This study aims to compare the family support factors and the condition of the preparation for old age in the babyboom generation and the post-babyboom generation and analyze the impact of the family support factors on the preparation for old age. This study set the influential factors contributing to the preparation for old age such as demographic characteristics, household-related factors, and parents and children characteristics as control variables, set the family support factors including parents support and children responsibility as independent variables, and then analyzed the relationship between independent variable, control variable and preparation for old age and the relative effect of independent variable and control variable on the preparation for old age.
To put it concretely, Research Question 1 analyzed the condition of family support factors for parents and children in the babyboom generation and the post-babyboom generation. Research Question 2 investigated the condition of preparation for old age in the babyboom generation and the post-babyboom generation. Research Question 3 analyzed the difference in family support factors depending on demographic characteristics, household-related factors, and parents and children characteristics in the babyboom generation and the post-baby generation. Research Question 4 analyzed the difference in the preparation for old age depending on demographic characteristics, household-related factors, parents and children characteristics, and family support factors in the babyboom generation and the post-babyboom generation. Research Question 5 analyzed the relative effects of demographic characteristics, household-related factors, parents and children characteristics, and family support factors that contributed to the preparation for old age in the babyboom generation and the post-babyboom generation.
As research data, the 2nd Family Survey, conducted by the Ministry of Gender Equality and Family in 2010, was used. As the focus of this study was on the preparation for old age in the babyboom generation and the post-babyboom generation who had double burden of parents support and children responsibility, a total of 938 householders, as final sample, were extracted from the householders who had children and responded to the retirement plan related to the preparation for old age. The final sample was divided into 352 householders in the babyboom generation (1955-1963) and 586 householders in the post-babyboom generation (1964-1978).
To analyze research questions, SPSS(ver.20.0 was used. And as statistic methods, conducted simple frequency and percentage, cross tabulation analysis, χ2-test, average and standard deviation, t-test, analysis of variance(ANOVA) and F-test, and multiple regression analysis which was a stepwise selection were carried out. In particular, first-step in multiple regression analysis included family support factors(parents support and children responsibility) as independent variables, and second-step in multiple regression model included demographic characteristics, household-related factors, and parents and children characteristics as control variables in addition to the independent variables in first-step regression model. Then, the change in the impact of variables on the preparation for old age was identified. Prior to the multiple regression analysis, Pearson's Corelation Coefficient and VIF(Variance Inflation Factor) were checked to find out the multicollinearity of variables.
The results of research questions can be summarized as follows:
Research Question 1 analyzed parents support expenditure, burden of support expenditure for parents, and awareness for supporting for parents(cohabitation support, economic support, and children’s awareness for supporting for parents) to identify the condition of parents support, of the family support factors in the babyboom generation and boomer households and the post-babyboom generation. The result showed that the variable that showed a significant difference between the two groups was burden of support expenditure for parents. The proportion that they said, “It’s burdensome”was 19.4% and 28.3%, respectively, in the babyboom generation and in the post-babyboom generation. The observational frequencies and the expected frequencies between the two groups were compared. As a result, the babyboom generation was more likely to say, “It’s burdensome” than the post-babyboom generation. Again, in the 5-point Likert scale, the babyboom generation scored at 2.72 point and the post-babyboom generation at 2.91. This suggested that the post-babyboom generation felt more burden fo support expenditure for parents than the babyboom generation did.
Next, educational expenditure of children, burden of children educational expenditure, and sense of responsibility for children(university tuition fee, marriage fund, and support after marriage) were analyzed to identify the condition of children responsibility, of the family support factors in the babyboom generation and the post-babyboom generation. As a result, educational expenditure of children and burden of children educational expenditure showed a statistically significant difference between the two groups. In other words, the babyboom generation and the post-babyboom generation spent 648,200 won and 523,100 won, respectively, for monthly educational expenditure of children. This showed that educational expenditure of children was higher in the babyboom generation than in the post-babyboom generation. To compare the burden of children educational expenditure, in the 5-point Likert Scale, the babyboom generation scored at 4.12 point and the post-babyboom generation at 3.95. This suggested that the babyboom generation felt a heavier burden from the educational expenditure for children than the post-babyboom generation did.
Research Question 2 compared the condition of the preparation for old age(partner to spend later life together, important later life, necessity of preparation for old age, economic preparation for old age, and later life preparation) in the babyboom generation and the post-babyboom generation. As a result, the variable that showed a significant difference was later life preparation. The proportion that the babyboom generation and the post-babyboom generation said that they did not prepare for later life was 9.1% and 7.2%, respectively. The observational frequencies and the expected frequencies were compared between the two groups. As a result, the proportion that they said, “It’s burdensome”was higher in the post-babyboom generation than in the babyboom generation. Again, in the 5-point Likert Scale, the babyboom generation scored at 2.88 point and the post-babyboom generation at 2.70. This suggested that the later life preparation was higher in the post-babyboom generation than in the babyboom generation.
