KRIVET Issue Brief People are Our Hope
The Effects of Drinking and Smoking on 4-Year College Graduates’ Wages
- Four-year college graduates earn an average monthly salary of 2.26 million won. Female graduates receive 84.0% of what their male counterparts receive, and the monthly average wage of 4-year college graduates from capital-area universities is the highest.
- Based on the results of the regression analysis, with all other conditions being equal, the wage of those who drank at least 3–4 times a week was higher than that of others who did not by 5.6% on average, while the wage of those who smoked at least 21 cigarettes a day was higher than that of others who did not smoke by 3.5%, on average.
- The need to realign the relationship-centered labor market into one focused on productivity and introduce a scheme imposing an appropriate tax level on alcoholic beverages and cigarettes to offset the potential economic gains of their use and thereby contain their consumption has arisen.
01 Need for the study and data
| Assuming that the effects of drinking and smoking on wages vary by labor market structure, policy implications are drawn by analyzing how they vary in the salaries of 4-year college graduates.
Alcohol and cigarettes are mild stimulants, but their consumption significantly affects social life. Drinking and smoking can enhance productivity through collaboration by facilitating interpersonal relationships but is simultaneously harmful to one’s health (and that of others) and addictive.
- Therefore, it is necessary to identify the effects of drinking and smoking on the income levels of the employed and college- graduate wage-earners in Korea and consider policy responses.
| Data: The Graduate Occupational Mobility Survey (2016GOMS1) conducted September 1, 2017
Study subjects and data: Respondents to 2016GOMS11) as described in 2016GOMS
- Respondents of the 2016GOMS1 survey were used as a final dataset for this study and equaled 8,614 4-year college graduates who graduated in August 2015 (1,936) and February 2016 (6,678) with bachelor’s degrees. They were employed earning wages as of September 1, 2017. The gender distribution, college locations, and majors are shown in Table 1.
<Table 1> Demographic Distribution of the Study Subjects (n=8,614) Category Distribution Percentage
(%) Category Distribution Percentage (%)
Gender Women 3,743 43.45
Majors
Humanities 1,115 12.94
Men 4,871 56.55 Social sciences 1,800 20.9
Location of colleges
Seoul 2,224 25.82 Education 590 6.85
Gyeonggi 1,592 18.48 Engineering 2,659 30.87
Chungcheong 1,565 18.17 Natural sciences 1,234 14.33
Gyeongsang 2,227 25.85 Medicine 491 5.7
Jeolla 1,006 11.68 Art, music,
physical
education 725 8.42
I Footnote I
1) Refers to “unpaid family workers” without income and “employers” or “self- employed” for whom capital and other conditions are likely to affect income. “Part- time” respondents whose job description is not consistent and whose incomes change significantly depending on the amount of work time were excluded from the analysis. Additionally, the upper and lower 1% of wage earners were excluded from the sample data because the number could have been entered by mistake, and the daily, monthly, and annual salaries could have been selected incorrectly.
Publisher: Young Sun Ra | Date of issue: November 29, 2020 | Issued by: Korea Research Institute for Vocational Education and Training (KRIVET)
2020 No.194
KRIVET Issue Brief
Data analysis: To analyze the data of 4-year college graduates’ drinking and smoking, descriptive statistics, the ordinary least square (OLS) model, the logistic regression model, and maximum likelihood estimates with Heckman’s sample were employed.
Analysis content: The Effects of Drinking and Smoking on 4-Year College Graduates’ Wages.
02 Descriptive statistics of 4-year college graduates ’ drinking and smoking
| Among Korea’s 4-year college graduates who earned wages, 70.4% drank but did not smoke, 17.4% drank and smoked, 11.0% neither drank nor smoked, and 1.2% smoked but did not drink.
Of the 4-year college graduates who were employed, the majority drank (87.8%). Of these, most drank 1–2 times a month (37.6%), and many drank 1–2 times a week (36.5%). This was higher than the average drinking rate of Koreans aged 19 or older (77.2%; 2017 National Health and Nutrition Survey).
- The majority of 4-year college graduates (81.4%) did not smoke, and among smokers, most smoked 6–10 cigarettes per day (8.7%), followed by 16–20 cigarettes per day (3.3%). This was similar to the average non-smoking ratio of people aged 19 or older (81.9%; 2017 National Health and Nutrition Survey).
- Of those employed, 17.4% (1,502) reported both drinking and smoking, and 11.0% (945) reported neither drinking nor smoking.
- 70.4% (6,063) said they drank but did not smoke, and 1.2% (104) said they smoked but did not drink.
