Data Sources and Definitions
This appendix contains a brief description of the data used in the estimation.
Data on skill levels by racial groups for the nonprimary sector plus mining are available from the manpower surveys, which measure the number of workers in 28 occupations by racial group. These occupations are then aggregated into three types of occupations, high level, middle level and half/unskilled. High level occupations are essentially professional jobs: they include managers, engineers, lawyers, nurses and educationalists. The later two occupations make up some 40 percent of the total, and are particularly important for the nonwhite racial groups. Middle level occupations represent clerical or skilled manual jobs, while half/unskilled jobs are not differentiated. In the estimation, the skilled workers were those in the high level occupations while the unskilled workers were an aggregate of the middle and half/unskilled job categories. This appeared to be the most reasonable division given the need of a modern economy for highly trained individuals. One concern, however, is that the mix of employment within these occupations may not be the same across racial groups; in particular, white workers may tend to have more skilled jobs within the broad skilled and unskilled job categories, which may cause biases in the estimation.
The surveys were carried out every other year from 1965 to 1987, after which they moved onto an annual basis; from 1965–1987 the data for even numbered years were linearly interpolated.
Annual data on remuneration of labor by racial group for the nonprimary sector between 1970 and 1989 were obtained from South African Statistics. Section 7, 1990, and earlier issues. The data give employment, total wages and salaries and wage rates by racial group. Standardized employment series, which were used in some of the calculations, were also obtained from South African Statistics, while the national accounts data come from a tape supplied by the Reserve Bank.
Bayoumi, Tamim, “Output, Employment and Financial Sanctions in South Africa”, International Monetary Fund Working Paper WP/90/113, (December 1990).
Findlay, R and M Lundahl “Racial Discrimination, Dualistic Labor Markets and Foreign Investment”, Journal of Development Economics (1987).
Hofmeyr, J. “Black Wages: the Post-War Experience” in The Political Economy of South Africa ed N. Nattrass and E. Ardington, Oxford University Press (Cape Town 1990).
Iyengar, M. and R. Porter, “South Africa Without Apartheid: Estimates from General Equilibrium Simulations”, Journal of International Development, Vol 2:1, (1990).
Knight, J. and M. McGrath “The Erosion of Apartheid in the South African Labor Market: Measures and Mechanisms”, Discussion Paper No. 35, Institute of Economics and Statistics, (September 1987).
McGrath, M. “Economic Growth, Income Distribution and Social Change” in The Political Economy of South Africa ed N. Nattrass and E. Ardington, Oxford University Press (Cape Town 1990).
Terreblanche, S. and N. Nattrass “A Periodization of the Political Economy since 1910” in The Political Economy of South Africa ed N. Nattrass and E. Ardington, Oxford University Press (Cape Town 1990).
Sadie, J., “A Reconstruction and Projection of Demographic Movements in the RSA and TBC Countries”, Bureau of Market Research, University of South Africa (1988).
Van den Berg, S., “On Interracial Income Distribution in South Africa to the End of Century,” The South African Journal of Economics, Vol. 57, No. 1 (1989).
The authors are grateful to Desmond Lachman and Ken Bercuson for their helpful comments.
Some exceptions would include the labor market study of Knight and McGrath (1987), the general equilibrium analysis in Iyengar and Porter (1990), and the projections of future income shares contained in van der Berg (1989) and Porter (1991).
There are conflicting estimates of the overall level of labor’s income share. For example, consistent data from South African Labor Statistics for the nonprimary sector estimate the share at around 45 percent (upper panel, Chart 2). This low level probably reflects an under-recording of employment: if the share is grossed up using recent estimates of employment on a “standardized basis” (also available in Labor Statistics), it rises to about 65 percent. By contrast, national accounts data for the whole economy put labor’s share at just under 60 percent. In this paper, the largest of these three estimates is used as it is the closest to international norms.
The data are based on South African Manpower Survey definitions. See the appendix for more details.
In principle, the labor force is composed of a continuous spectrum of skills. The division here (broadly speaking) classifies professionally qualified workers and managers in the skilled category and the remainder of the labor force in the unskilled category. See the appendix for more details.
This is an algebraic representation of the model of apartheid in Porter (1978); in particular see Figure 2. In the interests of brevity, the precise algebraic model derived by the present authors is not detailed here.
The numbers in Knight and McGrath refer to the difference between white and black workers. However, since the other races are a relatively small part of the overall workforce the comparison is still useful.
But because of rapid growth of skilled employment, the share of labor earned by the skilled segment of the labor force is estimated to have risen sharply over the sample period.
The decomposition Is presented for four successive five-year intervals to smooth out cyclical movements.
Nevertheless, even a modest rise in domestic savings might require a degree of fiscal stringency that could be at odds with the need to redress social imbalances through higher government spending. See IMF (1992).