ESS Data Analysis: Retirement Age, Parenthood, and Influencing Factors

This report presents an analysis of factors influencing retirement age and the ideal age to become a parent, utilizing data from the European Social Survey (ESS). The research explores the relationships between gender, education level, and these key life decisions. The study formulates hypotheses and develops a conceptual model, employing both descriptive and inferential statistical techniques including t-tests, ANOVA, and linear regression. The findings indicate statistically significant differences in the ideal age for parenthood between genders, and variations in retirement age expectations across different education levels. The regression model reveals a significant linear relationship between the ideal age for parenthood, gender, education, and the ideal retirement age. The report concludes by discussing the implications of these findings, offering valuable insights into the complex interplay of personal factors and societal influences on retirement planning and family formation.

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Factors Affecting Retirement Age, and Age to be a Father/Mother
Name
The Name of the Class (Course)
Professor (Tutor)
The Name of the School (University)
The City and State where it is located
Date

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Introduction
The ideal time to retire has been highly debated and both males and female seem to have
different ideologies. Also, the ideal time to marry (have kids) seem to differ by gender.
Scholars like Kumchulesi, et al., (2010, p. 7) and Chandrasekhar, (2010, p. 90) seem to agree
that there are a number of factors that influence people’s perception of ideal time of marriage
and time of retirement. Some research indicates that the majority of people hopes to retire
before the age of 65 years (Yih, n.d.). On the other hand, both male and female seem to have
a different retirement age plans, with female expected to retire earlier. Some of the factors
that seem to play a significant role in determining the ideal age to retirement and becoming a
father/mother include the age of an individual, gender, level of education, and socioeconomic
factors. The research will evaluate which factors affect retirement age, and ideal age to be a
parent.
The research used the European Social Survey (ESS) data, which are academically driven,
cross-national survey assessing the beliefs, attitudes, and behavior patterns among the
participants. The participants of this survey come from more than thirty nations across the
world. The survey data played an important role in assessing and understanding the
relationship between age at first marriage, gender, ideal age of retirement and the highest
level of education.
Research problem
This research was designed to assess whether using international data collected by ESS, there
existed a significant relationship between ideal age at retirement and age at first marriage
between gender and people with different level of education. Further, a linear model was to
be fitted to try and predict the ideal retirement age using the selected predictors. Nowadays, it
is important to have a strategic plan when retiring and predicting the expected age of

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retirement can greatly help. One can well prepare for how they would utilize their pension
and also can facilitate the pension earlier enough.
As suggested by Kumchulesi, et al., (2010, p. 7) using Malawi population and
Chandrasekhar, (2010, p. 84) using Indian population, gender, education level, among other
factors plays a significant role in determining the age at first marriage. The age at first
marriage in most cases affects the women who in most cases end up dropping from school.
Therefore, understanding such an issue has great implication in policy that targets to promote
women’s status. Recent trends show that there had been a drastic change in the labor force
which has been categorized by older men and women (Coile, 2015). This has been attributed
to the governments cutting pensions among other factors such as declining morbidity and
mortality (Fitzpatrick & Moore., 2018). Therefore, checking the connection between these
variables is quite important.
Conceptual model and hypotheses
From the literature, it is seen that there is a connection between age at first marriage and
gender and the level of education. However, does this connection hold when we hold one of
the factors constant? That is, do the age at first marriage affected by the highest level of
education between the men and women? In this case, the gender variable is held constant and
analysis performed. In this case, the hypothesis is that both male and female with different
level of education are expected to have a significantly different average age at first marriage
and more precise give birth (become a firth or mother). Also, an assessment will be carried
out to determine whether retirement age is significantly different between the male and
female. The hypothesis is that on average male and female are expected to retire at different
age. Lastly, it is expected that age at first marriage, gender, and level of income plays an
important role in predicting the retirement age of an individual. A linear regression model is

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fitted to test the hypothesis that at least one of the variables significantly predict the expected
age of retirement.
Variables from ESS
The research will use four variables from ESS data. First, the gender (gndr) which is coded a
one as male and two as female. This shows the gender of the participants of the survey.
Second, the variable “Become a mother/ father, ideal age. SPLIT BALLOT” (iagpnt) and
“Retire permanently, ideal age. SPLIT BALLOT” (iagrtr) are used to show ideal age for
marriage and retirement respectively. These variables are numerical in nature. Lastly,
“Highest level of education” (edulvla) is used to show the participants’ highest level of
education attained. This is a nominal variable. Note that the ideal age to become a parent is
used instead of the ideal age to get married for most of the people nowadays opt to cohabit
without necessarily giving birth. Thus, this variable will be ideal to measure the age at which
an individual is willing to settle down and get a family rather than a husband.
Results and Discussion
The social distribution of the data was carried out using the gender and level of education and
the results are as illustrated below.

