# Analytical Research for Marriage Delay in South Korea

Yoon Donghun

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Yoon Donghun. Analytical Research for Marriage Delay in South Korea. journal of economic and social development, 2023. hal-04132974

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# Analytical Research for Marriage Delay in South Korea

Yoon Donghun

Kyonggi University, South Korea

nature@kyonggi.ac.kr

## ABSTRACT

In existing research, the analysis of the cause of marriage delay has been focused on the educational level. Marriage influences the housing price because it increases housing demand. Also, it has greatly influenced the labor market participation of women. Marriage delay is the major factor of birthrate decrease because it decreases the child-bearing period and the possibility of childbearing in women. Finally, it is the major factor of the rate of decrease of the population and of economic growth. In this paper, we discuss the economic capacity as well as the educational level for the exact cause analysis. The purpose of this paper is cause analysis for marriage delay of singles in South Korea. We expect this research to propose new values for the government policy-making on marriage and birthrates through analysis of reasons for the delay in marriage. In this paper, we used the Korea Labor & Income Panel data (2004-2014). The survey was conducted among 500 men and women aged 20 to 40 through a marital status check for the last 10 years. In this study, we used estimation method and non-parametric statistics. In this paper, independent variables are the age, number of siblings, the metropolis residence, the economic level of family, the education level, the income, and the employment status. The dependent variable is the delay of marriage. Marriage encouragement is needed for birthrate increase. Also, analysis of the cause of the marriage delay of singles is essential for government policy-making. In this research, the sociocultural effect, the educational level, the economic capacity have been considered for the analysis of the cause of marriage delay. Also, we discussed the economic capacity as well as the educational level for the exact cause analysis.

**Keywords:** Analytical research, Marriage, South Korea, Economic growth, Society.

## 1. INTRODUCTION

Recently, marriages of singles have been gradually delayed in many countries around the world due to economic growth and the development of science and technology. Marriage delay leads to birthrate decrease. Therefore, the increase in the number of singles due to marriage delay is the major cause of a low birth rate. The marriage time is a very important economic and social variable because it influences the birthrate, the rate of the population growth, the labor supply, consumption. Social concern for the marriage delay of singles is on the rise in South Korea. The social and economic concerns have increased because the increase in the number of singles due to marriage delay is related to a low birth rate (Cherlin, 1980). Marriage delay leads to a lower birthrate because birth is possible through marriage. When marriage is delayed, the period when a woman can give birth decreases. This leads to a low birthrate because the childbearing period decreases. Therefore, scholars are watching marriage delay as the major cause of a low birthrate.

Recently, the increase in the number of singles is tantamount to a great change in the culture, customs, and thinking of the existing society. Marriage is delayed due to social structural factors and cultural influences. Economic growth and the advancement of science and technology are isolating people. Modern society is characterized by low economic growth, job reduction, competition for jobs, an increase in the number of temporary employees, early retirement, job instability. These are driving many people to choose to be single than to raise a family. These have also increased about the nuclear family, the one-person household, and the development of an individualistic culture. The present, freedom, self-realization, and economic satisfaction are more important than children and the future in an individualistic culture. Marriage and childbirth can be chosen depending on the conditions and the decision of individuals. Self-realization and economic satisfaction are becoming more and more important for social success. The social culture has a great influence on thinking and decision-making. In this research, the sociocultural effect, the educational level, the economic capacity were considered in the analysis of the cause of marriage delay.
The research organisation of this paper is introduction, literature review, research model, empirical results, and conclusions and limitations. The introduction is discussed and presented for the overall marriage delay of singles. The literature review discusses the single concept, the view on marriage, and the mate choice theory. The research model presents for factors that influence marriage and the analysis methodology. In this study, we used estimation method and non-parametric statistics. The estimation forecasts the parameters of the population through statistics calculation for the population sampling. The empirical results is discussed and presented for research results by the Korea Labor & Income Panel data (2004-2014). The discussion proposes in-depth discussion for research results and policy implication. Conclusions and limitations is discussed and presented for research results, the improvement of research limitations, and the future study.

