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Education and Early Labour Market Outcomes in Canada - December 2007

3. Data

3.1 Sample description and variable definitions

The data used in this paper is obtained from the first three cycles of the older cohort of the Youth in Transition Survey (YITS). The YITS contains detailed information on education activities as well as on subsequent labour market outcomes (wages, employment, occupation, industry etc.). Respondents in the YITS were interviewed every two years, with the initial interview conducted by Statistics Canada between January and April 2000.¹The target population at the initial survey for the older cohort was youth aged 18-20 in 2000. Shaienks et al (2006) reports that in December 2003, 32% were enrolled in school (the vast majority was enrolled in post-secondary school), 45% were working full-time (more than 30 hours per week), 9% were working part-time, while 14% were neither enrolled in school nor worked. Thus, any analysis of labour market outcomes using the YITS needs to acknowledge the fact that many respondents are still in school, and that these may be non-randomly selected from this young population. Ignoring this may substantially bias the results.

The analysis in this paper uses information extracted from all three surveys. In particular, information on high school grade average, if the respondent lived with both biological parents most of the time during high school, parents' education and occupation, and self-assessed scholastic abilities (writing, reading, solving mathematical problems) was obtained from the initial survey. Information on major field of study among post-secondary graduates was obtained from the second and third surveys. Finally, information on educational attainment and labour market outcomes, such as earnings, unemployment, and occupation, were obtained from the most recent survey. In this paper, labour market outcomes will generally be measured in December 2003, which is the most recent date available. More details on the construction of the variables used in this paper are provided below. Because of regional differences in both educational systems and labour market characteristics, the analysis will generally be conducted separately for the following four regions: Atlantic Canada (Newfoundland and Labrador, Nova Scotia, Prince Edward Island, and New Brunswick), Quebec, Ontario, and Western Canada (Manitoba, Saskatchewan, Alberta, and British Columbia).² Furthermore, all results will be presented separately for men and women. Finally, sample weights provided by Statistics Canada have been used throughout this paper.

3.2 Educational attainment

Considering educational attainment, Table 1 reports the highest certificate, diploma or degree the respondent has attained or graduated from as of December 2003. The upper panel shows entries for males while the lower panel shows entries for females. Starting with males, between 26% and 37% had not attained any PSE at this date. The proportion is highest in Western Canada (36.8%) and lowest in Ontario (26.3%), with Atlantic Canada and Quebec both close to 30%. Among those with no PSE, around a third had not completed high school (labeled High School Leaver in the table) in all regions except Quebec. In Quebec, over half (56%) of those with no PSE had not completed high school, suggesting a substantially higher high school drop-out rate among males in Quebec than in the rest of Canada.

Around 12% of respondents in all regions had started a post-secondary education but had left it prior to obtaining a certificate, diploma or degree (labeled PSE Leaver in the table). Further, around 30% were attending a post-secondary program in December 2003.³The attendance rate is highest in Ontario (33.6%) and lowest in Atlantic and Western Canada (28.3%). The higher attendance rate in Ontario, relative to Atlantic and Western Canada may partly be due to normal high school completion after grade 13 in Ontario compared to grade 12 in Atlantic and Western Canada.⁴ Considering post-secondary graduates, the entries in Table 1 (as well as throughout the paper) distinguish between high and low levels of PSE. High PSE graduates refer to graduates with a Bachelor's degree, a first professional degree, or a graduate-level diploma/degree (Master's or Ph.D.). Low PSE graduate refers to graduates from a vocational program, private business or training institute, apprenticeship program, or from a College or a CEGEP program. The post-secondary graduation rates vary from 23.6% (Western Canada) to 29.4% (Atlantic Canada).

