The power of bosses to set wages explains much of South Africa’s inequality

Image: Paul Hanaoka on Unsplash.

The power of bosses to drive down the wages of workers has long been foregrounded by the slogans of striking workers.

Economists have only recently returned to such notions of power in the workplace, with a focus on bosses who face limited competition from other bosses for the labour that they employ. This is referred to as monopsony power. In addition to driving down wages, monopsony power increases inequality. As Francis Wilson observed in his momentous study of South Africa’s gold mining sector, an enormous twenty to one earnings gap between white and black workers in 1971 was achieved “by the simple exercise of monopsony.” Monopsony power applies far beyond mining, is pervasive across workplaces, and is particularly severe in South Africa. It is also likely related to the high unemployment rate.

In a recent study, I show the connection between the power bosses have to set wages and South Africa’s extreme inequality. I document that this explains over a third of wage inequality in South Africa today, and show how this is driven by a combination of employer monopsony power and differences in productivity.

The country’s world-leading wage inequality, then, probably has as much to do with what bosses are doing as it does with how educated or experienced workers are.


How can we measure the wage inequality that is due to employers?

There are many sources of differences in wages between workers, including worker characteristics such as education, and the specific wage policies of employers. One way to separate these out is to see how a worker’s wage changes when she moves from one employer to another. These wage changes cannot be about her productivity or skills– she’s the same person being paid a different wage depending only on where she works.

Have you ever moved jobs and received a salary bump, even though you are doing roughly the same work? Economists call this an employer wage premium. Using tax data for the formal sector from 2011 to 2016, I track millions of job movers to estimate this premium for every employer in South Africa.

In a competitive labour market where bosses do not have the power to set wages, a worker should be paid similarly no matter where she goes, and there should be no employer wage premia. Yet anecdotally we know that high-wage and low-wage employers exist. Figure 1 shows that salary changes after moving jobs can be enormous. A worker lucky enough to move from a low-wage to a high-wage employer more than doubles their wage (light red line). The opposite may also happen: a worker at a high-wage job may be forced to move to a low-wage employer, and get paid much less (light blue line).

Figure 1: Wages over time of workers who switch to a new firm

Notes: The plot shows the wages of workers who stay at the same firm for three years (-3 to -1) then switch to a new employer and stay there for the next three years (0 to 2). The legend shows types of employer switches: “1 to 1” or “Quartile 1 to quartile 1” indicates the worker moved from a low wage employer (quartile 1) to another low wage employer (quartile 1), “1 to 4” indicates the worker moved from a low wage employer to a high wage employer, etc.


How much do employers contribute to wage inequality?

These differences between low- and high-wage employers drive up wage inequality. Altogether, I estimate that employers account for 36% of wage inequality in the formal sector. If one could observe the same detail in the informal sector, this proportion would likely increase, because wages in the informal sector are lower than the formal sector. Accounting for other sources of inequality (like that some people have jobs and others do not), employer wage premia account for roughly one fifth of overall income inequality in South Africa today.

Another way to illustrate the impact of employer-specific wages is shown in Figure 2. Much of the discussion on inequality in South Africa is about access to high quality education, which suggests a slow process of change through a better education system. While this is certainly important, a large part of inequality is also due to which specific employer you land at. In Figure 2, aside from the highest paid workers, the difference in total wages between workers is as much explained by differences in specific employers (red) as differences due to worker characteristics (blue).

Again: for the vast majority of workers, how much you are paid has as much to do with what employer you land at, as with what you bring to the table in skills and experience.

Such differences in wages due to the specific employer you land at are found in many other countries too. But South Africa stands out for just how much inequality is due to employers, at least compared to estimates for richer countries.

Figure 2: Components of income due to worker characteristics and employers, by decile

Notes: Workers’ wages are divided into deciles, and split into the average portion due to employer wage premia (red) and worker characteristics (blue). Premia are shown relative to workers with wages in the lowest decile.


What drives the large role of employers in South Africa’s wage inequality?

The leading economic models on employer wage premia focus on differences in employer productivity and monopsony power.

The amount of money you make for an employer, or revenue productivity, depends on many things that are specific to that employer. For example, they may have better technology or have a popular brand. Because more productive employers pay workers more, bigger differences in revenue productivity across employers induce greater wage inequality.

Differences in employer productivity are large in South Africa compared to estimates for richer countries, but are similar to other developing countries like India and China.

However, such differences in employer productivity only matter for wage inequality insofar as employers have monopsony power. With low monopsony power, workers can easily switch jobs, and they would just quit and move to the highest paying employer. Indeed, one way to measure monopsony power is to see how much employers can lower wages without workers quitting.

My estimates suggest monopsony power is particularly severe in South Africa. This means that there is a high rate of exploitation in South Africa. Employers can also pay workers very differently, depending on the employer’s revenue productivity.

This high employer monopsony power may be due to South Africa’s high unemployment. When unemployment is high, it is more difficult to find a job, and so workers are more reluctant to quit in response to an employer wage cut. This has long been popularly understood in terms of the Marxian “reserve army of labour”. Thus employers potentially link two of the country’s most devastating features, inequality and unemployment.


Implications for policy

While the exact policy prescriptions to reduce employer monopsony power are complicated, it should be clear that the contribution of employers to South Africa’s inequality crisis warrants attention.

One policy implication of a high degree of employer monopsony power is that wages are lower than they could be: rough estimates suggest a substantial increase in tax revenue returns and reductions in poverty from constraining employer power. Productivity may also be lower than it could be, as low productivity employers stay in business by paying low wages, when workers could instead be employed at higher wage, higher productivity firms.

Finally, high employer monopsony power may be a feature of developing countries more generally. Developing countries also generally have large differences in employer productivity, and high labour surpluses.

Overall, my analysis reinforces the need to centre the power of bosses over workers in economic analysis.


Ihsaan Bassier is a researcher at the Southern Africa Labour and Development Research Unit at the University of Cape Town, and is also a postdoctoral researcher at the London School of Economics and Political Science. Access to the SARS tax data used in this article was granted through the SA-TIED programme, a joint initiative between the National Treasury of South Africa and UNU-WIDER. Ihsaan also received funding and support from the Southern Centre for Inequality Studies at Wits University. This article is based on a forthcoming paper in the Journal of Development Economics by the author. A discussion paper is freely available here. A version of this article appeared in The Conversation.