**Basic Skills and Labor Market Success:**

**Findings from the VR Longitudinal Study**

by

Holly Schmidt-Davis, Research Triangle Institute

Harold Kay, Rehabilitation Services Administration

Becky J. Hayward, Research Triangle Institute

As noted in recent research on education and labor force participation,
completion of a postsecondary degree is a major contributor to a
person\'s subsequent success in the labor market (Boesel, 1998; Grubb,
1998). Access to postsecondary education and to the accommodations that
can facilitate completion of a course of study have historically been
problematic for youth with disabilities (Price-Ellingstad and Berry,
2000); this lack of access can limit the career prospects of individuals
with disabilities. Our current research indicates that educational
deficits at other levels can also have seriously deleterious effects on
the employment and earnings experiences of individuals with
disabilities. This research addresses the question: to what extent do
basic skills deficits limit employment or earnings potential among
individuals with disabilities, and what interventions can Vocational
Rehabilitation agencies use to ameliorate these deficits?

In this paper, we examine data from the Longitudinal Study of the
Vocational Rehabilitation (VR) Services Program, sponsored by the
Rehabilitation Services Administration (RSA); these data indicate that
basic skills deficits are a major deterrent to VR consumers ability to
achieve living earnings even when they succeed in entering competitive
employment as a result of VR services. These findings lead to our
recommendation that the state-federal VR program, with support from RSA,
explore strategies for improving the basic skills achievement among
consumers in need of such assistance. We suggest that services to
improve basic skills can facilitate entry into further education and
training and subsequently lead to improved employment and earnings among
a significant subset of individuals who enter VR services.

**Overview of the VR Longitudinal Study**

Commissioned by RSA and mandated by the Congress in the 1992
Rehabilitation Act Amendments, the Longitudinal Study of the VR Services
Program is a national impact evaluation that investigates the effects of
VR services on economic and other outcomes for individuals with
disabilities who receive such services. The study's design, reflecting
the typical service patterns of VR program participants, called for
repeated contacts with individuals over a three-year period to obtain
comprehensive information to support judgments about the benefits the VR
system provides to consumers and society. The findings contained in this
article come from two primary sources. First is information abstracted
from VR case files of study participants, including reading and
mathematics achievement levels where reported. Second is a series of
detailed interviews administered to all study participants at the time
of entry into the study and at annual intervals for a subsequent
three-year period. These interviews obtain information on work history,
functional status, vocational interests, attitudinal characteristics,
perspectives on the VR experience, and retention of earnings and
employment, as well as such other outcomes as independence and community
integration, over time.

The longitudinal study drew a nationally representative sample of over
8,000 respondents, including applicants for VR services (some of whom
were not accepted for services), VR consumers, and former VR consumers.
Weighted, this sample represents 1,001,870 individuals with disabilities
who applied for or received VR services.

Data from this study provide insight into the relationship between
educational experiences and employment outcomes. In this paper, we
consider the characteristics and experiences, including educational
experiences, of VR consumers who achieved a competitive employment
outcome at exit from VR. We are particularly interested in predicting
whether the earnings levels of these persons are sufficient to enable
them to achieve financial independence, as well as the interventions
that may improve the likelihood of earning a living wage. Here, we
define earnings greater than \$9.00 per hour as a living wage.

To examine this issue, we first describe the educational status of VR
consumers at entry to VR along dimensions of demographic and disability
characteristics. We then examine relationships between these
characteristics and earnings of consumers who obtain competitive
employment as a result of VR services, as well as relationships among
earnings, educational characteristics, measures of functional status,
and attitudes (e.g., self-esteem, internality) that may affect
employment success. Finally, we report findings on the relative
contribution of educational status and receipt of educational services
from VR to the earnings levels that consumers achieve as a result of VR.

**Study Findings**

We conducted three sets of analyses. In the first analyses, we examined
demographic characteristics and type and significance of disability by
educational status measures (grade level achievement in reading, grade
level achievement in math, and number of years of education consumers
have completed when they enter VR) and average earnings; results from
these analyses appear in Tables 1 and 2. Next, we looked at the
relationship of demographic, disability, attitudinal, and educational
factors to hourly earnings. For this analysis, we categorized hourly
earnings into four levels  up to \$5.00, between \$5.01 and \$7.00,
between \$7.01 and \$9.00, and greater than \$9.00. We focus on
differences between individuals who earn very low earnings (up to \$5.00
per hour) and those who earn a living wage (greater than \$9.00 per
hour). Tables 3 through 6 present these results. Finally, to explore
further important differences revealed in these tables, we present a
correlational analysis of selected factors and then a regression
analysis that predicts earnings levels from educational characteristics.

