At the Southern Africa Labour and Development Research Unit at the University of Cape Town, we were commissioned by The Presidency to draw on our knowledge of programme evaluation and South Africa’s social assistance policy to try to answer this question.
We evaluated spending associated with the largest component of the programme – the Basic Education Employment Initiative.
We found that the programme likely does support broader economic activity, and these effects partly persist after the end of the programme.
Participants buy goods that are produced to some extent in local value chains and which employ local labour, rather than being imported. The programme spending does not just “disappear” but recirculates in the South African economy.
The study
The Basic Education Employment Initiative has employed about 245 000 young people per phase to assist schools across the country. The duration of employment has varied with each phase.
More recently it has been eight months. Participants are employed in full-time positions and are paid the monthly national minimum wage, which is approximately R4 000 (US$209).
The programme completed its fourth phase in 2023. Since it was launched in December 2020 it has employed over 850 000 young people, becoming the largest youth employment programme in South Africa’s history.
Read: The double-edged sword of the minimum wage
In our study, we focused on phases 2 and 3 of the programme, from November 2021 to August 2022.
First, we looked at how the programme affected participant spending patterns. We then estimated what kind of economic activity this spending supported.
Our initial evidence came from a WhatsApp survey of 31 250 participants we ran with Harambee Youth Employment Accelerator, a non-profit which supported the programme in partnership with the Department of Basic Education. Harambee holds contact details of most participants for phases 2 and 3, with permission that the records may be used for programme evaluation.
The survey response rate was unfortunately low. But it showed participants spent their cash mostly on groceries (about 50%), transport and rent.
Most of their income went to necessities, much of it from local stores.
However, our main evidence comes from information provided by a leading grocery retailer. The retailer gave us limited access to fully anonymised sales records from its loyalty rewards programme.
In partnership with Omnisient, a privacy-preserving data collaboration platform, we were able to see who in the data was a participant in the programme and who wasn’t, while retaining individual anonymity. We explain in the paper how this was done without revealing or sharing any personally-identifying information. The data collaboration partnership went through a rigorous legal process and received University of Cape Town Research Ethics clearance.
Using this data, we found that average participant spending at the retailer increased from R327 (US$17) per month before the start of the programme to R437 (US$23.50) during the programme.
When compared to a control sample of other customers who shopped at the same locations and kinds of stores as the participants, using a statistical analysis method called difference-in-differences, we found that participant spending sharply increased by 15% during the programme.
ADVERTISEMENT
CONTINUE READING BELOW
Even after the programme ended, participants’ spending remained 4% higher than the baseline.
This might be due to participant savings during the programme, or participants being better placed to find work after the programme ends.
But this aggregate spending increase hides quite a lot of variety, per the following table. In the largest spending categories, participant spending increased by 16% (groceries; refrigerated and frozen perishables) and 20% (toiletries), but in some smaller categories the percentage increase was much higher (off a low base).
For example, spending on home and small appliances increased by 51% and kitchenware by 40%. In general, percentage spending increases were lower for food items. This was unsurprising as these necessities already took up a large part of participants’ budget before the programme.
This means the spending increase of 15% at the retailer is likely an underestimate of how much the programme increased participant spending overall, because food items make up over 80% of expenditure at the retailer and are therefore over-represented.
Another reason the 15% increase is probably an underestimate is because we can only see each individual’s shopping and not the rest of their household. But some participants were probably shopping on behalf of their families before the programme, and during the programme, someone else took over shopping responsibilities, using income from the Basic Education Employment Initiative.
Income effects
What can we then say about who receives income from this increased expenditure? This part of the paper is exploratory and speculative because we cannot directly see how spending from the programme flows through the economy and how firms respond to this increased revenue.
Instead, we have to use back-of-the-envelope calculations to scale up the expenditure, use input-output data from Stats SA to guide assumptions about which industries produce which kinds of goods, and use other firm data to see how firms’ wage bills and profits usually respond to sales increases. In our paper, we explain the methods, assumptions and limitations in detail.
With these caveats in mind, the implied direct effect of the programme on the retailer’s sales is about R8 million (US$417 500) per month.
Directly, this likely increased the wage bill for workers at the retailer by about R1 million (US$52 188) per month.
Indirectly, the increase in the retailer’s sales would have increased demand from their suppliers and, in turn, their suppliers’ suppliers, which we estimate increased employment and wages outside the retailer by another R1.7 million (US$88 734) per month.
What about participant spending outside the retail firm? By scaling up the retailer-specific results, we estimate that overall the programme generates about R38 million (US$2 million) per month in additional value added to the national economy, which translates to R19 million (US$991 473) in additional employment and wages per month, R13 million (US$678 376) of which went towards local community employment.
What next
The main beneficiaries of the Basic Education Employment Initiative programmes are the young people who are directly employed by it, and the students in the schools. But the money does not get “thrown away” – one person’s spending is another person’s income.
And the participants do buy goods that are produced locally, using local workers.
When evaluating the costs and benefits of the programme and similar programmes such as social grants, these ‘extra’ economic benefits need to be part of the calculation.
, PhD candidate in Economics, UMass Amherst, and , researcher in Economics, London School of Economics and Political Science.
This article is republished from The Conversation under a Creative Commons licence. Read the original article.