## 2. LITERATURE REVIEW

The major preceding research on the marriage delay of singles was a quantitative research. Most studies on causes of marriage delay have discussed the income, educational level, job, employment status, etc. Preceding researches have found that socio-demographic variables (the income, educational level, job, employment status, etc.) influence the age at the first marriage (Cooney & Hogan, 1991). Also, in preceding researches, family variables have influenced the age at the first marriage. Family variables are the socio-economic status and the married state of the parents, the co-residence state of the parents, the origin and the number of siblings (Tambashe & Shaprio, 1996). Most studies on marriage delay are quantitative researches. They explain only the causes and the correlations of the marriage delay. They cannot clearly explain the essential meaning of marriage delay. Qualitative research is needed for marriage delay due to the limitations of quantitative research. In this paper, we discussed the economic capacity as well as the educational level for the analysis of the exact cause. We find a positive causal impact of marriage delay on wages, with a larger effect for women (Wang & Wang, 2017).

A single person is an unmarried man or woman. Single individuals are classified as voluntary singles and involuntary singles (Huston, 2000). Voluntary singles are unmarried men and women who prefer celibacy. Involuntary singles are unmarried men and women who cannot marry or have not yet found a marriage partner. However, they have a marriage intention. The single classification criterion is the marital status. It is decided through the legal marital status. Voluntary singles were selected for this study due to their satisfaction with single life, their negative image of married life, etc. In general, their personal reason for choosing to be single is their foremost reason for staying single, rather than their disbelief in and negative image of married life. A single lifestyle is suitable for the stable and steady and the conventional and conservative than for positive-minded people and those faithful to themselves. Also, the single lifestyle of the stable and steady is not suitable for marriage. Not all singles are voluntary singles due to their pursuit of their career. Involuntary singles are singles who could not marry regardless of their intention to do so due to their obligation to support their family, chance loss of marriage, lack of a suitable marriage partner, etc. In developed countries, most involuntary singles occur due to the lack of a suitable marriage partner than their obligation to provide family support. However, they can marry when they meet a suitable marriage partner. Chance loss of marriage is experienced more by conventional and conservative singles than by singles who are positive-minded and faithful to themselves. Carrington (2002) shows that marriage means standard and values pertaining to the choice of marriage and of the marriage partner in his view. The standard decides on the individual behavior pattern. Values suggest the rationality and basis of the behavior pattern. The view on marriage is defined by the standard and the basis for the choice of the marriage partner and the behavior pattern of the married life design. The view on marriage consists of the marriage purpose, the marriage motive, the choice of the marriage partner, the behavior pattern of the married life design. The view on marriage has been changed through a variety of interactions, the social status, and periodic changes in society. Variation in ideal marriage timing does not account for gender, racial/ethnic, and class gaps in hookup participation (Allison & Risman, 2017).

Singles expect compensatory results from marriage. Therefore, they choose a spouse with similar values. The spouse is chosen through the relative concept and the relative predominance. Conditions of singles are exchanged such as dealing with the marriage market. Also, the spouse is chosen through the
preference response result of the relative value. Equity means fairness. The equity theory assumes that singles hope for a fair relationship as a reward. The theory considers the charm of a fair relationship. It also considers the mutual fairness of the quality and the quantity for the resource exchange process (Cole, 2015). The spouse is chosen through the recognition of his or her relative value and his or her psychological resemblance with the individual. Most people are generally attracted to people with conditions similar to or the same as theirs (Zhang, 2014). Singles choose a spouse with a similar age, education level, intelligence, social position, interest, attitude, values, economic capacity. People charm each other through complementary factors. Complementary factors are classified as follows. First, people with a higher desire are attracted to people with a lower desire. Second, people are charmed by a person with a desire different from theirs. The social resource is preferred, but the character interacts based on different factors (Germanacos, 2006). People are also charmed by mutual complementary factors. The filter theory explains mutual complementary factors through the progress of a relationship for the spouse choice.

The average age at marriage of women has been rising in most developing countries including India (Caldwell et al., 1983). Lowest-low fertility appeared quite suddenly in the Republic of Korea although fertility has consistently declined for several decades. Demographers in the mid-1990s could not have predicted that fertility would fall so rapidly to such levels (Eun, 2007). Social norms and community and family structures have not yet adapted fully to this remarkable increase in singlehood (Jones, 2010). Based on the assumption that buying a house and entering parenthood are the most expensive decisions, this hypothesis implies that buying real estate and entering parenthood should be delayed the most in the case of fixed-term employment, followed by marriage (Baron & Rapp, 2019).

