The Comprehensive Immigration Reform Act of 2006 (S. 2611): Potential Labor Market Effects of the Guest Worker Program



Order Code RL33772
The Comprehensive Immigration Reform Act of
2006 (S. 2611): Potential Labor Market Effects
of the Guest Worker Program
December 18, 2006
Gerald Mayer
Economic Analyst
Domestic Social Policy Division

The Comprehensive Immigration Reform Act of 2006
(S. 2611): Potential Labor Market Effects of the Guest
Worker Program
Summary
In the 109th Congress, the Senate passed S. 2611, the Comprehensive
Immigration Reform Act of 2006, which would have created a new H-2C guest
worker program. The 110th Congress may consider similar legislation.
The guest worker program included in S. 2611 would allow up to 200,000
foreign workers into the United States annually. An employer would have to pay an
H-2C worker the greater of the “actual” wage paid by the employer to other workers
who do the same kind of work and have similar experience or the “prevailing” wage.
Employers would be prevented from hiring H-2C workers if the area unemployment
rate for unskilled workers averaged more than 9% for the previous six months. The
language in S. 2611 would allow employers to hire skilled, semi-skilled, or unskilled
workers, but not agricultural workers or certain types of skilled workers. The kinds
of jobs filled under the H-2C program could be similar to the kinds of jobs filled
under an existing (H-2B) program, which is used mainly to hire lower-skilled
workers.
Initially, an increased supply of lower-skilled foreign workers could be expected
to lower the relative wages of lower-skilled U.S. workers. If the H-2C program were
enacted, an increased supply of lower-skilled foreign workers may have the greatest
impact on young, native-born minority men and on foreign-born minority men in
their early working years. In 2005, lower-skilled U.S. workers were mainly white,
non-Hispanic males under the age of 45. But a disproportionate number of these
workers were young (16 to 24), minority (black or Hispanic) men. The
unemployment rate among young, native-born minority men tends to be higher than
among similar nonminority men. In 2005, almost a fifth of lower-skilled workers
were foreign born, and a disproportionate number of these were minority (nonwhite
or Hispanic) men in their early working years (25 to 44). Foreign-born minority men
in their early working years tend to earn less than similar native-born workers.
In response to an initial decline in the relative wages of lower-skilled workers
employers may hire more lower-skilled workers and fewer skilled workers. Thus, the
initial widening of the wage gap may narrow over time. Other factors — such as
technological change, trade, saving and investment, education and training,
demographic changes — may also affect the wages of U.S. workers.
The H-2C program could be used by employers to meet seasonal demand, to
hire foreign workers at full employment, or to fill jobs when there is a mismatch in
a geographic area between the skills demanded and the skills available. In each case,
U.S. workers may not be available at the wages offered. They may or may not be
available at higher wages.
If employers are not able to hire qualified U.S. workers in high unemployment
areas (i.e., more than 9%), there may be a mismatch between the skills available and
the skills employers need. This report will be updated as warranted.

Contents
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
The Proposed H-2C Guest Worker Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Effects of a New Guest Worker Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
CBO Estimates of the Impact of the H-2C Program . . . . . . . . . . . . . . . . . . . 3
Characteristics of Competing Lower-Skilled U.S. Workers . . . . . . . . . . . . . 4
All Lower-Skilled Workers Compared to the Total Civilian
Labor Force . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Foreign-Born, Lower-Skilled Workers Compared to All
Lower-Skilled Workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
High School Dropouts Compared to All Persons With No More
than A High School Education . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
Occupations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
Earnings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Research on the Effect of Immigration on Earnings . . . . . . . . . . . . . . 11
Economic Framework For Understanding the Potential Labor Market
Effects of a New Guest Worker Program . . . . . . . . . . . . . . . . . . . . . . 12
Economic Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Effects of the 9% Area Unemployment Trigger . . . . . . . . . . . . . . . . . . . . . 15
Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
Appendix A. Data and Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Current Population Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Confidence Levels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Appendix B. Demographic Characteristics of Persons With Less than a
High School Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
Appendix C. Areas Potentially Affected by the 9% Unemployment Trigger
in S. 2611 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
List of Tables
Table 1. Demographic Characteristics of the U.S. Labor Force in 2005,
by Type . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Table 2. Employment of Lower-Skilled, Foreign-Born Workers in 2005,
by Occupation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
Table 3. BLS Employment Projections, 2004-2014, by Occupation . . . . . . . . . 10
Table B1. Demographic Characteristics of the U.S. Labor Force in 2005,
by Type . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
Table C1. Labor Force Size and Unemployment Rates in 2005,
by Metropolitan Statistical Area and Level of Education . . . . . . . . . . . . . . 22

The Comprehensive Immigration Reform
Act of 2006 (S. 2611): Potential Labor
Market Effects of the Guest Worker Program
Introduction
In the 109th Congress, the Senate passed S. 2611, the Comprehensive
Immigration Reform Act of 2006.1 The 110th Congress may consider similar
legislation. S. 2611 included provisions to improve border security and the
enforcement of immigration law. The bill would have also created legalization
programs for unauthorized aliens, increased existing limits on legal immigration, and
created a new H-2C guest worker program.
This report examines some potential labor market effects of the guest worker
program included in S. 2611. The report begins with a description of the program.
Next, the report describes some characteristics of lower-skilled U.S. workers with
whom many H-2C guest workers may compete. The report then examines some
potential labor market effects of an increased supply of lower-skilled foreign workers
on competing U.S. workers (i.e., workers in the United States who have similar skills
as H-2C workers). Finally, the report examines some possible effects of a provision
in S. 2611 that would prevent employers from hiring H-2C workers if the area
unemployment rate for unskilled workers averages more than 9% for the previous six
months.
The Proposed H-2C Guest Worker Program
S. 2611 would allow employers to hire up to 200,000 H-2C guest workers a
year.2 H-2C workers could be hired to fill skilled, semi-skilled, or unskilled jobs, but
employers could not use the program to hire agricultural workers or certain skilled
1 S. 2611 was approved by the Senate on May 25, 2006. On Dec. 16, 2005, the House
approved H.R. 4437, the Border Protection, Antiterrorism, and Illegal Immigration Control
Act of 2005. H.R. 4437 would not create a new guest worker program. For more
information on these bills and other immigration legislation in the 109th Congress, see CRS
Report RL33125, Immigration Legislation and Issues in the 109th Congress, coordinated by
Andorra Bruno; and CRS Report RL33181, Immigration Related Border Security
Legislation in the 109th Congress
, by Blas Nuñez-Neto and Janice Cheryl Beaver.
2 Under S. 2611, unauthorized workers who have been in the United States since Jan. 7,
2004, and meet certain conditions may be able to obtain H-2C visas. The 200,000 annual
cap on H-2C visas would not apply to these workers.

CRS-2
workers.3 The H-2C program would prohibit employers from hiring guest workers
in areas with high unemployment (i.e., more than 9%) among unskilled workers. S.
2611 defines the area unemployment rate as the unemployment rate in Micropolitan
Statistical Areas or Metropolitan Statistical Areas (MSAs). These areas are defined
by the Office of Management and Budget (OMB).4 S. 2611 defines unskilled
workers as persons with no more than a high school education.
Under S. 2611, to get an H-2C visa an individual would have to have a job offer
from a U.S. employer who meets the requirements of the act. Before hiring a foreign
worker, an employer would first have to try to recruit a U.S. worker.5 An employer
would have to offer the job to any U.S. worker who applies and is qualified and
available. An employer would also have to file a petition with the Secretary of
Homeland Security in which the employer states that the employment of a foreign
worker will not adversely affect the wages or working conditions of U.S. workers
who are “similarly employed.”
Once an H-2C worker is hired, an employer would have to pay the worker either
(1) the actual wage paid by the employer to other workers who do the same kind of
work and have similar experience or (2) the prevailing wage, whichever is greater.6
3 Under an existing (H-2A) program, employers may hire foreign workers to perform
temporary agricultural work. The H-2A program does not have an annual cap. For more
information on the H-2A program, see CRS Report RL32044, Immigration: Policy
Considerations Related to Guest Worker Programs
, by Andorra Bruno.
The H-2C program in S. 2611 would not apply to certain skilled workers who can enter the
United States under existing visas. For example, the H-2C visa would not apply to persons
covered by the H-1B program, which is for persons in specialty occupations (generally,
occupations that require the application of specialized knowledge and a bachelor’s degree
or its equivalent). Nor would the H-2C program apply to persons covered by the L, O, or
certain other visas. The L visa applies to intracompany transfers of executives, managers,
or workers with specialized knowledge. The O visa applies to persons with “extraordinary
ability” in science, business, education, the arts, or athletics or who have a record of
“extraordinary achievement” in the motion picture or television industry.
4 An MSA is a geographic area that consists of at least one urban area with a population of
50,000 or more and adjacent areas that have a high degree of economic and social
integration. A Micropolitan Statistical Area consists of at least one urban area with a
population of 10,000 to 50,000 and adjacent areas with a high degree of economic and social
integration. U.S. Office of Management and Budget, Metropolitan Statistical Areas,
Metropolitan Divisions, Micropolitan Statistical Areas, Combined Statistical Areas, New
England City and Town Areas, and Combined New England City and Town Areas
, OMB
Bulletin 06-01, available at [http://www.whitehouse.gov/omb/bulletins/fy2006/
b06-01_rev.pdf], Dec. 5, 2005, p. 2.
5 S. 2611 defines a “United States worker” as a citizen of the United States; an alien who has
been admitted as a permanent resident or refugee; an alien who has been granted asylum;
or an alien who has been authorized to work in the United States.
6 If a job is covered by a collective bargaining contract, the prevailing wage would be the
wage covered by the agreement. If the job is not covered by a collective bargaining contract
but is an occupation covered by either the Davis-Bacon Act or the Service Contract Act, the
(continued...)