Overall, 78.4 percent of VR consumers who left VR with an employment
outcome entered competitive employment. Table 1 shows the average years
of education, reading and math achievement levels, and earnings at
closure by demographic characteristics. Table 2 contains average years
of education, reading and math achievement levels, and earnings at
closure by type and significance of disability.

As shown in Table 1, competitively employed consumers overall average
12.1 years of education, a grade level reading achievement of 8.5, a
grade level math achievement of 7.8, and hourly wages of \$7.56 (median
of \$6.25). While men have lower basic skills achievement levels than
women (8.1 versus 8.9 for reading, 7.6 versus 8.0 for math), they earn
substantially higher wages (\$7.91, with a median of \$6.50, for men,
versus \$7.18, with a median of \$6.00, for women). On average, white
consumers earn higher than average hourly wages (\$7.73; median of
\$6.45), while minority consumers earn lower than average (\$6.65;
median of \$5.96). Additionally, minority consumers average fewer years
of education (11.7 versus 12.2) and lower grade level achievement in
reading and math (7.0 versus 8.8 for reading achievement, 6.6 versus 8.1
for math achievement) than white consumers.

Earnings, years of education, and achievement levels are all higher at
higher age ranges through age 55, at which point they decrease slightly.
For example, competitively employed consumers 25 years or younger earn
an average \$5.97 (median of \$5.25) per hour compared to

**Table 1. Characteristics of Competitively Employed Consumers, by Race
and Age**

  -------------------- --------------- --------------- --------------- ------------- -------------
  Characteristic       **Percentage of **Reading       **Math          **Years of    **Earnings at
                       competitively   Achievement**   Achievement**   education**   closure**
                       employed                                                      
                       consumers**                                                   

  **Percentage         78.4%                                                         
  competitively                                                                      
  employed of all                                                                    
  consumers**                                                                        

  **Gender**                           ***Mean         ***Mean         ***Mean       ***Mean
                                       (Median)***     (Median)***     (Median)***   (Median)***

  Male                 52.8%           8.1 (8.0)       7.6 (7.0)       12.0 (12.0)   \$7.91
                                                                                     (\$6.50)

  Female               47.2%           8.9 (10.0)      8.0 (7.2)       12.2 (12.0)   \$7.18
                                                                                     (\$6.00)

  **Race/ethnicity**                                                                 

  White                85.2%           8.8 (9.7)       8.1 (7.5)       12.2 (12.0)   \$7.73
                                                                                     (\$6.45)

  Minority             14.8%           7.0 (7.0)       6.6 (6.0)       11.7 (12.0)   \$6.65
                                                                                     (\$5.96)

  **Age**                                                                            

  \<=25                14.5%           6.0 (5.1)       5.4 (5.2)       11.1 (11.0)   \$5.97
                                                                                     (\$5.25)

  26-35                25.5%           8.4 (9.0)       7.8 (7.0)       12.1 (12.0)   \$7.09
                                                                                     (\$6.00)

  36-45                29.6%           9.3 (11.0)      8.5 (8.0)       12.4 (12.0)   \$7.82
                                                                                     (\$7.00)

  46-55                20.5%           10.6 (12.0)     9.7 (10.0)      12.5 (12.0)   \$8.64
                                                                                     (\$7.00)

  \>55                 9.8%            9.2 (10.0)      8.5 (8.0)       11.7 (12.0)   \$8.09
                                                                                     (\$6.49)

  **Receipt of public                                                                
  benefits at entry**                                                                

  Yes                  28.8%           8.2 (8.0)       7.4 (7.0)       12.2 (12.0)   \$6.94
                                                                                     (\$5.98)

  No                   71.2%           8.6 (9.0)       8.0 (7.6)       12.1 (12.0)   \$7.82
                                                                                     (\$6.50)

  **All competitively  100.0%          8.5 (9.0)       7.8 (7.0)       12.1 (12.0)   \$7.56
  employed consumers**                                                               (\$6.25)
  -------------------- --------------- --------------- --------------- ------------- -------------

*Source: VR Longitudinal Study, November 1999*

\$8.64 (median of \$7.00) per hour for those 46 to 55 years old and
\$8.09 (median of \$6.49) for consumers over 55. The youngest consumers
average 11.1 years of education, a grade level reading achievement of
6.0 years, and a math achievement level of 5.4 years, while those aged
46 to 55 have a mean of 12.5 years of education, a mean reading
achievement level of 10.6, and a mean math achievement level of 9.7.
Individuals over 55 average 11.7 years of education, a grade level
achievement in reading of 9.2, and a math achievement level of 8.5.