Table 1: Educational attainment, by gender and region
	Region
Post-Secondary Education (PSE) Status	Atlantic	Quebec	Ontario	Western	All regions
	Males
No PSE	0.299	0.294	0.263	0.368	0.306
High School Leaver	0.101	0.167	0.080	0.138	0.121
PSE Leaver	0.123	0.128	0.138	0.114	0.127
PSE Continuer	0.283	0.305	0.336	0.283	0.308
PSE Graduate	0.294	0.273	0.263	0.236	0.259
High PSE	0.077	0.052	0.097	0.077	0.078
Low PSE	0.217	0.221	0.166	0.159	0.181
	Females
No PSE	0.175	0.178	0.168	0.266	0.201
High School Leaver	0.043	0.087	0.063	0.072	0.070
PSE Leaver	0.135	0.116	0.107	0.105	0.111
PSE Continuer	0.299	0.373	0.389	0.303	0.352
PSE Graduate	0.391	0.333	0.336	0.326	0.336
High PSE	0.161	0.096	0.120	0.133	0.121
Low PSE	0.230	0.237	0.216	0.193	0.215
Source: Calculations based on survey data from the oldest cohort in the Youth in Transition Survey (YITS), cycle 3. Notes: Entries were calculated using information on overall post-secondary status and highest certificate, diploma or degree attained as of December 2003. High School Continuer refers to respondents who had not completed a high school diploma or its equivalence in December 2003. PSE Leaver refers to respondents who had attended PSE prior to December 2003 but had left PSE before graduation. PSE Continuer refers to respondents who were enrolled in PSE program in December 2003. Finally, High PSE refers to graduates from a post-secondary program at a Bachelor's degree level or higher, while Low PSE refers to graduates from college/CEGEP, apprenticeship programs or other forms of post-secondary training.

Regarding females, the entries in the lower panel suggest that females acquire more schooling than males. High school drop-out rates are substantially lower among females, around half those for males in most regions. The drop-out rate from PSE, as well as the attendance rate, is similar to that of males while post-secondary graduation rates are substantially higher. Again, Atlantic Canada shows the highest graduation rate.

3.3 Differences between PSE graduates and high school graduates

Table 2 provides a profile of post-secondary students in Canada by highlighting differences in selected observable characteristics between post-secondary graduates and high school graduates.⁵ The gender difference in post-secondary graduation is again shown as males dominate the high school graduate category while females dominate the PSE category. There are only small regional differences in this gender gap. The variable nuclear equals one if the respondent lived with both biological parents most of the time during high school and has been found to be an important determinant of school attendance in previous studies, e.g. Belzil and Hansen (2002) and Belzil and Hansen (2006). However, it appears from Table 2 that living with both biological parents during high school is not a major determinant of PSE graduation since the differences between high school graduates and post-secondary school graduates are small across all regions. Differences in parents' education, both mother's and father's, may also explain whether or not a student chooses to acquire a post-secondary degree. Previous literature has documented significant intergenerational correlations in educational attainment, both in Canada and elsewhere. Such a relationship can also be observed in Table 2 for most regions although somewhat weak, with the exception of Ontario. The weak correlation between parents' education and the respondent's education in Table 2 may partially be due to the fact that high school drop-outs were removed from the sample as well as the fact that those enrolled in PSE but who have not yet graduated are included in the high school graduate category.

Table 2: Differences in selected characteristics between high school graduates and PSE graduates, by region
	Atlantic		Quebec		Ontario		Western		All regions
	HS	PSE	HS	PSE	HS	PSE	HS	PSE	HS	PSE
Male	0.55	0.44	0.52	0.47	0.53	0.44	0.55	0.42	0.54	0.44
Nuclear	0.86	0.93	0.92	0.96	0.89	0.90	0.86	0.89	0.88	0.91
Mother's education
Less than high school	0.19	0.17	0.21	0.16	0.12	0.13	0.13	0.10	0.15	0.13
High school	0.43	0.35	0.37	0.32	0.37	0.36	0.42	0.36	0.39	0.35
More than high school	0.38	0.48	0.42	0.53	0.50	0.51	0.45	0.53	0.46	0.52
Father's education
Less than high school	0.25	0.25	0.26	0.22	0.15	0.15	0.20	0.17	0.19	0.18
High school	0.34	0.32	0.24	0.22	0.28	0.29	0.32	0.26	0.29	0.27
More than high school	0.41	0.43	0.50	0.56	0.56	0.56	0.49	0.57	0.52	0.55
High school grade average
80% +	0.37	0.48	0.31	0.49	0.38	0.47	0.32	0.49	0.35	0.48
Less than 80%	0.63	0.52	0.69	0.51	0.62	0.53	0.68	0.51	0.65	0.52
Source: Calculations based on survey data from the oldest cohort in the Youth in Transition Survey (YITS), cycle 1 (the initial survey). Note: Information on high school grade average refers to self-reported overall grade average in the last year of high school. Sample restricted to those with high school degree and/or a post-secondary degree (high school drop-outs were removed).