<Table 2> Drinking and Smoking among Four-year College Graduates
(Unit: people, %)
Non-smoking 1–5
cigarettes a day 6–10
cigarettes a day 11–15
cigarettes a day 16–20
cigarettes a day More than 21
cigarettes a day Total (%) Non-
drinking 945 28 47 13 16 0 12.18
1–2 times a
year 522 10 21 8 15 0 6.69
1–2 times a
month 2,794 87 215 73 68 5 37.64
1–2 times a
week 2,360 109 398 139 129 11 36.52
3–4 times a
week 340 31 60 28 51 5 5.98
Almost
every day 47 7 11 8 8 5 1.00
Total (%) 81.36 3.16 8.73 3.12 3.33 0.30 100.0
임.
임.
03 Income distribution of 4-year college graduates
| The average monthly wage of 4-year college graduates was 2.26 million won, but graduates from capital-area colleges earned considerably more. Graduates majoring in arts and sports earned significantly lower statistically.
A college graduate’s average monthly salary was 2.263 million won, ranging from 500,000 won to 5 million won.
- By gender, the average salary of men (2.431 million won) was 388,000 won, higher than that of women (2.043 million won;
t=23.48, p<.001).
In terms of college location, graduates from capital-area universities earned significantly more, validating the so-called
“in-Seoul premium” in post-graduate income. In comparison, the statistical significance of the Chungcheong and Jeolla provinces was much lower.
- Graduates specializing in medical and engineering earned extremely high wages upon graduation, while graduates concentrating in the arts and sports earned much less.
[Figure 1] Wage level by college location and major I Note I
χ2(25)=478.9920, p<.001
247.3
223.3
217.3
221.6
209.0 250.0
240.0
230.0
220.0
210.0
200.0
Seoul Gyeonggi Chungcheong Gyeongsang Jeolla
207.5 230.5
222.5 246.9
208.5 247.6
188.0 250.0
240.0 230.0 220.0 210.0 200.0 190.0 180.0
Humanities Social
sciences Education Engineering Natural Medicine sciences Art, music,
physical education
November 29, 2020
<Table 3> Comparative Verification of Wages by College Location and Major
Category F-test result Comparison group t-test result
College location
and wage F(4, 8,609)=61.75*
Gyeonggi vs. Seoul t=-9.48*
Chungcheong vs. Seoul t=-11.77*
Gyeongsang vs. Seoul t=-11.10*
Jeolla vs. Seoul t=-13.06*
Jeolla vs. Gyeonggi t=-4.59*
Jeolla vs. Gyeongsang t=-4.30*
Major and wage F(6, 8,607)=93.53*
Arts and sports vs. humanities t=5.38*
Arts and sports vs. social sciences t=12.71*
Arts and sports vs. education t=8.20*
Arts and sports vs. engineering t=18.50*
Arts and sports vs. natural sciences t=5.77*
Arts and sports vs. medicine t=13.43*
04 Drinking, smoking and wages of college graduates
| The higher the frequency of drinking, the more positive its influence on overall salary; smoking frequency had to be above a certain level to have a positive effect.
Looking at the wage differences, depending on drinking frequency, the salaries of the non-drinking and low-frequency drinking groups were significantly lower, and salary increased as drinking frequency increased.
- The salaries of employed graduates who did not drink at all were lower than those of the drinking group. However, there was no significant difference in wages between the very low-frequency drinking group (1–2 times a year) and the non-drinking group.
- Respondents who said they drink more than 1–2 times a month earned significantly higher income statistically than those who did not drink. In particular, the average wage of those who drink 3–4 times a week was the highest, which suggests that drinking contributes to increasing wages.
- Drinking volume and average wage were estimated to show a concave curve to the origin, and the explanatory power of the trend line was high (0.88).
Depending on smoking frequency, smokers had a significantly higher wage level on average than non-smokers.
- The wages of employed graduates who did not smoke tended to be lower than that of the smoking group. However, those who smoked 1–5 cigarettes a day showed no statistically significant difference from non-smokers in terms of wage.
- Those who smoked 6–20 cigarettes a day had a significantly higher wage than non-smokers statistically.
- Smoking frequency and average wage were estimated to show a convex curve to the origin, and the explanatory power was high (0.91).
[Figure 2] Drinking and Smoking Frequency and Wage Level
<Table 4> Comparative Verification of Wages by Drinking and Smoking Groups
Category F-test result Comparison group t-test result
Drinking and wages F(5, 8,608)=62.72*
1–2 times a month vs. non-drinking t=5.75*
1–2 times a week vs. non-drinking t=13.66*
3–4 times a week vs. non-drinking t=10.46*
Almost every day vs. non-drinking t=4.14*
3–4 times a week vs. 1–2 times a year t=10.07*
3–4 times a week vs. 1–2 times a week t=11.30*
Smoking and wages F(5, 8,608)=11.90*
1–5 cigarettes (per day) vs. non-smoking t=0.30 6–10 cigarettes (per day) vs. non-smoking t=5.36*
11–15 cigarettes (per day) vs. non-smoking t=3.72#
16–20 cigarettes (per day) vs. non-smoking t=4.17*
More than 21 cigarettes (per day) vs. non-smoking t=2.44 6–10 cigarettes (per day) vs. 16–20 cigarettes (per day) t=2.64 I Note I
χ2(25)=478.9920, p<.001
I Note I
Significant when lower than the
*=.001, #=.05 level.
