Labor market performance gaps and the role of secondary vocational education at meister high school in Korea

Figures & data

Table 1. Analysis variable in KEEP II

Dimension		Variable	Characteristics of variable	Data
Influencing factor	Characteristic of high school	School type	MSH = 1, SVHS = 2	1st
		School location	17 cities and provinces (Seoul = 1, Jeju = 17)	1st
	Individual characteristic	Father’s education level	None = 1, Elementary = 2, Middle school = 3, High school = 4, College = 5, University = 6, Master graduate = 7, Doctoral graduate = 8	1st
		Mother’s education level	None = 1, Elementary = 2, Middle school = 3, High school = 4, College = 5, University = 6, Master graduate = 7, Doctoral graduate = 8	1st
		Monthly income of household	Log value of the monthly income of household	1st
		Understanding of vocational courses	Understanding degree on the contents of vocational courses (Never = 1, Very much = 5)	1st, 2nd
		Participation of vocational courses	Participation hours of the vocational courses (Never = 1, Very much = 5)	1st, 2nd
Labor market performance		Employment status	Employment = 1, Unemployment = 2	4th
		Workplace size	Total number of employees (1 ~ 4 = 1, 5 ~ 9 = 2, 10 ~ 29 = 3, 30 ~ 49 = 4, 50 ~ 69 = 5, 70 ~ 99 = 6, 100–299 = 7, 300 ~ 499 = 8, 500 ~ 999 = 9, 1,000 or more = 10)	4th
		Working form	Regular = 1, Temporary = 2, Daily = 3	4th
		Job pattern	Permanent(full time) = 1, Permanent(part time) = 2, Non-permanent(full time) = 3, Non-permanent(part time) = 4	4th
		Monthly average salary	Log value of the monthly average salary	4th
		Labor contract	Less than 1 month = 1, More than 1 month~Less than 1 year = 2, More than 1 year~Less than 2 years = 3, More than 2 years~Less than 3 years = 4, More than 3 years = 5	4th
		After expiration of contract	Re-contract = 1, Indefinite contract = 2, Non-contract = 3, Fluid = 4	4th
		Type of working hours	Part time = 1, Full time = 2	4th
		Working days	Log value of the average working days per week	4th
		Working hours	Log value of the total working hours per week	4th
		welfare	Registration status of retirement benefits, bonuses, overtime pay, paid leave, corporate pension, national pension, national health insurance, employment insurance, industrial accident insurance (Yes = 1, No = 2)	4th
		Subjective labor market performance	Horizontal mismatch, Vertical mismatch, Job satisfaction, Wage satisfaction, Welfare satisfaction, Working hours satisfaction, Working environment satisfaction, Stability satisfaction (Never = 1, Very much = 5)	3rd, 4th
		Life satisfaction	Overall Satisfaction with High School Life, Overall Satisfaction with Workplace Life (Never = 1, Very much = 5)	1 ~ 4th

Figure 1. PSM Graph (Density balance)

Table 2. PSM on predictors of labor market performance

Predictors		Before PSM (n = 2,344)				After PSM (n = 1,166)
		MHS (n = 741)	SVHS (n = 1,603)	Mean difference	t-value	MHS (n = 694)	SVHS (n = 472)	Mean difference	t-value
School Location (%)	Seoul	5.5	13.7	0.753	3.694***	5.3	8.9	0.096	0.244
	Busan	8.4	7.3			8.6	8.5
	Daegu	6.3	4.9			6.2	4.9
	Incheon	4.9	7.9			4.5	6.8
	Gwangju	2.8	3.2			2.6	2.8
	Deajeon	7.1	2.5			6.6	3.4
	Ulsan	10.4	2.9			10.1	5.1
	Gyeonggi	5.9	18.5			6.2	11.7
	Kangwon	3.8	2.2			4	3.2
	Chungcheong	13.5	10.7			13.8	12.7
	Jeolla	15.2	11.9			15.6	15.7
	Gyeongsang	16.2	12.4			16.4	15.1
	Jeju	0	1.9			0	1.5
Father Edu-level(%)	High school below	57.6	69.3	0.251	5.393***	57.6	63.1	0.143	1.873
	Undergraduate	39.5	28.9			39.5	35.2
	Graduate	2.9	1.8			2.9	1.7
Mother Edu-level(%)	High school below	59.2	73.7	0.38	8.560***	58.4	64.6	0.073	0.083
	Undergraduate	38.5	24.9			39.2	34.1
	Graduate	2.3	1.4			2.4	1.3
Household income (Monthly, Won)		471.5	427.8	43.739	3.096**	479.3	469.5	9.738	0.614

*PSM formula (Rosenbaum & Rubin, 1983): e_i = Pr(Z_i = 1|X_i), the probability of conditional treatment assignment on observed baseline covariates

