In part two of his blog examining inequality in Johannesburg, guest blogger Owen Crankshaw uses census data to explore reasons behind inequalities in the workforce and challenges accepted wisdom, writes David Satterthwaite, who curates this series of blogs. The first part looked at trends in racial inequality including the extent of desegregation in neighbourhoods that were formerly Whites-only (as defined by the apartheid-era 1950 group areas act), and the growing size of a high-income Black middle class.
Is the economically-active population of global cities becoming more polarised into occupational classes of mostly low-paid service sector jobs at one extreme, and highly-paid professionals, technicians and managers, at the other?
Or is the employed population becoming generally more skilled and better paid, alongside growing unemployment? These are the claims concerning urban inequality made by the social polarisation theory and the professionalisation theory respectively.
Proponents of social polarisation theory argue that inequality is caused by the concentration of employed workers at the extremes of the earnings distribution.
By contrast, proponents of the professionalisation theory argue that inequality is caused by the concentration of employed workers at the higher end of the earnings distribution alongside growing unemployment.
Testing the two theories
This study of employment trends in the province of Gauteng, which I will call ‘greater Johannesburg’, provides us with an important test of these competing theories. The reason for this is that the long-term employment trends in greater Johannesburg show that there was occupational and earnings professionalisation among employed workers in the context of growing levels of unemployment among low-skilled workers.
In a nutshell, there were employment trends of many more people in middle- and high-income occupations than there were in low-income occupations.
Meeting three conditions
This study is an important test of the social polarisation theory because greater Johannesburg meets the three conditions that are argued to be its main causes:
- The labour market underwent dramatic deindustrialisation. This is claimed to reduce the number of middle-income manual workers employed in the manufacturing sector, and increase the number of low-income and high-income workers employed in the service sector.
- An adequate supply of low-skilled labour. Scholars have reasoned that social polarisation can only occur under conditions of large-scale in-migration of low-skilled workers to deindustrialising cities. They argue that the increased supply of low-skilled workers results in the growth of low-wage employment necessary for social polarisation to occur.
- No substantial unemployment benefits for unemployed workers. Scholars argue that the absence of unemployment benefits forces low-skilled workers into low-paid jobs that they would otherwise avoid, hence causing social polarisation.
So, according to these theories, employment trends in greater Johannesburg should demonstrate a polarising trend with strong employment growth in low-income and high-income jobs, and a decline in middle-income jobs.
However, the study of employment trends over the period 1970 to 2011 shows that there was a trend of professionalisation, in which there was more employment growth in middle-income and high-income jobs and much less growth in low-income jobs, alongside growing unemployment among low-skilled workers.
This is the latest in a series of blogs and interviews, curated by IIED senior fellow David Satterthwaite, examining different aspects of global urban change.
What the data reveals
Looking at the population censuses, in 1970, 64% of all workers were employed in low-income and middle-income manual jobs. By 2011, employment in these manual jobs had declined to only 40%. Over the same period, the percentage of workers employed in high-income managerial, professional and technical jobs increased from 19% of all employment in 1970, to 28% in 2011.
Employment in middle-income clerical, sales and service jobs also increased from 14% of all employment in 1970 to 31% in 2011 (see the chart below). Over the same period unemployment grew from only 5% to 26%.
These results show that middle-income and high-income jobs grew much more than low-income jobs. Of particular interest is that the largest growth took place among middle-income clerical, sales and services jobs. This conforms more closely to the theory of professionalisation than that of social polarisation, which would require more employment growth in high- and low-income jobs, with less growth in middle-income jobs.
It is also important to note that the growing demand for more educated workers and the declining demand for workers who did not complete high school, contributed to the rising unemployment rate.
Adding to our understanding of inequality in global cities
Studying greater Johannesburg – a city region in the global South – has advanced our understanding of post-industrial labour market inequality and its causes.
First, it confirms the results of research undertaken in other deindustrialising cities, such as Hong Kong, Shanghai, Sydney, Cape Town, London and New York. Notably that urban inequality has taken the form of an increasingly better-qualified and better-paid workforce alongside unemployment among low-skilled workers, rather than a divide between increasing numbers of high-paid workers and low-paid workers.
Second, the main causes of these changes to the labour market were not deindustrialisation, the in-migration of low-skilled workers and the absence of unemployment benefits. Instead, they were largely caused by increased automation in all economic sectors and the associated demand by employers for non-manual and more educated workers.
A word about statistical sources
These results on employment trends by occupational group are based on my analysis of the 1970 and 2011 population census results. Specifically, I used the 10% samples of the full count. These are large samples that provide very precise estimates at a high (95%) level of probability. The precision of these estimates is demonstrated by the narrow confidence intervals in the chart above.
The statistical trends on unemployment are based on my analysis of the population censuses and the quarterly labour force surveys (QLFS). These are sample surveys, with sample sizes ranging from about 3,000 to 4,500 individual cases – giving a high level of precision and reliability.
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Previously Published on iied.org with Creative Commons License
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