# 3. RESEARCH MODEL AND METHOD

## 3.1 Research model

In this paper, we designed a research model to pinpoint the reasons for late marriage. For this study, we analyzed the data using the Statistical Package for the Social Sciences (SPSS). In this study, we used estimation method and non-parametric statistics. The research model presented for factors that influence marriage and the analysis methodology. In this study, we used estimation method and non-parametric statistics. The estimation forecasted the parameters of the population through statistics calculation for the population sampling. The empirical results was discussed and presented for research results by the Korea Labor & Income Panel data (2004-2014). In this paper, we explain the late marriage phenomenon by analysis of reasons for the delay in marriage. In the existing research, the analysis of the causes of marriage delay was focused on the education level. In this paper, we focused on the economic capacity as well as the education level. In the research results, the marriage probability of the women with master's and bachelor's degrees were higher than that of the women with master's and doctor's degrees. The marriage probability of the male employees was higher than that of the unemployed males. The marriage probability of the permanent employees was higher than that of the temporary employees. Also, when the economic level of the family was below average at the age of 15, the marriage probability was low. The cost of the search for singles residing in the metropolis was lower than the cost of the search for singles residing in small and medium-sized cities. The marriage probability was higher with advancing years. When the men were 33.1 years old and the women were 27.6 years old, their marriage probability started to decline. Also, the opportunity for a meeting can lower the search cost. The deduced implications of these analysis results are as follows. The economic capacity is a very important variable. Job stability is especially important for married men. Policy-making on employment and economic capacity is needed for the marriage promotion of singles. We know that economic problems are the major causes of marriage delay. Also, the search cost must be reduced for marriage promotion. In this study, the individual characteristics were limited for the explanatory variables. Marriage is important both for the individual and the family. For example, the property level and the job stability of parents are influenced by marriage. Therefore, these variables can improve the accuracy of the model. In this paper, the hypothesis of the late marriage for the age is follows as.
$H_0$ = Age is influenced in the late marriage

$H_1$ = Age is not influenced in the late marriage

In this paper, the hypothesis of the late marriage for the number of siblings is follows as.

$H_0$ = Number of siblings is influenced in the late marriage

$H_1$ = Number of siblings is not influenced in the late marriage

In this paper, the hypothesis of the late marriage for the metropolis residence is follows as

$H_0$ = Metropolis residence is influenced in the late marriage

$H_1$ = Metropolis residence is not influenced in the late marriage

In this paper, the hypothesis of the late marriage for the economic level of family is follows as.

$H_0$ = Economic level of family is influenced in the late marriage

$H_1$ = Economic level of family is not influenced in the late marriage

In this paper, the hypothesis of the late marriage for the education level is follows as.

$H_0$ = Education level of family is influenced in the late marriage

$H_1$ = Education level of family is not influenced in the late marriage

In this paper, the hypothesis of the late marriage for the income is follows as.

$H_0$ = Income influenced in the late marriage

$H_1$ = Income is not influenced in the late marriage

In this paper, the hypothesis of the late marriage for the employment status is follows as.

$H_0$ = Employment status influenced in the late marriage

$H_1$ = Employment status is not influenced in the late marriage

## 3.2 Data and analysis

In this paper, we used the Korea Labor & Income Panel data (2004-2014). The survey was conducted among 500 men and women aged 20 to 40 through a marital status check for the last 10 years. Of the 500 men and women, 59.7% married within 10 years. The rest was censored because they were singles or were omitted from the survey. Women accounted for 49.5% of all the samples. In this survey, the maximum marriage duration was 10 years, and the minimum duration was one year. The sample parameter is described in Table 1.

<table><caption>Table 1. Sample parameter</caption><thead><tr><th>Classification</th><th></th><th>Man</th><th>Women</th></tr></thead><tbody><tr><td rowspan="3">Ages</td><td>20s</td><td>138</td><td>123</td></tr><tr><td>30s</td><td>249</td><td>270</td></tr><tr><td>40s</td><td>113</td><td>107</td></tr><tr><td rowspan="2">Employment</td><td>Employed temporal</td><td>203</td><td>282</td></tr><tr><td>Employed permanent</td><td>297</td><td>218</td></tr></tbody></table>

Source: Korea Labor & Income Panel data (2004-2014)