The last entries in Table 2 illustrate the link between high school grade average and PSE status. As expected, students with average high school grades above 80% are much more likely to have graduated from a post-secondary program than those with lower grade averages.

3.4 Major field of study among PSE graduates

As discussed above, PSE in Canada is heterogeneous and some of that heterogeneity is displayed in Table 3 which shows the major field of study among post-secondary graduates, separately for males and females and by region.⁶ The entries display substantial differences between males and females. For instance, females are more concentrated in the humanities/social sciences and business, while males are heavily concentrated in mathematical sciences/engineering. This gender segregation is relatively constant across regions and has been observed elsewhere, e.g. Drewes (2006) and Hansen (2006).

Table 3: Major field of study among PSE Graduates, by gender and region

3.5 Occupation and post-secondary education

Using information on the most recent job held between January 2002 and December 2003, Table 4 shows the distribution of occupation by PSE status. To allow for a transition period between school and work for post-secondary graduates, the sample used for Table 4 removed respondents who attended a post-secondary program after December 2001. Occupations have been aggregated into five categories: management/business; natural sciences/health; social sciences/education/government/art; sales/service; and trades/primary production/processing. Although these categories are quite general, the first three categories can probably be regarded as containing mostly high skill occupations while the last two categories mainly contain low skill occupations.⁷ With little regional variation, post-secondary school graduates are less likely to work in sales/service or trades/primary production/processing than respondents without a post-secondary degree.

Table 4: Occupation in most recent job, by PSE status and region

3.6 Major field of study and occupational choices

In order to analyze the link between major field of study and occupational choices for post-secondary graduates, Tables 5a and 5b present occupational distributions by major field of study for males and females, respectively. For males whose major field of study was humanities/social sciences, 32.6% worked in occupations classified as social sciences/art, occupations that presumably correspond well to the field of humanities/social sciences. Almost as many, however, worked with sales (31.2%) and 20% worked in management/business occupations. As expected, the fraction working in this occupation is higher for respondents with business as their main field of study (39.8%). A large fraction of these respondents also worked in sales (29.7%). Respondents whose major field of study was math sciences/engineering/agriculture or health are predominantly working in natural science/health occupations (around 40%). For the former group, almost as many (38%) worked in trades/primary production/processing occupations.

For females, a similar pattern is observed although the correspondence between major field of study and occupation appears even stronger. For instance, 57% of female respondents whose main field of study was business worked in management/business. Overall, there is a fairly strong correspondence between major field of study and occupation among respondents in this sample.

Table 5a: Major field of study and occupations among male PSE graduatesn
	Occupation
Major field of study	Management/ Business	Natural sciences/ Health	Social sciences/ Art	Sales	Trades/ Primary production/ Processing
Humanities/Social sciences/Education	0.200	0.041	0.326	0.312	0.122
Business	0.398	0.073	0.118	0.297	0.115
Physical and life sciences/Technologies	0.081	0.319	0.243	0.226	0.132
Math Sciences/Engineering/Agriculture	0.050	0.381	0.054	0.134	0.380
Health	0.039	0.414	0.232	0.169	0.145
Personal and transportation services	0.089	0.060	0.055	0.586	0.211
Other	0.195	0.171	0.164	0.271	0.199
Source: Calculations based on survey data from the oldest cohort in Youth in Transition Survey (YITS), cycle 3. Note: See notes to Tables 3 and 4.