Research Question 3 analyzed the burden of support expenditure for parents depending on demographic characteristics and household-related factors in the babyboom generation and the post-babyboom generation. As a result, burden of educational expenditure for children showed a statistically significant difference depending on the education level in the babyboom generation, whereas burden of educational expenditure for children showed a statistically significant difference depending on financial assets, debts, and subjective economic status in the post-babyboom generation. Next, the burden of parents support expenditure was analyzed depending on the parents and children characteristics. As a result, it showed a statistically significant difference depending on the presence of children who were over 25 years old in the babyboom generation.
Again, the burden of educationa expenditure for children was analyzed depending on demographic characteristics and household-related factors in the babyboom generation and in the post-babyboom generation. As a result, it showed a statistically significant difference depending on gender of householder, employment and occupation, double-income couples, savings, debts, and subjective economic status in the babyboom generation, whereas it showed a statistically significant difference depending on education level of householder, financial assets, savings, home ownership, and subjective economic status in the post-babyboom generation. Next, the burden of educational expenditure for children was analyzed depending on parents and children characteristics. As a result, there was a difference in burden of educational expenditure for children depending on the presence of children who were over 25 years old in the babyboom generation, whereas there was a significant difference depending on the presence of parents who are alive, total number of children, and presence of children who are from 12 to 24 years old in the post-babyboom generation.
In Research Question 4, to look at the preparation for old age depending on demographic characteristics and household-related factors in the babyboom generation and the post-babyboom generation, it showed a statistically significant difference depending on education level of householder, occupation, subjective evaluation on health, average monthly household income, savings, financial assets, home ownership, debts, and subjective economic status in the babyboom generation, whereas it showed a statistically significant difference depending on education level of householder, occupation, average monthly household income, savings, financial assets, home ownership, and subjective economic status in the post-babyboom generation.
Next, the preparation for old age was analyzed depending on parents and children characteristics in the babyboom generation and the post-babyboom generation. As a result, it showed a statistically significant difference depending on the presence of children who were 12-24 years old in the babyboom generation, whereas it showed a statistically significant difference depending on the presence of parents who are alive in the post-babyboom generation.
Research Question 5 carried out an first-step multiple regression analysis on the independent variables such as parents support factors(parents support expenditure, burden of support expenditure for parents, and awarenss of supporting for parents) and children responsibility factors(educational expenditure of children, burden of educational expenditure for children, and sense of responsibility for children) to identify the influential factors contributing to the later life preparation in the babyboom generation. As a result, the most significantly influential variable was burden of educational expenditure for children, followed by parents support expenditure, awareness of supporting for parents, and educational expenditure of children in order. In other words, as they had lower burden of educational expenditure for children, as they had heavier parents support expenditure, as sense of supporting for parents was lower and as they had to spend more educational expenditure of children, their later life preparation was higher. The relative influence of all variables was 18.9%(Adj R2).
In second-step multiple regression analysis, as control variables of parents and children characteristics(presence of parents who are alive, total number of children), demographic characteristics(householder gender, age, education level, employment and subjective evaluation on health) and household-related factors(average monthly household income, savings, home ownership, and subjective economic status) were added. As a result, the variable that was most significantly influential was savings, followed by burden of educational expenditure for children, subjective economic status and parents support expenditure in order. In other words, when they saved than when they didn’t, as they felt burden of educational expenditure for children less heavily, as they recognized the subjective economic status more positively, as they had more parents support expenditure, their later life preparation was higher. In second-step multiple regression analysis, R2 was .356, which was an increase by 0.148 than first-step, and R2 increase was statistically significant(F variance=6.870, P-value=0.01).
In the post-babyboom generation, first-step multiple regression analysis was carried out on the independent variables such as family support factors(parents support expenditure, burden of support expenditure for parents, and awareness of suppoting for parents), and children responsibility factors(educational expenditure of children, burden of educational expenditure for children, and sense of responsibility for children) to analyze the influential factors contributing to the later life preparation. As a result, the influential variables were parents support expenditure, burden of educational expenditure for children, and educational expenditure of children in order, and as they had more parents support expenditure, as they felt burden of educational expenditure for children less heavily, and as they had more educational expenditure of children, their later life preparation was higher. The relative influence of all variables was 10.3%(Adj R2).
In two-step multiple regression analysis, parents and children characteristics(presence of parents who are alive, total number of children), demographic characteristics(householder gender, age, education level, employment, and subjective evaluation on health), and household-related factors(monthly household income, savings, home ownership, and subjective economic status) were added as control variables. As a result, the most influential variable was subjective economic status, followed by average monthly household income(over 4 million won), employment, and parents support expenditure in order. In other words, as they recognized subjective economic status more positively, when their average monthly household income was more than 4 million won than when it’s less than 4 million won, when a householder was unemployed than when he/she was employed, as they spent more parents support expenditure, their later life preparation was higher. In two-step multiple regression analysis, R2 was .229, which was an increase by 0.116 than first-step, and R2 increase was statistically significant (F variance=4.551, P-value=0.05).