## 3.3 Measures and methods

We used the Korea Laboratory & Income Panel Data (2004-2014) of Korea Labor Institute for reliable research. In this paper, independent variables are the age, number of siblings, the metropolis residence, the economic level of family, the education level, the income, and the employment status. The dependent variable is the delay of marriage. In existing research, the analysis of the cause of marriage delay has been focused on the education level. In this study, various factors were considered for the detailed analysis of late marriage. In this paper, the age, number of siblings, the metropolis residence, the economic level of family, the education level, the income, and the employment status set as independent variables for the most accurate analysis. In this study, we used estimation method and non-parametric statistics. The sign
test is used as the statistical hypothesis test for the median value of the population. The Wilcoxon signed-ranks test is the statistical method of determining the order of priority and the measurement through the median value and the observed value. The Wilcoxon rank sum test is the statistical method for comparatively analyzing the median value by sampling two independent populations. In this study, dependent variables are the age, the education level, the job, the employment status, and the income. In the model of the immutable variable for the time, the time dummy showed an effect on the macroeconomic change. When the explanatory variable was changed, the coefficient was influenced by the Log (Odds) a coefficient. When the coefficient had positive definiteness, the marriage probability was high. Also, when the coefficient was exponential, it was influenced by the Log (Odds).

### 3.4 Research model and method

In the estimation results, the marriage probability on the first year was the highest. The marriage probability of the women was higher than that of the men. Also, the age at the first marriage of the women was nearly three years lower than that of the men. A large number of siblings increased the marriage probability. The marriage probability of the singles residing in the metropolis was low. Both the men and women enrolled in the general science courses of the academic high school had a low marriage probability. The women enrolled in the liberal arts courses of the academic high school also had a low marriage probability. When the economic level of the family was below average at the age of 15, the marriage probability was low. The model with only time-constant regressors is described in Table 2.

<table><caption>Table 2. Model with only time-constant regressors</caption><thead><tr><th>Classification</th><th>β</th><th>Exp(β)</th><th>S.E</th></tr></thead><tbody><tr><td>Women</td><td>0.706*</td><td>1.601</td><td>0.210</td></tr><tr><td>Number of siblings</td><td>0.160***</td><td>1.047</td><td>0.161</td></tr><tr><td>Metropolis residence</td><td>-0.258**</td><td>0.503</td><td>0.170</td></tr><tr><td>Academic high school + Liberal arts</td><td>0.371**</td><td>1.769</td><td>0.223</td></tr><tr><td>Academic high school + General science courses</td><td>-0.191</td><td>0.763</td><td>0.207</td></tr><tr><td>Academic high school + General science courses + men</td><td>-0.210***</td><td>1.432</td><td>0.281</td></tr><tr><td>Academic high school + Liberal arts + women</td><td>-0.967***</td><td>0.371</td><td>0.206</td></tr><tr><td>Economic level of the family is below average at the age of 15</td><td>-0.435***</td><td>0.623</td><td>0.267</td></tr><tr><td>Time dummy 1</td><td>-0.313</td><td>0.691</td><td>0.149</td></tr><tr><td>Time dummy 2</td><td>-0.278</td><td>0.710</td><td>0.218</td></tr><tr><td>Time dummy 3</td><td>-0.269*</td><td>0.834</td><td>0.255</td></tr><tr><td>Time dummy 4</td><td>-0.621</td><td>0.110</td><td>0.274</td></tr><tr><td>Time dummy 5</td><td>-0.459</td><td>0.710</td><td>0.338</td></tr><tr><td>Time dummy 6</td><td>-0.562***</td><td>0.561</td><td>0.261</td></tr><tr><td>Time dummy 7</td><td>-0.916</td><td>0.393</td><td>0.290</td></tr><tr><td>Time dummy 8</td><td>-0.147*</td><td>0.817</td><td>0.235</td></tr><tr><td>Constant term</td><td>-0.201**</td><td>0.706</td><td>0.271</td></tr></tbody><tfoot><tr><td colspan="4">**** p < 0.1, ** p < 0.05, *** p < 0.01</td></tr></tfoot></table>

Source: Korea Labor & Income Panel data (2004-2014)

The time-varying regressors is described in Table 3.

