)

Respondent stated the ORS element is present, but does not 

know the duration for which the ORS element is present.

Unknown (UK) Respondent does not know or did not provide data on the ORS 

element.

3. Calculation of Response Rates 

The Office of Management and Budget (OMB)-approved methods [9] and formulas [10] 

were used to produce detail statistics on response rates and efficiency rates. 

The formulas used to compute the two rates are as follows: 

3.1 Types of Rates

Two types of rates were calculated: response rates and efficiency rates. Response rates 

measure how much of the viable sample yielded usable data for estimation. Viable sample 

is the original sample excluding establishments or occupations that are considered out-ofbusiness, out-of-scope, or have no matching jobs. Efficiency rates measure how much of 

the original sample yielded results usable for estimation. Efficiency rates are not calculated 

for ORS element data since all ORS elements are collected for all occupations, and none 

are out-of-scope. Response rates and efficiency rates both include collapsed data. 

Collapsed data occur when the same occupation is selected more than once from an 

establishment. 

3.1.1 Unweighted vs. Weighted Data 

Unweighted and weighted data for response rates and efficiency rates are both 

needed to fully evaluate survey performance. Unweighted rates provide a useful 

description of the operational aspect of the survey and indicate how many of the 

raw number of cases were successfully collected. Unweighted rates are 

computed using unit counts. Weighted rates provide a better indication of the 

potential impact of response on estimates. Weighted rates are computed using 

the original sample weights for each unit, rather than final sample weight, 

because the final sample weights are only assigned to establishments and 

occupations that are usable for estimation.

3.2 Types of Units 

Computations for rates are based on in the following inputs: 

- Establishment data: establishments in the sample 

- Occupational data: selected occupations for each establishment in the sample 

Response Rate Efficiency Rate

(For establishment and occupational data)

 = USE / (USE + REF)

(For ORS element data)

 = (KN+PU) / (KN + PU + UK)

(For establishment data) 

 = USE / (USE + REF + OOB + OOS + NMJ)

(For occupational data)

 = USE / (USE + REF + NMJ)

JSM 2016 - Government Statistics Section

1626
- ORS Element data: ORS elements eligible to be collected for each occupation in 

each establishment in the sample 

3.3 Levels of Details 

Rates are calculated at various levels of data aggregation for the three types of units. The 

levels of data aggregation are: 

- Aggregate industries, which include 24 private industries and 10 government 

industries, as listed below. 

Private Industry Government Industry

1) Mining

2) Utilities

3) Construction

4) Manufacturing

5) Aircraft Manufacturing

6) Wholesale Trade

7) Retail Trade

8) Transportation and Warehousing

9) Information

10) Finance (excluding Insurance)

11) Insurance Carriers and Related Activities

12) Real Estate and Rental and Leasing

13) Professional, Scientific, and Technical Services

14) Management of Companies and Enterprises

15) Administrative and Support, Waste Management

16) Education (rest of)

17) Elementary & Secondary Educations

18) Colleges & Universities Educations

19) Health and Social Assistance (rest of)

20) Hospitals

21) Nursing Homes

22) Arts, Entertainment, and Recreation

23) Accommodation and Food Services

24) Other Services (except Public Administration)

1) Mining, Construction, 

Manufacturing

2) Wholesale and Retail 

Trades

3) Elementary & Secondary 

Educations

4) Colleges & Universities 

Educations

5) Educational Services

6) Hospitals

7) Nursing & Residential 

Cares

8) Other Health Care

9) Public Administration 

(excluding National 

Security Information, 

Finance, Food Services, 

Professionals)

10) Other service providing

- Census Regions and Divisions 

There are 4 census regions, each with 2 or 3 census divisions. The regions are West 

with Pacific and Mountain divisions; Midwest with West North Central and East 

North Central divisions; Northeast with Middle Atlantic and New England 

divisions; and South with West South Central, East South Central, and South 

Atlantic divisions. [11] 

- Establishment Size Class is assigned based on establishment employment size, 

as listed below. 

Establishment Size Class Employment Size

1 Less than 50 employees

2 Between 50 and 99 employees

3 Between 100 and 499 employees

4 More than 499 employees

JSM 2016 - Government Statistics Section

1627
- Ownership 

An establishment can be labelled as private entity, state government, or local 

government. 

- Major occupational groups are identified with 2-digit Standard Occupational 

Classification (SOC) codes, as listed below. 

