Student loans were included on the questionnaires from 2007 onwards and the information is therefore available for respondents aged from 26 to 32. Student loan usage for the age group used in this study is indicated Figure 5.7.
Figure 5.7: Respondents making use of student loans
Source: Author’s calculations.
It appears that as the students reach their thirties, their need to make use of student loans decreases. As the data was only available from 2007 onwards, the position relating to 18–25 year-olds was subsequently unavailable. However, the results are valuable in determining up to which age the youth have the greatest need for student loans.
Sub-hypothesis 4
𝐻04: There is no statistically significant relationship between age and student
loans uptake.
𝐻𝐴4: There is a statistically significant relationship between age and student loans
uptake.
Table 5.8 indicates the results of sub-hypothesis 4.
0.00% 0.10% 0.20% 0.30% 0.40% 0.50% 0.60% 0.70% 0.80% 0.90% 1.00% 26 27 28 29 30 31 32
Table 5.8: Chi-square test Student loan and Age Value df Asymptotic Significance (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Point Probability Pearson Chi-Square 8.308a 6 .216 .203 Likelihood Ratio 8.940 6 .177 .276
Fisher’s Exact Test 7.026 .229
Linear-by-Linear Association 5.064 1 .024 .026 .014 .005
N of Valid Cases 3 412
a. 7 cells (50.0%) have expected count less than 5. The minimum expected count is 1.54.
Source: Author’s calculations.
Table 5.8 indicates that the basic assumption of the test was not met as 50% of the cells have expected frequencies of less than 5. However, as described in section 4.4.4.2 the Fisher’s Exact test should thus be reported as a result of this violation. The null hypothesis cannot be rejected, as it is evident that there is no statistically significant relationship between age and student loan uptake, based on a 0.229 exact significance level.
Following on from the results of the chi-square test, it was necessary to determine which of the variables presented in the heuristic model in Table 4.1 have an impact on the respondents’ usage of student loans. The results of the impact of the independent variables on the use of student loans are presented in Table 5.9.
Table 5.9: Impact of the independent variables on the usage of student loans by the respondents
β SE Wald df Sig. Exp(β)
Life stage .097 .270 .129 1 .720 1.102
Number of financial assets .631 .227 7.759 1 .005 *** 1.880
Housing assets -.356 .707 .253 1 .615 .701
Currently living with your parents .099 .785 .016 1 .899 1.104 Children/dependants up to 12 years -1.891 1.054 3.220 1 .073 * .151 Children/dependants 13 years and
plus -13.684 674.819 .000 1 .984 .000 Level of education .514 .169 9.244 1 .002 *** 1.672 Household income -.642 .537 1.428 1 .232 .526 Personal income .195 .538 .132 1 .716 1.216 Marital status .250 .516 .235 1 .628 1.284 Family size .167 .171 .953 1 .329 1.182 Work status .206 .190 1.179 1 .278 1.229 Self employed .431 .772 .312 1 .576 1.540 Occupation .264 .178 2.212 1 .137 1.303
Changed jobs in the past 12
months 1.372 .717 3.658 1 .056 * 3.943
Got married in the past 12 months -14.044 1906.088 .000 1 .994 .000
Moved in the past 12 months -.199 .740 .072 1 .788 .820
Spent money on education in the
past 12 months 1.690 .670 6.354 1 .012 ** 5.418
*p<0.1, **p<0.05, ***p<0.01
Source: Author’s calculations.
In accordance with the life cycle model, as a household progress through the various life stages, this has an impact on its participation in the student loan market. As a household accumulates more financial assets, there is a positive effect on the holding of student loan facilities. For more information, refer to a similar discussion in section 5.3.1 regarding credit card debt. Households who rent the property they reside in have the highest probability of holding student loans as opposed to households who are homeowners. Households headed by respondents who currently live with their parents are more likely to make use of student loan facilities than those who do not live with their parents. When looking at the overall position relating to households who have dependent children up to and including 12 years of age and households who have dependents older than 13 years of age, it appears as though they have less demand for student loan facilities than households who do not have any dependents or who have fewer
dependents. As the head of the household becomes more educated, there is a positive effect on the use of student loan facilities. This is in line with the heuristic model in Table 4.1. Households who have lower levels of income are more likely to make use of student loans. Personal income is not statistically significant in explaining take-up of student loans. Households headed by people who are married, divorced or separated are expected to have an increased need for student loan facilities as compared to households who are headed by singles. Households that consist of more people tend to have a greater demand for student loans facilities, which is in line with the heuristic model in Table 4.1; however, this predictive effect is low. In terms of the work status of a household head, people working full-time are least likely to make use of student loans, while people who are not working are most likely to use student loans, followed by part-time employees. The reason may be that students may take time off their studies to gain an education and thus require the assistance of a student loan. A self- employed person is more likely to hold a student loan. The reason behind this may be that self-employed individuals are not in the position to receive study assistance from their employers as is the case with individuals who do not work for themselves – in line with the heuristic model in Table 4.1. As a person moves into an occupation requiring higher levels of skill, they have an increase in the demand for student loans. On the one hand, households headed by individuals who have changed jobs in the past 12 months and spent money on education are predicting factors for households making use of student loan facilities. Then again, households who have individuals who got married and moved in the past 12 months are not likely to make use of student loans. The statistical significance relating to the various variables will be discussed in greater detail in section 5.4.
Figure 5.8: Hazard function for student loans use
Source: Author’s calculations.
Figure 5.8 indicates that the respondents have an increased probability of taking up student loans from approximately 26 years of age, which steadily increases as an individual ages. This variable was only included from the 2007 survey and thus the information was only available from the age of 26. As expected and referring back to the heuristic model in Table 4.1, the probability of holding this type of debt therefore increases as the head of the household gets older. The results are consistent with the life cycle hypothesis, which suggests that the debt holding of households has a pronounced life cycle pattern.