<table><caption>Table 3. Time-varying regressors</caption><thead><tr><th>Classification</th><th>Logit</th><th>Cloglog</th><th></th></tr></thead><tbody><tr><td>Time dummy 1</td><td>-0.710***</td><td>-0.678***</td><td>(-2.91)</td></tr><tr><td>Time dummy 2</td><td>-0.451***</td><td>-0.403***</td><td>(-2.16)</td></tr></tbody></table>
<table><tr><td>Time dummy 3</td><td>-0.864***</td><td>(-3.13)</td><td>-0.805***</td><td>(-2.87)</td></tr><tr><td>Time dummy 4</td><td>-0.916***</td><td>(-3.58)</td><td>-0.885***</td><td>(-3.61)</td></tr><tr><td>Time dummy 5</td><td>-0.878***</td><td>(-3.21)</td><td>-0.813***</td><td>(-3.07)</td></tr><tr><td>Time dummy 6</td><td>-0.962***</td><td>(-3.76)</td><td>-0.896***</td><td>(-3.43)</td></tr><tr><td>Time dummy 7</td><td>-0.905***</td><td>(-3.40)</td><td>-0.871***</td><td>(-3.45)</td></tr><tr><td>Time dummy 8</td><td>-1.213***</td><td>(-4.72)</td><td>-1.150***</td><td>(-4.56)</td></tr><tr><td>Age</td><td>0.831***</td><td>(-3.78)</td><td>0.769***</td><td>(-3.38)</td></tr><tr><td>Square of age</td><td>-0.050***</td><td>(-3.61)</td><td>-0.043***</td><td>(-3.47)</td></tr><tr><td>Age*Women</td><td>1.437***</td><td>(-3.09)</td><td>1.206***</td><td>(-3.00)</td></tr><tr><td>Square of age *Women</td><td>-0.041***</td><td>(-3.20)</td><td>-0.023***</td><td>(-3.13)</td></tr><tr><td>Women</td><td>-12.632***</td><td>(-2.76)</td><td>-11.901***</td><td>(-2.50)</td></tr><tr><td>Number of siblings</td><td>0.041</td><td>(-1.63)</td><td>0.678*</td><td>(-2.91)</td></tr><tr><td>Metropolis residence</td><td>-0.279***</td><td>(-2.08)</td><td>-0.239***</td><td>(-1.85)</td></tr><tr><td>Academic high school + Liberal arts</td><td>0.180</td><td>(-1.29)</td><td>0.165</td><td>(-1.07)</td></tr><tr><td>Academic high school + General science courses</td><td>-0.283</td><td>(-0.65)</td><td>-0.271</td><td>(-0.53)</td></tr><tr><td>Academic high school + General science courses + men</td><td>-0.052</td><td>(-0.30)</td><td>-0.049</td><td>(-0.16)</td></tr><tr><td>Academic high school + Liberal arts + women</td><td>-0.431*</td><td>(-1.83)</td><td>-0.390*</td><td>(-1.71)</td></tr><tr><td>Bachelor's degree</td><td>0.513*</td><td>(-1.14)</td><td>0.508*</td><td>(-1.18)</td></tr><tr><td>Master's degree + Doctor's degree</td><td>1.658***</td><td>(-3.93)</td><td>1.607***</td><td>(-3.87)</td></tr><tr><td>Women*Bachelor's degree</td><td>-0.712</td><td>(-1.90)</td><td>-0.696</td><td>(-1.85)</td></tr><tr><td>Women*Master's degree + Women*Doctor's degree</td><td>-1.813*</td><td>(-2.51)</td><td>-1.701*</td><td>(-2.43)</td></tr><tr><td>Employee</td><td>-0.583*</td><td>(-1.72)</td><td>-0.547*</td><td>(-1.62)</td></tr><tr><td>Men*Employee</td><td>0.851***</td><td>(-2.67)</td><td>0.839***</td><td>(-2.55)</td></tr><tr><td>Annual salary</td><td>0.061</td><td>(-0.31)</td><td>0.054</td><td>(-0.26)</td></tr><tr><td>Permanent employee</td><td>0.550**</td><td>(-2.85)</td><td>0.519**</td><td>(-2.62)</td></tr><tr><td>Economic level of the family is below average at the age of 15</td><td>-0.627***</td><td>(-3.01)</td><td>-0.595***</td><td>(-2.83)</td></tr><tr><td>Constant term</td><td>-17.801***</td><td>(-5.03)</td><td>-16.847***</td><td>(-4.58)</td></tr><tr><td>LogLikelihood</td><td>-961.5</td><td></td><td>-961.3</td><td></td></tr><tr><td>Obs</td><td>3416</td><td></td><td>3416</td><td></td></tr><tr><td colspan="5">*** p < 0.1, ** p < 0.05, *** p < 0.01</td></tr><tr><td colspan="5">() is t-value</td></tr></table>

Source: Korea Labor & Income Panel data (2004-2014).

