Secondary career and technical education (vocational education) provides general workplace and, to some extent, specific occupational skills instruction to high school students. In other programs analyzed in this project, the participating population included completers as well as “non-completers.” However, with the high school career and technical education students, the “treatment”
is full-time equivalent vocational completers only, defined as completing 360 hours of sequenced vocational classes. The Office of the Superintendent of Public Instruction (OSPI) provided the WTECB with individual-level data from general administrative information provided by public high schools in the state about their student enrollment (Form SPIP-210). The intent of the data collection was to have universal coverage, but some high schools did not provide the data. So the representativeness and generalizability of the data may be at question. A significant advantage to our analyses, however, was the ability to use the same data set for the comparison group pool as the treatment. That is, the observations in the high school data that were not classified as vocational completers (by the high school) comprised the comparison group pool.
CTE programs are designed to develop the skills, understanding, and attitudes needed by workers in their occupations. Instructional programs organized within career pathways include agriculture, family and consumer sciences, trade and industry, marketing, business, diversified occupations, technology education, cosmetology, health education, and others.
Participant Characteristics
Table 11.1 provides descriptive data that compare the students in the treatment group to those in the comparison group pool. The first two columns of numbers compare the high school career and
technical education completers who graduated in 2001/2002 to the remaining students in the sample.
The final two columns compare the 2003/2004 career and technical education graduates to other graduates.23
The two populations of high school graduates are closely aligned to each other. There appear to be slightly more males and low socio-economic status (SES) students in the career and technical education programs. Also there are fewer students from urban high schools. A higher percentage of the CTE completers graduated from high school, and in the 2001/2002 cohort, had a higher average grade point average. Prior to graduation, a higher percentage of career and technical education
23We also matched the career and technical students from high schools to individuals on the ES file who were 16–19 years old. However, the participation model and the quality of the matches were not as believable or as statistically robust as the models using the high school data.
Table 11.1 Descriptive Statistics for High School Career and Technical Education Treatment Group and Comparison Group Pool
2001/2002 2003/2004 Characteristics Demographics and Education
Female Minority Disability
Limited English proficiency GPA
Low Socioeconomic Status Graduated
Employment and Earnings (prior to registration)a Ave. percentage of (prior) quarters with employmentb Average quarterly earningsb, c
Mean, earnings trendd
Mean, earnings varianced (in 106 $) Mean, number of quarters with job changec Had earnings dip
Mean, number of quarters since dip at registrationc Ave. earnings dipc
Sample size 12,150 35,470 13,394 30,570
NOTE: Monetary data in 2000 $.
aPrior to registration is defined as prior to September 1 of grade 12.
bObservations with no quarters of prior earnings were excluded from analyses.
cAverages include observations with values of zero.
dTrend and variance calculations include quarters with zero earnings, if any.
††Differences in means are not statistically significant at 0.05 level (t-test).
students had been employed, and their average quarterly earnings were slightly higher. Other than that, the employment and earnings histories of the two groups are statistically indistinguishable.
Participation Model
Table 11.2 provides the results from the logit estimation of participation. Using the high school data base, we estimated a model of being a vocational completer. That was the dependent variable, which took on a value of 1 for the treatment group, and 0 for the other students. The table provides the logit coefficient estimates and standard errors. As with the previous programs, the magnitude of the coefficients is not particularly meaningful, but the sign and statistical significance are. If the coefficient is negative, then a (positive) change in that variable will decrease the likelihood of being a career and technical education completer.
The coefficient estimates seem quite reasonable. The following variables are significantly correlated with being in the treatment group (i.e., career and technical education completer) in both years of data: having a disability, low SES, and percentage of quarters employed. The following variables are significantly correlated with being in treatment group: female, GPA, and residing in an urban county.
Propensity Score Statistics
The propensity score for an observation is the predicted probability using the estimated coefficients and the observation’s actual data. If the logit model has substantial predictive capability, then the mean propensity score for the comparison group should be small (near zero) and should be much less than the mean score for the treatment. As argued earlier, a measure of how well the logit
model discriminates between comparison group members and treatment group members is the cumulative percentile for the comparison group at the propensity score that is the 20th percentile.
Table 11.3 provides these data for the secondary CTE completer group. The mean propensity scores for the treatment groups are roughly 0.28 and 0.32 whereas they are 0.25 and 0.30 for the comparison group for 2001/2002 and 2003/2004 respectively. The 20th percentile indicator is approximately 36 percent for 2001/2002 and 31 percent for 2003/2004. The means and the 20th percentile statistics indicate that the logit model of participation did not discriminate well between treatment and comparison group observations. We could have used the entire comparison group pool for the analyses.
