A. Adult Education and Training (AET) Participation Rates

Before estimating the wage returns to the AET participation, I begin by comparing the AET participation rates by country. Columns (1), (2), and (3) of Table 2 present the participation rates of all AET, job-related AET, non-job-related AET, respectively. Numbers in square brackets in each column indicate the ranking of a given country out of all 33 countries. Column (4) in Table 2 indicates the number of observations for each country. The countries in Table 2 are arranged in descending order of their AET participation rates in column (1). All statistics in Table 2 were computed using the sampling weights of the OECD Survey of Adult Skills.

Column (1) in Table 2 shows that Anglo-Saxon and Scandinavian countries tend to have high AET participation rates. New Zealand (66.8%) has the highest AET participation rate among the 33 countries, followed by Denmark (66.1%) and Finland (65.9%). On the other hand, the AET participation rates in eastern and southern European countries are relatively low. Russia (19.9%) has the lowest rate, followed by Greece (20.5%), Turkey (22.8%), and Italy (24.3%). The AET participation rate of Korea is 50.0%, placing Korea 16th among the 33 countries, similar to the rate of Israel (50.4%) and Austria (48.8%).

Comparing columns (2) and (3) of Table 2, it can be seen that Korea's AET participation tends to be biased toward non-job-related AET. In Korea, 38.0% of the Respondents reported that they had participated in job-related AET, ranking the country 21st out of the 33 countries. On the other hand, 12.0% reported that they had participated in non-job-related AET, second highest out of the 33 countries. To summarize the results in Table 2, AET participation of Korea, relative to the rates of other countries, tends to be skewed toward AET with low job relevance. Table A2 in the appendix shows replicated results relative to those in Table 2 for the restricted sample of 98,115 workers for which the wage equations are estimated in the following sub-section. The results in Table A2 also confirm that AET participation by Korean workers is skewed toward non-job-related AET.

TABLE 2

ADULT EDUCATION AND TRAINING (AET) PARTICIPATION RATE

Note: 1) Countries are listed in descending order of the adult education and training (AET) participation rate, 2) Numbers in brackets denote the ranking of a given country’s AET participation rate among the 33 countries listed.

Source: Data from the OECD Survey of Adult Skills.

B. Estimating Wage Returns to the AET Participation

In order to estimate the wage returns to AET participation across countries, I consider the following regression equation:

where ln(wage_ic) indicates the natural logarithm of the hourly wage rate of worker i in country c , AET_ic is an indicator for whether worker i reported any participation in AET within the last 12 months,5 X_ic denotes a vector of covariates of worker i , in this case gender, age, years of schooling, years of current employer tenure, a dummy for permanent-contract worker, numeracy scores in units of ten percentile scores within country c , a dummy for public-sector worker, a list of dummies for the size of the workplace (less than ten workers, 11~250 workers, 251~1000 workers, 1001 workers or more), a list of dummies for ten occupation categories, and a list of dummies for 21 industry categories. δ_c represent a list of dummies for each country c , or country fixed effects. Finally, ε_ic is an error term.

β₁ in equation (1) identifies the difference in log hourly wages between those who participated in AET and those who did not participate in AET within country c , controlling for the worker characteristics included in X_ic . I estimate equation (1) with the ordinary least square (OLS) method, clustering standard errors at the country level.

The estimation result of equation (1) is summarized in column (1) of Table 3. I found that AET participation is associated with a 7.0% increase in hourly wages, conditional on the country and the worker characteristics. Columns (2) to (5) of Table 3 show the estimation results of equation (1) for Korea and for the three major countries of the U.S., Japan, and Germany, respectively. The estimated wage return to AET participation is 11.4% in Korea, which is higher than those of the 33 countries (7.0%) higher than Germany (8.0%), and similar to that of Japan (11.3%). The estimated wage return to AET participation in the U.S. is statistically insignificant.

Figure 1 shows the distribution of the β₁ estimates in equation (1) across all 33 countries, including the four major countries analyzed in Table 3. Korea’s estimate (0.114) is denoted by the vertical line. It can be seen that the estimate for Korea is located in the upper part of the distribution. This suggests that Korea’s estimated wage return to AET participation tends to be larger than those of other countries.

FIGURE 1.

DISTRIBUTION OF WAGE RETURNS TO AET PARTICIPATION ACROSS 33 COUNTRIES

Note: The wage return estimate in Korea (0.114) is indicated by the vertical line.

Source: Data from the OECD Survey of Adult Skills.

