Collins C. Ngwakwe¹, Badar A. Iqbal²

Abstract: financial grant creates an avenue to reduce poverty, inequality and to improve equitable economic development. The objective of this paper is to examine the effect of social financial grant increases on poverty alleviation in South Africa. The paper inclines on prior poverty theories of economic growth, which highlights the use of social financial grants to achieve poverty reduction and equitable economic growth. The paper applies a quantitative approach; data on social grants were from the publications of the South African department of statistics and the South African Social Security Agency. The ensuing cross-sectional data were analysed using the structural equation modelling approach. Findings from the analysis indicate that, amongst the seven types, only three namely, the grants for old age, grants for disability and grants for supporting a child enhances reduction in inequality. On the contrary, four of the seven social grant types enhance reduction in poverty level; these are the grants for war veterans, aid grants, grants for dependency, and grants for fostering a child. The paper highlights policy implications of the findings, which includes inter alia, that policy makers may target poverty reduction or inequality reduction using specific social grant types. Findings from this paper provide an avenue for further research to assess poverty and inequality reduction through these social grant types in other developing economies. Such research should check if this current research result is replicable using social grant data from other developing countries. This paper uniquely applies the SEM model to evaluate poverty and inequality implication of social grants in South Africa.

Keywords: economic development; social financial grant, social security; poverty alleviation; inclusive growth

JEL Classification: O10; O15; O20

1. Introduction

The last twenty years has experienced a continuous rise in poverty trend with attendant increase in inequality level, which is still one of the biggest issues for developing economies even if they are on the steady pace of growth (Lilenstein, et. al., 2016). From the economic, social and political perspective, income inequality is disadvantageous as it leads to various social issues (Chetty et. al., 2016). Since 1994, South Africa has persistently shown positive economic growth until 2018, except in the year 2009, where it showed a negative growth. To reverse the adverse effect of dismantled domineering regime, the South African government has taken significant steps to improve citizens’ access to basic public goods to reduce inequality and poverty (South African Government, 1997). However, even after such initiatives, South Africa is still ranking high in inequality in the world; this shows that the perceived economic growth has had no significant reduction effect on inequality (World Bank, 2018). Hence Tseng (2013) bemoans that the post-apartheid growth appear to benefit those at the top of the society more than those at the bottom end as the celebrated growth has not proven to be pro-poor and inclusive (Tseng, 2013). However, research suggests that social grant should have a direct effect on inequality (Mabugu, 2019; Tseng, 2013).

Some scholars have evaluated social grant impact on the recipients in South Africa; for instance, Granlund and Hochfeld (2019) applied a qualitative study to find that social grant in the form of child support grant has had a positive effect on the social life of recipients and their families in a rural community in South Africa. In another research, Dubihlela (2014) applied a qualitative analysis and find that social grant has alleviated poverty level amongst female headed households in Bophelong district of South Africa. This paper is different from existing research and makes new contribution because previous research on social grant in South Africa are more sectorial in approach – that is, the previous research have focussed on either a particular community, a province, on women or on men and most of these have also adopted a qualitative approach. Accordingly, previous researches have not holistically covered the entire spectrum of the nine provinces of the country to look at how the entire genre of social grant affects inequality and poverty in the entire country. This paper contributes to existing research because, it covers the entire seven social grants in South Africa; in addition, the paper uses a quantitative approach (structural equation model approach), not applied in previous research and covers the entire nine provinces of South Africa. This holistic coverage of the whole country provides a new and broader policy insight to social security agency department on how each social security type is affecting inequality in the country. This approach is the first in current literature in South Africa and hence contributes to existing research and social grant policy.

1.1. Objective of the Paper

Accordingly, the objective of this paper is to examine whether increases in social grant (according to grant types) assists in reducing inequality and if the social grant increase helps in poverty reduction. Hence, this paper provides an answer to two main research questions namely, how increase in social grant influences inequality reduction, and how does social grant affect poverty reduction in South Africa?

1.2. Problem Statement

The current democratic government in South Africa inherited economic inequality and poverty from the previous undemocratic regimes (Tshishonga, 2019). Accordingly, the democratic government instituted many equitable economic development policies amongst which includes the currently expanded social grant system, which takes care of all the citizens (Salahuddin, et al. 2020). However, despite all these measures, economic inequality is still on the rise and poverty is not dropping to a desired significant level (Cheteni, et al. 2019). Extant literature is still scant on how the increased grants types and number of grant recipients is influencing poverty reduction in South Africa especially by using a structural equation model approach. This paper thus makes a nuance contribution to the literature.

