The effects and challenges of vocational training in Korea

Figures & data

Table 1. Classification of vocational training programs in Korea.

Training programs		Recipients of Financial Support
Target(s)	Goals	Employers	Individuals
Existing employees	Upgrade training	1) Employer-Initiated Vocational Skills Development Training 2) SME-specific Training 3) Consortium for National HRD	1) Naeil Baeum Card for Employees (Vocational Skills Development Account System)
Unemployed	Initial training		1) Naeil Baeum Card for the Unemployed (Vocational Skills Development Account System)
Training in Strategic areas		Training for National Basic and Strategic Industry

Note: Modified from Ministry of Employment and Labor "Human Development Service of Korea" (2015).

Figure 1. Trends in number of participants in skills development training. Source: Statistics of Korea (2019); Original data from Employment Insurance DB.

Figure 2. Expenditure for skills development training.Source: Statistics of Korea (2019); Original data from Employment Insurance DB.

Table 2. Characteristics of the Korean sample.

Variables	Mean	Standard deviation
Skills proficiency
Literacy score	267.2	39.7
Basic background
Age (years)	44.9	10.9
Female (%)	53.1	-
Hourly wage (Korean won)	15,447	13,487
Educational background
Lower secondary and below (%)	21.1	-
Upper secondary (%)	37.2	-
Tertiary – College (%)	17.0	-
Tertiary – University and above (%)	24.6	-
Non-formal education
Job-related (%)	36.1	-
No. of observations	5,481

Notes: The sample consists of Korean PIAAC participants aged 26–65. The number of observations in the parentheses represents the number of observations with problem-solving measures.

Source: PIAAC data from OECD (2013b)

Table 3. Characteristics of non-formal job-related education participants vs. non-participants in the sample.

	Participants (36.1%)		Non-participants (63.6%)
	Mean	SD	Mean	SD
Skills proficiency
Literacy score	281.3	35.0	259.2	40.0
Basic background
Age (years)	41.5	10.0	46.9	10.9
Female (indicator)	0.42	-	0.59	-
Hourly wage (Korean won)	17,731	13,781	13,162	12,791
Educational background
Lower secondary and below (%)	8.4	-	28.4	-
Upper secondary (%)	30.4	-	41.1	-
Tertiary – College (%)	22.6	-	13.8	-
Tertiary – University and above (%)	38.6	-	16.8	-
No. of observations	1,978		3,487

Notes: The sample consists of Korean PIAAC participants aged 26–65.

Source: PIAAC data from OECD (2013b)

Figure 3. Participation in non-formal job-related education by age group.

Source: PIAAC from OECD (2013b)

Table 4. Estimation results for wage equation.

	(1)	(2)	(3)	(4)
Non-formal job-related education	0.212*** (0.024)	0.168*** (0.024)	0.193*** (0.024)	0.157*** (0.024)
Age	0.073***	0.079***	0.074***	0.079***
	(0.010)	(0.010)	(0.010)	(0.010)
Age squared	−0.075***	−0.082***	−0.074***	−0.081***
	(0.012)	(0.012)	(0.012)	(0.012)
Female	−0.348***	−0.312***	−0.344***	−0.306***
	(0.024)	(0.029)	(0.023)	(0.029)
Lower secondary and below	−0.221***	−0.139***	−0.154***	−0.099*
	(0.047)	(0.049)	(0.051)	(0.052)
Tertiary – College	0.302***	0.205***	0.262***	0.184***
	(0.032)	(0.032)	(0.031)	(0.032)
Tertiary – University and above	0.499*** (0.030)	0.340*** ^(0.033)	0.422*** (0.031)	0.298*** (0.033)
Literacy skills			0.102***	0.074***
			(0.015)	(0.015)
Constant	7.467***	7.488***	7.433***	7.459***
	(0.215)	(0.221)	(0.216)	(0.222)
Industry and occupation	No	Yes	No	Yes
R-Square	0.314	0.368	0.329	0.376
N	2447	2430	2447	2430

Notes: Least squares regressions weighted by sampling weights are used. The dependent variable is the log of hourly earnings, including bonuses for wage and salary earners. The sample consists of full-time employees aged 26–65 who work at least 30 hrs per week. Age squared is divided by 100. The standardized literacy test scores are used as a skills measure. Robust standard errors are reported in parentheses. *, ** and *** indicate significance at the 10%, 5% and 1% levels, respectively.

Table 5. Estimation results for wage equation with age cohort effects.