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The H-2C visa would be effective for an initial period of three years and could
be extended for another three years. The visa would be portable; that is, an H-2C
worker could accept a job offer from another U.S. employer, provided the employer
meets the recruitment, wage, and other requirements of the act.
Persons who receive a temporary H-2C visa could adjust to permanent status.
After four years in the United States, an H-2C worker could file a petition for an
employment-based visa.7 At any time, an employer could file a petition on behalf of
a worker for an employment-based visa.8
Effects of a New Guest Worker Program
The 110th Congress may consider a new guest worker program similar to the H-
2C program approved by the Senate in the 109th Congress. If so, questions will likely
arise about the potential economic effects of such a program. This section begins
with a summary of estimates by the Congressional Budget Office (CBO) of the
effects of the H-2C program on federal spending and the U.S. population. Next, the
section describes some characteristics of lower-skilled U.S. workers with whom
many H-2C workers would likely compete. The section then describes an economic
framework that is useful in understanding the potential labor market effects of a new
guest worker program. Finally, the section considers some possible effects of the
provision in S. 2611 that would prevent employers from hiring H-2C workers if the
area unemployment rate for unskilled workers averages more than 9% for the
previous six months.
CBO Estimates of the Impact of the H-2C Program
According to estimates by CBO, the H-2C program in S. 2611 would raise direct
federal spending by $4.1 billion from 2007 to 2016. Most of this spending ($3.9
billion) would be for Medicaid benefits. CBO also projects that the H-2C program
would increase the U.S. population by 3.3 million persons from 2007 through 2016.
The projection includes both workers and their dependents (including children born
to new entrants after they arrive in the United States). Of the 3.3 million increase,
6 (...continued)
prevailing wage would be the wage that applies under those acts. If a job is not covered by
a collective bargaining contract or either the Davis-Bacon or Service Contract Acts, the
prevailing wage would be based on wage data for the occupation from the Bureau of Labor
Statistics (BLS) or, if BLS does not have wage data that applies to the occupation, on data
from another survey approved by the Secretary of Labor. For descriptions of the Davis
Bacon and Service Contract Acts, see CRS Report RL32086, Federal Contract Labor
Standards Statutes: An Overview
, by William G. Whittaker.
7 For an explanation of employment-based visas, see CRS Report RL32235, U.S.
Immigration Policy on Permanent Admissions
, by Ruth Ellen Wasem.
8 The spouses and children of H-2C workers would be able to enter the United States under
a different visa (H-4).

CRS-4
CBO estimates that a half million persons would have entered the United States
illegally under current law.9
Characteristics of Competing Lower-Skilled U.S. Workers
The H-2C program in S. 2611 would allow up to 200,000 guest workers into the
United States each year. These workers would compete with U.S. workers and,
eventually, with previously admitted H-2C workers. The language in S. 2611 would
allow employers to hire skilled, semi-skilled, or unskilled workers. However, the
kinds of jobs filled under the program may be similar to the kinds of jobs filled under
an existing (H-2B) program, which is used mainly to hire lower-skilled workers.10
Also, S. 2611 includes a provision that would prevent employers from hiring H-2C
workers in areas with high unemployment among unskilled workers. Thus, the rest
of this report focuses on the potential labor market effects of the proposed H-2C
program on competing lower-skilled workers. This section of the report follows S.
2611 and defines lower-skilled workers as persons with a high school education or
less. The definition of unskilled workers does not include agricultural workers (i.e.,
because the H-2C program in S. 2611 would not apply to agricultural workers).
This section compares three groups of U.S. workers:

! the total civilian labor force;11
! all lower-skilled workers; and
! lower-skilled, foreign-born workers (a subset of all lower-skilled
workers).
The description of U.S. workers is based on data from the Current Population
Survey (CPS). The CPS is a monthly survey of about 55,500 households conducted
by the U.S. Census Bureau for BLS.12 In the CPS, persons with a high school
education include persons with either a diploma or GED (i.e., persons who have
passed General Educational Development tests). See Appendix A for more
information on the CPS.
9 Congressional Budget Office, S. 2611: Comprehensive Immigration Reform Act of 2006,
Aug. 18, 2006, pp. 4-7, 22.
10 Under the H-2B program, employers may hire temporary nonagricultural workers.
Currently, the H-2B program is capped at 66,000 visas annually. The requirements for the
proposed H-2C visa would not be same as the requirements for the H-2B visa. For more
information on the H-2B program, see CRS Report RL32044, Immigration: Policy
Considerations Related to Guest Worker Programs
.
11 Persons who are in the labor force are either working or actively looking for work.
12 In this report, foreign-born persons include both citizens and noncitizens of the United
States. The CPS does not ask noncitizens if they are legal permanent residents,
nonimmigrants who are in the United States temporarily (e.g., guest workers), or whether
they are in the country without authorization. Therefore, in this report, the definition of
foreign-born persons includes legal immigrants, legal nonimmigrants, and unauthorized
aliens.

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Table 1 shows that an increased supply of foreign-born, lower-skilled workers
may have the greatest impact on young, native-born minority men and on foreign-
born minority men in their early working years. The unemployment rate among
young, native-born minority men tends to be higher than among similar nonminority
men.13 Foreign-born minority men in their early working years tend to earn less than
similar native-born workers.14

All Lower-Skilled Workers Compared to the Total Civilian Labor
Force. In 2005, lower-skilled U.S. workers were mainly white (81.1%), non-
Hispanic (79.7%) males (56.9%) under the age of 45 (62.7%). However, compared
to the total civilian labor force, a disproportionate number of lower-skilled workers
were black or Hispanic (13.5% and 20.3%, respectively), between the ages of 16 and
24 (19.7%), and male (56.9%).15
Foreign-Born, Lower-Skilled Workers Compared to All Lower-
Skilled Workers. Some research suggests that new immigrants may compete
mainly with prior immigrants.16 Therefore, this section compares foreign-born,
lower-skilled workers to all lower-skilled workers. A disproportionate number of
lower-skilled workers are foreign-born. In 2005, foreign-born, lower-skilled workers
accounted for 18.6% of all lower-skilled workers. By comparison, foreign-born
workers with more than a high school education accounted for 11.6% of all workers
with more than a high school education.17 Compared to all lower-skilled workers,
foreign-born, lower-skilled workers were disproportionately nonwhite (23.0%),
Hispanic (68.0%), between the ages of 25 and 44 (55.2%), and male (63.8%).
13 In 2005, the unemployment rate among native-born, lower-skilled minority men (either
black or Hispanic) between the ages of 16 and 24 was 8.5%. Among similar nonminority
men, the unemployment rate was 3.9%. Calculated by CRS from the monthly Current
Population Survey (CPS).
14 In 2005, foreign-born, lower-skilled minority men (either black or Hispanic) between the
ages of 25 and 44 had median weekly earnings of $440. Similar native-born men had
median weekly earnings of $508. Calculated by CRS from the monthly Current Population
Survey (CPS).
15 When answering the question about race in the CPS survey, respondents are allowed to
choose more than one race. This report follows BLS practice and only counts blacks and
whites who selected one race category. Hispanic persons may be of any race. The
comparisons discussed in the text of this report are significant at the 95% confidence level.
See Appendix A for a discussion of confidence levels.
16 One reason why new immigrants may have a greater effect on the wages and employment
of earlier immigrants is that many new immigrants move to areas where there are large
concentrations of immigrants. James P. Smith and Barry Edmonston, eds., The New
Americans: Economic, Demographic, and Fiscal Effects of Immigration
, Washington:
National Academy Press, 1997, pp. 223-224.
17 In 2005, 11.7 million of 62.6 million lower-skilled nonagricultural workers were foreign
born; 10.0 million of 85.7 million nonagricultural workers with more than a high school
education were foreign-born.

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Table 1. Demographic Characteristics of the U.S. Labor Force
in 2005, by Type
Number
Characteristic
Percent
(in 1,000s)
Gender
Total civilian labor force
Male
80,033
53.6%
Female
69,288
46.4%
Total
149,320
100.0%
All lower-skilled, nonagricultural workers
Male
35,619
56.9%
Female
26,944
43.1%
Total
62,563
100.0%
Foreign-born, lower-skilled nonagricultural workers
Male
7,441
63.8%
Female
4,225
36.2%
Total
11,666
100.0%
Race
Total civilian labor force
White Only
122,291
81.9%
Black Only
17,013
11.4%
Other
10,017
6.7%
Total
149,320
100.0%
All lower-skilled nonagricultural workers
White Only
50,745
81.1%
Black Only
8,428
13.5%
Other
3,390
5.4%
Total
62,563
100.0%
Foreign-born, lower-skilled nonagricultural workers
White Only
8,984
77.0%
Black Only
976
8.4%
Other
1,706
14.6%
Total
11,666
100.0%
Hispanic Origin
Total civilian labor force
Hispanic
19,824
13.3%
Non-Hispanic
129,497
86.7%
Total
149,320
100.0%
All lower-skilled nonagricultural workers
Hispanic
12,725
20.3%
Non-Hispanic
49,839
79.7%
Total
62,563
100.0%
Foreign-born, lower-skilled nonagricultural workers
Hispanic
7,937
68.0%
Non-Hispanic
3,728
32.0%
Total
11,666
100.0%

CRS-7
Number
Characteristic
Percent
(in 1,000s)
Age
Total civilian labor force
16-24
22,290
14.9%
25-34
32,341
21.7%
35-44
36,030
24.1%
45-54
34,402
23.0%
55-64
18,980
12.7%
65 and over
5,278
3.5%
Total
149,320
100.0%
All lower-skilled nonagricultural workers
16-24
12,331
19.7%
25-34
12,466
19.9%
35-44
14,465
23.1%
45-54
13,483
21.6%
55-64
7,293
11.7%
65 and over
2,525
4.0%
Total
62,563
100.0%
Foreign-born, lower-skilled nonagricultural workers
16-24
1,635
14.0%
25-34
3,252
27.9%
35-44
3,180
27.3%
45-54
2,222
19.1%
55-64
1,101
9.4%
65 and over
275
2.4%
Total
11,666
100.0%
Source: Calculated by the Congressional Research Service (CRS) from the monthly Current
Population Survey (CPS).
Notes: Estimates are for persons age 16 and older and in the civilian labor force. Lower-skilled
workers are persons with no more than a high school education. Employment estimates of lower-
skilled workers are for nonagricultural persons. Estimates are monthly averages for calendar year
2005. Details may not add to totals because of rounding.
High School Dropouts Compared to All Persons With No More than
A High School Education. Analysts often compare workers who have not
completed high school (i.e., who do not have a diploma or GED) with workers who
have no more than a high school education. Table B1 in Appendix B is similar to
Table 1, except it compares the civilian labor force to nonagricultural workers
without a high school education.
Compared to all lower-skilled workers (from Table 1), more persons without
a high school education (from Table B1) were male (60.7% vs. 56.9%), Hispanic
(37.9% vs. 20.3%), and under the age of 25 (31.7% vs. 19.7%). Over half of foreign-
born nonagricultural workers with no more than a high school education had not
finished high school.