Individuals who received public benefits (including SSI, SSDI, AFDC,
veteran's benefits, and other disability benefits) average lower reading
and math achievement levels (8.2 versus 8.6 for reading, 7.4 versus 8.0
for math) than other individuals, although their average years of
education are very similar (12.2 versus 12.1). Additionally, these
individuals earn much lower wages (\$6.94, with a median of \$5.98,
versus \$7.82, with a median of \$6.50).

As Table 2 indicates, individuals with physical disabilities form the
largest group of competitively employed consumers (40.2 percent); they
also earn higher hourly wages than average (\$7.76, with a median of
\$6.51) and have slightly more education (12.2) and higher grade levels
of reading and math achievement (10.0 for reading achievement, 9.1 for
math achievement) than the average. Those with mental retardation, on
the other hand, constitute only 7.4 percent of competitively employed
consumers, earn substantially less per hour (\$5.03; median of \$4.96),
are less well educated (mean of 11.1 years), and have very low reading
and math grade level achievement (3.9 for reading achievement, 4.0 for
math achievement). Consumers with learning disabilities (8.5 percent of
competitively employed consumers) also

**Table 2. Characteristics of Competitively Employed Consumers, by
Disability Type and Significance**

  -------------------- --------------- --------------- --------------- ------------- -------------
  **Characteristic**   **Percentage of **Reading       **Math          **Years of    **Earnings at
                       competitively   Achievement**   Achievement**   education**   closure**
                       employed                                                      
                       consumers**                                                   

  **Percentage         78.4%                                                         
  competitively                                                                      
  employed of all                                                                    
  consumers**                                                                        

  **Type of                            ***Mean         ***Mean         ***Mean       ***Mean
  disability**                         (Median)***     (Median)***     (Median)***   (Median)***

  Mental illness       18.0%           9.8 (11.5)      8.6 (8.8)       12.4 (12.0)   \$7.33
                                                                                     (\$6.24)

  Mental retardation   7.4%            3.9 (3.0)       4.0 (3.0)       11.1 (12.0)   \$5.03
                                                                                     (\$4.96)

  Learning disability  8.5%            6.5 (5.7)       6.1 (6.0)       11.3 (12.0)   \$6.52
                                                                                     (\$5.98)

  Sensory disability   16.7%           8.7 (9.0)       8.5 (8.0)       12.2 (12.0)   \$8.93
                                                                                     (\$7.20)

  Physical disability  40.2%           10.0 (12.0)     9.1 (9.0)       12.2 (12.0)   \$7.76
                                                                                     (\$6.51)

  Other                9.1%            9.5 (10.0)      8.3 (8.0)       12.1 (12.0)   \$7.68
                                                                                     (\$6.40)

  **Significance of                                                                  
  disability**                                                                       

  Significant/most     77.0%           8.4 (8.7)       7.7 (7.0)       12.2 (12.0)   \$7.49
  significant                                                                        (\$6.24)

  Not significant      23.0%           8.8 (10.0)      8.2 (8.0)       11.7 (12.0)   \$7.83
                                                                                     (\$6.50)

  **Onset of                                                                         
  disability**                                                                       

  Congenital           29.5%           6.3 (5.1)       5.9 (5.6)       11.8 (12.0)   \$6.67
                                                                                     (\$5.50)

  Acquired             70.5%           10.0 (12.0)     9.0 (9.0)       12.3 (12.0)   \$8.00
                                                                                     (\$6.60)

  **All competitively  100.0%          8.5 (9.0)       7.8 (7.0)       12.1 (12.0)   \$7.56
  employed consumers**                                                               (\$6.25)
  -------------------- --------------- --------------- --------------- ------------- -------------

*Source: VR Longitudinal Study, November 1999*

earn lower than average hourly wages (\$6.52; median of \$5.98), have
fewer years of education (11.3), and have lower reading and math
achievement levels (6.5 for reading, 6.1 for math). Consumers with
significant or most significant disabilities (77.0 percent of all
consumers) have lower earnings than do persons with nonsignificant
disabilities (\$7.49, with a median of \$6.24, versus \$7.83, with a
median of \$6.50), as well as lower reading and math achievement (8.4
versus 8.8 for reading, 7.7 versus 8.2 for math); however, they average
more years of education (12.2 versus 11.7). Consumers with congenital
disabilities have lower reading and math achievement (6.3 versus 10.0
for reading, 5.9 versus 9.0 for math) fewer years of education (11.8
versus 12.3), and lower wages (\$6.67, with a median of \$5.50, versus
\$8.00, with a median of \$6.60) than do those with acquired
disabilities.