2-digit SOC Codes Standard Occupational Classification

11 Management Occupations

13 Business & Finance Operations Occupations

15 Computer & Mathematical Occupations

17 Architecture & Engineering Occupations

19 Life, Physical, & Social Science Occupations

21 Community & Social Service Occupations

23 Legal Occupations

25 Education, Training, & Library Occupations

27 Arts, Design, Entertainment, Sports, & Media Occupations

29 Healthcare Practitioners & Technical Occupations

31 Healthcare Support Occupations

33 Protective Service Occupations

35 Food Preparation & Serving Related Occupations

37 Building, Grounds Cleaning, & Maintenance Occupations

39 Personal Care & Service Occupations

41 Sales & Related Occupations

43 Office & Administrative Support Occupations

45 Farming, Fishing, & Forestry Occupations

47 Construction & Extraction Occupations

49 Installation, Maintenance, & Repairing Occupations

51 Production Occupations

53 Transportation & Material Moving Occupations

4. Analysis of Response Rate 

4.1 Establishment Level 

Table 1 below shows that there are 2,549 establishments in the Occupational Requirements 

Survey pre-production sample. Of the 2,549 establishments, 168 establishments were 

either out of business, out of scope, or had no jobs in scope for ORS. Of the remaining 

2,381 establishments, 1,851 establishments provided usable data, indicating a usable 

establishment unweighted response rate of 78 percent, weighted response rate of 76 

percent, unweighted efficiency rate of 73 percent, and weighted efficiency rate of 69 

percent. 

Table 1. Overall Response and Efficiency Rates for Establishment Level Data 

Total Establishments USE REF OOB/OOB/NMJ

2,549 1,851 530 168

Unweighted Response Rate = 78% Weighted Response Rate = 76%

Unweighted Efficiency Rate = 73% Weighted Efficiency Rate = 69%

JSM 2016 - Government Statistics Section

1628
For the section below, refer to the Figures in the attachment provided at the end of the 

paper. 

Figures 1, 3, 5, and 8 display result for establishment units. In each of the four Figures, 

the darker line represents weighted data and the lighter line represents unweighted data 

for both response (red) and efficiency (blue) rates. If the darker line is greater than the 

lighter line, then more data were collected on establishments that have greater 

representation in the population sampled. 

Figure 1 displays the weighted and unweighted response rates and efficiency rates for 

private aggregate industries. The private aggregate industries are listed in descending 

order by (dark red) weighted response rates. The weighted response rates range from 

52 percent for ‘Information’ industry to 93 percent for ‘Utilities’ industry. 

Figure 3 displays the weighted and unweighted response rates and efficiency rates for 

census regions and divisions. Figure 3 is sorted by (dark red) weighted response rates 

in descending order for census region and for census division within each census 

region. The weighted response rates for census regions range from 73 percent for 

‘Midwest’ region to 81 percent for ‘West’ region. The weighted response rates for 

census division range from 71 percent for ‘West South Central’ division to 81 percent 

for ‘Mountain’ division. 

Figure 5 displays the weighted and unweighted response rates and efficiency rates for 

employment size. The employment sizes are listed in descending order by (dark red) 

weighted response rates. The weighted response rates range from 72 percent for 

establishments with ‘More than 499 Employees’ to 81 percent for establishments with 

‘Less than 50 Employees.’ 

Figure 8 displays the weighted and unweighted response rates and efficiency rates for 

ownership status. The ownership statuses are listed in descending order by (dark red) 

weighted response rates. Government establishments appear to have better response 

rates than private establishments.

4.2 Occupation Level 

Table 2 below shows within the 1,851 usable establishments, 10,495 occupational 

observations or quotes were attempted to be collected. Of the 10,495 quotes, 9,132 

provided usable data, 1,232 refused, and 131 are out of scope. Collapsed quotes are counted 

once for each time selected. The occupational level response rates are 88 percent for 

unweighted data and 89 percent for weighted data. The occupational level efficiency rates 

are 87 percent for unweighted data and 88 percent for weighted data. 

Table 2. Overall Response and Efficiency Rates for Occupational Level Data

From 1,851 Usable Establishments:

Total Occupations USE REF NMJ

10,495 9,132 1,232 131

Unweighted Response Rate = 88% Weighted Response Rate = 89%

Unweighted Efficiency Rate = 87% Weighted Efficiency Rate = 88%

JSM 2016 - Government Statistics Section

1629
For the section below, refer to the Figures in the attachment provided at the end of the 

paper. 

Figures 2, 4, 6, and 9 display results for occupational units. In each of the four Figures, 

the darker line represents weighted data and the lighter line represents unweighted data 

for both response (red) and efficiency (blue) rates. If the darker line is greater than the 

lighter line, more data were collected on occupations that have greater representation 

in the population sampled. 