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Occupations. Column 4 of Table 2 shows that, in 2005, more than half
(57.3%) of foreign-born, lower-skilled nonagricultural workers were employed in
four major occupations: construction, production, building and grounds cleaning, and
food services. In construction, the largest number of workers were employed as
laborers, carpenters, painters, roofers, drywall installers, and carpet installers. In
production occupations, the largest number of workers were employed as assemblers;
metal and plastic workers; sewing machine operators; packaging machine operators;
and meat, poultry, and fish processing workers.

Table 2. Employment of Lower-Skilled, Foreign-Born Workers
in 2005, by Occupation
Number
Percent
(1,000s)
Foreign-Born
All Lower- Foreign-Born, Workers as a Foreign-Born
Occupation
Skilled
Lower-Skilled Percent of All Workers by
Workers
Workers
Lower-Skilled Occupation
(1)
(2)
Workers
(4)
(3)
Construction and extraction
7,117
2,071
29.1%
17.8%
Production
6,963
1,750
25.1%
15.1%
Building and grounds cleaning and
maintenance 4,315
1,522
35.3%
13.1%
Food preparation and serving related
5,304
1,315
24.8%
11.3%
Transportation and material moving
6,448
1,170
18.1%
10.1%
Sales and related
7,247
925
12.8%
8.0%
Office and administrative support
8,796
822
9.3%
7.1%
Personal care and service
2,511
484
19.3%
4.2%
Installation, maintenance, and repair
3,090
455
14.7%
3.9%
Management occupations
3,510
349
9.9%
3.0%
Healthcare support occupations
1,667
297
17.8%
2.6%
Education, training, and library
817
77
9.5%
0.7%
Protective service
1,087
75
6.9%
0.6%
Healthcare practitioners and technical
614
67
10.9%
0.6%
Business and financial operations
895
63
7.1%
0.5%
Arts, design, entertainment, sports,
and media
537
62
11.5%
0.5%
Community and social services
248
37
15.1%
0.3%
Architecture and engineering
318
24
7.7%
0.2%
Computer and mathematical
268
23
8.7%
0.2%
Life, physical, and social science
116
11
9.8%
0.1%
Legal
115
6
5.2%
0.1%
Total
61,985
11,605
18.7%
100.0%
Source: Calculated by the Congressional Research Service (CRS) from the monthly Current
Population Survey (CPS).
Notes: Estimates are for persons age 16 and older and in the civilian labor force. Lower-skilled
workers are persons with no more than a high school education. Employment estimates of lower-
skilled workers are for nonagricultural persons. Total employment in Table 2 is less than total
employment in Table 1 because some persons did not report an occupation (e.g., they may have been
in the labor force but unemployed). Estimates are monthly averages for calendar year 2005. Details
may not add to totals because of rounding.

CRS-9
Column 3 of Table 2 shows that, in the four occupations where over half of
foreign-born, lower-skilled workers were employed, one-fourth or more of the lower-
skilled workers were foreign-born. In building and grounds cleaning occupations,
35.3% of lower-skilled workers were foreign born. In construction, 29.1% of lower-
skilled workers were foreign born; in production, 25.1% of lower-skilled workers
were foreign born; and in food preparation and serving occupations, 24.8% of lower-
skilled workers were foreign born. If employers used the proposed H-2C program
to hire workers for these occupations, the impact on foreign-born workers may be
greater than if the program were used to hire workers for other occupations. If S.
2611 were enacted, some of the workers with whom newer H-2C workers may
compete could be H-2C workers admitted in previous years.
Table 3 shows that, according to BLS employment projections, from 2004 to
2014 employment will increase by 18.9 million jobs (from 145.6 million to 164.5
million, or 13.0%).18 In those occupations that employed foreign-born, lower-skilled
workers in 2005, employment is projected to increase by 17.7 million jobs (from
135.6 million to 153.4 million, or 13.1%). Employment is projected to increase in
all occupations, except production (reflecting a projected decline in manufacturing
employment). But the 17.7 million increase in new jobs is for all jobs, regardless of
the educational attainment of the person holding the job. BLS estimates that, from
2004 to 2014, 6.9 million jobs will be filled by persons with a high school education
or less (an increase from 68.5 million to 75.4 million, or 10.1%).19 The persons who
fill these jobs may be either native-born or foreign-born.
Projections of job growth do not take into account vacancies that may occur in
existing jobs. Employers may replace workers who change occupations or who leave
the labor force (e.g., to return to school, raise children, or retire). Therefore, the
number of job openings by occupation consists of the sum of the number of jobs
created or lost and the number of vacancies caused by workers who change
occupations or leave the labor force.20 According to BLS projections, from 2004 to
18 Every two years BLS publishes employment projections for the next 10 years. The
projections are made in a series of steps, beginning with estimates of the future size of the
labor force. Projections of the size of the labor force take into account population
projections by Census Bureau. The population projections include estimates of net
international migration. U.S. Department of Labor, Bureau of Labor Statistics,
“ E m p l o y m e n t P r o j e c t i o n s , ” B L S H a n d b o o k o f M e t h o d s , a t
[http://stats.bls.gov/opub/hom/pdf/homch13.pdf], pp. 123-126; Norman C. Saunders, “A
Summary of BLS Projections to 2014,” Monthly Labor Review, v. 128, Nov. 2005, available
at [http://stats.bls.gov/opub/mlr/2005/11/art1full.pdf], pp. 6-7. Mitra Toossi, “Labor Force
Projections to 2014: Retiring Boomers,” Monthly Labor Review, v. 128, Nov. 2005,
available at [http://stats.bls.gov/opub/mlr/2005/11/art3full.pdf], p. 27.
19 Daniel E. Hecker, “Occupational Employment Projections to 2014,” Monthly Labor
Review
, vol. 128, Nov. 2005, at [http://stats.bls.gov/opub/mlr/2005/11/art5full.pdf], pp. 71,
79-80.
20 For information on “replacement needs,” see chapter 5 in Bureau of Labor Statistics, U.S.
Department of Labor, Occupational Projections and Training Data, available at
[http://www.bls.gov/emp/optd/home.htm].

CRS-10
2014, there will be 24.5 million job openings in occupations filled by persons with
no more than a high school education.21 The proposed H-2C program could allow
as many as 200,000 foreign workers into the United States annually. The H-2C visa
would be effective for an initial period of three years, with one three-year extension.
Table 3. BLS Employment Projections, 2004-2014,
by Occupation
Projected Employment
(in 1,000s)
Occupation
Change,
Job
2004
2014
2004-2014 Openingsa
All jobs
Construction and extraction
7,666
8,597
931
2,439
Production
10,260
10,169
-91
2,811
Building and grounds cleaning and maintenance
5,582
6,530
948
2,062
Food preparation and serving related
10,739
12,453
1,714
5,981
Transportation and material moving
10,249
11,365
1,116
3,509
Sales and related occupations
13,803
15,082
1,279
5,890
Office and administrative support
21,149
22,454
1,304
6,803
Personal care and service
4,721
5,713
991
2,121
Installation, maintenance, and repair
5,683
6,335
652
1,963
Management
8,666
9,639
974
2,618
Healthcare support
3,092
4,149
1,057
1,540
Education, training, and library
7,992
9,589
1,596
3,242
Protective service
2,999
3,419
420
1,258
Healthcare practitioners and technical
6,015
7,562
1,548
2,706
Business and financial operations
5,736
6,831
1,095
2,105
Arts, design, entertainment, sports, and media
2,112
2,425
313
699
Community and social services
2,317
2,800
483
928
Architecture and engineering
2,360
2,649
289
809
Computer and mathematical
2,410
3,186
775
1,097
Life, physical, and social science
902
1,046
144
354
Legal
1,173
1,363
190
326
Total
135,627
153,355
17,714
51,544
Jobs filled by lower-skilled workers
68,506
75,424
6,919
24,518
Total Civilian Labor Force
145,612
164,540
18,928
54,680
Sources: U.S. Department of Labor, Bureau of Labor Statistics, Employment by Occupation, 2004
and Projected 2014
, at [http://stats.bls.gov/emp/emptabapp.htm].
a. The number of job openings consists of the sum of the number of jobs created or lost and the
number of vacancies caused by workers who change occupations or leave the labor force.
21 The 24.5 million projection accounts for 44.8% of all job openings during the 10-year
period. One reason for the large number of job openings in occupations filled by persons
with a high school education or less is that employee turnover in lower-skilled jobs tends
to be greater than in jobs requiring more education.