To look more closely at factors that influence earnings +levels, we
analyzed demographic, disability, attitudinal, and educational
characteristics by earnings levels. These results appear in Tables 3
through 6. We conducted significance tests[^1] to detect differences on
these factors between individuals earning no more than \$5.00 per hour
and those earning more than \$9.00 per hour.

Table 3 reports differences in earnings levels at closure by consumers
demographic characteristics. While we found no significant difference
between the percentage of men earning low, versus high, wages (25.8
percent versus 26.2 percent), women are almost twice as likely to be in
the low wage group as in the high wage group (32.6 percent versus 17.2
percent). On average, earnings increase as consumers age; the mean age
for those earning \$5.00 or less per hour was 37.5, while the mean age
for consumers earning more than \$9.00 per hour was 43.0. Race also has
a significant relationship to earnings levels: African-Americans and
Hispanics are

**Table 3. Demographic Characteristics, by Earnings Levels**

  ---------------------- ------------------ ------------------ ------------------ ------------------ ------------------
                         **EARNINGS                                                                  
                         LEVELS**                                                                    

  **Characteristic**     **Less than or     **\$5.01 - \$7.00  **\$7.01 - \$9.00  **Greater than     **Total**
                         equal to \$5       per hour**         per hour**         \$9.00 per hour**  
                         per hour**                                                                  

  **Percentage of all    29.0%              31.9%              17.2%              21.9%              100.0%
  competitively employed                                                                             
  consumers**                                                                                        

  **Gender**             ***Percentage***   ***Percentage***   ***Percentage***   ***Percentage***   ***Percentage***

  Male                   25.8%              30.9%              17.1%              26.2%              100.0%

  Female\*               32.6%              33.0%              17.3%              17.2%              100.0%

  Total\*                29.0%              31.9%              17.2%              21.9%              100.0%

                         ***Mean            ***Mean            ***Mean            ***Mean            ***Mean
                         (median)***        (median)***        (median)***        (median)***        (median)***

  **Age\***              37.5 (36.0)        38.0 (37.0)        41.0 (40.0)        43.0 (42.0)        39.4 (39.0)

  Range                  18-91              18-86              20-77              19-78              18-91

  **Race/ethnicity**     ***Percentage***   ***Percentage***   ***Percentage***   ***Percentage***   ***Percentage***

  White                  28.4%              30.3%              17.6%              23.7%              100.0%

  African‑American\*     34.3%              41.5%              15.0%              9.3%               100.0%

  Alaska Native or       27.9%              40.4%              13.1%              18.6%              100.0%
  American Indian                                                                                    

  Asian or Pacific       10.5%              30.6%              19.2%              39.8%              100.0%
  Islander\*                                                                                         

  Total\*                28.9%              31.8%              17.3%              22.0%              100.0%

  Of Hispanic origin\*   36.3%              37.2%              16.7%              9.9%               100.0%

                         ***Percentage***   ***Percentage***   ***Percentage***   ***Percentage***   ***Percentage***

  **Receipt of public    35.4%              30.0%              17.1%              17.5%              100.0%
  benefits at entry\***                                                                              
  ---------------------- ------------------ ------------------ ------------------ ------------------ ------------------

\* Indicates a significant difference in means or percentages between
those earning less than or equal to \$5.00 per hour and those earning
more than \$9.00 per hour (p\<.05).

*Source: VR Longitudinal Study, November 1999*

three times as likely to earn low wages as high wages (34.3 versus 9.3
percent for African-Americans; 36.3 versus 9.9 percent for Hispanics),
while Asians are almost four times as likely to earn high wages as low
wages (39.8 percent versus 10.5 percent). Finally, those who received
public benefits at entry to VR (including SSI, SSDI, AFDC, veteran's
benefits, and other disability benefits) were twice as likely to earn
low wages as high wages (35.4 percent versus 17.5 percent).

As Table 4 shows, disability characteristics also affect earnings
levels. Individuals with mental illness, learning disabilities, and
mental retardation are more likely to earn low wages than high wages
(30.3 percent versus 18.5 percent for those with mental illness; 33.2
percent

**Table 4. Disability Characteristics, by Earnings Levels**

  ---------------------- ------------------ ------------------ ------------------ ------------------ ------------------
                         **EARNINGS                                                                  
                         LEVELS**                                                                    

  **Characteristic**     **Less than \$5    **\$5.00 - \$7.00  **\$7.00 - \$9.00  **Greater than     **Total**
                         per hour**         per hour**         per hour**         \$9.00 per hour**  

  **Type of disability** ***Percentage***   ***Percentage***   ***Percentage***   ***Percentage***   ***Percentage***

  Mental illness\*       30.3%              31.8%              19.4%              18.5%              100.0%

  Mental retardation\*   64.0%              32.9%              1.7%               1.4%               100.0%