The unobserved heterogeneity is described in Table 4. It is similar to the coefficient value of the time-varying regressors. This is because $\sigma_v$ was almost closer to 0. Also, the null hypothesis was not adopted for $p= \sigma_v/(1+\sigma_v)$. In the LR test result, the frailty was not statistically significant.

<table><caption>Table 4. Unobserved heterogeneity</caption><thead><tr><th>Classification</th><th colspan="2">Logit</th><th colspan="2">Cloglog</th></tr></thead><tbody><tr><td>Time dummy 1</td><td>-0.710***</td><td>(-3.10)</td><td>-0.678***</td><td>(-2.87)</td></tr><tr><td>Time dummy 2</td><td>-0.451***</td><td>(-2.67)</td><td>-0.403***</td><td>(-2.10)</td></tr><tr><td>Time dummy 3</td><td>-0.864***</td><td>(-3.12)</td><td>-0.805***</td><td>(-2.83)</td></tr><tr><td>Time dummy 4</td><td>-0.916***</td><td>(-3.56)</td><td>-0.885***</td><td>(-3.58)</td></tr></tbody></table>
<table><tr><td>Time dummy 5</td><td>-0.878***</td><td>(-3.17)</td><td>-0.813***</td><td>(-2.99)</td></tr><tr><td>Time dummy 6</td><td>-0.962***</td><td>(-3.71)</td><td>-0.896***</td><td>(-3.37)</td></tr><tr><td>Time dummy 7</td><td>-0.905***</td><td>(-3.31)</td><td>-0.871***</td><td>(-3.41)</td></tr><tr><td>Time dummy 8</td><td>-1.213***</td><td>(-4.68)</td><td>-1.150***</td><td>(-4.54)</td></tr><tr><td>Age</td><td>0.831***</td><td>(-3.72)</td><td>0.769***</td><td>(-3.37)</td></tr><tr><td>Square of age</td><td>-0.050***</td><td>(-3.59)</td><td>-0.043***</td><td>(-3.45)</td></tr><tr><td>Age*Women</td><td>1.437***</td><td>(-3.04)</td><td>1.206***</td><td>(-2.91)</td></tr><tr><td>Square of age *Women</td><td>-0.041***</td><td>(-3.16)</td><td>-0.023***</td><td>(-3.08)</td></tr><tr><td>Women</td><td>-12.632***</td><td>(-2.72)</td><td>-11.901***</td><td>(-2.46)</td></tr><tr><td>Number of siblings</td><td>0.041</td><td>(-1.59)</td><td>0.678*</td><td>(-2.87)</td></tr><tr><td>Metropolis residence</td><td>-0.279***</td><td>(-2.03)</td><td>-0.239***</td><td>(-1.83)</td></tr><tr><td>Academic high school + Liberal arts</td><td>0.180</td><td>(-1.26)</td><td>0.165</td><td>(-1.04)</td></tr><tr><td>Academic high school + General science courses</td><td>-0.283</td><td>(-0.63)</td><td>-0.271</td><td>(-0.47)</td></tr><tr><td>Academic high school + General science courses + men</td><td>-0.052</td><td>(-0.29)</td><td>-0.049</td><td>(-0.14)</td></tr><tr><td>Academic high school + Liberal arts + women</td><td>-0.431*</td><td>(-1.80)</td><td>-0.390*</td><td>(-1.69)</td></tr><tr><td>Bachelor's degree</td><td>0.513*</td><td>(-1.12)</td><td>0.508*</td><td>(-1.16)</td></tr><tr><td>Master's degree + Doctor's degree</td><td>1.658***</td><td>(-3.89)</td><td>1.607***</td><td>(-3.85)</td></tr><tr><td>Women*Bachelor's degree</td><td>-0.712</td><td>(-1.86)</td><td>-0.696</td><td>(-1.82)</td></tr><tr><td>Women*Master's degree + Women*Doctor's degree</td><td>-1.813*</td><td>(-2.47)</td><td>-1.701*</td><td>(-2.40)</td></tr><tr><td>Employee</td><td>-0.585*</td><td>(-1.68)</td><td>-0.547*</td><td>(-1.59)</td></tr><tr><td>Men*Employee</td><td>0.851***</td><td>(-2.61)</td><td>0.839***</td><td>(-2.54)</td></tr><tr><td>Annual salary</td><td>0.061</td><td>(-0.29)</td><td>0.054</td><td>(-0.23)</td></tr><tr><td>Permanent employee</td><td>0.550**</td><td>(-2.83)</td><td>0.519**</td><td>(-2.58)</td></tr><tr><td>Economic level of the family is below average at the age of 15</td><td>-0.627***</td><td>(-2.96)</td><td>-0.595***</td><td>(-2.81)</td></tr><tr><td>Constant term</td><td>-17.801***</td><td>(-4.87)</td><td>-16.849***</td><td>(-4.54)</td></tr><tr><td>LogLikelihood</td><td colspan="2">-961.5</td><td colspan="2">-961.3</td></tr><tr><td>Obs</td><td colspan="2">3416</td><td colspan="2">3416</td></tr><tr><td>LR test H0 : ρ=0</td><td colspan="2">p-value : 0.494</td><td colspan="2">p-value : 0.495</td></tr><tr><td colspan="5">**** p < 0.1, ** p < 0.05, *** p < 0.01</td></tr><tr><td colspan="5">() is t-value</td></tr></table>