***p < .01, ***p < .001

Table 3. Objective labor market performances

Objective Labor Market Performance	MHS		SVHS		t-value
	M	SD	M	SD
Current status of employment	1.47	0.5	1.65	0.47	−4.269***
Workplace size	7.35	2.76	4.76	3.1	7.685***
Job pattern	1.09	0.28	1.24	0.49	−3.906***
Work type	1.28	0.72	1.72	1.12	−4.713***
Monthly salary	224.73	57.53	184.63	55.25	5.050***
Working contract period	3.07	0.88	2.98	1.11	0.276
Situation after the contract	1.33	0.61	2.13	1.34	−3.975***
Working hours type	1.94	0.24	1.76	0.42	5.323***
Working days per week	5.13	0.57	4.91	0.89	2.106*
Working hours per week	42.13	10.05	38.2	14.39	3.053**
Severance pay	1.13	0.33	1.21	0.41	−2.066*
Bonus	1.2	0.4	1.42	0.49	−4.479***
Overtime pay	1.23	0.42	1.41	0.49	−3.506**
Paid vacation	1.23	0.42	1.49	0.5	−5.068***
Corporate pension	1.71	0.45	1.88	0.32	−3.103**
National pension	1.11	0.31	1.25	0.43	−3.373**
National health insurance	1.06	0.24	1.17	0.37	−3.471**
Unemployment insurance	1.1	0.3	1.17	0.37	−1.888
Industrial injury insurance	1.09	0.28	1.18	0.38	−2.587*

**p < .05, **p < .01, ***p < .001

Table 4. Subjective labor market performance

Subjective Performance	Descriptive statistics				MANOVA
	MHS		SVHS		School type	School type × Vocational courses achievement
	M	SD	M	SD	F-value (Pillai’s Trace)	F-value (Pillai’s Trace)
Horizontal mismatch(1st year)	3.59	0.89	3.23	1	6.202**	3.126***
Horizontal mismatch(2nd year)	3.68	0.88	3.26	0.93	9.936**	2.466***
Vertical mismatch(1st year)	2.75	0.48	2.97	0.57	7.062**	1.595*
Vertical mismatch(2nd year)	3.09	0.67	3.04	0.61	0.264	0.863
Job satisfaction(1st year)	3.82	0.66	3.49	0.8	8.718**	1.659*
Job satisfaction(2nd year)	3.45	0.78	3.42	0.75	0.046	1.372
Wage satisfaction(1st year)	3.73	0.77	3.34	0.95	8.811**	1.083
Wage satisfaction(2nd year)	3.43	0.83	3.23	0.88	2.609	1.109
Welfare satisfaction(1st year)	3.64	0.88	3.34	0.98	4.791*	1.399
Welfare satisfaction(2nd year)	3.41	0.95	3.29	0.91	0.844	1.029
Satisfaction with working hours(1st year)	3.84	0.85	3.7	0.92	1.153	2.022**
Satisfaction with working hours(2nd year)	3.7	0.91	3.6	0.82	0.685	1.299
Satisfaction with working environment(1st year)	3.73	0.65	3.74	0.79	0.001	1.411
Satisfaction with working environment(2nd year)	3.63	0.8	3.6	0.81	0.036	1.749*
Stability satisfaction(1st year)	3.75	0.84	3.6	0.86	1.419	1.746*
Stability satisfaction(2nd year)	3.66	0.9	3.56	0.81	0.774	1.263

*Significance of School type (Blau & Duncan model): Pillai’s Trace = 0.129, F(20,380) = 2.820, p = 0.000

*Significance of School type×Vocational courses achievement (Wisconsin model): Pillai’s Trace = 1.434, F(464, 5584) = 1.185, p = 0.005

**p < .05, **p < .01, ***p < .001

Table 5. Effects of labor market performance

Satisfaction	Descriptive statistics				MANOVA
	MHS		SVHS		School type	School type ×
						Vocational courses achievement
	M	SD	M	SD	F-value	F-value
					(Pillai’s Trace)	(Pillai’s Trace)
School-life(1^st year)	3.85	0.87	3.73	0.77	1	3.392***
School-life(2^nd year)	3.92	0.71	3.87	0.73	0.275	2.108**
Work-life(1^st year)	3.9	0.53	3.56	0.74	10.154**	1.756**
Work-life(2^nd year)	3.73	0.66	3.45	0.76	6.345*	1.798**

*Significance of School type (Blau & Duncan model): Wilk’s Lambda = 0.956, F(8, 372) = 2.125, p = 0.033

*Significance of School type×Vocational courses achievement (Wisconsin model): Pillai’s Trace = 0.915, F(232, 2800) = 1.558, p = 0.000

**p < .05, **p < .01, ***p < .001

Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55. https://doi.org/10.1093/biomet/70.1.41

 Web of Science ®Google Scholar