  Learning disability\*  33.2%              43.0%              11.9%              11.9%              100.0%

  Sensory disability     19.7%              28.7%              21.3%              30.2%              100.0%

  Physical disability    25.8%              30.1%              18.6%              25.6%              100.0%

  Other                  24.5%              35.4%              17.0%              23.1%              100.0%

  Total                  29.0%              31.9%              17.2%              21.9%              100.0%

  **Significance of      ***Percentage***   ***Percentage***   ***Percentage***   ***Percentage***   ***Percentage***
  disability**                                                                                       

  Significant/most       30.0%              31.9%              17.6%              20.6%              100.0%
  significant\*                                                                                      

  Nonsignificant         25.9%              31.7%              16.1%              26.4%              100.0%

  Total\*                29.0%              31.8%              17.2%              21.9%              100.0%

  **Onset of             ***Percentage***   ***Percentage***   ***Percentage***   ***Percentage***   ***Percentage***
  disability**                                                                                       

  Congenital\*           37.5%              35.2%              12.6%              14.7%              100.0%

  Acquired               25.2%              29.9%              19.3%              25.6%              100.0%

  Total\*                28.9%              31.5%              17.3%              22.3%              100.0%

  **Functional           ***Mean***         ***Mean***         ***Mean***         ***Mean***         ***Mean***
  limitations at                                                                                     
  entry^a^**                                                                                         

  Gross motor function   1.88               1.86               1.86               1.87               1.87

  Cognitive function\*   1.83               1.89               1.93               1.93               1.89

  Personal care function 1.98               1.99               1.98               1.98               1.98
  ---------------------- ------------------ ------------------ ------------------ ------------------ ------------------

\* Indicates a significant difference in means or percentages between
those earning less than or equal to \$5.00 per hour and those earning
more than \$9.00 per hour (p\<.05).

^a^ Based on the results of a factor analysis, we created these three
composite scales of functional status from ADL and IADL questions. Each
scale ranges from 1 to 2, with a higher score indicating higher levels
of functioning, and all three scales have acceptable levels of
reliability (alpha greater than .80).

*Source: VR Longitudinal Study, November 1999*

versus 11.9 percent for those with learning disabilities; 64.0 percent
versus 1.4 percent for those with mental retardation  the largest
difference of all). Additionally, consumers with significant or most
significant disabilities and those with congenital disabilities are more
likely to earn low wages than high wages (30.0 percent versus 20.6
percent for consumers with significant or most significant disabilities;
37.5 percent versus 14.7 percent for consumers with congenital
disabilities). Although there were no significant differences in gross
motor functioning or in personal care functioning between these two
groups, those earning high wages scored significantly higher on the
cognitive functioning scale than did those earning low wages (1.93
versus 1.83).

Consumers' self-esteem and locus of control are also strongly related to
earnings levels at closure for VR consumers who entered competitive
employment (Table 5). Those with high earnings have significantly higher
self-esteem scores at entry to VR (2.64 versus 2.46) and are less likely
to believe that chance or other people determine their experiences and
outcomes (1.51 versus 1.75 for chance; 1.52 versus 1.76 for powerful
others). The two groups did not differ significantly in terms of
internality, although those in the high wage category were somewhat
higher on this dimension (2.55 versus 2.49 for those in the low wage
category).

**Table 5. Attitudinal Characteristics^a^ at Entry, by Earnings Levels**

  -------------------- ------------ ------------ ------------ ------------ ------------
                       **EARNINGS                                          
                       LEVELS**                                            

  **Characteristic**   **Less than  **\$5.01 -   **\$7.01 -   **Greater    **Total**
                       or equal to  \$7.00       \$9.00       than \$9.00  
                       \$5          per hour**   per hour**   per hour**   
                       per hour**                                          

                       ***Mean***   ***Mean***   ***Mean***   ***Mean***   ***Mean***

  **Self‑esteem\***    2.46         2.51         2.54         2.64         2.53

  **Locus of                                                               
  control:**                                                               

  Chance\*             1.75         1.72         1.63         1.51         1.67

  Powerful others\*    1.76         1.70         1.64         1.52         1.66

  Internality          2.49         2.49         2.51         2.55         2.51
  -------------------- ------------ ------------ ------------ ------------ ------------

\* Indicates a significant difference in means or percentages between
those earning less than or equal to \$5.00 per hour and those earning
more than \$9.00 per hour (p\<.05).