2. Literature Review

This paper inclines on the economic theories of poverty, which regards poverty as anti-developmental (Davis & Sanchez-Martinez, 2015). When summarized, the economic theorization of poverty sees poverty as a negative force to retards economic development. Scholars of economic theorization of poverty also regards the existence of poverty as economic discrimination, which inhibits economic development of a nation. Therefore, in order to enable social and economic justice, the government uses anti-poverty measures such as payment of minimum wage and social security or social grant for the unemployed and old aged citizens (Lita, 2020; Aribaba et al, 2020).

Van der Berg et al (2010) opined that social grants assists in cushioning various types of risks associated with loss of income such as unemployment, basic health, old age, and disability. With the help of social grants, efforts on redistribution of income in order to curb the level of inequality can also be feasible. Bergh and Nilsson (2014) through theoretical assessment found that price changes induced by higher inequality of income might be profitable for the poor people. Accordingly, the market of goods focusing the poor has the potential to grows up and become profitable with an increase in the number of poor.

Schiel et al (2014) applied income decomposition technique to study the impact of transfers from government on inequality. They found that grants given to old age people has no effect on income inequality, however it leads to poverty decline. On the other hand, grants for children had an equalizing effect (Schiel, et al, 2014). In his research, Kyophilavong (2011) finds that in both rural and urban areas, cash availability to impoverished families with children can help in reducing poverty. In addition, the study suggested the widening of grants’ coverage to the society strata, especially among females in order to reduce poverty and inequality among them. Xaba (2016) focuses on whether the livelihood of the recipients is having influence by the social grants in a positive way or not. Social grants also help in generating additional income, which is useful in finding jobs or in starting small businesses. However, due to small amount of grants, poverty and big families, these grants may not be effective in attracting additional benefits (Xaba, 2016).

Satumba et al (2017) studied the impact of social grants as a social protection measure implemented by the government of South Africa. The study applied the income decomposition analysis and Foster-Thorbecke indices. They found that anti-poverty measure plays an important role towards reducing the level of poverty in South Africa. Further, it shows that areas like Limpopo provinces and Eastern Cape of Africa have positive and significant impact of social grants, as in these areas the grants are specifically targeted. Also, the main beneficiaries of such grants are families which are headed by female when compared to male counterpart. Further, a study by Ferreira (2017) found that the size of grant given to older persons have important effect on reduction of poverty. Bhorat et al. (2009) found that South Africa has two sides to its economy as those who have access to wealth found the economy as modern and developed, on the other hand those who are poor, still do not have access to the basic services. According to the study’s findings, wage income is the factor, which influences 80 percent level of the income inequality for all race groups consisting of colored and African group of population. Their research also suggested that the government can redistribute income to cope with inequality through social grant provisions. Further, they found a neutral distribution of grants for both colored and African population (Bhorat et al, 2009).

Biyase and Rooderick (2018) applied a cross-sectional households’ survey and propensity score technique and studied the impact of social grants on the welfare of poor rural households. The study found that social grants have a positive and significant impact on the welfare of rural household also, suggesting that South Africa should continuously focus on rural areas for alleviation of poverty. Mtantato and Ngozo (2018) found that if the government of South Africa increases the amount of social grants consistently at the cost of decreasing investment on infrastructure, it will reduce poverty but without providing employment and growth of the economy. Therefore, the study suggested that infrastructure investment should also increase in order to improve employment and growth of the economy. Therefore, the government should subordinate the social grant reform structure in order to decrease its dependence at the bottom and to have a substantial effect on economic activities (Greenblo, 2019). Social grant programs of other economies around the world have shown growth in terms of poverty alleviation (Osei 2011). However, some researchers indicate that the long-term effect of such grants is still not clear (Molyneux et. al., 2016; Granlund & Hochfeld, 2019). The following section presents a snapshot overview of social grants in South Africa.

According to SASSA (2019), South Africa has seven types of social grants that the government pay out. These are Old AgeGrant, War Veterans Grant, and Disability Grant, The Grant in Aid, Care Dependency Grant, Foster Child Grant, and Child Support Grant. Although SA is in the group of middle-income nation, it ranks high in global inequality measure (ODI 2005). Hence, the SA social security programme is a veritable means of bridging inequality and widespread poverty. The advent of democracy in 1994 witnessed an existing racialized social security system. Accordingly, one of the dividends of democracy has been the dismantling of the barriers to social security system, which has paved a way to improved non-racial system that now service the social security needs of all South African citizens (SASSA 2019). Within this democratic period and the concomitant inclusive social security system, the country has had an expanded growth in social assistance programmes. For instance, whilst the number of social grant recipients stood at 2 million in 1994 (at the birth of democracy), as of March 2019, the total number of social grant recipients had risen to 17.8 million (SASSA 2019). This growth in social grant (Figure 1) provides benefits to about 30 percent of the South African population. This expansion in social security has meant additional financial responsibility for the government as it gulped more than 3 percent of the country’s GDP in 2018-2019 fiscal year, with a financial implication amounting to R163 billion on social assistance for the 2018-2019 financial year (SASSA 2019).