Drinking Smoking
203.5 205.9
219.3 241.1
246.9
239.3 250.0
240.0
230.0
220.0
210.0
200.0
drinking Non- 1–2 times a year 1–2 times
a month 1–2 times
a week Almost
every day 3–4 times
a week y=-1.4289x2+19.244x+180.31
R2=0.8761
223.5
239.6 241.6 243.1
261.0 270.0
260.0
250.0
240.0
230.0
220.0
smoking Non- 1–5 cigarettes 6–10
cigarettes 11–15
cigarettes More than 16–20 21
cigarettes 225.0
y=0.5282x2+3.2695x+219.5 R2=0.9111
KRIVET Issue Brief
｜ KRIVET Social Policy Building, Sejong National Research Complex, 370, Sicheong-daero, Sejong-si, Republic of Korea ｜ Tel: 044-415-5000/5100 ｜ www.krivet.re.kr ｜
05 Multidimensional influence analysis of the effect of college graduates ’ drinking and smoking on wages
| A regression analysis considering other variables simultaneously revealed that drinking more than 3–4 times a week and smoking more than 21 cigarettes a day had an evident positive effect on wages.
As a result of the estimation, drinking and smoking had a positive effect on wage increase, with the effect of drinking being higher than that of smoking.
- Other conditions being equal, drinking more than 3–4 times a week increased wages by more than 5.6% compared to non- drinkers, and smoking more than 21 cigarettes a day increased salaries by more than 3.5% compared to non-smokers (Model III).
- Alternatively, those who smoked fewer than 10 cigarettes a day had lower wages than non-smokers, whereas those who smoked more than 11 cigarettes (Model II), or 16 cigarettes (Model III) had increased salaries.
[Table 5] Effects of Drinking and Smoking on Employed College Graduates’ Income ㅤ
ㅤ
Model I Model II Model III
B S.E. B S.E. B S.E.
Drinking
1–2 times a year 0.010*** 0.0027 0.009*** 0.0028
1–2 times a month 0.018*** 0.0019 0.018*** 0.0019
1–2 times a week 0.043*** 0.0019 0.043*** 0.0019
3–4 times a week 0.057*** 0.0029 0.056*** 0.0029
Almost every day 0.048*** 0.0059 0.045*** 0.0060
Smoking (day)
1–5 cigarettes -0.023*** 0.0034 -0.025*** 0.0035
6–10 cigarettes -0.004* 0.0021 -0.009*** 0.0021
11–15 cigarettes 0.011*** 0.0034 0.005 0.0035
16–20 cigarettes 0.019*** 0.0032 0.012*** 0.0032
More than 21 cigarettes 0.047*** 0.0109 0.035*** 0.0109
Constant term 4.454*** 0.0292 4.504*** 0.0292 4.467*** 0.0292
Lambda (λ) -0.060*** 0.0037 -0.063** 0.0037 -0.071*** 0.0036
Cut/Non-Cut/Wald 1,553/6,069/107,977 1,553/6,069/106,725 1,553/6,069/107,248
06 Implications
The premium in income earned by graduates from capital-area colleges was confirmed; the negative premium received by arts and sports majors was also evident.
- The need to resolve differences between colleges by regional location and support for the transition of the labor market by major is proposed.
Among employed college graduates, the majority reported drinking but not smoking (70.4%), and many reported both drinking and smoking (17.4%); 11.0% of the respondents reported neither drinking nor smoking, and the sum of those who smoke but did not drink was minimal (1.2%).
- There was a mixed possibility that drinking or smoking negatively affected wages by harming health and positively affected wages by expanding social networks and increasing collaboration.
Drinking was found to have a positive effect on wages in proportion to its frequency. By contrast, those who smoke fewer times earned less than non-smokers, and increased smoking positively affected wages.
- These results are very different from studies in other countries, in which appropriate drinking positively affects wages, and drinking and smoking generally have a negative effect on wages. It seems that the Korean ways of handling work, when informal meetings or personal relationships are important, relate to wage increases.
- Therefore, measures need to be reviewed to improve efficiency through a productivity-oriented wage payment structure and curb consumption of stimulants to offset economic profits by imposing appropriate taxes on drinking and smoking.
Park, Cheonsoo (Ph.D., Senior Research Fellow, KRIVET) Park, HwaChoon (Ph.D., Associate Research Fellow, KRIVET)
I Note I
*Considering the sample selection bias, a general earnings profile function as a regression model was used, and the dependent variable was a log wage
I Note I
1) *p<1. **p<.05. ***p<.01.
2) 54 variables, including individuals (including gender, etc.), university (college, etc.), and work role (corporate size, etc.), were abbreviated; 69 standard selection variables were deleted.