CRS-11
Within six years, there could be as many as 1.2 million H-2C guest workers in
the United States. Persons who receive an H-2C visa could adjust to permanent
status and become U.S. citizens.22 If most of the annual 200,000 H-2C visas were
issued to lower-skilled workers, they could fill up to 8% of the projected job
openings in occupations requiring a high school education or less.
Earnings. Lower-skilled workers generally earn less than more skilled
workers. In 2005, foreign-born, lower-skilled workers had median weekly earnings
of $400, before taxes and other deductions. This amount compares to median weekly
earnings of $576 for all workers and $438 a week for all lower-skilled workers.
These estimates include both full-time and part-time workers.23
Research on the Effect of Immigration on Earnings. Researchers do
not agree on the effect of immigration on earnings.24 According to George Borjas,
between 1979 and 1995, immigration of unskilled workers (defined as high school
dropouts) reduced the wages of all high school dropouts by five percentage points
relative to the wages of all other workers.25 David Card, on the other hand, has
concluded that an increased supply of less skilled immigrants (also defined as high
school dropouts) has had little impact on the wages of dropouts relative to the wages
of high school graduates. According to Card, the main reason for this finding is that
industries change their methods of production to employ the increased supply of less
skilled foreign workers.26
22 Because S. 2611 included provisions intended to improve border security and increase
enforcement of immigration law, some H-2C guest workers may be substitutes for
unauthorized workers.
23 Calculated by CRS from the monthly Current Population Survey (CPS).
24 For a review of research on the labor market effects of immigration on U.S. workers, see
CRS Report 95-408, Immigration: The Effects on Native-Born Workers, by Linda Levine;
and Congressional Budget Office, The Role of Immigrants in the U.S. Labor Market, Nov.
2005, pp. 19-24.
25 George J. Borjas, Heaven’s Door: Immigration Policy and the American Economy,
Princeton: Princeton University Press, 2001, pp. 82-83.
26 According to Card, between 1979 and 2001, the wage gap between high school graduates
and dropouts remained relatively steady, but the gap between college and high school
graduates increased. David Card, “Is the New Immigration Really So Bad?” The Economic
Journal
, v. 115, Nov. 2005, pp. F307-F315, F321. Also see Ethan Lewis, Local Open
Economies Within the U.S.: How Do Industries Respond to Immigration?
Working Paper
No. 04-1, Federal Reserve Bank of Philadelphia, available at [http://www.phil.frb.org], pp.
21-23.
If an increased supply of lower-skilled workers does not affect the relative wages of workers
in different skill groups, it could nevertheless change the distribution of earnings if the
relative number of workers in different skill groups changes. For example, an increase in
the relative number of lower paid (or higher paid) workers could increase earnings
inequality.

CRS-12
Economic Framework For Understanding the Potential
Labor Market Effects of a New Guest Worker Program

The potential labor market effects of a new guest worker program can be
examined from different perspectives: (a) the initial effect of an increased supply of
foreign workers on the wages and employment of competing U.S. workers; (b) the
long-run effect of an increased supply of foreign workers, as U.S. workers and
employers adjust to the initial change in wages and employment; and (c) the effects
that take place over time as other changes (social, economic, and demographic)
occur.

Initially, an increased supply of lower-skilled foreign workers can be expected
to lower the relative wages of lower-skilled U.S workers. In response to the initial
change in wages, employers may hire more lower-skilled workers (because they are
relatively cheaper) and fewer skilled workers (because they are relatively more
expensive). Some employers and workers may move to areas where there are better
investment and employment opportunities. Other factors may also affect
employment and wages; for example, changes in technology, foreign trade, saving
and investment, education and training, and demographic changes.
The effects of a guest worker program may also depend on why U.S. workers
are not available to meet employer demand. Thus, the effects of a guest worker
program would likely differ if employer demand is for seasonal workers, for workers
at full employment, or for workers with skills that are not available in local labor
markets. Employers may be able to fill jobs by offering higher wages. But, at full
employment, higher wages may cause inflation without increasing employment. If
there is a mismatch between the skills demanded by employers and the skills
available, vacancies could be filled by training workers. But worker training can take
time. Qualified workers may not be available soon enough to meet employer
demand.
Economic Analysis. The different perspectives for analyzing the labor
market effects of a guest worker program can be described using standard economic
concepts.
Short-Term and Longer-Term Effects. Economists distinguish between
the short-term and the long-term effects of an increased supply of workers. For an
employer, the common definition of the short-term is a period during which the
quantity of at least one input is fixed and cannot be changed. It is generally assumed
that the fixed input is the stock of capital goods (i.e., buildings and equipment and
associated technology). If the stock of capital is fixed, in the short-term a firm can

CRS-13
only change the quantity of variable factors, principally labor.27 In the long-term, a
firm can change the quantity of both fixed and variable inputs.
Scale Effect. For employers, the stock of capital goods is generally fixed in
the short run. If there is a change in the price of labor relative to the price of capital
or a change in the relative wages of workers with different skills, the scale of
production may change. In the short run, an increased supply of workers can be
expected to lower the wages of competing workers.28 Therefore, if employers used
the H-2C program to hire lower-skilled workers, in the short run, the wages of
competing U.S. workers could be expected to fall relative to the wages of other
workers.29 At the same time, relative wages may rise for workers whose skills are
complements (e.g., supervisors) to the skills of lower-skilled workers.
Substitution Effect. In the long run, employers can change the quantities of
both fixed and variable inputs. In response to a change in the relative prices of
inputs, employers may use relatively more of the factor that has fallen in price.
Holding output constant, employers may substitute the lower-priced factor for other
inputs. Therefore, if the H-2C program increased the supply of lower-skilled
workers, employers may substitute less-skilled labor for both skilled labor and
capital. Employers may hire more lower-skilled workers and fewer skilled workers.
Therefore, in the short run, the wages of unskilled workers may fall relative to the
wages of skilled workers (the scale effect). But, in the long run, employers may
adopt more labor-intensive production methods (the substitution effect). If so, in the
long run, the initial (i.e., short-run) widening of the wage gap between skilled and
unskilled workers may narrow.
In the long run, both labor and capital are mobile. An increased supply of
foreign workers in one geographic area may affect investment decisions and the
behavior of other workers. For instance, employers may move their businesses to
where there is a greater supply of labor. Workers may move to where there is a
greater demand for labor. Thus, an increased supply of workers in one area of the
country may affect employment and wages throughout the economy.
Social, Economic, and Demographic Changes. The scale and substitution
effects of employer demand for labor are useful in explaining how an increased
supply of lower-skilled workers may affect employment and relative wages in the
short run and long run. But the scale effect holds the stock of capital goods constant
27 Because labor consists of both variable and fixed costs, it is sometimes called a quasi-
fixed factor of production. Fixed labor costs vary with the number of workers employed,
and include hiring and training costs, certain payroll taxes, and fringe benefits. Variable
costs vary with the number of hours worked, and consist mainly of wages. Walter Y. Oi,
“Labor as a Quasi-Fixed Factor,” Journal of Political Economy, v. 70, Dec. 1962, pp. 538-
539; Daniel S. Hamermesh, Labor Demand, Princeton, NJ: Princeton University Press,
1993, pp. 44-48; and Reynolds et al., Labor Economics and Labor Relations, pp. 94-95.
28 The wages of competing workers may not fall in absolute terms, but they can be expected
to fall relative to the wages of other workers.
29 For an explanation of how an increase in labor supply may affect wages and employment,
see CRS Report 95-408, Immigration: The Effects on Native-Born Workers.

CRS-14
and the substitution effect holds output constant. Over time, other changes may make
it difficult to identify the effects of an increased supply of lower-skilled workers. For
example, the size and composition of the domestic labor force may change. The
work force may become younger or older. More U.S. workers may finish high school
or go to college. Savings and investment may cause the stock of capital,
employment, and output to grow. Changes in technology, consumer preferences, or
trade may affect the demand for workers with different skills.30 Some changes may
be due, in part, to an increased supply of foreign workers. For example, because of
an increased supply of lower-skilled foreign workers, some U.S. workers may get
more education and training; others may leave the labor force. An increased supply
of lower-skilled foreign workers may also affect the amount, kind, and location of
investment as well as the kinds of technology adopted.
The Availability of U.S. Workers. The labor market effects of a new guest
worker program may also depend on why U.S. workers are not available to meet
employer demand.
Seasonal Demand. Employers may need workers to meet seasonal demand.
An adequate supply of qualified U.S. workers may be available among unemployed
workers or among persons willing to enter the labor force in response to a demand
for temporary workers. Under the proposed H-2C program, an employer would have
to pay a foreign worker the actual wage paid to other workers for the same kind of
work and similar experience or the prevailing wage, whichever is greater. But, in
local labor markets, an adequate supply of workers may not be available at these
wages. Workers may be available from outside the area, but they may not be willing
to travel or relocate for a temporary job. Workers with permanent jobs may not be
willing to leave those jobs for a temporary job. Thus, a guest worker program may
help employers meet seasonal demand by providing a temporary supply of workers.
On the other hand, the availability of guest workers may discourage employers from
raising wages to recruit U.S. workers. A guest worker program may also discourage
employers from adopting different production methods or introducing new
technologies that could reduce the demand for seasonal workers.
A Geographic Mismatch Between the Skills Demanded and Skills
Supplied. In some labor markets, employers may not be able to fill openings if the
skills that are available locally do not match the skills that employers need.31 Foreign
workers may help meet employer demand if qualified U.S. workers are not available
at the wages paid to other workers for the same kind of work or at the prevailing
wage. At higher wages, employers may be able to recruit qualified workers from
outside the local labor market. Alternatively, local workers could be trained to
perform the available work. But training can take time, depending on the kinds of
skills needed. Training may, however, be a longer-term solution to local labor
shortages. Qualified U.S. workers could also be attracted to an area by higher wages.
30 Technological change consists of improved equipment, the introduction of new products,
and improved methods of production, transportation, and communication.
31 When there is unemployment because of a mismatch in a labor market between the skills
available and the skills demanded, unemployment is called structural unemployment.