Figure 1. Growth in Number of Social Grants Recipients in South Africa (1996/1997 – 2018/2019)

Source: Authors Graph, with Data from SASSA’s Various Annual Reports

3. Method and Result

Data for this paper were from various annual reports of the South African Social Security Agency (SASSA), which is publicly available at the SASSA’s annual reports archives. Furthermore, data on inequality trend (proxied by expenditure inequality per capita per province) in South Africa were from the Statistics South Africa (2019). As recognized by the World Bank (2018), the expenditure inequality is by proxy of the GINI coefficient; hence, the data on expenditure GINI coefficient per capita by province represents inequality. The focus on the nine provinces of South Africa makes the result more reliable as it covers both the most poor and rich provinces of the country.

Data is valid since the data compilation and validation is from the Statistics South Africa. In order to capture the current situation, cross-sectional data on social grant per type and per province were in the analysis against expenditure inequality per capita and per province using the structural equation modelling (SEM). The SEM is a statistical approach used in testing the relationship between cross-sectional data on observed and latent variables (Hoyle, 1995; Anderson & Gerbing, 1988).

The data is cross-sectional because the research collected the 2018 data on social grant, which is the latest comprehensive government data on the seven social grant types from each of the nine provinces of South Africa. The represents the nine observations taken at one period (cross-section); this form of cross-sectional data is also indicated and supported by experts such as (Hoyle 1995; Anderson and Gerbing 1988). The number of social grant given out is in the official report of South African Social Security Agency 2018. In the same vein, the latest data on inequality measured by Gini Coefficient were from Statistics South Africa, the research made use of the Gini figures contained in the report of the Statistics South Africa. This analysis focuses on inequality and poverty because inequality transcends the poor and measures inequality across the entire population (World Bank 2018). Amongst others, there are two key measures of inequality by the World Bank, namely the expenditure inequality or income inequality (World Bank 2018). This paper chose to use expenditure inequality since peoples’ expenditure is relies on their total income ability and expenditure is a better measure of individuals’ ability to pay for his/her needs (Daneshkohan et. al., 2011).

Figure 2 is the graphic that depicts the Structural Equation Model (SEM) and Table 1 contains the Structural Equation Model (SEM) result for unstandardized estimate approach of SEM. The SEM analysis comprised seven cross-sectional data, which made up of the independent variables namely, the old age grant, war veterans grant, disability grant, grant in aid, care dependency grant, foster care grant, child support grant, and the dependent variable, which is the GINI (inequality index for expenditure per capita by province).

The SEM model in Figure 2 shows the independent variables at the left hand-side and the dependent variable is flanked at the right hand-side with arrows pointing from the left to the right to indicate the effect of the independent variables (social grant types) on the dependent variable, which is inequality represented by (GINI index on expenditure per capita). The coefficients for each variable are contained in column 2 of Table 1. These coefficients appears on the side of the arrows linking each independent variable to the dependent variable in Figure 2. Since the objective of the paper is to examine the degree to which social grant increases affect inequality in South Africa, attention is on column 2 and column 5 of Table 1. The coefficients in column 2 represent the degree of change in inequality arising from one unit increase in social grant. Also column 5 contains the probability value (p-value), which shows whether a significant relationship exists between social grant type and inequality. At an alpha level of 0.05 (5%), the P-values, which are below or equal to 5% indicate a significant relationship. Accordingly, it shows that all the social grant types (except child support grant (csg)) have p-values less than 5%. This indicates a significant relationship between the six social grant types (Care Dependency Grant (cdg), Disability Grant (dg), Foster Child Grant (fcg), Grant-In-Aid (gia), Older Persons Grant (oag) and War Veterans Grant (wvg)). On the contrary, the child support grant (csg) indicate a p-value of 0.139, which is higher than 5% alpha value; this shows that within the data scope of this paper, child support grant has no significant relationship with inequality. It is likely that social grant per child support may not be sufficient to support the needy child (this requires the attention of future researchers).