Source: Korea Labor & Income Panel data (2004-2014)

The mundlak correction is described in Table 5. The temporal average term was estimated by two models. The marriage probability of the permanent employees was higher than that of the temporary employees. When the economic level of the family was below average at the age of 15, the marriage probability was low. In this result, the economic variable was always statistically significant.

<table><caption>Table 5. Mundlak correction</caption><thead><tr><th>Classification</th><th colspan="2">Model 1</th><th colspan="2">Model 2</th></tr></thead><tbody><tr><td>Age</td><td>0.991***</td><td>(3.81)</td><td>0.967***</td><td>(3.80)</td></tr><tr><td>Square of age</td><td>-0.034***</td><td>(-3.17)</td><td>-0.033***</td><td>(-3.14)</td></tr></tbody></table>
<table><tr><td>Age*Women</td><td>1.687***</td><td>(3.97)</td><td>1.658***</td><td>(3.93)</td></tr><tr><td>Square of age *Women</td><td>-0.045***</td><td>(-3.38)</td><td>-0.043***</td><td>(-3.31)</td></tr><tr><td>Women</td><td>-17.658**</td><td>(-2.62)</td><td>-16.913**</td><td>(-2.59)</td></tr><tr><td>Number of siblings</td><td>0.030</td><td>(0.41)</td><td>0.029</td><td>(0.38)</td></tr><tr><td>Metropolis residence</td><td>-0.319***</td><td>(-2.67)</td><td>-0.332***</td><td>(-2.81)</td></tr><tr><td>Academic high school + Liberal arts</td><td>0.160</td><td>(1.49)</td><td>0.165</td><td>(1.54)</td></tr><tr><td>Academic high school + General science courses</td><td>-0.265</td><td>(-0.68)</td><td>-0.271</td><td>(-0.69)</td></tr><tr><td>Academic high school + General science courses + men</td><td>-0.028</td><td>(-0.62)</td><td>-0.030</td><td>(-0.66)</td></tr><tr><td>Academic high school + Liberal arts + women</td><td>-0.417</td><td>(-1.71)</td><td>-0.423</td><td>(-1.79)</td></tr><tr><td>Bachelor's degree</td><td>0.701</td><td>(0.50)</td><td>0.711</td><td>(0.56)</td></tr><tr><td>Master's degree + Doctor's degree</td><td>2.817*</td><td>(1.39)</td><td>2.819*</td><td>(1.43)</td></tr><tr><td>Women*Bachelor's degree</td><td>1.432</td><td>(1.07)</td><td>0.870</td><td>(-1.38)</td></tr><tr><td>Women*Master's degree + Women*Doctor's degree</td><td>3.317</td><td>(1.60)</td><td>1.639</td><td>(-2.63)</td></tr><tr><td>Employee</td><td>-0.062</td><td>(-0.34)</td><td>-0.058</td><td>(-0.31)</td></tr><tr><td>Men*Employee</td><td>0.867</td><td>(1.58)</td><td>0.834</td><td>(1.55)</td></tr><tr><td>Annual salary</td><td>-0.696</td><td>(-3.19)</td><td>-0.691</td><td>(-3.13)</td></tr><tr><td>Permanent employee</td><td>0.768**</td><td>(2.18)</td><td>0.765**</td><td>(2.13)</td></tr><tr><td>Economic level of the family is below average at the age of 15</td><td>-0.550***</td><td>(-3.04)</td><td>-0.556***</td><td>(-3.09)</td></tr><tr><td>LogLikelihood</td><td colspan="2">-920.6</td><td colspan="2">-921.3</td></tr><tr><td>Obs</td><td colspan="2">3416</td><td colspan="2">3416</td></tr><tr><td colspan="5">**** p < 0.1, ** p < 0.05, *** p < 0.01</td></tr><tr><td colspan="5">() is t-value</td></tr></table>