Table 11.2 Coefficient Estimates from a Logit Model of being a High School CTE Completer
2001/2002 2003/2004 Characteristics Coefficient Std. Error Coefficient Std. Error
Demographics and Education Female
Minority Disability
Limited English proficiency GPA Employment and Earnings (prior to registration)
Percentage of quarters with employment Average quarterly earningsa
Earnings trenda Earnings varianceb
Number of quarters with job change Had earnings dip
Number of quarters since dip at registration Percent of earnings dip NOTE:Model included last industry of employment prior to registration and an intercept term. Samples sizes were 47,620 and 43,964 for 2001/2002 and 2003/2004, respectively.
aScaled in $100 (2000 $).
bScaled in $108 (2000 $)
*Significant at the 0.10 level; **significant at the 0.05 level; ***significant at the 0.01 level (two-tailed test).
Table 11.3 Indicators of Propensity Score Model Quality for High School CTE Completer Analyses
Statistic 2001/2002 2003/2004
Mean p-score, HS CTE Completers 0.284 0.322
Mean p-score, Non-completers 0.245 0.297
Percentile Non-completers, at 20th percentile HS CTE Completers
36.40% 31.47%
Statistical Match
Nevertheless, we performed a match. For every observation j in T, we found the observation k in U that minimized the absolute value of the difference between the propensity score for j and k.
We then added k to the comparison group sample if the difference was less than the caliper. The statistical match was done with replacement, so some observations in U were the “matches” for more than one observation in the treatment group. Table 11.4 provides data about the sample sizes, number of matched observations that were duplicates, and a comparison of descriptive statistics between the treatment group, comparison group, and pool of observations from which the comparison group was chosen. Notice that means for the matched comparison group are quite close to the treatment group (none of the demographic and education or employment and earnings characteristics had means that differed from each other statistically), but we believe this was an artifact of the original distribution rather than the matching process because the logit model did not discriminate well between the comparison group pool or treatment group.
Net Impacts
The major purpose of the study was to estimate the net impacts of the education and training programs on clients. Tables 11.5 and 11.6 provide the estimated net impacts for secondary career
and technical education. As with comparable tables in the prior chapters, the first table displays the short-term (3 quarters after exit) and the longer-term (9-12 quarters after exit) outcomes for the 2001/2002 cohort of program exiters. The second table is limited to the short-term net impacts for the 2003/2004 cohort. The first column in each of the tables presents the estimates from the block matching technique, which uses the full comparison set (i.e., U) and the treatment group. The second column presents a comparison of means between the treatment group and the matched comparison group. The third column presents an estimate from a regression adjustment of that mean.
Table 11.4 Matching Algorithm Statistics and Post-Match Comparison of Characteristics for High School CTE
2001/2002 2003/2004
Statistic/Characteristic CTE
Completers Sample size
Sample size used in match Matched sample size
Number of observations used once
Number of observations used multiple times Maximum number of repeats
12,150 Demographics and Education
Female Minority Disability
Limited English proficiency GPA
Employment and Earnings (prior to registration) Percentage employed prior to registration Average quarterly earningsa
Mean, earnings trendb
Mean, earnings varianceb (in 106 $) Mean, number of quarters with job changea Had earnings dip
Mean, number of quarters since dip at registrationa Ave. earnings dipa
Sample size 12,146 12,146 13,392 13,392
NOTES: Monetary data in 2000 $. None of the differences in means are statistically significant at the 0.05 level (t-test).
aAverages include observations with values of zero.
bTrend and variance calculations include quarters with zero earnings, if any.
Table 11.5 Net Impact Estimates for High School CTE Completers for 2001/2002 Cohort
Block Matching Estimator
Matched Sample Estimator
Comparison Group Means
Full Sample Matched Sample Outcome
Ever employed - longer term (%) Percent of quarters, longer term
Percent of quarters, longer term, diff-in-diff
6.0*** Average hourly wage
Short term ($)
Short term diff-in-diff ($)
0.51***
Longer term, diff-in-diff ($)
0.63*** Average quarterly hours
Short term
Short term, diff-in-diff
27.2*** Longer term
Longer term, diff-in-diff
36.8*** Average quarterly earnings
Short term ($)
Short term, diff-in-diff ($)
224***
Longer term, diff-in-diff ($)
390*** Unemployment Insurance Benefits (average quarterly)
Percent receiving, short-term Benefits - short term ($) Percent receiving, longer term
Benefits - longer term ($)
1.0*** Public Assistance and Medicaid (average quarterly)
Percent receiving TANF, short term TANF benefits - short term ($)
−0.4*** Percent receiving TANF, longer term
TANF benefits - longer term ($)
−0.5*** Percent receiving FS, short term
FS benefits - short term ($)) Percent receiving FS, longer term
FS benefits - longer term ($) Percent enrolled Medicaid, short-term
Percent enrolled Medicaid, longer term
−0.3 NOTE: See Appendix B for explanatory notes. Sample sizes differ for virtually every entry in the table because of observations with missing data. If there were no missing data, the sample sizes would be those displayed in rows 2 and 3 of Table 11.4.
* significant at the 0.10 level; ** significant at the 0.05 level; *** significant at the 0.01 level (two-tailed test). -- means not applicable.