CRS-15
Employers could also relocate to an area where there is an adequate supply of
qualified workers.
Demand at Full Employment. At full employment (whether for seasonal or
year-round work), employers may only be able to hire qualified U.S. workers by
raising wages and hiring workers away from other employers.32 But higher wages
may cause inflation. Therefore, at full employment, foreign workers may help meet
employer demand for labor and help curb inflation. Because H-2C visas would be
effective for three years (and renewable for another three years), the economy may
not be at full employment when the visas expire. But without the H-2C program,
some employers could potentially relocate or outsource work to a country where there
is an adequate supply of labor.
Effects of the 9% Area Unemployment Trigger
S. 2611 included a provision that would not allow employers to hire H-2C
workers if the area unemployment rate for unskilled workers averages more than 9%
for the previous six months. The trigger would not affect the overall limit of 200,000
H-2C visas, which would be available to the rest of the country.
Before hiring an H-2C worker, employers would first have to try to recruit and
hire U.S. workers. In high unemployment areas, the 9% trigger would restrict the
supply of H-2C workers. Thus, in these areas, the potential labor market effects of
the H-2C program may depend on whether U.S. workers are available to meet
employer demand.
In high unemployment areas, employers may be able to hire unemployed
workers, whether at the same wage paid to other workers for the same kind of work
or at a higher wage. However, if employers are not able to hire qualified U.S.
workers, it may be because there is a mismatch in the area between the skills some
employers demand and the skills available. If there is a mismatch, employers would
not be allowed to hire H-2C workers. U.S. workers could be trained to fill the
demand or they could be recruited from outside the local area. Employers could also
alter their method of production to reduce their need for skills that are not available
or they could move to where the skills are available and the unemployment rate is 9%
or lower.
Table C1 in Appendix C shows those areas of the country that may have been
affected by the 9% unemployment trigger if it had been in effect in 2005. The
unemployment rates shown in the table are based on the monthly CPS. If S. 2611
32 At full employment, there are typically persons who are between jobs (e.g., because they
have quit or been laid off) or persons who have entered the labor force and are looking for
work. Economists call this frictional unemployment.
Full employment is commonly defined as the lowest rate of unemployment that is consistent
with stable prices. This rate may vary over time. CRS Report RL33734, Economic Growth,
Inflation, and Unemployment: Limits to Economic Policy
, by Brian Cashell; and CRS
Report RL32274, A Changing Natural Rate of Unemployment: Policy Issues, by Marc
Labonte.

CRS-16
were enacted, BLS estimates of the unskilled unemployment rate may be more
precise than those shown. Column 5 shows the confidence intervals for the
unemployment rates for lower-skilled workers (in column 4). The confidence
intervals show the lower and upper bounds of the estimated unemployment rates.
(See Appendix A for a discussion of confidence levels.) Table C1 follows the
language in S. 2611, and includes agricultural workers in the estimates of the
unskilled unemployment rate.
Table C1 indicates that if the 9% trigger had been in effect in 2005, visas for
H-2C guest workers would not have been issued in approximately 65 Metropolitan
Statistical Area (MSAs). The labor force in these 65 MSAs accounted for an
estimated 11.8% of the total labor force of 63.4 million lower-skilled workers. More
than half of the MSAs were in the Midwest and West. In the Midwest, 7 of the
MSAs were in Michigan, 4 in Ohio, and 3 in Illinois.33 In the West, 11 of the MSAs
were in California and 4 were in Washington. Texas had 4 MSAs where the
unemployment rate among unskilled workers was more than 9%.
As the national unemployment rate rises or falls, the number of MSAs that could
be affected by the 9% trigger may also rise or fall. In 2005, the national
unemployment rate was 5.1%. In 2004, unemployment was 5.5%.34 In 2004, BLS
adopted new MSA definitions issued by OMB. Therefore, the unemployment
estimates for 2005 in Table C1 can be compared with estimates for 2004. If the 9%
trigger had been in effect in 2004, employers would not have been able to hire H-2C
workers in approximately 63 MSAs. Compared with 2005, however, these MSAs
accounted for a larger share of the lower-skilled labor force: 13.2% of an estimated
labor force of 63.2 million. Eight of the MSAs were in California, 7 were in
Michigan, 5 in Texas, and 4 each were in Alabama, Colorado, Illinois, and Ohio.35
Conclusions
If the 110th Congress were to enact a guest worker program like the H-2C
program that was approved by the Senate in the 109th Congress, the initial labor
market effects may be different from the long-term effects. Initially, an increased
supply of foreign workers could be expected to lower the relative wages of
competing U.S. workers. If the program were used mainly to hire lower-skilled
foreign workers, the greatest impact may be on young, native-born minority men and
on foreign-born minority men in their early working years. In response to the initial
change in wages, employers may hire more lower-skilled workers and fewer skilled
workers. Some employers and workers may also move to where there are better
investment and employment opportunities.
33 Some MSAs cross state lines. One of the three MSAs in Illinois (the
Davenport-Moline-Rock Island MSA) includes parts of Iowa.
34 U.S. Department of Labor, Bureau of Labor Statistics, Labor Force Statistics from the
Current Population Survey
, available at [http://stats.bls.gov/cps/cpsaat1.pdf].
35 BLS adopted the new MSA definitions effective with the May 2004 CPS. Therefore, the
unemployment estimates by MSA for 2004 are averages for the eight months from May to
December 2004.

CRS-17
An increased supply of foreign workers would likely increase total U.S.
employment and output. But economists do not agree on the effect of immigration
on wages. Other factors — such as technological change, trade, saving and
interment, education and training, and demographic changes — may also affect
wages and make it difficult to identify the effects of an increased supply of foreign
workers.
The effects of a guest worker program may also depend on why U.S. workers
are not available to meet employer demand. The effects would likely differ if
employer demand is for seasonal workers, for more workers at full employment, or
for workers with skills that are not available in the local labor market. Employers
may be able to fill jobs by offering higher wages. But, at full employment, higher
wages may cause inflation without increasing employment. If there is a mismatch
between the skills demanded and the skills available, higher wages may not attract
an adequate supply of qualified workers.
The 9% trigger in S. 2611 may encourage employers to hire U.S. workers. But,
workers may not be available in local labor markets because there is a mismatch
between the skills demanded and the skills available.

CRS-18
Appendix A. Data and Methodology
Current Population Survey
The CPS is a household survey conducted by the U.S. Bureau of the Census for
the Bureau of Labor Statistics (BLS) of the U.S. Department of Labor. The monthly
CPS is the main source of labor force data for the nation, including estimates of the
monthly unemployment rate. The CPS collects a wide range of demographic, social,
and labor market information. Approximately 55,500 households are interviewed
each month, either in person or by phone.36
The CPS sample is representative of the civilian noninstitutional population; it
does not include persons on active duty in the Armed Forces or persons in institutions
such as nursing homes or correctional facilities. The survey includes civilian
noninstitutional persons living in group quarters. (Group quarters are living quarters
where residents share common facilities; examples include group homes, fraternities,
or sororities.)37
The labor force includes both employed and unemployed persons. Unemployed
persons are individuals who are not working but who are available and actively
looking for work. Employed persons are individuals who are working for a private
or public employer, are self-employed, or who work 15 hours or more per week as
unpaid workers on a family farm or business. Also counted as employed are persons
who are temporarily absent from work because of illness, bad weather, vacation, job
training, labor-management dispute, childcare problems, maternity or paternity leave,
or other family or personal reasons.38
Each month one-fourth of the CPS sample is asked questions about current
earnings. Weekly earnings are reported for wage and salary workers. Weekly
earnings consist of usual earnings before taxes and other deductions, and include tips,
overtime pay, and commissions usually received (at a person’s main job). The
monthly CPS does not collect information on the weekly earnings of persons who are
self-employed.
In this report, the data from the basic monthly CPS are annual monthly averages.
The data for each month for 2005 were combined to calculate annual monthly
averages.
Confidence Levels
Estimates based on survey responses from a sample of households have two
kinds of error: nonsampling and sampling. Examples of nonsampling error include
information that is misreported and errors made in processing collected information.
36 U.S. Department of Labor, Bureau of Labor Statistics, Current Population Survey:
Design and Methodology
, Technical Paper 63RV, Mar. 2002, p. J-8.
37 Ibid., pp. 1-1, 3-7 to 3-9, 5-4.
38 Ibid., pp. 5-3, 5-5.

CRS-19
Sampling error occurs because a sample, and not the entire population, of households
is surveyed. The difference between an estimate based on a sample of households
and the actual population value is known as sampling error. When using sample
data, researchers typically construct confidence intervals around population
estimates. Confidence intervals provide information about the accuracy of estimated
values. With a 95% confidence interval and repeated samples from a population,
95% of intervals will include the average estimate of a population characteristic. In
Table C1, the estimated unemployment rate for persons with no more than a high
school education is 7.4%. The confidence interval is between 7.2% and 7.6%.
Because the estimate of 7.4% is based on a sample (and not the entire population) of
persons with no more than a high school education, the actual unemployment rate
may be higher or lower than 7.4%. With a 95% confidence interval, it can be
concluded that the average unemployment rate estimated from repeated samples is
between 7.2% and 7.6%.