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Figure 1: Gender distribution bar char
In total, there were 19,530 male participants, which represented 45.52% of the participants.
On the other hand, there were 23,372 female participants (54.58%). This is quite a large
sample which increases the results reliability and validity (Keller, 2015).
Figure 2: Level of education distribution
The chart in Figure 1 shows that most of the participants had completed an upper secondary
education (n = 16,316), which was 38.08% of all the participants. The category with the least
participants “others” had in total of 54 people, which was 0.13% of all the participants
(Chambers, 2017). This distribution is a representative of the population as fewer people are
expected to have higher education, and fewer with less than lower secondary education and
the majority to be in between.
The descriptive statistics for the numerical variables was carried out and the summary is as
follows.
Report
Become mother/ father, ideal age. SPLIT BALLOT

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Gender Mean N Std. Deviation
Male 23.41 18711 8.039
Female 23.66 22515 8.267
Total 23.54 41226 8.165
On average, the male thinks that the ideal age to get married is 23.41 years (SD = 8.039
years). On the other hand, the female participants think that that the ideal age to marry is
23.66 years (SD = 8.267 year). These averages are very close, but due to the large sample
used and small standard deviation, it is important to test whether the difference is significant
(Anderson, et al., 2016).
The descriptive statistics for the ideal age for retire by the level of education were carried out
and the results are as follows.
Report
Retire permanently, ideal age. SPLIT BALLOT
Highest level of education Mean N Std. Deviation
Less than lower secondary
education (ISCED 0-1)
55.15 5381 22.721
Lower secondary education
completed (ISCED 2)
54.21 7459 22.941
Upper secondary education
completed (ISCED 3)
53.28 15430 22.989
Post-secondary non-tertiary
education completed (ISCED
4)
53.82 1070 22.522
Tertiary education completed
(ISCED 5-6)
53.25 11132 24.848
Other 55.12 49 31.543
Total 53.71 40521 23.480
On average, those with less than lower secondary education has the highest average (mean =
55.15, sd = 22.721 years), whereas those with tertiary education have the lowest average.
From this, it seems like there is a trend; people with lower education qualification expecting
to retire are older age and those with tertiary education and younger age. However, a

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confirmatory test is required to determine whether at least one of the level of education has a
different average.
Test of the hypothesis was performed to determine whether male and female participants
have a different average ideal age of first marriage. Since the sample is very large and the
data are random, the variables are assumed to be normally distributed. The test results are as
follows.
Independent Samples Test
Levene's Test for
Equality of Variances t-test for Equality of Means
F Sig. t df
Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower Upper
Become
mother/
father, ideal
age. SPLIT
BALLOT
Equal
variances
assumed
3.771 .052 -3.119 41224 .002 -.252 .081 -.410 -.094
Equal
variances
not assumed
-3.127 40226.179 .002 -.252 .081 -.410 -.094
The Levene’s test first indicates that equal variances for the groups is assumed (F (1, 41224)
= 3.771, p-value > .05) (Chatfield, 2018). The t-test for the equality of the means which is the
main interest of the analysis shows that there is enough evidence to warrant the rejection of
the null hypothesis (t (41224) = -3.119, p-value < .05) (Keller, 2015). This implies that the
male and female ideal average age to become a father or mother is statistically different. In
particular, the female average is higher than that of the males average ideal time to become a
father/mother (t (-3.119), p-value = 0.001).
An assessment to determine whether the ideal age for retirement is different by the level of
education attained for the male participants was carried out and the results are as follows.
ANOVA
Retire permanently, ideal age. SPLIT BALLOT
Sum of Squares df Mean Square F Sig.
Between Groups 6935.507 5 1387.101 2.443 .032
Within Groups 10469822.077 18437 567.870
Total 10476757.584 18442