Table 5b: Major field of study and occupations among male PSE graduatesn
	Occupation
Major field of study	Management/ Business	Natural sciences/ Health	Social sciences/ Art	Sales	Trades/ Primary production/ Processing
Humanities/Social sciences/Education	0.210	0.028	0.366	0.374	0.022
Business	0.566	0.026	0.121	0.279	0.009
Physical and life sciences/Technologies	0.098	0.261	0.231	0.306	0.103
Math Sciences/Engineering/Agriculture	0.187	0.260	0.128	0.306	0.120
Health	0.120	0.515	0.114	0.232	0.020
Personal and transportation services	0.234	0.062	0.132	0.513	0.059
Other	0.195	0.171	0.164	0.271	0.199
Source: Calculations based on survey data from the oldest cohort in Youth in Transition Survey (YITS), cycle 3. Note: See notes to Tables 3 and 4.

3.7 Labour force status and educational attainment

The entries in Table 6 show the proportion of sample respondents who were either employed, unemployed (looking for work) or neither employed nor unemployed in December 2003. The sample excludes full-time students and self-employed workers. Thus, the category Home (neither employed nor unemployed) contains individuals who were not active in the labour market. To illustrate the effect of education on labour force status, the proportions in each category is showed separately for four levels of education: high school drop-outs, high school graduates with no further schooling, graduates from low PSE, and graduates from high PSE. Proportions for males are shown in the first column while proportions for females are presented in the second column.

Table 6: Labour Force Status, by educational attainment
	Males	Females
	High school drop-out
Employed	0.836	0.629
Unemployed	0.095	0.063
Home	0.069	0.307
	High school only
Employed	0.856	0.816
Unemployed	0.067	0.051
Home	0.077	0.133
	Low PSE
Employed	0.898	0.879
Unemployed	0.056	0.041
Home	0.047	0.080
	High PSE
Employed	0.835	0.861
Unemployed	0.093	0.062
Home	0.071	0.077
Source: Calculations based on survey data from the oldest cohort in Youth in Transition Survey (YITS), cycle 3. Note: Entries were calculated using information on labour force status and highest education attained (or graduated from) as of December 2003. Full-time students and self-employed workers were removed from the sample. The Home category is defined as a residual state and includes all respondents who were not employed or unemployed in December 2003.

Among high school drop-outs, 83.6% of males were employed while that number is only 62.9% for females. The fraction being unemployed are 9.5% and 6.3% for males and females, respectively. Finally, the proportion of high school drop-outs that were classified as being home is 6.9% for males and 30.7% for females. The importance of high school completion is illustrated in the second panel of results for those with a high school diploma but with no additional education. Although the employment rate for males is similar to that of high school drop-outs, that is not the case for females, whose employment rate among high school graduates is 81.6%, close to that of males. Further, for both men and women, the unemployment rate is lower and the proportion of women being classified in the home state is substantially lower (13.3%).

The employment rate is even higher among those with low PSE, both for men and women, and again there is only a small difference between males and females. Both the unemployment rate and the home rate are lower than for the high school only category. Finally, for those with high PSE, the employment rate for males is lowest of all educational levels, even below that of high school drop-outs. In fact, both the employment rate and the unemployment rate for males with high PSE are very similar to those of males with incomplete high school. For females, the employment rate is slightly lower than that of women with low PSE and the unemployment rate is higher. However, the home category is low at 7.7%, much below that of female high school drop-outs. The relatively high unemployment rate among those with high PSE might be explained by the fact that, given the young sample, these individuals have had little time to establish themselves on the labour market after completing their studies. The figures in Table 6 do not control for differences in time since last in school which may substantially affect the proportion being employed in any educational category.