CRS-20
Appendix B. Demographic Characteristics of
Persons With Less than a High School Education
Immigration analysts often distinguish between persons with a high school
diploma or GED and persons who have not completed high school. Table B1 is
similar to Table 1 in the text but compares the total labor force with persons who
have not finished high school.
Table B1. Demographic Characteristics of the U.S. Labor Force
in 2005, by Type
Characteristic
Number (1000s)
Percent
Gender
Total civilian labor force
Male
80,033
53.6%
Female
69,288
46.4%
Total
149,320
100.0%
All nonagricultural persons with less than a high school education
Male
10,933
60.7%
Female
7,064
39.3%
Total
17,997
100.0%
Foreign-born nonagricultural persons with less than a high school education
Male
4,131
67.0%
Female
2,038
33.0%
Total
6,169
100.0%
Race
Total civilian labor force
White Only
122,291
81.9%
Black Only
17,013
11.4%
Other
10,017
6.7%
Total
149,320
100.0%
All nonagricultural persons with less than a high school education
White Only
14,566
80.9%
Black Only
2,293
12.7%
Other
1,138
6.3%
Total
17,997
100.0%
Foreign-born nonagricultural persons with less than a high school education
White Only
5,192
84.2%
Black Only
341
5.5%
Other
636
10.3%
Total
6,169
100.0%
Hispanic Origin
Total civilian labor force
Hispanic
19,824
13.3%
Non-Hispanic
129,497
86.7%
Total
149,320
100.0%
All nonagricultural persons with less than a high school education
Hispanic
6,824
37.9%
Non-Hispanic
11,173
62.1%
Total
17,997
100.0%
Foreign-born nonagricultural persons with less than a high school education
Hispanic
5,050
81.9%
Non-Hispanic
1,119
18.1%
Total
6,169
100.0%

CRS-21
Characteristic
Number (1000s)
Percent
Age
Total civilian labor force
16-24
22,290
14.9%
25-34
32,341
21.7%
35-44
36,030
24.1%
45-54
34,402
23.0%
55-64
18,980
12.7%
65 and over
5,278
3.5%
Total
149,320
100.0%
All nonagricultural persons with less than a high school education
16-24
5,696
31.7%
25-34
3,514
19.5%
35-44
3,494
19.4%
45-54
2,803
15.6%
55-64
1,716
9.5%
65 and over
773
4.3%
Total
17,997
100.0%
Foreign-born nonagricultural persons with less than a high school education
16-24
890
14.4%
25-34
1,788
29.0%
35-44
1,679
27.2%
45-54
1,133
18.4%
55-64
543
8.8%
65 and over
135
2.2%
Total
6,169
100.0%
Source: Calculated by the Congressional Research Service (CRS) from the monthly Current
Population Survey (CPS).
Notes: Data are for persons age 16 and over. Persons with less than a high school education are
nonagricultural persons who do not have a high school diploma or GED. Estimates are averages of
the monthly labor force for calendar year 2005. Details may not add to totals because of rounding.

CRS-22
Appendix C. Areas Potentially Affected by the 9%
Unemployment Trigger in S. 2611

Table C1. Labor Force Size and Unemployment Rates in 2005, by
Metropolitan Statistical Area and Level of Education
Civilian Labor Force
Total Civilian
With a High School
Confidence
Metropolitan
Labor Force
Education or Less
Intervals for
Statistical Areas
Number
Unemploy-
Number
Unemploy-
Column 4
(MSAs)
(1,000s)
ment Rate
(1,000s)
ment Rate
(5)
(1)
(2)
(3)
(4)
United States
149,320
5.1%
48,428
7.4%
(7.2%-7.6%)
Estimated Unemployment Rate Over 9.0%
(13.3%-
Lawton, OK
78
13.1%
40
22.6%
32.0%)
(12.6%-
Youngstown-Warren-Boardman, OH
250
11.4%
138
17.1%
21.6%)
(10.3%-
Yakima, WA
139
11.7%
76
16.2%
22.2%)
(10.5%-
Visalia-Porterville, CA
180
8.9%
84
16.1%
21.8%)
Muskegon-Norton Shores, MI
118
11.3%
53
15.6%
(8.6%-22.7%)
Lansing-East Lansing, MI
239
8.9%
83
15.4%
(9.8%-21.0%)
Toledo, OH (Ottawa County not in sample)
325
6.9%
106
14.7%
(9.9%-19.6%)
Durham, NC
211
7.5%
78
14.0%
(8.5%-19.6%)
Waterbury, CT
105
10.2%
54
13.5%
(6.9%-20.1%)
Kalamazoo-Portage, MI
151
8.0%
56
13.4%
(7.0%-19.7%)
South Bend-Mishawaka, IN-MI (Michigan
portion not identified)
167
8.4%
74
13.0%
(7.5%-18.5%)
Waco, TX
165
7.9%
76
12.9%
(7.5%-18.3%)
Albany, GA (Baker, Terrell, and Worth
Counties not in sample)
81
10.8%
46
12.9%
(5.9%-19.9%)
Bakersfield, CA
357
9.1%
191
12.7%
(9.3%-16.1%)
Cedar Rapids, IA (Benton and Jones
Counties not in sample)
97
7.4%
35
12.7%
(4.8%-20.6%)
Augusta-Richmond County, GA-SC
248
9.5%
117
12.6%
(8.3%-17.0%)
Tuscaloosa, AL (Greene and Hale Counties
not in sample)
111
7.1%
48
12.4%
(5.7%-19.1%)
Santa Barbara-Santa Maria-Goleta, CA
182
10.1%
101
12.2%
(7.6%-16.8%)
Racine, WI
133
7.9%
66
12.1%
(6.4%-17.7%)
Bremerton-Silverdale, WA
115
7.8%
35
12.1%
(4.4%-19.9%)
Fresno, CA
404
8.5%
173
12.0%
(8.5%-15.4%)
Bellingham, WA
118
5.4%
44
11.8%
(4.9%-18.7%)
Salinas, CA
186
7.6%
85
11.7%
(6.8%-16.6%)
Jackson, MS
267
5.5%
95
11.7%
(7.0%-16.3%)
Salem, OR
184
7.8%
83
11.7%
(6.7%-16.7%)
Dayton, OH
414
7.8%
210
11.6%
(8.5%-14.7%)
Pueblo, CO
108
8.6%
42
11.6%
(4.7%-18.5%)
Leominster-Fitchburg-Gardner, MA
111
6.5%
44
11.5%
(4.8%-18.3%)
Monroe, LA
226
7.9%
122
11.5%
(7.4%-15.5%)
Memphis, TN-MS-AR (Arkansas portion
not identified and Tunica County, MS not
611
7.6%
287
10.9%
(8.3%-13.5%)

CRS-23
Civilian Labor Force
Total Civilian
With a High School
Confidence
Metropolitan
Labor Force
Education or Less
Intervals for
Statistical Areas
Number
Unemploy-
Number
Unemploy-
Column 4
(MSAs)
(1,000s)
ment Rate
(1,000s)
ment Rate
(5)
(1)
(2)
(3)
(4)
in sample)
Trenton-Ewing, NJ
160
6.2%
83
10.7%
(5.9%-15.5%)
Rochester, NY
566
6.9%
232
10.7%
(7.9%-13.6%)
Detroit-Warren-Livonia, MI
2,312
7.1%
926
10.7%
(9.2%-12.1%)
Corpus Christi, TX
200
6.8%
100
10.7%
(6.3%-15.0%)
Evansville, IN-KY (Gibson County, IN and
Kentucky portion not in sample)
133
8.9%
63
10.5%
(5.0%-16.0%)
Winston-Salem, NC
152
7.4%
69
10.5%
(5.4%-15.7%)
Laredo, TX
105
7.4%
69
10.5%
(5.3%-15.8%)
Beaumont-Port Author, TX
164
6.7%
68
10.5%
(5.3%-15.7%)
Anniston-Oxford, AL
106
7.7%
58
10.5%
(4.9%-16.2%)
Oxnard-Thousand Oaks-Ventura, CA
415
6.4%
157
10.4%
(7.0%-13.9%)
Stockton, CA
266
6.9%
120
10.3%
(6.4%-14.2%)
Baton Rouge, LA
379
6.8%
184
10.3%
(7.2%-13.5%)
Vallejo-Fairfield, CA
225
5.4%
76
10.2%
(5.3%-15.1%)
Rockford, IL
197
5.9%
97
10.1%
(5.8%-14.4%)
Saginaw-Saginaw Township North, MI
97
7.4%
48
10.1%
(3.9%-16.2%)
Las Cruses, NM
104
6.3%
41
10.0%
(3.4%-16.5%)
Akron, OH
375
6.3%
180
9.9%
(6.8%-13.1%)
Lexington-Fayette, KY
246
5.1%
87
9.8%
(5.3%-14.3%)
Kansas City, MO-KS (Franklin, KS;
Leavenworth, KS; Linn, KS; Bates, MO;
and Caldwell, MO Counties not in sample)
1,048
6.3%
391
9.7%
(7.6%-11.8%)
Spokane, WA
239
5.6%
75
9.7%
(4.9%-14.5%)
Merced, CA
108
6.9%
49
9.6%
(3.6%-15.5%)
San Francisco-Oakland-Fremont, CA
2,370
5.6%
705
9.6%
(8.1%-11.2%)
Monroe, MI
89
6.8%
38
9.5%
(2.8%-16.2%)
Eugene-Springfield, OR
174
7.1%
66
9.5%
(4.4%-14.6%)
Davenport-Moline-Rock Island, IA-IL
183
5.2%
72
9.5%
(4.6%-14.4%)
Holland-Grand Haven, MI
120
5.1%
47
9.4%
(3.4%-15.4%)
Johnstown, PA
90
5.9%
47
9.4%
(3.4%-15.4%)
Kankakee-Bradley, IL
142
6.6%
67
9.2%
(4.2%-14.2%)
Madera, CA
95
7.3%
65
9.2%
(4.1%-14.3%)
Altoona, PA
66
6.7%
41
9.2%
(2.8%-15.6%)
Jacksonville, NC
62
7.5%
36
9.2%
(2.4%-16.0%)
Louisville, KY-IN (Washington, IN;
Henry, KY; Nelson, KY; Shelby, KY; and
Trimble, KY Counties not in sample)
545
6.8%
233
9.2%
(6.6%-11.9%)
Topeka, KS (Jackson and Jefferson
Counties not in sample)
130
5.0%
57
9.2%
(3.8%-14.6%)
Appleton,WI
104
6.6%
54
9.2%
(3.6%-14.7%)
Lake Charles, LA (Cameron Parish not in
sample)
124
6.1%
60
9.1%
(3.9%-14.4%)
Estimated Unemployment Rate 9.0% or Less
Wichita, KS
296
6.7%
129
9.0%
(5.4%-12.5%)
Huntsville, AL
185
4.1%
64
9.0%
(3.9%-14.0%)
Michigan City-La Porte, IN
91
6.9%
60
8.9%
(3.7%-14.1%)
Victoria, TX
181
6.7%
102
8.9%
(4.9%-12.9%)
Provo-Orem, UT (Juab County not in
189
5.0%
55
8.9%
(3.5%-14.3%)