^a^ Based on the results of a factor analysis, we created a self‑esteem
scale and three locus of control scales from items on psychosocial
functioning. Each scale ranges from 1 to 3, and all scales have
acceptable levels of reliability (alpha greater than .80). Items were
coded so that a higher score indicates more of the given characteristic.
The chance scale measures the extent to which a person believes that
chance has an important effect on his/her experiences and outcomes; the
powerful others scale measures the extent to which a person believes
that other people have a major influence on his/her experiences and
outcomes, and the internality scale measures the extent to which a
person believes that he/she has control over his/her own life.

*Source: VR Longitudinal Study, November 1999*

Table 6 reports our analyses of the relationship between educational
characteristics at entry to VR and earnings levels at closure for
persons who entered competitive employment. As shown, consumers who are
in school at entry to VR are not significantly more likely to earn low

Table 6. Educational Characteristics, by Earnings Levels

  ---------------------- ------------------ ------------------ ------------------ ------------------ ------------------
                         **EARNINGS                                                                  
                         LEVELS**                                                                    

  **Characteristic**     **Less than or     **\$5.01 - \$7.00  **\$7.01 - \$9.00  **Greater than     **Total**
                         equal to \$5       per hour**         per hour**         \$9.00 per hour**  
                         per hour**                                                                  

                         ***Percentage***   ***Percentage***   ***Percentage***   ***Percentage***   ***Percentage***

  **Still in school**    32.9%              31.0%              14.7%              21.5%              100.0%

  **Received special     49.4%              33.1%              11.1%              6.4%               100.0%
  education services\***                                                                             

                         ***Mean            ***Mean            ***Mean            ***Mean            ***Mean
                         (median)***        (median)***        (median)***        (median)***        (median)***

  **Years of education   11.4 (12.0)        11.9 (12.0)        12.3 (12.0)        13.1 (12.0)        12.1 (12.0)
  completed\***                                                                                      

  **Reading achievement  7.1 (6.0)          8.4 (9.0)          9.9 (11.0)         10.3 (12.0)        8.5 (9.0)
  level\***                                                                                          

  **Mathematics          6.4 (6.0)          7.6 (7.0)          9.0 (8.8)          9.9 (10.0)         7.8 (7.0)
  achievement level\***                                                                              

                         ***Percentage***   ***Percentage***   ***Percentage***   ***Percentage***   ***Percentage***

  **Receipt of           16.0%              31.9%              21.2%              30.8%              100.0%
  postsecondary                                                                                      
  education service                                                                                  
  through VR**\*                                                                                     

  **Receipt of           14.4%              24.7%              24.1%              36.8%              100.0%
  postsecondary                                                                                      
  education degree (of                                                                               
  those who received a                                                                               
  service)\***                                                                                       
  ---------------------- ------------------ ------------------ ------------------ ------------------ ------------------

\* Indicates a significant difference in means or percentages between
those earning less than or equal to \$5.00 per hour and those earning
more than \$9.00 per hour (p\<.05).

*Source: VR Longitudinal Study, November 1999*

wages rather than high wages. However, consumers who received special
education services in high school are more than seven times more likely
to earn low wages than high wages (49.4 percent versus 6.4 percent). (We
note that 31.0 percent of these consumers have mental retardation as
their primary disability. As reported in Table 2, consumers with mental
retardation have lower post-VR earnings than persons with other
disabilities.) Furthermore, on average, persons who earn more than
\$9.00 per hour have almost two more years of education than those who
earn \$5.00 or less per hour (13.1 versus 11.4), and they average more
than three grade levels higher in reading and math achievement (10.3
versus 7.1 for reading achievement, 9.9 versus 6.4 for math
achievement). Again, higher basic skills achievement is associated with
higher earnings for the jobs that consumers obtain as a result of VR
services.

Individuals with low earnings levels also have low grade level
achievement scores. As consumers\' basic skills increase, their earnings
also increase. Average reading achievement is over one grade level
higher for the group earning between \$5.01 and \$7.00 per hour (8.4)
than for the group earning up to \$5.00 per hour (7.1); while the group
earning between \$7.01 and \$9.00 per hour has even higher reading
achievement levels (from 8.4 to 9.9). On average, individuals earning
over \$9.00 per hour have somewhat higher reading achievement levels
than those earning between \$7.01 and \$9.00 per hour (10.3 versus 9.9).
Increases in math achievement levels follow a similar pattern, with a
large jump between the first two wage groups (from 6.4 to 7.6), an even
more substantial increase between the second and third groups (7.6 to
9.0), and a more modest increase between the third wage group and the
highest wage group (9.0 to 9.9). As these findings demonstrate, the
relationship between basic skills achievement and wages is strong at all
earnings levels.