Source: Korea Labor & Income Panel data (2004-2014)

4. RESEARCH LIMITATIONS AND DISCUSSION

In this paper, research limitations are that the research need to be more reflected in a number of considerations besides reviewed considerations in this study. We attempted to make an accurate analysis by reflecting the age, number of siblings, the metropolis residence, the economic level of family, the education level, the income, and the employment status. However in addition to the factors discussed, a wide variety of factors can affect late marriage. A case in point is that student loans can affect late marriages. A variety of factors are expected to affect late marriage and new factors will emerge in the future as the social environment continues to change. Therefore, the marriage delay needs to be continued research and we will proceed with future research on the social and economic impacts of marriage delay. The discussion of marriage research is as follows. Men have a more positive attitude to marriage than women. Men highly recognize the rewards of marriage. Women highly recognize the cost of marriage. Men have a positive position, a conservative position, and a traditional position with respect to their views on marriage. Women have a mixed view of modernity and tradition. They have equaled men in social position through increased education opportunities. Women insist on equality in marriage and an open view on marriage. They also have traditional views on marriage for a stable life due to economic uncertainty and job instability. The higher the age is, the lower the marriage intention is. The increase in educational opportunities is influenced by marriage. Highly educated women have delayed marriage because their education period is longer. Highly educated men can marry easily due to the rise of their socioeconomic status and resources. Employed people can marry more easily than unemployed people due to their economic resources. Men can marry easily due to their high income level. Women delay marriage due to their high income level. The family
community is influenced positively by marriage. The family strength performs a suitable function for the family relationship, sense of fellowship, and happiness. The family strength is influenced by the individual values and attitudes, and by the family and the young generation's views on marriage. The family strength is an important variable of the marriage preparation of the young generation. In the family, rational decision-making, open communication, and crisis management ability are influenced positively by the young generation's views on marriage. A relationship refers to the state of dating single men and women without contractual liability. It pertains to the marriage preparation process through a natural meeting. The relationship can specify the ideal type of person for the spouse choice. Also, it is an important variable of the spouse choice. The marriage image is the cognitive attitude and the definite attitude to marriage. It forms a positive image or a negative image through the interaction of the parent, the family relations, acquaintances, the mass media, etc. When the marriage image is good, singles have greater expectations from marriage.

## 5. CONCLUSIONS

The purpose of this paper is cause analysis for marriage delay of singles in South Korea. In this research, we attempted to analyze the cause of the delay in the marriage of singles. The social concern for the marriage delay of singles is a global issue. The rate of economic growth due to the increase in the number of singles has fallen. Also, social problems have come up. Marriage delay is influenced by the perception change in the family system. Marriage delay is the major factor of the rate of decrease of the population and of economic growth. Marriage encouragement is needed for birthrate increase. Also, the analysis of the cause of delay in the marriage of singles is essential for government policy-making. In existing research, the analysis of the cause of marriage delay has been focused on the education level. In this research, the sociocultural effect, the educational level, the economic capacity have been considered for the analysis of the cause of marriage delay. Also, we discussed the economic capacity as well as the educational level for the exact cause analysis. Recently, single families are growing very fast in South Korea. Around the world, the rate of births without marriage is also increasing very rapidly. There are many other considerations. Future studies will attempt to reflect these considerations. We expect this research to contribute greatly to the deduction of implications of, and government policy-making on, marriage and birthrates through analysis of the cause of marriage delay.

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