In answering the research question on which of the social grants may reduce inequality, attention is on the signs of the social grants’ coefficients on column 2 of Table 1. Since one of the major goal for instituting social grant is to curb inequality, it is therefore pertinent to point out the social grant types that help to reduce inequality so that social grant policy makers may pay attention to these social grant types. From column 2 of Table 1, it can be seen that three social grant types, namely old age grant (oag), disability grant (dg) and child support grant (csg) show negative signs on their coefficients, which thus shows that the increase in these social grants has the propensity to decrease inequality. This is in consonance with Armstrong and Burger (2009) wherein they opine that social grants with negative signs contributes to inequality reduction. Table 2 and Figure 3 provides additional analysis, which evaluates how the social grant types relate with poverty reduction. A different result emerges regarding how the social grant types affect poverty, which is completely different from those under inequality analysis contained in Tale 1 and Figure. Observing the signs of the coefficients in Table 2 shows that four social grant types namely war veterans grant, grant-in-aid, care dependency grant and foster child grant enhances poverty reduction. This is because these four social grant types have negative coefficients, which indicates that increase in these social grants will lead to a reduction in poverty.

From the foregoing results, Figure 4 presents a schematic representation of findings regarding influence of the social grant types on poverty and inequality reduction. Thus, drawing from the results in Table 1 and Table 2, Figure 4 give a snap short view, which shows that the social grant types that enhance inequality reduction are different from social grant types that enhance poverty reduction. Out of the seven social grants, only the old age grant, disability grant and child support grant enhances reduction in inequality. However, four social grant types namely war veterans’ grant, grant-in-aid, care dependency grant and foster child grant enhances reduction in poverty. This is particularly important for policy makers to which social grant to focus attention when targeting poverty or inequality reduction; reason being that the results indicate that one type of social grant may not necessarily achieve both poverty and inequality reduction at the same time (this is however subject to further research verification).

Table 1. Structural Equation Model Results for Social Grant and Inequality in South Africa

Source: Authors’ Result

Figure 2. Structural Equation Model for social grant and inequality in South Africa

Source: Authors’ result

Table 2. Structural Equation Model Results for Social Grant and Poverty in South Africa

Figure 3. Structural Equation Model for Social Grant and Poverty in South Africa

Source: Authors’ Result

Figure 4. Social Grant Types versus Inequality and Poverty in South Africa

Source: Authors

2.1. Implication

The foregoing findings has practical, academic and research implications. On the practice aspect, policy makers may target equitable economic growth policy through poverty reduction or inequality reduction using specific social grant types as indicated in Figure 4. Furthermore, these findings provide valuable academic and research material for teaching and researching economic development policies at the university level. Findings from this paper provide an avenue for further research to assess poverty and inequality reduction through these social grant types in other developing economies. Such research should check if this current research result, which is relies on South African data is replicable using social grant data from other developing countries.

2.2. Value (Contribution)

This paper makes a novel contribution to the literature by being one of the few papers that uniquely applies the structural equation model to evaluate poverty and inequality implication of social grants in South Africa. It further contributes by providing a new framework as in Figure 4 for understanding variables that have relational links with inequality and poverty respectively.

3. Conclusion

This paper set out to analyse the effect of social grant increases on inequality and poverty reduction in South Africa. Applying the structural equation modelling approach, the paper makes novel findings from the statistical results. The findings indicate that, within the data scope of this paper, not all the social grants types enhance reduction in poverty and inequality jointly. Amongst the seven types of social grants, only three of these, namely, the old age grant, disability grant and child support grant enhances reduction in inequality. On the contrary, from the seven genre of social grants, four of these enhances reduction in poverty level; these are the grants for war veterans, aid grants, grants for dependency and grants for fostering a child. It is noteworthy to point out important policy feature from the results, which is that the social grant types, which reduce inequality are different from the social grant types that may reduce poverty (Figure 4). This paper thus provides new contribution for policies toward inequality and poverty reduction in South Africa. On the one hand, if the government intends to reduce inequality through the social grants, it should pay closer attention (in terms of administrative and revenue policies) on (Oag, dg, csg), which is the grand for old age, grants for disability and grants for child. On the other hand, government’s poverty reduction policies through the social grants should be more focussed on (wvg, gia, cdg and fcg), which is the grants for war veterans, aid grants, grants for dependency and grants for fostering a child. The implication thus is that policy makers may target poverty reduction or inequality reduction using specific social grant types to achieve equitable economic development in South Africa. These new findings provide an avenue for further research to assess poverty and inequality reduction through these social grant types in other developing economies. Such research would check if this current research result, which relies on South African social grant data is replicable using social grant data from other developing countries.

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