Table 7: Labour Force Status after finishing school
Time since last in school (months)	Females			Males
Time since last in school (months)	Employed	Unemployed	Home	Employed	Unemployed	Home
	High school drop-out
1	0.654	0.104	0.242	0.651	0.108	0.241
3	0.708	0.105	0.187	0.667	0.101	0.231
6	0.679	0.130	0.192	0.687	0.102	0.211
12	0.721	0.102	0.178	0.764	0.047	0.189
24	0.721	0.077	0.202	0.769	0.062	0.170
	High school only
1	0.746	0.106	0.148	0.739	0.104	0.157
3	0.759	0.118	0.123	0.785	0.090	0.125
6	0.799	0.078	0.122	0.813	0.072	0.115
12	0.799	0.096	0.106	0.836	0.064	0.099
24	0.844	0.069	0.087	0.823	0.065	0.111
	Low PSE
1	0.807	0.080	0.113	0.808	0.060	0.132
3	0.850	0.062	0.089	0.853	0.053	0.094
6	0.877	0.055	0.068	0.863	0.047	0.090
12	0.887	0.033	0.080	0.901	0.033	0.066
24	0.877	0.051	0.072	0.909	0.031	0.060
	High PSE
1	0.757	0.111	0.132	0.654	0.151	0.195
3	0.827	0.098	0.075	0.746	0.101	0.153
6	0.859	0.069	0.071	0.834	0.086	0.080
12	0.903	0.061	0.036	0.911	0.040	0.049
24	n.a.	n.a.	n.a.	n.a.	n.a.	n.a.
Source: Calculations based on survey data from the oldest cohort in Youth in Transition Survey (YITS), cycles 1-3. Note: Entries were calculated using information on labour force status and highest education attained (or graduated from) from January 1999 to December 2003. The Home category is defined as a residual state and includes all respondents who were not employed or unemployed.

However, the longitudinal nature of the YITS survey enables a detailed analysis of the transition from school to work. In Table 7, the proportion of former students that are employed, unemployed, and home are shown as a function of time since they were last enrolled in school. The entries in the table show a clear relationship between educational attainment and subsequent labour market success. The employment rate is generally higher for those with more education and the unemployment rate is lower. For example, one month after leaving school, 65.4% of female high school dropouts were employed while this figure is 80.7% for females who had graduated from a low PSE program. Similar figures can be observed for males, 65.1% of high school dropouts were employed compared to 80.8% for low PSE program graduates. However, the employment rates for high PSE graduates one month after school are lower than those for low PSE graduates.

The entries also show that the employment rate increase with time. This is especially true for graduates from a high PSE program. Because of sample size limitations, it is only possible to follow these graduates for 12 months after school. For these graduates, the employment rates increase from 75.7% one month after school to 90.3% for females, and from 65.4% to 91.1% for males. Thus, time since last in school is an important factor to consider when comparing labour market outcomes across different levels of education for these young respondents. Once we control for differences in such time, we find that more educated respondents are more likely to be employed and less likely to be unemployed than less educated respondents. Finally, the entries in Table 7 suggest that while the employment rates increase during the first year out of school, they do not change much during the second year. This is true for all levels of education from high school drop-outs to graduates from a low PSE program.⁸ Thus, students who are unable to find a job during the first year after finishing school may find it difficult to enter the labour market in subsequent years.

Table 8: Unemployment after leaving school
	Females	Males
	High school drop-out
Unemployment duration (months)	7.826	5.225
	(0.820)	(0.619)
Proportion ever unemployed	0.208	0.195
	(0.031)	(0.023)
	High school only
Unemployment duration (months)	5.576	4.541
	(0.314)	(0.290)
Proportion ever unemployed	0.239	0.223
	(0.012)	(0.010)
	Low PSE
Unemployment duration (months)	3.484	3.061
	(0.299)	(0.277)
Proportion ever unemployed	0.168	0.147
	(0.010)	(0.010)
	High PSE
Unemployment duration (months)	3.528	2.482
	(0.315)	(0.296)
Proportion ever unemployed	0.201	0.25
	(0.014)	(0.021)
Source: Calculations based on survey data from the oldest cohort in Youth in Transition Survey (YITS), cycles 1-3. Note: Entries were calculated using information on labour force status and highest education attained (or graduated from) from January 1999 to December 2003. Duration is measured during the first year after finishing school for respondents who went directly from school to unemployment. The proportion ever unemployed reflects the fraction of respondents that experienced any unemployment during that year. Standard errors are in parentheses.