Table 11.6 Net Impact Estimates for High School CTE Completers for 2003/2004 Cohort Block
Matching Estimator
Matched Sample Estimator
Comparison Group Means
Full Sample Matched Sample Outcome
Average hourly wage Short term ($)
Short term diff-in-diff ($)
0.56*** Average quarterly hours
Short term
Short term, diff-in-diff
25.4*** Average quarterly earnings
Short term ($)
Short term, diff-in-diff ($)
222*** Unemployment Insurance Benefits (average quarterly)
Percent receiving, short term Benefits - short term ($) Public Assistance and Medicaid (average quarterly)
Percent receiving TANF, short term TANF benefits - short term ($)
−0.2 Percent receiving FS, short term
FS benefits - short term ($) NOTE: See Appendix B for explanatory notes. Sample sizes differ for virtually every entry in the table because of observations with missing data. If there were no missing data, the sample sizes would be those displayed in rows 2 and 3 of Table 11.4.
* significant at the 0.10 level; ** significant at the 0.05 level; *** significant at the 0.01 level (two-tailed test). -- means not applicable.
This column represents the preferred specification, which in this case uses the levels of the outcome variables as the dependent variable. The coefficient estimates that are in “boxes” represent the final,
“official” estimates using the preferred specification as chosen by WTECB staff. The final four columns of the tables provide the means of the comparison group, both the full comparison group pool and the matched comparison group. These columns are provided so that the net impacts can be estimated on a percentage basis.
Career and technical education pays off for secondary school students economically. The short-term impacts include increases in employment (6.7percentage points), hourly wage ($0.47 per hour), hours working (21.8 hours in a quarter), and quarterly earnings ($191). The earnings impact is on the order of 9–10 percent. The economic advantages persist, and even grow, in the longer term.
The employment net impact estimate is 5.4 percentage points; the hourly wage increases by $0.59 per hour; the hours worked increase by 35.5 hours per quarter; and earnings increase by about $378 or about 13 percent. There is little effect of high school career and technical education on public assistance or UI—perhaps a slight reduction in public assistance, especially food stamps in the longer-term.
Subgroup Analyses
Approximately 55 to 60 percent of the high school CTE completers went on to enroll in a public higher education institution in Washington. Tables 11.7 and 11.8 provide estimates of the net impacts of high school CTE completion for the students who went into higher education. The first column of estimates are for CTE completers who did not participate in higher education, whereas the second column provides net impact estimates for the treatment group individuals who did enroll in higher education. The short-term impacts may reflect part-time employment of students in higher education. Employment (7.7 percent), hourly wages ($0.50), and hours worked (12.8) all have positive impacts that are significant. However, the combination of these increases quarterly earnings by only $86, which is less than 4 percent. At the same time, CTE completers who do not pursue higher education have positive, but smaller, impacts on employment and wage rates than do the higher education attendees. On the other hand, their hours worked and earnings impacts are much larger.
Table 11.7 shows a different story. In longer-term estimates, CTE completers who go on to postsecondary schooling dominate all of the employment and earnings impacts. So the results indicate that CTE completers have better economic outcomes than other high school graduates. In the short-term, CTE completers who do not go on to higher education have relatively higher earnings impacts. But in the longer term, CTE completers who do enroll in higher education have better outcomes.
Table 11.7 Selected Longer-Term Net Impact Estimates for a Subgroup of High School CTE Completers, 2001/2002 Cohort
Subgroup Outcome No Higher Education
Participants with Higher Education
Matched Comparison Group Mean
Employment −2.8%** 9.8%** 55.7%
Hourly Wage −$0.09 $0.98** $5.66
Hours Worked 25.2** 43.0** 175.6
Earnings $319** $438** $1,757
UI Receipt 1.3%** 0.8%** 3.1%
TANF Receipt −0.1%** 0.0% 2.4%
Food Stamps Recipient −1.9%** −1.3%** 8.6%
Medicaid Enrollment −2.9%** 0.8% 20.1%
Subgroup Sample Size 4,298 7,848 —
NOTE: Monetary data in ’00 $.
**Significant at the 0.05 level (two-tailed test).
Table 11.8 Selected Short-Term Net Impact Estimates for a Subgroup of High School CTE Completers, 2003/2004 Cohort
Subgroup Outcome No Higher Education
Participants with Higher Education
Matched Comparison Group Mean
Employment 5.3%** 7.7%** 46.7%
Hourly Wage $0.44** $0.50** $4.21
Hours Worked 35.4** 12.8** 117.9
Earnings $342** $86** $1,047
UI Receipt 0.3% −0.1% 0.7%
TANF Receipt 0.1% 0.1% 1.0%
Food Stamps Receipt 0.4% −0.2% 5.1%
Medicaid Enrollment −0.1% 1.1%** 17.4%
Subgroup Sample Size 6,278 7,114 —
NOTE: Monetary data in ’00 $.
**Significant at the 0.10 level (two-tailed test).