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The summary shows that at least one of the group has a different average ideal age for
retirement (F (5, 18437) = 2.443, p-value = 0.032) (Lowry, 2014). In particular, when post
hoc analysis is carried out, it was found that those with less than secondary education and
those with tertiary education have a significantly different average (95% CI = [0.18, 3.71]).
A similar assessment was carried out for the female and the summary is as follows.
ANOVA
Retire permanently, ideal age. SPLIT BALLOT
Sum of Squares df Mean Square F Sig.
Between Groups 14000.469 5 2800.094 5.242 .000
Within Groups 11753795.450 22003 534.191
Total 11767795.919 22008
At least one of the group has a significantly different average ideal age of becoming a mother
or a father (F (5, 22003) = 5.242, p-value < .05) (Lowry, 2014). The post hoc analysis
indicated that there is a significance difference between the less than secondary and upper
secondary (95% CI = [0.86, 3.61]) and those with tertiary education (95% CI = [0.47, 3.32]).
A regression model was fitted to assess whether there is a linear relationship between ideal
age for becoming a father/mother and ideal age to retire, gender and level of education. The
results are summarized below.
Model Summaryb
Model R R Square
Adjusted R
Square
Std. Error of the
Estimate Durbin-Watson
1 .268a .072 .072 22.255 1.881
a. Predictors: (Constant), Highest level of education, Become mother/ father, ideal age. SPLIT
BALLOT, Gender
b. Dependent Variable: Retire permanently, ideal age. SPLIT BALLOT
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 1512228.283 3 504076.094 1017.730 .000b
Residual 19568583.896 39509 495.294

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Total 21080812.179 39512
a. Dependent Variable: Retire permanently, ideal age. SPLIT BALLOT
b. Predictors: (Constant), Highest level of education, Become mother/ father, ideal age. SPLIT BALLOT,
Gender
Coefficientsa
Model
Unstandardized
Coefficients
Standardized
Coefficients t Sig. Collinearity Statistics
B Std. Error Beta Tolerance VIF
1 (Constant) 37.439 .512 73.053 .000
Become mother/ father,
ideal age. SPLIT BALLOT
.766 .014 .268 55.170 .000 .999 1.001
Gender -.692 .225 -.015 -3.076 .002 .999 1.001
Highest level of education -.193 .050 -.019 -3.856 .000 .998 1.002
a. Dependent Variable: Retire permanently, ideal age. SPLIT BALLOT
The results show that the developed model is significant (F (3, 39509) = 1017.730, p-value
< .001) (Cohen, et al., 2014). A consideration was carried out to determine whether each
independent variable is significantly related to the dependent variable. It was established that
all the variables are significantly related to ideal age for permanent retirement, there is no
collinearity as the VIF is approximately 1.00. When the ideal age for becoming a
father/mother is increased by one year the ideal age for retirement is expected to increase by
0.766 years. The males have on average 0.692 years less than the female. Lastly, when the
education level is increased by one level, one is expected to reduce the expected ideal age of
retirement. The developed model could only take into account 7.2% of sources of variation
(Lowry, 2014). This proportion of variation is quite low. The maximum Cook’s distance
value is 0.218, which indicates that there is no influential data point. Thus, this model can be
used to make predictions; for instance, a female with tertiary education and expected to be a
father/mother at 29 years can be predicted. The prediction is:
Ideal retire age = 37.439 + .766(ideal age to be mother/father) + -.692 (gender) - 0.193
(education)

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= 37.439 + .766(29) + -.692*(2) - 0.193*(5)
= 57.304
This person indicates that the ideal age of retirement to be 57.304 years.
Conclusion
The research has successfully achieved the primary objectives. The research established that
male and female had different perceptions on the ideal age to become a father/mother. For a
matter of factor, the female average was a bit higher than that of males. The level of
education was found to have a significant impact on the ideal age for retirement by gender.
Those with a tertiary level of education were found to have a lower average than those with
less than secondary education level. There was a significant linear association between ideal
age for retirement and the predictors ideal age to be a father/mother, gender, and level of
education. Therefore, if the prediction of the expected retirement age is to be done, age at
which an individual become a parent, his/her gender and education level can play a vital role.
The research model had a low value of coefficient of determination, which means that
although the variables are significant, they could only take into account a small proportion of
variation. Thus, if other research on the same issue is carried out, the research should include
more factors, to improve the model reliability, such as socioeconomic factors.

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Bibliography
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Coile, C. C., 2015. Economic determinants of workers' retirement decisions. Journal of
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Available at: https://retirehappy.ca/when-is-the-best-time-to-retire/

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