Utilización de una pantalla LCD en una aplicación basada en microcontroladores

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70 characteristics of the surveyed households, which are divided into ‘savers’ and ‘non-savers’. Kochhar and Cohn (2011:3) argue that the demographic characteristics of a research population can provide better understanding of their socio-economic circumstances. In this study, the demographic characteristics of the respondents (i.e.

age, gender, and ethnicity) who are the households’ financial handlers have a direct influence on the households’ income, consumption and savings behaviour.

Literature on the life-cycle hypothesis indicates that age is one of the main factors that influence expenditure and savings patterns (Beckmann, 2013:9; Modigliani, 1966:

163; Sarantis & Stewart, 2001:24). The age of the household financial handlers is categorised into youth (16 to 24 years), young adults (25 to 34), adults (35 to 59) and grandparents (60 and above). These categories were chosen by the researcher based on the age of a respondent and are used to take into account the life-cycle hypothesis of savings by household financial handlers. The hypothesis argues that working age individuals (16 to 59) save, while those outside this bracket do not save (Modigliani, 1966:163).

71 The ages of the surveyed household financial handlers range between 16 and 89. The majority (66 respondents representing 30.70 per cent) are adults between 36 and 59 years old. Similar findings were reported by DeNavas-Walt and Proctor (2014:13) in their study of income and poverty in the United States where 62 per cent of the household financial handlers were between the ages of 36 and 59 years. In this study, the average age of adult financial handlers that save is 44.6 with a standard deviation of 6.33. The statistics are similar to those of the adult financial handlers who do not save (with an average age of 44.8 and a standard deviation of 6.56).

In terms of gender, the study finds that 19 (8.8 per cent) respondents are males and 196 (91.2 per cent) are females. From the 19 male financial handlers, 14 (6.5 per cent) are financial handlers of households who save and five (2.33 per cent) are handlers of non-saving households. Saving households that have female financial handlers are 136 (63.26 per cent), while 60 (27.91 per cent) females handle non-saving households. These results indicate that majority of the surveyed households have female financial handlers. Similarly, Paxton’s (2009:209) study of rural farmers’

savings in Mexico revealed that the majority of the household financial handlers were female. Another study by Buijs (1998:55) also found that the primary caregivers who stay at home and handle the finances of poor households are usually females. It was therefore not surprising that the overwhelming number of respondents in this study were females.

Of the 215 households with social grant recipients surveyed, 97.7 per cent (210) classify themselves as Africans and 2.30 per cent (five) classify themselves as Coloureds². The sample area is predominantly populated by Africans, hence majority of the research population classified themselves as Africans. Out of the 210 African households, 149 (69.30 per cent) were financial handlers of households that save and 61 (28.37 per cent) from households that do not save. Out of the five household financial handlers that classify themselves as Coloureds, only one (0.47 per cent) household financial handler saves while the four others (1.86 per cent) do not save.

2 The term coloured in South Africa refers to individuals of a mixed race.

72 Two important factors identified in the theoretical and empirical literature that influence spending and savings patterns are household size and composition. Case and Deaton (1996:1), as well as Duflo (2003:4) have reported that South African households with social grant recipients tend to consist of more members than those without social grant recipients. A similar pattern is reported about Mexican households also (Paxton, 2009:154; Gutiérrez, Juárez & Rubli, 2005:5).

In the South African context, a large household is one that has more than two members (StatsSA, 2011:88). Generally in South Africa, the size of wealthier households is two, while that of poor households is three and above with the national average household size being 3.4 (StatsSA, 2011:7). In this study, households that save have a minimum of one, a maximum of 14 and an average of 4.8 members. Households that do not save have a minimum of one, maximum of 12, and an average of 4 members. This means that on average, the majority of both saving and non-saving households are large.

Besides household composition and demographics, other economic variables might also influence the savings behaviour of households with social grant recipients. Table 5.1 reveals that these are the type of social grants received, remittances, income sources, income pooling and consumable goods purchased by the household.

