Ebook Earnings and Employment Dynamics for Africans in Post-apartheid South Africa: A Panel Study of KwaZulu-Natal
The problems of low labour market earnings and high unemployment are at the forefront of debates about labour market policy in contemporary South Africa. High and rising unemployment rates contribute massively to poverty, but many people also earn little in the labour market because they work for few hours per week or receive low hourly wages, particularly in the informal sector. For individual South Africans, moving between the categories of unemployment, informal sector work and formal employment usually means big shifts in earnings and well-being. To understand poverty and inequality in South Africa, it is therefore crucially important to examine earnings dynamics and the patterns and dynamics of shifts (or transitions) between the categories of involvement in the labour market.
The orthodox view of contemporary labour market dynamics in South Africa points to very low entrance rates into regular employment (i.e., the opportunities to move into formal sector employment are small in comparison to the number of people wanting to make this move). Recent studies confirm this by showing that while there was growth in formal sector employment in the late 1990s, this was far short of the number of jobs required to match new entrants (Poswell, 2002; Statistics South Africa, 2002).
On the earnings side, real wages in regular employment have stayed constant or increased despite the fall in employment (Fields et. al., 2000; Fedderke and Mariotti 2002). Wage trends thus appear to be insensitive to unemployment. It has been argued that this wage rigidity, due primarily to labour market legislation, contributes to the inability of the labour market to create formal sector jobs and to a lack of integration of earnings and conditions of employment between the formal and informal sectors of the economy (Nattrass, 2000a)
Most recent analyses of these employment and earnings issues have carried out econometric modeling using national data from surveys such as the 1993 survey conducted by the South African Labour and Development Research Unit (SALDRU) at the University of Cape Town or the 1995 October Household Survey conducted by Statistics South Africa. Data from these surveys provide ‘snapshot’ views of the operation of the labour market at one point in time. Using these data, studies have revealed the importance of a range of factors including race, gender, education, and location in the determination of both employment and earnings (Hofmeyr, 2000; Fallon and Lucas, 1998; Bhorat and Leibbrandt, 2001; Kingdon and Knight, 2000 and 2001a). In addition to these factors, hours of work, public/private divisions, industry, occupation, union membership and racial and gender discrimination have also been shown to be significant determinants of earnings (Moll, 1993; Mwabu and Schultz, 1996, 1998, and 2000; Jensen, 1999).
Given the static nature of these data, the authors have been appropriately reluctant to make simple extrapolations from their analyses of the labour market at one point in time to dynamic earnings and employment issues. A number of empirical studies have attempted to deal with these dynamic questions by comparing data from at least two cross-sectional surveys. These studies have shown that one can use these series of cross-sections to profile accurately employment, unemployment and earnings changes at aggregate and even disaggregated levels.
The analysis of aggregate, sectoral and occupational employment trends has highlighted the impacts of trade and technology in driving formal sector employment changes (Bhorat and Hodge, 1999; Edwards, 2000). The analysis of unemployment has shown that both measured unemployment rates and the profile of the unemployed are robust across data sets and across time (Klasen and Woolard, 1999; Nattrass, 2000b; Kingdon and Knight 2001a). The analysis of earnings has revealed a persistence of large earning sinequalities (Moll, 2000; Bhorat, 2000), large average arnings differences by race and gender that cannot be accounted for by measurable characteristics of the earners (Moll, 2000; Allanson et al, 2000; Rospabe, 2001), and large average wage premia for unionised African workers (Rospabe, 2001; Hofmeyr and Lucas, 2000; Michaud and Vencatachellum, 2001).
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