Although equation (1) controls for various worker characteristics, including a worker’s cognitive ability, there may be unobserved factors that affect both hourly wages and AET participation. This can lead to selection bias in β₁ in equation (1). In other words, based on the estimation results in Table 3, it is difficult to distinguish whether AET participation increases hourly wages or whether high- wage workers are more likely to participate in AET than low-wage workers.

TABLE 3

WAGE RETURNS TO AET PARTICIPATION

Note: 1) The dependent variable is the natural logarithm of hourly wage, 2) All statistics are calculated using sampling weights, 3) Robust standard errors are in parentheses, 4) In column (1), country fixed effects are additionally controlled and the standard errors are clustered at the country level.

Source: Data from the OECD Survey of Adult Skills.

Considering the potential endogenous selection into AET participation, I estimate the following regression equation:

where AETJR_ic is an indicator for whether worker i reported that he or she had participated in job-related AET within the last 12 months. All other variables and the parameters in equation (2) are defined as those in equation (1). Unlike equation (1), equation (2) includes AETJR_ic as an additional explanatory variable. With the inclusion of AETJR_ic , θ₂ in equation (2) identifies the difference in log hourly wages between those who participated in non-job-related AET and those who did not participate in any type of AET within country c , controlling for the worker characteristics in X_ic , θ₁ in equation (2) identifies the difference in log hourly wages between those who participated in job-related AET and those who participated in non-job-related AET after controlling for the other covariates. Put differently, θ₁ refers to the additional wage returns that receiving job-related AET has over non-job-related AET participation. It may be reasonable to assume that receiving job-related AET will be better compensated in terms of wages than non-job-related AET in the labor market. Thus, if AET indeed causally increases hourly wages, any potential wage effect of job-related AET would be greater than that of non-job-related AET, and thus θ₁ is likely to be positive. In other words, a finding that θ₁ is close to zero for a given country suggests that the true wage return to AET participation is likely negligible for that country.

Column (1) of Table 4 summarizes the estimation results of equation (2) for the entire sample from 33 countries. The estimated θ₁ is -0.008 and is statistically insignificant, indicating that workers who received non-job-related AET earned as much as those who did not participate in any AET. On the other hand, the estimated θ₁ is 0.088 and statistically significant at the 1% level, implying that workers who received job-related AET earned about 8.8% more than those who participated in non-job-related AET. The fact that job-related AET is better compensated than non-job-related AET suggests that there is a positive wage return to AET participation.

TABLE 4

WAGE RETURNS TO AET PARTICIPATION BY JOB RELEVANCE

Note: 1) The dependent variable is the natural logarithm of hourly wage, 2) All statistics are calculated using sampling weights, 3) Robust standard errors are in parentheses, 4) In column (1), country fixed effects are additionally controlled and the standard errors are clustered at the country level.

Source: Data from the OECD Survey of Adult Skills.

The country-specific results in columns (3) to (5) for the U.S., Japan, and Germany also suggest that there are positive wage returns to AET participation in each of the three countries. The estimated values of θ₁ , capturing the additional wage return to job-related AET over non-job-related AET, are all positive, despite the imprecise estimation for Japan. The size of the additional wage returns of receiving job-related AET over non-job-related AET is largest in the U.S. at 11.3%, with German also at 8.2%; in Japan, although statistically insignificant, at 2.8% the size is non-negligible.

In contrast, the result for Korea in column (2) reveals that there is no additional wage return of receiving job-related AET over non-job-related AET. The estimated θ₁ is -0.006, which is close to zero and statistically insignificant. This indicates that workers who received job-related AET earn just as much as workers who received non-job-related AET in Korea, which casts doubt on the existence of a positive wage return to AET participation in Korea.

Figure 2 presents the distribution of the θ₁ estimates in equation (2) across all 33 countries, with Korea’s estimate (-0.006) represented by the vertical line. This figure shows that the estimate for Korea is relatively close to the bottom of the distribution, suggesting that the additional wage return on job-related AET participation over non-job-related AET participation in Korea is typically lower than in many other countries.

FIGURE 2.

DISTRIBUTION OF ADDITIONAL WAGE RETURNS TO JOB-RELATED AET PARTICIPATION OVER NON-JOB-RELATED AET PARTICIPATION ACROSS 33 COUNTRIES

Note: The additional wage return estimate in Korea (-0.006) is indicated by the vertical line.

Source: Data from the OECD Survey of Adult Skills.