CRS-24
Civilian Labor Force
Total Civilian
With a High School
Confidence
Metropolitan
Labor Force
Education or Less
Intervals for
Statistical Areas
Number
Unemploy-
Number
Unemploy-
Column 4
(MSAs)
(1,000s)
ment Rate
(1,000s)
ment Rate
(5)
(1)
(2)
(3)
(4)
sample)
Greenville-Spartanburg-Anderson, SC
88
5.4%
44
8.9%
(2.9%-15.0%)
Lynchburg, VA (Appomattox and Bedford
Counties and Bedford City not In sample)
104
7.6%
54
8.8%
(3.4%-14.3%)
Chicago-Naperville-Joliet, IN-IN-WI
(DeKalb, IL; Jasper, IN; and Kenosha, WI
Counties not in sample)
4,512
5.9%
1,631
8.8%
(7.8%-9.8%)
Greenville, SC (Laurens and Pickens
Counties not in sample)
198
4.9%
75
8.8%
(4.2%-13.4%)
Springfield, MA-CT (Connecticut portion
not identified)
329
6.0%
134
8.8%
(5.3%-12.2%)
New Orleans-Metairie-Kenner, LA
530
5.7%
214
8.8%
(6.0%-11.5%)
Buffalo-Niagara Falls, NY
577
6.4%
224
8.7%
(6.1%-11.4%)
Cleveland-Elyria-Mentor, OH
1,054
5.6%
439
8.7%
(6.8%-10.6%)
Baltimore-Towson, MD
1,340
4.9%
522
8.7%
(6.9%-10.4%)
Allentown-Bethlehem-Easton, PA-NJ
538
5.7%
251
8.6%
(6.1%-11.1%)
Kingston, NY
112
4.7%
48
8.6%
(2.9%-14.4%)
Spartanburg, SC
131
4.9%
57
8.5%
(3.3%-13.7%)
Anderson, IN
90
7.8%
57
8.5%
(3.3%-13.7%)
Santa Rosa-Petaluma, CA
243
5.6%
66
8.5%
(3.7%-13.4%)
Shreveport-Bossier City, LA (De Soto
Parish not in sample)
203
5.7%
87
8.4%
(4.2%-12.5%)
St. Louis, MO-IL (Calhoun County, IL not
in sample)
1,512
5.2%
597
8.4%
(6.8%-10.0%)
Omaha-Council Bluffs, NE-IA
437
4.7%
148
8.3%
(5.1%-11.5%)
Dallas-Fort Worth-Arlington, TX (Delta
and Hunt Counties not in sample)
3,223
5.8%
1,335
8.3%
(7.2%-9.3%)
Knoxville, TN (Anderson County not in
sample)
287
5.0%
111
8.2%
(4.5%-11.8%)
Mobile, AL
201
5.0%
81
8.2%
(3.9%-12.4%)
Waterloo-Cedar Falls, IA (Grundy County
not in sample)
99
5.2%
37
8.2%
(1.8%-14.6%)
San Antonio, TX
881
5.3%
408
8.0%
(6.1%-9.9%)
Tucson, AZ
400
7.4%
159
8.0%
(4.9%-11.0%)
Indianapolis, IN
881
5.3%
347
8.0%
(5.9%-10.0%)
Ann Arbor, MI
225
4.5%
52
8.0%
(2.7%-13.3%)
Scranton-Wilkes Barre, PA
288
5.5%
145
7.9%
(4.7%-11.0%)
Atlanta-Sandy Springs-Marietta, GA
(Haralson, Heard, Jasper, Meriwether and
Spalding Counties not in sample)
2,631
5.2%
979
7.9%
(6.7%-9.1%)
San Jose-Sunnyvale-Santa Clara, CA
1,038
5.2%
310
7.9%
(5.7%-10.0%)
Hartford-West Hartford-East Hartford, CT
622
4.8%
236
7.8%
(5.3%-10.2%)
Providence-Fall River-Warwick, MA-RI
690
5.2%
319
7.8%
(5.7%-10.0%)
Brownsville-Harlingen, TX
143
8.1%
95
7.8%
(3.9%-11.7%)
Johnson City, TN
104
5.0%
54
7.8%
(2.7%-12.9%)
Roanoke, VA (Craig and Franklin Counties
not in sample)
121
5.2%
57
7.7%
(2.7%-12.7%)
Riverside-San Bernardino, CA
1,636
6.0%
818
7.7%
(6.4%-9.0%)
Pittsburgh, PA
1,199
5.2%
500
7.7%
(6.0%-9.4%)
Colorado Springs, CO
287
6.5%
96
7.7%
(3.9%-11.5%)

CRS-25
Civilian Labor Force
Total Civilian
With a High School
Confidence
Metropolitan
Labor Force
Education or Less
Intervals for
Statistical Areas
Number
Unemploy-
Number
Unemploy-
Column 4
(MSAs)
(1,000s)
ment Rate
(1,000s)
ment Rate
(5)
(1)
(2)
(3)
(4)
Worcester, MA-CT (Connecticut portion
not identified)
242
6.2%
107
7.6%
(4.0%-11.2%)
Charlotte-Gastonia-Concord, NC-SC
(Anson County, NC not in sample)
891
5.5%
380
7.6%
(5.7%-9.5%)
Poughkeepsie-Newburgh-Middletown, NY
348
5.3%
131
7.6%
(4.4%-10.9%)
Boulder, CO
188
5.1%
57
7.6%
(2.6%-12.5%)
Salt Lake City, UT (Toole County not in
sample)
583
4.6%
225
7.6%
(5.1%-10.1%)
Olympia, WA
132
3.9%
38
7.6%
(1.6%-13.6%)
Myrtle Beach-Conway-North Myrtle
Beach, SC
110
6.7%
48
7.6%
(2.2%-13.0%)
Houston-Baytown-Sugar Land, TX
2,463
5.7%
1,155
7.5%
(6.4%-8.5%)
Seattle-Tacoma-Bellevue, WA
1,771
5.0%
540
7.5%
(5.9%-9.1%)
Dover, DE
80
5.0%
43
7.5%
(1.8%-13.2%)
Portland-Vancouver-Beaverton, OR-WA
(Yamhill County, OR not in sample)
1,139
5.2%
354
7.5%
(5.5%-9.4%)
Denver-Aurora, CO
1,320
4.8%
440
7.5%
(5.7%-9.3%)
Bridgeport-Stamford-Norwalk, CT
435
4.8%
143
7.5%
(4.4%-10.6%)
Fayetteville, NC
145
5.0%
63
7.4%
(2.8%-12.1%)
Jackson, MI
152
4.9%
65
7.4%
(2.8%-12.0%)
Bloomington, IN (Owen County not in
sample)
141
5.1%
59
7.4%
(2.6%-12.2%)
Milwaukee-Waukesha-West Allis, WI
820
4.6%
357
7.4%
(5.4%-9.4%)
Philadelphia-Camden-Wilmington, PA-NJ-
DE
2,801
4.8%
1,162
7.4%
(6.3%-8.4%)
Green Bay, WI (Oconto County not in
sample)
184
4.8%
85
7.3%
(3.3%-11.2%)
Flint, MI
173
4.8%
76
7.3%
(3.1%-11.5%)
Nashville-Davidson-Murfreesboro, TN
(Cannon, Hickman and Macon Counties
not in sample)
800
4.9%
342
7.3%
(5.3%-9.3%)
Boston-Cambridge-Quincy, MA-NH
2,411
4.6%
784
7.3%
(6.0%-8.6%)
Austin-Round Rock, TX
879
4.9%
290
7.2%
(5.0%-9.3%)
Norwich-New London, CT-RI (RI portion
recoded to Providence NECTA)
124
6.1%
59
7.1%
(2.4%-11.9%)
Wausau, WI
89
5.0%
48
7.0%
(1.8%-12.2%)
Sacramento — Arden-Arcade Roseville,
CA
1,027
5.0%
392
7.0%
(5.2%-8.9%)
New Haven, CT
308
4.6%
102
7.0%
(3.5%-10.6%)
Fort Collins-Loveland, CO
176
4.6%
54
7.0%
(2.1%-11.9%)
Canton-Massillon, OH
219
6.5%
122
6.9%
(3.7%-10.2%)
Longview, TX (Rusk and Upshur Counties
not in sample)
107
6.3%
43
6.9%
(1.4%-12.4%)
Grand Rapids-Muskegon-Holland, MI
144
4.7%
64
6.8%
(2.4%-11.2%)
Modesto, CA
261
4.1%
128
6.8%
(3.7%-10.0%)
Albuquerque, NM
424
5.2%
145
6.7%
(3.8%-9.7%)
Killeen-Temple-Fort Hood, TX
162
5.0%
88
6.6%
(2.9%-10.4%)
Des Moines, IA
311
3.9%
119
6.6%
(3.4%-9.8%)
Charleston-North Charleston, SC
292
4.3%
99
6.6%
(3.1%-10.2%)
Greensboro-High Point, NC
496
5.2%
221
6.6%
(4.3%-9.0%)