The entries in Table 7 also suggest that the incidence of unemployment is reduced with time since last in school. This finding can be observed for all levels of schooling. Further information on unemployment experiences following school is presented in Table 8. The entries show the average duration of unemployment spells for those who went from school to unemployment as well as the proportion of respondents that experienced unemployment during the first year following school completion. There is a clear pattern in unemployment spell duration with high school drop-outs showing the longest spells (7.8 months for females and 5.2 months for males) and graduates from high PSE programs showing the shortest spells (3.5 months for females and 2.5 months for males). Between 15% and 25% experienced unemployment during the first year after school, and unlike unemployment spell durations, there is no clear link between educational attainment and risk of being unemployed.

3.8 Wages and educational attainment

Tables 9a and 9b summarize the distribution of hourly wages by educational attainment for males and females, respectively. As regional differences are likely to exist, the summary statistics are also shown separately for each of the four regions considered in this paper: Atlantic Canada, Quebec, Ontario and Western Canada. In the tables, the wage information is summarized by presentation of the mean, the median and the lower and upper quartiles. The samples are restricted to those who held a job in December 2003. Full-time students, self-employed workers, and respondents who held a job but provided no wage information were excluded. Starting with the results for males, there are only small differences in average wage rates across different levels of education, although the average wage generally rises with education. A similar pattern is observed for the median wage rates. In all regions except for Atlantic Canada, the average wage of those with high school only is $1 per hour higher than the average wage for high school drop-outs. The difference in average wage rate between those with low PSE and high school only is $2 per hour for all regions. Finally, the average wage of those with high PSE is lower ($1 per hour) than the average wage of those with low PSE in Atlantic Canada, the same in Ontario and Western Canada and higher (1$ per hour) in Quebec.

Table 9a: Distribution of wage per hour for males
	Atlantic	Quebec	Ontario	Western	All regions
	High school drop-out
Mean	11	13	14	14	13
Median	9	12	12	12	12
Lower Quartile	8	10	9	10	10
Upper Quartile	14	15	17	17	16
	High school only
Mean	11	14	15	15	14
Median	10	12	13	13	13
Lower Quartile	8	10	10	10	10
Upper Quartile	12	17	17	18	17
	Low PSE
Mean	13	16	17	17	16
Median	12	15	16	16	15
Lower Quartile	10	12	12	13	12
Upper Quartile	15	19	22	21	20
	High PSE
Mean	12	17	17	17	17
Median	11	16	17	18	16
Lower Quartile	9	10	12	12	11
Upper Quartile	16	21	22	21	21
Source: Calculations based on survey data from the oldest cohort in Youth in Transition Survey (YITS), cycle 3. Note: Entries were calculated using earnings per hour information from job held in December 2003. Full-time students, self-employed workers, and respondents with no wage information were excluded.

Table 9b: Distribution of wage per hour for females
	Atlantic	Quebec	Ontario	Western	All regions
	High school drop-out
Mean	9	10	10	10	10
Median	8	10	10	9	10
Lower Quartile	7	8	7	8	8
Upper Quartile	13	11	12	12	12
	High school only
Mean	10	11	12	12	12
Median	9	10	11	11	11
Lower Quartile	7	8	9	9	9
Upper Quartile	10	13	14	15	14
	Low PSE
Mean	12	15	14	14	14
Median	11	15	13	12	13
Lower Quartile	8	11	10	10	10
Upper Quartile	14	18	16	16	17
	High PSE
Mean	16	18	16	17	16
Median	15	16	15	17	16
Lower Quartile	11	11	10	11	11
Upper Quartile	20	21	20	21	21
Source: Calculations based on survey data from the oldest cohort in Youth in Transition Survey (YITS), cycle 3. Note: Entries were calculated using earnings per hour information from job held in December 2003. Full-time students, self-employed workers, and respondents with no wage information were excluded.

