SA’S DILEMMA WITH STATS ON JOBLESSNESS

IT’S BEEN 25 years since democracy dawned, but apartheid’s legacies still scar the country. Poverty remains high; inequality extreme – both along racial lines. The same is true for unemployment. By conservative official standards, it is at a staggering 27.6%, disproportionately affecting black South Africans.

Effective policies to combat this require good ideas, resources and political will built on a solid understanding of the problem.

Good and relevant statistics are central to effective policies.

The international gold standard for employment figures comes from the International Labour Organisation. Its template states you count as unemployed if you (a) don’t work (a lot) for money, (b) are available for work, and (c) are actively looking for a job.

This definition originated in the 1920s, built on the image of white, male factory workers in Europe and North America. If these men lost their jobs, it spelt social and political trouble in factory economies.

After apartheid ended, South Africa’s statisticians tried to move away from the traditional unemployment definition, experimenting with various extended definitions that would capture “discouraged work seekers”.

But, as our recent research found, the country’s appetite for statistical creativity has slowly waned; increasingly embracing the ill-fitting international standard. But this global standard risks creating a skewed image of South Africa’s labour market woes. Poorly crafted policies may be the result.

There are a number of problems with sticking to narrow, global definitions of “unemployment”, “job searching” or “industry” in the local context. For instance, apartheid’s spatial legacies mean that for many industrial jobs are far removed from where they live. Many don’t actively look for jobs because none are to be found near. For all intents and purposes, they are unemployed. But they wouldn’t pass the International Labour Organisation definition – so they drop out of the stats.

In rural areas, many people – and women in particular – labour on the land to grow their own food. They might prefer a salaried job to escape poverty. But their hand-to-mouth existence may prohibit an extensive “job search”. They, too, would fail the statistical litmus test.

International unemployment standards would thus ignore a big part of South Africa’s labour market problems. The other problem with existing definitions is that nuance tends to fall by the wayside. Take “discouraged work seeker”. It’s an ambiguous category. Qualifying depends on your own judgement: maybe you don’t look for a job actively, but would you like one?

Not everyone answering “no” is voluntarily jobless. People might answer “yes” but lack personal effort to find work. Such vagaries are at odds with the exactness expected from statistics. Statistics privilege easy-to-quantify indicators; important nuances vanish.

This tendency to ignore soft, hard-to-measure issues is amplified by politicians. Statistics SA has over the years often been criticised – unfairly – for unemployment figures that tried to paint a more realistic picture. Yet less than rock-solid statistics have invited the charge that Stats SA would inflate the numbers intentionally, or manipulate them.

To safeguard its credibility, the agency had to seek refuge in an international definition, even if it fails to do local circumstances justice. South Africa faces a genuine statistics dilemma. It is impossible to capture the complex ills of its economy and society in single headline figures.

But all too often, this strategy biases the numbers against people who fall between the cracks. Our research suggests the country’s statisticians should paint a bold picture that reflects the “rainbow nation” if they are genuinely committed to effective policies. Mügge is a political arithmetic professor and Alenda-Demoutiez a post-doctoral researcher at University of Amsterdam’s political science department.