Poor households have different sources of income, and social grants are only one of these sources. The data indicates that from the seven common social grants, only four social grants were received by the household sampled in Freedom Park. These are the child support, old age, foster child and disability grants. The minimum number of child support grants received by households that save was one, and the maximum received by the saving households was eight. The minimum number of child support grants received by households that do not save was one, and the maximum was five.

The minimum number of old age grants received by households that save was one and the maximum was five. Non-saving households had the same minimum and maximum values for the old age grants. Both the saving and non-saving households had a maximum of three disability grants. The maximum number of foster care grants received by savers is two, and the maximum for non-savers is one. Child support grants are the most received grants, confirming Williams’s (2007:33) study that poor

73 households tend to receive more child support grants than any other type of social grant.

Besides social grants, poor households typically receive additional income from various labour market activities whether in the formal, semi-formal or informal economies, as well as remittances from family and friends (Erfe, 2007; Krige, 2011:22;

Leibbrandt et al., 2011:1). Of the 214 households surveyed, 75 (34.88 per cent) claim that their entire livelihoods are financed by the social grant income. One household did not answer the question on whether the household earns additional income while the remaining 139 households (65 per cent) receive other incomes.

These findings are similar to those of Meyer et al. (2009:43) who found that the majority of households with social grant recipients earn additional income. In this study, additional income come mainly from labour market activities in the semi-formal and informal economies. From the 139 households who receive additional income, 36 (16.74 per cent) saving households and 16 (7.44 per cent) participate in labour market activities. The second major income source for households that save is renting, followed by piece (ad-hoc) jobs. The second dominating income source for households that do not save is domestic work.

Analysing the amount of additional income received from other income sources will provide information on the income patterns of these households. Although 139 households reported to be receiving other income besides the social grant income and remittances, only 110 household respondents could report the monthly income earned from these sources. For saving households, the minimum monthly income value is R100, the maximum is R8 200, and the average is R2 335.50. For their part, non-saving households reported a minimum amount of R260, maximum of R13 000 and an average of R1 927.30. Out of the 110 respondents reporting additional income, 36 claimed that the monthly income is often uncertain and unpredictable in line with Bhat and Nengroo’s (2013:114) argument that remuneration and profits from informal sector activities are often unpredictable.

Only 42 (20 per cent) households indicated that they receive remittances while the majority (173 households representing 80 per cent) reported that they do not. The high

74 percentage that do not receive remittances seem to confirm Ezemenari’s (1997:666) claim that remittances tend to cease to households whose members receive social grants. However, Neves et al. (2009:20) have shown that social grants do not completely crowd out remittances, especially remittances received from relatives and friends. In this study, the saving households received a minimum of R150 remittances, a maximum of R2 500 and an average of R547.90. The households that do not save received a minimum of R100 remittances, a maximum of R1 950 and an average of R761.10.

Literature revealed that extended households often pool resources, especially income, to improve the welfare of the entire household (Case & Deaton, 1998:1340; Neves et al., 2009:17). Table 5.1 shows that households that save pool a monthly minimum of R320, a maximum of R12 450, and an average of R3 267.10 with a standard deviation of 2 139.294. For their part, households that do not save pool a minimum of R320, a maximum of R13 320, and an average of R2 628.20 with a standard deviation of 2 508.264.

Given the relatively low income of the surveyed households, it would be interesting to examine what they spend their aggregate incomes on. It is argued that poor households make use of their aggregate income to purchase consumable items, particularly necessity and normal goods and services such as food, clothing, transport, energy and shelter (Case & Deaton, 1998:1349; Neves et al., 2009:13; Paxton, 2009:211). Necessities are made up of food, shelter, energy, water, clothing and transport while normal goods and services comprise fuel, cosmetics, debt, airtime, school or tuition fees and school uniforms. Luxury goods and services are made up of drugs, gambling, alcohol and tobacco. The expectation of this study was that the households with social grant recipients will mostly spend their income on necessity and normal goods and services.