The distributions of female wages are shown in Table 9b. Unlike the wages for males, there is a monotonic increase in the average wage with increases in educational attainment across all regions. This is also true for the median wages. Overall, the entries in Tables 9a and 9b suggest that education is generally associated with higher wages, and more so for women than for men. Tables 9a and 9b also show a measure of wage dispersion, the interquartile range. For both men and women, and across all regions, the dispersion is higher for higher levels of education.

The longitudinal nature of the data also allows an analysis of early wage growth. In Table 10, median wage rates are shown as a function of time since they were last enrolled in school. The table illustrates the difference in entry wages across different levels of education as well as differences in wage growth during the first two years after leaving school. The entry wage (the wage observed during the first month after leaving school) is positively correlated with education and women with a high PSE diploma have a median wage that is 70% higher than that of female high school drop-outs. The figure is somewhat lower for men, 60%.

Table 10: Median wages and time since last in school
Time since last in school (months)	Females	Males
	High school drop-out
1	7.0	8.0
3	7.0	8.0
6	7.0	8.5
12	8.0	9.0
24	9.0	10.0
% difference m12-m1	14.3	12.5
% difference m24-m1	28.6	25.0
	High School only
1	8.0	9.0
3	8.0	9.0
6	8.0	9.5
12	8.5	10.5
24	9.0	11.0
% difference m12-m1	6.3	16.7
% difference m24-m1	12.5	22.2
	Low PSE
1	10.0	11.0
3	10.0	11.5
6	10.0	12.0
12	11.0	12.5
24	12.0	13.5
% difference m12-m1	10.0	13.6
% difference m24-m1	20.0	22.7
	High PSE
1	12.0	13.0
3	12.0	13.5
6	14.0	15.0
12	15.0	16.0
24	n.a.	n.a.
% difference m12-m1	25.0	23.1
Source: Calculations based on survey data from the oldest cohort in Youth in Transition Survey (YITS), cycles 1-3. Note: Entries were calculated using information on wages and highest education attained (or graduated from) from January 1999 to December 2003.

The table entries also show that (median) wages grow much faster for workers with a high PSE diploma. The percentage increase in median wages during the first year for this group is 25% for females and 23% for males. For those with lower levels of education the wage increase is lower, between 6% and 16%. For these groups, the table also displays the wage growth over two years. For females, this wage growth is 28% for high school drop-outs, 12% for those with high school only and 20% for those with a low PSE diploma. For males, the two-year wage increase is between 22% and 25%.

A possible reason for the finding that higher education improves wage growth is that individuals with higher education may attract more and better job offers than otherwise similarly endowed workers. In fact, the entries in Table 8 show that the duration of unemployment spells during the first year out of school is significantly shorter for more educated workers, a finding that is consistent with the hypothesis that better educated workers receive more and better job offers than less educated workers.

¹ The YITS was conducted by Statistics Canada with the co-operation and support of Human Resources and Social Development Canada.
²Disclosure rules prevent analysis at provincial levels for this sample. The information refers to the region where the respondent resided at the most recent interview (cycle 3).
³ Respondents who had graduated from one post-secondary program and were attending an additional post-secondary program in December 2003 were coded as post-secondary continuer.
⁴ However, since September 2003, students in Ontario graduate high school after completion of grade 12.
⁵ High school drop-outs were removed from the sample used to construct Table 2.
⁶ Disclosure rules by Statistics Canada prevent a more disaggregated description of major field of study for this sample.
⁷ Naturally, a number of exceptions apply. For example, many engineers would be employed in the last category, trades/primary production/processing.
⁸ One exception is females with high school only. Their employment rate increases from 79.9% one year after leaving school to 84.4% two years after leaving school.

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Date Modified:: 2008-01-24

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