While it seems clear that the demographic, disability, attitudinal, and
educational characteristics of consumers at entry to VR have a
substantial influence on their earnings potential, we also examined
selected VR experiences to assess the extent to which the services that
VR consumers obtain have an effect on their subsequent earnings. Very
few VR consumers (less than one percent) received basic literacy
instruction while in VR, so we were unable to analyze the effects of
such services on consumers subsequent earnings. We looked specifically
at the effects of receipt of postsecondary education services and of the
receipt of a postsecondary education degree through VR. As other
research has shown (Price-Ellingstad and Berry, 2000), postsecondary
education positively affects earnings levels. Table 6 reports our
findings on postsecondary education services. These services include
enrollment in business or vocational technical school, a two-year
community college, or a four-year college or university. As shown,
individuals who received any postsecondary education service through a
VR agency (32.6 percent of consumers) were almost twice as likely to
earn high wages as low wages (30.8 percent versus 16.0 percent), and
those who also completed a postsecondary degree (11.8 percent of
consumers) were even more likely to earn high wages rather than low
wages (36.8 percent versus 14.4 percent).

Since these analyses revealed significant differences among individuals
who earned low wages versus those who earned high wages, we decided to
explore these differences further by computing the correlation
coefficients between earnings and variables that we hypothesized were
related to earnings. Each correlation coefficient describes the
direction and magnitude of the linear relationship between two
variables. If the coefficient is positive, individuals with a high value
for one variable are likely to have a high value for the other variable.
If the coefficient is negative, individuals with a high value for one
variable are likely to have a low value for the other variable. The
absolute value of the coefficient represents the magnitude of this
relationship; pairs of variables with correlations close to 1 or -1 are
more strongly related to each other than those with values close to
zero.

Table 7 shows the correlation coefficients between earnings and years of
education, reading and math achievement, receipt of postsecondary
service, receipt of postsecondary degree, functional status measures,
self-esteem, and three locus of control scales.[^2] Reading and math
achievement levels are more highly correlated with earnings (.29 for
reading achievement and .34 for math achievement) than are years of
education (.17); receiving special education services in high school is
associated with lower earnings (-.25). Both receipt of postsecondary
service and receipt of postsecondary degree have significant, but small,
correlations with earnings (.08 for postsecondary service, .06 for
postsecondary degree). All of the educational characteristics at

Table 7. Correlations between Earnings and Educational Characteristics,
Functional Status, and Attitudinal Characteristics

  ---------------------------------------------- ------------------------
  **Characteristic**                             **Correlation with
                                                 Earnings**

  **Educational Characteristics**                

  Years of education                             0.17\*

  Reading achievement                            0.29\*

  Math achievement                               0.34\*

  Special education                              -0.25\*

  Receipt of postsecondary education service     0.08\*

  Receipt of postsecondary education degree      0.06\*

  **Functional Limitation at Entry**             

  Gross motor function                           0.01

  Cognitive function                             0.08\*

  Personal care function                         ‑0.01

  **Attitudinal Characteristics**                

  Self-esteem                                    0.07\*

  Chance                                         ‑0.06\*

  Powerful others                                ‑0.07\*

  Internality                                    0.04
  ---------------------------------------------- ------------------------

\*Indicates that the correlation coefficient is significant (p\<.05).

*Source: VR Longitudinal Study, November 1999*

entry to VR relate more strongly to earnings at closure than do the
functional status measures (.08 for cognitive function, nonsignificant
correlations for gross motor function and personal care function) or the
attitudinal measures (.07 for self-esteem, -.06 for chance, ‑.07 for
powerful others, and a nonsignificant correlation for internality). As
these correlation coefficients demonstrate, educational characteristics
have the strongest relationship to earnings among the variables we
examined. Therefore, we decided to look at the relative contribution of
these variables to earnings.

With the correlational analysis, it is not clear whether the effect of
postsecondary services results from the services themselves or from an
interaction between the educational characteristics at VR entry and
receipt of these postsecondary services from VR. Therefore, we chose to
look at the effects of receipt of any postsecondary service through VR
and the subsequent attainment of a postsecondary degree after taking
into account the educational characteristics that VR consumers bring to
VR. To examine this issue, we conducted a multiple regression analysis
to predict earnings at closure[^3] from educational characteristics,
including receipt of special education services in high school, number
of years of education completed at entry, reading and math achievement
levels, receipt of any postsecondary service through a VR agency, and
receipt of a postsecondary degree through a VR agency. Results from this
analysis appear in Table 8 and are depicted in Figure 1. Together, these
educational characteristics account for 18 percent of the variance in
earnings.[^4] Among characteristics of consumers at entry to VR, both
receipt of special education services (standardized weight of -0.10) and
math achievement level (standardized weight of 0.24) are significant
predictors of earnings: individuals who received special education in
high school earn **significantly less** than other

