The data available for vehicle finance was only included on the questionnaires from 2007 onwards and the information is therefore available for respondents aged from 26 to 32. Vehicle finance usage for the age group used in this study is indicated in Figure 5.9.
Figure 5.9: Respondents making use of vehicle finance
Source: Author’s calculations.
As the youth complete their studies and find employment, they find themselves in a position to be able to apply for vehicle finance. This trend is indicated in Figure 5.9, which reflects the percentage of the respondents who indicated that they make use of vehicle finance.
Sub-hypothesis 5
𝐻05: There is no statistically significant relationship between age and vehicle
finance uptake.
𝐻𝐴5: There is a statistically significant relationship between age and vehicle
finance uptake.
Table 5.10 indicates the results of sub-hypothesis 5.
Table 5.10: Chi-square test Vehicle finance and Age
Value Df Asymptotic Significance (2- sided) Pearson Chi-Square 6.964a 6 .324 Likelihood Ratio 6.745 6 .345 Linear-by-Linear Association .768 1 .381 N of Valid Cases 3412
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 9.69.
Source: Author’s calculations.
0.00% 0.50% 1.00% 1.50% 2.00% 2.50% 3.00% 3.50% 4.00% 26 27 28 29 30 31 32
The null hypothesis cannot be rejected, as it is evident that there is no statistically significant relationship between age and vehicle finance uptake, based on a 0.324 asymptotic 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 vehicle finance. The results of the impact of the independent variables on the use of vehicle finance are presented in Table 5.11.
Table 5.11: Impact of the independent variables on the usage of vehicle finance by the respondents
β SE Wald Df Sig. Exp(β)
Life stage -.007 .090 .007 1 .936 .993
Number of financial assets .691 .090 58.841 1 .000 *** 1.997
Housing assets -.820 .283 8.383 1 .004 *** .440
Currently living with your parents .887 .367 5.834 1 .016 ** 2.429 Children/dependants up to 12
years .168 .342 .243 1 .622 1.183
Children/dependants 13 years and
plus -.159 .394 .163 1 .686 .853 Level of education .148 .083 3.192 1 .074 * 1.160 Household income .676 .224 9.099 1 .003 *** 1.966 Personal income -.013 .211 .004 1 .950 .987 Marital status .013 .216 .004 1 .951 1.013 Family size -.139 .111 1.569 1 .210 .871 Work status -.279 .142 3.877 1 .049 ** .756 Self employed -.876 .418 4.400 1 .036 ** .416 Occupation .033 .058 .329 1 .566 1.034
Changed jobs in the past 12
months .365 .353 1.071 1 .301 1.441
Got married in the past 12 months .614 .565 1.184 1 .277 1.848
Moved in the past 12 months .106 .309 .117 1 .732 1.111
Spent money on education in the
past 12 months .452 .368 1.507 1 .220 1.571
*p<0.1, **p<0.05, ***p<0.01
Source: Author’s calculations.
It appears that a household in the earlier stages has an increased demand for vehicle finance. As a household accumulates more financial assets there is a positive effect on the holding of vehicle finance facilities. The discussion in section
5.3.1 likewise applies to vehicle finance. Households who pay rent for the property they reside in have the highest probability of holding vehicle finance, as opposed to home-owners, who are less likely to make use of vehicle finance. Households headed by respondents who currently live with their parents are more likely to make use of vehicle finance facilities than those who do not live with their parents. Households who have dependent children up to and including 12 years of age have a greater demand for vehicle finance as opposed to households who have dependents older than 13 years of age, who have less demand for vehicle finance facilities. Level of education is positively associated with vehicle finance usage and is in line with the heuristic model in Table 4.1. Personal income has a low predictive effect. Household income has a positive predictive effect on the particular household making use of vehicle finance facilities, which is in line with the heuristic model in Table 4.1. In particular, household income has a statistically significant effect. Thus, as a household earns more income it is more likely to utilise vehicle finance facilities. Households headed by people who are married, divorced or separated are expected to have an increased need for vehicle finance as compared to households who are headed by singles. Larger households are less likely to hold vehicle finance debt, the reason being similar to the explanation given in section 5.3.1. Respondents who are employed full time are the most likely to take on vehicle financing – in line with the heuristic model in Table 4.1. Self- employed individuals as opposed to individuals who work are less likely to make use of vehicle finance debt. Occupation is not statistically significant in explaining the usage of vehicle finance. Households headed by individuals who have experienced the following events during the past 12 months are more likely to make use of vehicle finance: changing jobs, getting married, moving house and spending money on part-time or correspondence education. These activities are valuable in determining the events that may drive households to participate in the vehicle finance market. The statistical significance relating to the various variables will be discussed in greater detail in section 5.4.
Figure 5.10: Hazard function for vehicle finance use
Source: Author’s calculations.
Figure 5.10 indicates that the respondents have an increased probability of taking up vehicle finance from approximately 26 years of age, which steadily increases as individuals age. 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.