The average amount spent on necessities are almost the same for saving and non-saving households. For non-saving households, the average is R772.10 per month and for the non-saving households, it is R760.80 per month. Saving households spend a lower average amount of R949 per month on normal goods and services compared to an average of R1 201.20 per month by non-saving households. Thus both saving and

75 non-saving households tend to purchase necessity goods and services more than normal goods. Although the surveyed households are poor, 24 (11.6 per cent) saving households and 24 (11.6 per cent) non-saving households spend some of their income on luxury goods and services. Households that save spend a lower average amount (R153 per month) on luxury goods and services whereas households that do not save spent an average of R186 per month on luxury goods and services. Thus, non-saving households spend more than saving households on luxury goods.

The discussion will now turn to a descriptive analysis of the savings patterns of the surveyed households. A summary of their savings instruments and motives in Table 5.2 below.

Table 5.2: Saving instruments and saving motives of households that save

Variable Obs Mean Max Min SD

Burial society 129 163.6 846 25 108.93

Stokvel 72 366.6 1500 80 261.77

Bank account 56 298.7 1340 50 256.27

Post office bank account 1 - 500 - -

Investment account 1 - 30 - -

Save at home (hoard) 7 381.4 800 100 264.17

Precautionary 119 - - -

Transactional 61 - - -

Liquidity 10 - - -

Housing 15 - - -

Education 13 - - -

Bequest 1 - - -

Source: Survey data

This table shows that out of the 215 households with social grant recipients, 150 save some of their income but mostly using semi-formal and informal saving instruments.

This means that households with social grant recipients do save as has been argued by Armstrong et al. (2008:2), Devereux (2002:657), Leibbrandt et al. (2010:9) and Williams (2007:1). Of the 150 households that save a portion of their income, an overwhelming 129 use burial societies, 56 use bank accounts, one uses an investment

76 account, one saves at the post office, 72 save in stokvels and seven save at home (or hoard money). A minimum of R25 and a maximum of R846 is saved within a burial society with an average of R163.60. For those saving with stokvels, the minimum amount is R80, the maximum is R1 500 and the average is R366.60. Households that save with a bank account save a minimum of R50, a maximum of R1 340 and an average of R298.70.

The information above reveals that majority of the households surveyed belong to a burial society, which they uses as a precaution against experiencing the future financial shock associated with the death and burial of a household member. Burial society monthly contributions are less than those of stokvels and banks, suggesting that households choose burial societies because of their affordable subscriptions.

Similarly, savings in a post office account, investment account and cash hoarding are all more than burial society contributions. The surveyed household that saves with a post office account, saves R500 and the other household with an investment account saves R30. Households that save at home (or hoard cash) save a minimum of R100, a maximum of R800 and an average of R381.40.

Table 5.2 also depicts the savings motives of the surveyed 150 households with social grant recipients that save a portion of their household income. These are revealed to be precautionary, transactional, liquidity, housing, education and bequest. One household saves for bequest, 13 households save for education, 15 for housing, ten for liquidity, 61 for transactional purposes and 119 for precautionary reasons. Saving within a burial society indicates that a household has a precautionary savings motive to cover funeral expenses (Chrétien, 1986:27), something that has been identified among households that reside in informal settlements such as Freedom Park, who mostly save in stokvels and burial societies (Armstrong et al., 2008:18; Djebbari &

Mayrand, 2011:10; Leibbrandt et al., 2010:9).

Typically, stokvel savings are one of the most popular savings instruments for poor households who use them for transactional purposes during holidays, especially Easter and Christmas (Collins, 2005:9-12; Neves et al., 2009:42). This corresponds with the findings of this study, which show that stokvels are the second largest savings

77 instruments and the transactional saving motive is also the second largest saving motive found the 150 households who save.