Figure 2 displays the weighted and unweighted response rates and efficiency rates for 

private aggregate industry. The private aggregate industries are listed in descending 

order by (dark red) weighted response rates. The weighted response rates range from 

65 percent for ‘Colleges & Universities Educations’ industry to 100 percent for ‘Arts, 

Entertainment, and Recreation’ industry. 

Figure 4 displays the weighted and unweighted response rates and efficiency rates for 

census regions and divisions. The weighted response rates are sorted in descending 

order for census region and for census division within each census region. The 

weighted response rates for census region range from 88 percent for ‘West’ region to

90 percent for ‘Midwest’ region. The weighted response rates for census division range 

from 87 percent for ‘Pacific’ division to 93 percent for ‘East South Central’ division. 

Figure 6 displays the weighted and unweighted response rates and efficiency rates for 

establishment employment size. The employment sizes are listed in descending order 

by (dark red) weighted response rates. The weighted response rates range from 80 

percent for establishments with ‘More than 499 Employees’ to 93 percent for 

establishments with ‘Less than 50 Employees.’ 

Figure 9 displays the weighted and unweighted response rates and efficiency rates by 

ownership status. The ownership statuses are listed in descending order by (dark red) 

weighted response rates. Private establishments appear to have better response rates 

than government establishments. 

4.3 ORS Element Level 

There are up to 70 ORS elements [12] collected for each occupational observation. Table 

3 below shows response rate range for ORS elements in 9,132 usable occupations from 

1,851 usable establishments. The weighted response rates range from 77 percent to 98 

percent. Efficiency rates are not calculated for ORS element data since all elements are 

collected for all occupations, and an ORS element can never be out-of-scope. 

Table 3. Overall Response Rates for ORS Element Level Data

ORS elements data were also analyzed at various level of detail. For example, among the 

5 elements with the top weighted response rates, establishments with ’50 to 99 Employees’ 

provide answers at a higher rate than establishments in the other three size classes. Whereas 

within the 5 elements with the bottom response rates, establishments with ‘More than 499 

From 9,132 Usable Occupations in 1,851 Usable Establishments:

Unweighted Response Rate Range: (76%, 98%)

Weighted Response Rate Range: (77%, 98%)

JSM 2016 - Government Statistics Section

1630
Employees’ provide answers at a lower rate than establishments in the other three size 

classes. 

4.4 Comparison Across the Types of Units 

Further analyses were performed on a combination of establishment data, occupational 

data, and ORS element data. Figure 7 displays combined effect of establishment and 

occupational response on the overall response and efficiency rates. For example, the 

combined weighted response rate for the entire sample of occupations within 

establishments with ‘More than 499 employees’ is 58 percent. The 58 percent is the result 

of 72 percent response at the establishment level and 88 percent at the occupational level. 

The overall response rates for the entire sample of occupations within establishments range 

from 58 percent with ‘More than 499 Employees’ to 75 percent with ‘Less than 50 

Employees’.

5. Conclusion and Future Work 

Considering the amount of data requested by ORS, the response and efficiency rates for 

pre-production sample are fairly high. The collected data show that the rates vary by 

industry, occupational group, establishment size, and ownership. This indicates that 

industry, occupational group, establishment size, and ownership are important auxiliary 

variables; and they should be used in adjustment for nonresponse process to reduce 

potential bias due to nonresponse. 

We plan to continue to monitor, calculate, and analyze response rates by available auxiliary 

variables from the ongoing ORS production sample each year. The results from further 

analysis may lead to additional improvements in the nonresponse adjustment process for 

ORS. We also plan to carefully analyze the potential for non-response bias in key subsets 

of the data collected. 

Any opinions expressed in this paper are those of the authors and do not constitute policy 

of the Bureau of Labor Statistics or the Social Security Administration.

JSM 2016 - Government Statistics Section

1631
References 

[1] Bureau of Labor Statistics, Occupational Requirements Survey, http://www.bls. 

gov/ors/.

[2] Social Security Administration, Occupational Information System Project, http:// 

www.ssa.gov/disabilityresearch/occupational_info_systems.html. 

[3] U.S. Department of Labor, Employment and Training Administration (1991), 

“Dictionary of Occupational Titles, Fourth Edition, Revised 1991”. 

[4] Occupational Information Development Advisory Panel, 2010, http://www.social 

security.gov/oidap/index.htm. 

[5] U.S. Department of Labor, O*Net Online, http://www.onetonline.org/.