	(1)	(2)	(3)	(4)
Non-formal job-related education	0.146***	0.125***	0.122***	0.108***
	(0.036)	(0.034)	(0.035)	(0.034)
Non-formal job-related education X 36–45 Age group	0.050	0.032	0.056	0.039
	(0.043)	(0.042)	(0.042)	(0.041)
X 46–55 Age group	0.114**	0.065	0.125**	0.079
	(0.056)	(0.055)	(0.056)	(0.055)
X 56–65 Age group	0.260***	0.218**	0.257***	0.221**
	(0.094)	(0.092)	(0.094)	(0.092)
Age	0.072***	0.080***	0.072***	0.079***
	(0.012)	(0.012)	(0.012)	(0.012)
Age squared	−0.077***	−0.086***	−0.075***	−0.084***
	(0.014)	(0.014)	(0.014)	(0.014)
Female	−0.348***	−0.311***	−0.344***	−0.306***
	(0.024)	(0.029)	(0.023)	(0.029)
Lower secondary and below	−0.202***	−0.126***	−0.135***	−0.085*
	(0.047)	(0.049)	(0.051)	(0.052)
Tertiary – College	0.302***	0.206***	0.262***	0.186***
	(0.032)	(0.032)	(0.031)	(0.032)
Tertiary – University and above	0.500***	0.343***	0.423***	0.301***
	(0.030)	(0.033)	(0.031)	(0.033)
Skills			0.102***	0.075***
			(0.015)	(0.015)
Constant	7.568***	7.507***	7.561***	7.509***
	(0.262)	(0.270)	(0.261)	(0.269)
Occupation & Industry	No	Yes	No	Yes
R-Square	0.317	0.370	0.332	0.378
No. of Observations	2447	2430	2447	2430

Notes: Least squares regressions weighted by sampling weights are used. The dependent variable is the log of hourly earnings, including bonuses for wage and salary earners. The sample consists of full-time employees aged 26–65 who work at least 30 hrs per week. Age squared is divided by 100. The standardized literacy test scores are used as a skill measure. Occupation and industry fixed effects are included in Columns (2) and (4). Robust standard errors are reported in parentheses. *, ** and *** indicate significance at the 10%, 5% and 1% levels, respectively.

Table 6. Estimation results for employment equation.

	(1)	(2)	(3)	(4)
Non-formal job-related education	0.286***	0.287***	0.279***	0.280***
	(0.014)	(0.014)	(0.025)	(0.025)
Non-formal job-related education X 36–45 Age group			−0.028	−0.028
			(0.027)	(0.027)
X 46–55 Age group			0.042	0.041
			(0.032)	(0.032)
X 56–65 Age group			0.075*	0.076*
			(0.046)	(0.046)
Age	0.060***	0.060***	0.062***	0.061***
	(0.006)	(0.006)	(0.007)	(0.007)
Age squared	−0.073***	−0.072***	−0.075***	−0.075***
	(0.006)	(0.006)	(0.008)	(0.008)
Female	−0.280***	−0.280***	−0.278***	−0.278***
	(0.014)	(0.014)	(0.014)	(0.014)
Lower secondary and below	−0.016	−0.023	−0.012	−0.019
	(0.023)	(0.023)	(0.023)	(0.024)
Tertiary – College	−0.020	−0.017	−0.020	−0.017
	(0.020)	(0.020)	(0.019)	(0.020)
Tertiary – University and above	−0.032*	−0.025	−0.030*	−0.023
	(0.018)	(0.019)	(0.018)	(0.019)
Literacy skills		−0.010		−0.009
		(0.009)		(0.009)
Constant	−0.448***	−0.440***	−0.466***	−0.459***
	(0.124)	(0.124)	(0.161)	(0.160)
R-Square	0.263	0.264	0.265	0.265
N	4299	4299	4299	4299

Notes: Least squares regressions weighted by sampling weights are used. The dependent variable is an indicator for employment last week. The sample consists of Korean respondents. Age squared is divided by 100. The standardized literacy test scores are used as a skills measure. Robust standard errors are reported in parentheses. *, ** and *** indicate significance at the 10%, 5% and 1% levels, respectively.

Ministry of Employment and Labor and Human Resource Development Service of Korea. (2015). Regional human resource development committee: A member of a standing committee workshop. Paper presented at the Regional Human Resource Development[in Korean], Seoul.

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Statistics of Korea (2019). Employment insurance DB. Seoul: Statistics of Korea (accessed Feb. 2019).

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Organization for Economic Co-operation and Development. (2013b). OECD skills outlook 2013. Paris: Author.

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