CRS-26
Civilian Labor Force
Total Civilian
With a High School
Confidence
Metropolitan
Labor Force
Education or Less
Intervals for
Statistical Areas
Number
Unemploy-
Number
Unemploy-
Column 4
(MSAs)
(1,000s)
ment Rate
(1,000s)
ment Rate
(5)
(1)
(2)
(3)
(4)
Raleigh-Cary, NC
626
3.6%
217
6.6%
(4.2%-9.0%)
Niles-Benton Harbor, MI
64
6.5%
35
6.6%
(0.7%-12.5%)
Columbus, OH (Morrow County not in
sample)
932
4.9%
361
6.5%
(4.7%-8.3%)
Madison, WI
346
3.3%
107
6.5%
(3.1%-9.8%)
Deltona-Daytona Beach-Ormond Beach,
FL
211
4.5%
87
6.5%
(2.8%-10.2%)
Pensacola-Ferry Pass-Brent, FL
201
4.7%
88
6.5%
(2.8%-10.2%)
Tulsa, OK (Okmulgee County not in
sample)
440
3.8%
170
6.5%
(3.8%-9.1%)
New York-Northern New Jersey-Long
Island, NY-NJ-PA (Pennsylvania portion
not in sample. White Plains central city
recoded to balance of metropolitan.)
9,171
4.7%
3,581
6.4%
(5.8%-7.0%)
Los Angeles-Long Beach-Santa Ana, CA
6,533
4.9%
2,671
6.4%
(5.7%-7.0%)
San Diego-Carlsbad-San Marcos, CA
1,449
3.5%
444
6.4%
(4.8%-8.1%)
Gulfport-Biloxi, MS
69
7.5%
37
6.4%
(0.7%-12.1%)
Minneapolis-St Paul-Bloomington, MN-
WI (Wisconsin portion not identified)
1,765
3.9%
554
6.4%
(4.9%-7.8%)
Oklahoma City, OK
676
3.7%
259
6.3%
(4.2%-8.4%)
Syracuse, NY
299
5.3%
125
6.3%
(3.2%-9.3%)
Savannah, GA
288
4.4%
141
6.3%
(3.5%-9.2%)
Richmond, VA (Cumberland County not in
sample)
656
4.8%
309
6.3%
(4.3%-8.2%)
Montgomery, AL
165
4.9%
77
6.2%
(2.3%-10.1%)
Orlando, FL
1,081
4.0%
457
6.2%
(4.6%-7.8%)
Champaign-Urbana, IL (Ford County not
in sample)
136
2.8%
47
6.2%
(1.2%-11.2%)
El Centro, CA
74
3.5%
37
6.2%
(0.6%-11.7%)
Fort Smith, AR-OK (Oklahoma portion not
in sample)
107
4.4%
54
6.2%
(1.6%-10.8%)
Grand Rapids-Wyoming, MI
415
4.8%
157
6.2%
(3.5%-8.9%)
La Crosse, WI (Houston County not in
sample)
121
2.7%
44
6.2%
(1.1%-11.3%)
El Paso, TX
324
5.2%
157
6.1%
(3.4%-8.8%)
Portland-South Portland, ME
202
3.5%
68
6.0%
(1.9%-10.0%)
Fayetteville- Springdale-Rogers, AR-MO
(Madison County, AR and Missouri
portion not in sample)
233
3.7%
99
6.0%
(2.7%-9.4%)
Birmingham-Hoover, AL
620
4.2%
249
5.9%
(3.8%-8.0%)
Ocala, FL
125
4.7%
66
5.8%
(1.7%-9.9%)
Boise City-Nampa, ID (Owyhee County
not in sample)
284
3.9%
114
5.8%
(2.7%-8.9%)
Tampa-St. Petersburg-Clearwater, FL
1,323
4.2%
536
5.7%
(4.3%-7.1%)
Fort Wayne, IN
200
5.5%
77
5.7%
(2.0%-9.5%)
Sioux Falls, SD
131
2.7%
51
5.6%
(1.1%-10.1%)
Panama City-Lynn Haven, FL
95
3.4%
46
5.6%
(0.8%-10.4%)
Chattanooga, TN-GA
254
3.5%
126
5.6%
(2.7%-8.5%)
Bend, OR
94
5.0%
45
5.5%
(0.7%-10.3%)
Phoenix-Mesa-Scottsdale, AZ
1,985
3.9%
812
5.5%
(4.4%-6.7%)

CRS-27
Civilian Labor Force
Total Civilian
With a High School
Confidence
Metropolitan
Labor Force
Education or Less
Intervals for
Statistical Areas
Number
Unemploy-
Number
Unemploy-
Column 4
(MSAs)
(1,000s)
ment Rate
(1,000s)
ment Rate
(5)
(1)
(2)
(3)
(4)
Fort Walton Beach-Crestview-Destin, FL
126
3.3%
54
5.5%
(1.1%-9.9%)
Reno-Sparks, NV
233
3.9%
96
5.4%
(2.2%-8.7%)
Hickory-Morgantown-Lenoir, NC
(Caldwell County not in sample)
139
4.8%
76
5.3%
(1.7%-8.9%)
Cincinnati-Middletown, OH-KY-IN
(Franklin County , IN not in sample;
Dearborn and Ohio Counties, IN not
identified)
1,071
4.2%
485
5.3%
(3.8%-6.7%)
Miami-Fort Lauderdale-Miami Beach, FL
2,612
3.9%
1,116
5.3%
(4.4%-6.3%)
Las Vegas-Paradise, NM
857
4.5%
444
5.3%
(3.8%-6.8%)
Binghamton, NY
111
5.8%
50
5.3%
(0.8%-9.8%)
Vineland-Millville-Bridgeton, NJ
98
4.0%
54
5.2%
(1.0%-9.5%)
Harrisburg-Carlisle, PA
299
4.0%
147
5.2%
(2.6%-7.8%)
Virginia Beach-Norfolk-Newport News,
VA-NC (North Carolina portion not
identified)
738
3.8%
295
5.0%
(3.2%-6.8%)
Jacksonville, FL
659
3.5%
269
5.0%
(3.1%-6.9%)
Columbus, GA-AL (Harris County, GA not
in sample)
123
3.9%
69
4.9%
(1.2%-8.5%)
Little Rock-North Little Rock, AR (Perry
County not in sample)
341
3.2%
153
4.8%
(2.4%-7.3%)
Honolulu, HI
455
3.0%
164
4.8%
(2.5%-7.2%)
York-Hanover, PA
224
3.0%
125
4.7%
(2.0%-7.3%)
Washington-Arlington-Alexandria, DC-
VA-MD-WV (West Virginia portion not
identified. Reston central city recoded to
balance of metropolitan)
3,012
2.8%
944
4.7%
(3.8%-5.7%)
Cape Coral-Fort Myers, FL
262
2.7%
122
4.7%
(2.0%-7.4%)
Charleston, WV (Clay County not in
sample)
158
3.9%
74
4.7%
(1.2%-8.1%)
Joplin, MO
129
3.2%
62
4.5%
(0.8%-8.2%)
Peoria, IL
175
4.5%
64
4.5%
(0.9%-8.2%)
Springfield, IL
106
2.7%
43
4.4%
(0.0%-8.8%)
Erie, PA
112
4.1%
65
4.2%
(0.7%-7.7%)
Albany-Schenectady-Troy, NY
476
2.6%
185
4.2%
(2.2%-6.3%)
Amarillo, TX (Armstrong and Carson
Counties not in sample)
123
2.6%
52
4.2%
(0.3%-8.1%)
Lafayette, LA
284
4.5%
159
4.2%
(1.9%-6.4%)
Janesville, WI
93
2.8%
51
4.2%
(0.3%-8.2%)
Port St. Lucie-Fort Pierce, FL
171
2.6%
90
4.1%
(1.1%-7.0%)
Harrisonburg, VA
112
2.4%
52
4.1%
(0.2%-8.0%)
Greeley, CO
123
3.0%
53
3.8%
(0.1%-7.4%)
Asheville, NC (Haywood and Henderson
Counties not in sample)
204
3.8%
80
3.7%
(0.7%-6.6%)
Midland, TX
116
2.4%
56
3.6%
(0.1%-7.1%)
Florence, AL
103
2.3%
55
3.6%
(0.0%-7.1%)
Ogden-Clearfield, UT
168
2.5%
78
3.6%
(0.6%-6.6%)
Springfield, MO (Dallas and Polk Counties
not in sample)
184
2.4%
76
3.5%
(0.5%-6.5%)
Atlantic City, NJ
151
3.7%
72
3.5%
(0.5%-6.5%)

CRS-28
Civilian Labor Force
Total Civilian
With a High School
Confidence
Metropolitan
Labor Force
Education or Less
Intervals for
Statistical Areas
Number
Unemploy-
Number
Unemploy-
Column 4
(MSAs)
(1,000s)
ment Rate
(1,000s)
ment Rate
(5)
(1)
(2)
(3)
(4)
Reading, PA
222
2.4%
130
3.5%
(1.2%-5.7%)
McAllen-Edinburg-Pharr, TX
263
2.9%
172
3.4%
(1.4%-5.3%)
Lancaster, PA
228
2.8%
129
3.4%
(1.2%-5.7%)
Lakeland-Winter Haven, FL
217
3.0%
125
3.4%
(1.1%-5.7%)
Columbia, SC
330
2.9%
136
3.4%
(1.2%-5.6%)
Utica-Rome, NY
150
4.7%
65
3.0%
(0.0%-6.0%)
Naples-Marco Island, FL
156
2.1%
80
2.9%
(0.3%-5.5%)
Palm Bay-Melbourne-Titusville, FL
322
1.6%
109
2.9%
(0.6%-5.1%)
Sarasota-Bradenton-Venice, FL
317
2.2%
150
2.7%
(0.8%-4.6%)
Source: Calculated by CRS from the monthly Current Population Survey (CPS).
Notes: Data are for persons age 16 and older and in the labor force. Confidence intervals were calculated at a 90%
level. See Appendix A for a description of confidence intervals. Following BLS practice, Table C1 does not show
estimates of the size of the labor force or the unemployment rate if the estimated size of the labor force is 35,000
persons or less. Estimates of unemployment for persons with a high school education or less are not shown if the
estimate is not statistically significant (i.e., if the lower bound of the confidence interval is less than zero).
Estimates are monthly averages for calendar year 2005. Details may not add to totals because of rounding.