C. Korea’s Unique Wage Compensation Structure

The estimation results in Table 4 also reveal several differences in the estimated wage equations between Korea and other countries. First, the estimated wage returns to job tenure in Korea are substantially greater than those of the major countries. It is estimated that an additional year of job tenure is associated with approximately a 2.0% increase in the hourly wage in Korea, more than double the corresponding amount for all 33 countries (0.8%) and in the U.S. (0.8%), Japan (1.0%), and Germany (1.0%).

Second, the estimated wage returns to cognitive ability (numeracy score) in Korea are substantially smaller than those of the other countries. When a worker’s cognitive ability increases by ten percentile scores, hourly wages tend to increase by 2.7% in the U.S., 2.2% in Japan and Germany, and 2.3% in the 33 countries as a whole. On the other hand, there is no statistically significant increase in hourly wage in Korea. Third, the estimated wage returns to the workplace size in Korea show a more extreme pattern than those in other countries. Looking at the results for the 33 countries in column (1) of Table 4, hourly wages tend to increase gradually as the workplace size increases. Compared to the reference group of workers in workplaces with fewer than ten employees, the estimated wage returns to working in firms with eleven to 50 employees, those with 51 to 250 employees, those with 251 to 1,000 employees, and those with 1,001 or more employees are 7.1%, 11.9%, 19.6%, and 28.2%, respectively. Similar corresponding wage gap patterns according to the workplace size are confirmed in the cases of the U.S., Japan, and Germany. On the other hand, the results for Korea in column (2) show that only workers in workplaces with 1,001 or more employees show a statistically significant wage premium of 25.6% compared to the reference group, while the hourly wage levels of workers at smaller workplaces are statistically insignificant relative to those of the reference group.

D. Characteristics of AET Participating Workers

To summarize the main findings thus far, although Korea has a larger wage gap according to AET participation (Table 3), it is unclear whether AET participation in Korea causally increases hourly wages (Table 4). This suggests the possibility that high-wage workers tend to participate more actively in AET than low-wage workers in Korea. To compare the characteristics of workers participating in AET in Korea with the corresponding rates in other countries, I estimate the following regression equation:

where AET_ic and X_ic are correspondingly defined as in equations (1) and (2). μ_c and φ_ic are country fixed effects and the error term, respectively. I estimate equation (3) with the OLS method or the linear probability model, clustering standard errors at the country level.

Column (1) in Table 5 summarizes the OLS estimation results for the entire sample from 33 countries. The results generally show that the AET participation rate is higher for men than for women, higher among the younger than the elderly, higher as the levels of education and cognitive skills increase, and higher among those employed in the public sector and/or large-sized workplaces. These results are generally consistent with economic theory or empirical findings. For example, human capital theory predicts that younger workers have a greater incentive to participate in education because they have a longer period to recoup the human capital investment. The theory also predicts that on-the-job training investments more commonly occur in stable employment relationships, often characterized as those in public sector and/or large enterprises. It has also been reported that college graduates are the most active AET participants in most countries (OECD, 2021).

The country-specific results in columns (2) to (5) in Table 5 reveal that Korea’s AET participation is mainly associated with job characteristics, rather than worker characteristics, relative to other countries. First, permanent-contract workers in Korea are approximately 4% points more likely to participate in AET than temporary-contract workers, whereas no statistically significant difference was observed for the other major countries assessed here. Second, the gap in the AET participation rate between public and private sector workers tends to be substantially larger in Korea (about 10.0% points) than in the three major countries (about 6.2% points in the U.S.; statistically insignificant in Japan and Germany). Third, the disparity in AET participation rates by workplace size is significantly greater in Korea than in the three major countries. The gap in the AET participation rate between workplaces with more than 1,000 employees and those with ten or fewer employees amounts to approximately 31.1% points in Korea but only 9.9% points in the U.S., 8.1% points in Japan, and 13.9% points in Germany. Park (2019) argued that because government subsidies for AET in Korea are mainly financed by the Employment Insurance Fund, AET participation is biased toward permanent-contract workers in the public sector and at large corporations, where the employment insurance coverage rate is high. The finding that AET participation in Korea is largely concentrated among permanent-contract workers in the public sector and/or large-sized workplaces, as shown in Table 5, may be related to the country’s AET financing structure, as indicated in Park (2019).

TABLE 5

DETERMINANTS OF AET PARTICIPATION

Note: 1) The dependent variable is an indicator for AET participation within the last 12 months, 2) All statistics are calculated using sampling weights, 3) Robust standard errors are in parentheses, 4) In column (1), country fixed effects are additionally controlled and the standard errors are clustered at the country level.

Source: Data from the OECD Survey of Adult Skills.