[6] Bureau of Labor Statistics, Occupational Employment Statistics Program, http:// 

www.bls.gov/oes/. 

[7] Bureau of Labor Statistics, Occupational Requirements Survey Pre-Production 

Report September 28, 2015. Occupational Requirements Survey, http://www.bls. 

gov/ncs/ors/pre-prod-report.htm. 

[8] Ferguson, Gwyn R., McNulty, Erin. 2015. Occupational Requirements Survey 

Sample Design. In JSM proceedings, Government Statistics Section. Alexandria, 

VA: American Statistical Association. 

[9] OMB Statistical Standards and Guidelines, page 8, https://www.whitehouse.gov/ 

sites/default/files/omb/assets/omb/inforeg/statpolicy/standards_stat_surveys.pdf. 

[10] “Questions and Answers When Designing Surveys for Information Collections”, 

pages 56-71, https://www.whitehouse.gov/sites/default/files/omb/inforeg/pmc_ 

survey_guidance_2006.pdf. 

[11] “Census Regions and Divisions of the United States”, https://www2.census.gov/ 

geo/pdfs/maps-data/maps/reference/us_regdiv.pdf. 

[12] Bureau of Labor Statistics, Occupational Requirements Survey Pre-Production 

Estimation and Validation Report September 10, 2015. Occupational 

Requirements Survey, http://www.bls.gov/ncs/ors/pre-prod-estval.htm. 

JSM 2016 - Government Statistics Section

1632
Aggregate Industry: Rates (in Occupational Units) Figure 2

Response Rates for Establishment (Figure 1) and Occupational (Figure 2) Units by 

Aggregate Industry Aggregate Industry: Rates (in Establishment Units) Figure 1

JSM 2016 - Government Statistics Section

1633
60%

65%

70%

75%

80%

85%

90%

95%

Mountain Pacific Middle

Atlantic

New

England

South

Atlantic

West

South

Central

East South

Central

West

North

Central

East North

Central

West Northeast South Midwest

Census Regions and Divisions: Rates

(in Establishment Units)

Weighted Efficiency Rate Unweighted Efficiency Rate

Weighted Response Rate Unweighted Response Rate

Response Rates for Establishment (Figure 3) and (Figure 4) Occupational Units by 

Census Regions and Divisions 

60%

65%

70%

75%

80%

85%

90%

95%

West

North

Central

East North

Central

East South

Central

South

Atlantic

West

South

Central

Middle

Atlantic

New

England

Mountain Pacific

Midwest South Northeast West

Census Regions and Divisions: Rates

(in Occupational Units)

Weighted Efficiency Rate Unweighted Efficiency Rate

Weighted Response Rate Unweighted Response Rate

Figure 3

Figure 4

JSM 2016 - Government Statistics Section

1634
Response Rates for Establishment (Figure 5) and Occupational (Figure 6 & 7) Units 

by Employment Size 

Less than 50

Employees

50 to 99

Employees

100 to 499

Employees

More than 499

Employees

Weighted Efficiency Rate 0.67 0.71 0.69 0.71

Unweighted Efficiency Rate 0.72 0.74 0.71 0.74

Weighted Response Rate 0.81 0.76 0.72 0.72

Unweighted Response Rate 0.83 0.77 0.73 0.75

60%

65%

70%

75%

80%

85%

90%

95%

Employment Size: Rates (in Establishment Units)

Less than 50

Employees

50 to 99

Employees

100 to 499

Employees

More than 499

Employees

Weighted Efficiency Rate 0.92 0.91 0.87 0.78

Unweighted Efficiency Rate 0.93 0.91 0.87 0.80

Weighted Response Rate 0.93 0.92 0.88 0.80

Unweighted Response Rate 0.93 0.92 0.88 0.81

60%

65%

70%

75%

80%

85%

90%

95%

Employment Size: Rates (in Occupational Units)

Figure 5

Figure 6

JSM 2016 - Government Statistics Section

1635
Occupational Rates out of the Entire Sample of Occupations

(Including Establishment’s Non-usable Occupations)

Response Rates for Establishment (Figure 8) and Occupational (Figure 9) Units by 

Ownership Status 

60%

65%

70%

75%

80%

85%

90%

95%

State

Government

Local

Government

Private

Establishment

Ownership Status: Rates

(in Establishment Units)

60%

65%

70%

75%

80%

85%

90%

95%

State

Government

Local

Government

Private

Establishment

Ownership Status: Rates

(in Occupational Units)

Figure 7

Figure 8 Figure 9

JSM 2016 - Government Statistics Section

1636