**Table 8. Relationship of Educational Experiences and Post-VR Earnings
(R^2^ = .18)**

  ---------------------------------- ------------------ ------------------
  **Factor**                         **Unstandardized   **Standardized
                                     Weight**           Weight**

  Receipt of special education       ‑0.07              ‑0.10
  services in high school                               

  Number of years of education       NS                 NS
  completed at entry to VR                              

  Reading achievement^a^             NS                 NS

  Math achievement                   0.03               0.24

  Receipt of postsecondary service   0.10               0.13
  through VR agency                                     

  Receipt of postsecondary degree    0.13               0.12
  through VR agency                                     
  ---------------------------------- ------------------ ------------------

All listed values are significant at p\<.05.

^a^ Reading and math achievement levels are highly correlated (.77) with
each other, probably because most measures of math achievement involve
reading skills. This strong association is likely to be the reason that
only math achievement is a significant predictor in this model.

*Source: VR Longitudinal Study, November 1999*

individuals, while those who have relatively higher levels of math
achievement earn **significantly more**. As Hayward and Schmidt-Davis
(1999) report, youth who received special education in high school have
higher rates of significant, congenital disabilities, including mental
retardation and other developmental delays; these characteristics are
likely to account for lower earnings levels among individuals who
received special education.[^5] Both receipt of a postsecondary service
through a VR agency (standardized weight of 0.13) and receipt of a
postsecondary degree (standardized weight of 0.12) significantly predict
higher earnings, even after other educational characteristics are taken
into account.

Interestingly, in this model, math achievement level, rather than other
characteristics at entry, makes the largest contribution to predicting
earnings at closure among the educational variables that we tested,
while special education status is also a significant (negative)
influence. While receipt of a postsecondary service and of a
postsecondary degree also contribute significantly to predicting
earnings, the magnitude of their influence is much smaller than that of
grade level achievement in math. (As noted previously, reading and math
achievement are highly correlated, probably accounting for the fact that
reading achievement does not appear to be a significant predictor in
this model.) These results suggest that, while receiving postsecondary
education is an important step towards achieving financial independence,
improving basic skills may be equally important, particularly to the
extent that such improvement increases VR consumers' ability to benefit
from further education and training.

In sum, these findings suggest that VR agencies may need to offer basic
skills improvement services to consumers whose basic skills are low when
they enter VR. Such services might well improve consumers\' ability to
enter better paying jobs as well as increasing their likelihood to
qualify for postsecondary education services or additional training that
may further enhance their later labor market success.

**References**

Boesel, D., Alsalam, N., & Smith, T. M. (1998). *Educational and Labor
Market Performance of GED Recipients*. Washington, DC: US Department of
Education.

Grubb, W. N. (1998). The Returns to Education in the Sub-baccalaureate
Labor Market, 1984-1990. *Economics of Education Review, 16*(3),
231-245.

Hayward, B.J. & Schmidt‑Davis, H. (1999). *A Longitudinal Study of the
Vocational Rehabilitation Service Program: Fourth Interim Report.*
Research Triangle Park, NC: Research Triangle Institute.

Price-Ellingstad, D. & Berry, H. G. (2000). *Postsecondary Education,
Vocational Rehabilitation, and Students with Disabilities: Gaining
Access to Promising Futures*. Unpublished draft.

[^1]: ^?^The longitudinal study involved a complex sampling design that
    necessitates the use of specialized statistical software for
    significance testing and modeling; we used SUDAAN for these
    analyses.

[^2]: ^?^Since SUDAAN does not compute correlation coefficients, we used
    SAS to create this correlation matrix and to test each coefficient
    for significance. Thus, this analysis does not take fully take into
    account the sampling design of the study.

[^3]: ^?^The assumptions of multiple regression modeling require that
    the dependent variable (i.e., earnings) have a normal distribution.
    When this assumption is violated, researchers typically transform
    the variable into a form in which it has a normal distribution. In
    this case, since earnings were not normally distributed, we
    calculated the natural logarithm of each value and conducted the
    regression analysis using the transformed earnings as the dependent
    variable. Therefore, the unstandardized and standardized weights
    presented on Table 8 refer to the effects of the independent
    variable on the natural logarithm of earnings rather than on actual
    earnings.

[^4]: ^?^We note that this model achieves a level of prediction that is
    quite strong, accounting for nearly 20 percent of the variance in
    outcomes. This level of prediction is unusual in social science
    research, especially when several of the measures were obtained at
    much earlier timepoints.

[^5]: ^?^While the effect of receiving special education on earnings is
    negative in this model, further research may well show that
    receiving these services actually improves basic skills levels and
    employment outcomes.