This study does not explicitly investigate the determinants of entry into self- employment however it does ask the question: ‘Why is the self-employment rate so low despite high levels of unemployment?’ The findings of this study indicate that self-employment does not act as a ‘free entry zone’ in South Africa. As a result, it seems likely that barriers to self-employment entry must exist. This finding is consistent with other South African literature on the subject (see Kingdon & Knight 2007). However, the study found gender parity in self-employment entry despite evidence of significantly higher female unemployment rates. This finding begs the question: ‘If entry barriers into self-employment were the same for men and women, what accounts for this discrepancy?’ The answer may be that entry barriers into self- employment are more severe for women than men.71
71 The presence of low returns to NASE could be a factor in explaining low female self-employment rates, particularly if self-employment is riskier or generates less secure income than wage employment.
In Chapter Four, I disaggregated self-employment by sector and demonstrated that females are disproportionately over-represented in the informal sector and tended to be ‘crowded’ into service sector work, particularly the wholesale and retail trade industry. Although the feminisation of self-employment has continued during the 2001-2007 period, I found little evidence to suggest that this skewed composition was changing. Indeed the observed trends in self-employment seemed to have only cemented gender inequality within self-employment.
In Chapter Four, I also tracked changes in the size of the earnings gap between men and women in NASE. The focus of this analysis was an exploration of the observed gap in order to identify determinants. A partial explanation could be the gender difference in hours worked, with men working significantly longer hours than their female counterparts. This is consistent with the hypothesis advanced by Hundley (2001a, 2001b) who argues that women devote less time to their self-employment activities due to domestic burdens and, as a result, have lower earnings. The concentration of the female self-employed in the informal sector may also offer an explanation, as the informal non-agricultural self-employed earn substantially less than their formal sector counterparts. However, even after controlling for hours worked and the sector of employment, I still identified a clear gender gap in returns to NASE.
In Chapter Five, I examined characteristics of the non-agricultural self-employed using multivariate econometric techniques, and probed the determinants of NASE earnings among men and women. The estimated coefficients in these earnings regressions showed that being male is associated with higher returns, even after controlling for a series of demographic employment-related and human capital variables. Indeed, the findings of Chapter Five, suggest the presence of gender discrimination either in the form of consumer discrimination or ‘statistical discrimination’. The estimates also reveal that working in the informal sector has a significantly negative impact on returns.
In order to provide clarity on this issue, this study notes the suggestion by Steenkamp (2008:98), and similarly suggests that an in-depth investigation of ‘reservation wages’ is required.
I also investigated different determinants of NASE earnings disaggregated by gender.
While differing returns to human capital variables were not found to explain adequately the observed gender gap, key differences were noted when examining race, location and employment sector. Unlike other econometric studies in South Africa, this study also identified location of business premises as a key determinant of earnings and found that although home-based individuals earned less than those operating outside the home, if this finding is disaggregated by gender it is evident that being home-based had a greater penalty on NASE returns for women when compared to men.
While the investigation in Chapter Five offers a partial explanation for the observed gender gap, this investigation does not touch on access to finance and basic services for those in informal NASE. Research has shown that access to these services can serve as a significant determinant of business performance (see Parker 2004; Hughes 2005; Maas & Herrington 2006; Allen et al. 2008; and Elam 2008). These services also play a role in explaining entry barriers to informal self-employment. In order to provide clarity on this issue, access to financial and basic services for NASE owners is investigated in Chapter Six.
Despite a clear policy directive by government as well as pledges by civil society groups to assist the informal self-employed with business start-up (see Rogerson 2008:62-70), limited access to formal credit markets or government and/or NGO grants was reported. This seems to indicate that public and private credit institutions have failed to service NISE-owners adequately, which is consistent with the findings of more localised studies (see, for example, Chandra et al. 2001; Skinner 2005;
Cichello et al. 2006; and Clarke et al. 2006). Most of the non-agricultural self- employed utilised stockpiles of financial capital accumulated from wage employment and credit from friends and/or relatives. Given the more unfavourable position of women in the labour market, female NISE-owners reported having more limited access to these sources of capital. Facing greater financial constraints to start-up, it is unsurprising that female NISE-owners reported lower expenditures, gross incomes and net profits. In addition to inferior access to financial services, female NISE- owners reported poor levels of service delivery as well as inadequacies in location and
access to transport. These findings suggest that financial constraints and unfavourable environments hinder the economic progress of female NISE-owners and probably obstruct the entry of women into informal NASE.