To validate our approach for the informal economy, we conducted a survey among a subset of South African micro-entrepreneurs registered to the Harambee website.
To assess the applicability of the ESCO taxonomy to the informal micro-entrepreneur economy of South Africa, we conducted a series of primary data collection exercises with Harambee users. The core objective of this data collection was to finally address two key questions:
1 - Can all activities in the informal micro-entrepreneur economy in South Africa be associated to at least one ESCO occupation?
2 - Does the ESCO taxonomy effectively encompass both occupation-specific skills and entrepreneurial skills prevalent in the informal micro-entrepreneur economy?
Throughout the data collection process, we collaborated closely with the Harambee team to ensure its relevance to the youth in South Africa. This collaboration encompassed various stages, including conceptualization, survey instrument design, and sampling.
Microentrepreneurs constitute a unique segment within the workforce, as they possess two distinct sets of skills. First, they possess occupation-specific skills directly related to their trade; for instance, a hairdresser possesses skills such as hair washing and styling. Second, microentrepreneurs also exhibit general entrepreneurial skills required for self-employment or own-account work, such as identifying suppliers, resource management, and understanding customer needs.
Harambee facilitated focused group discussions (FGD) with 18-35 year-old, prior or current informal micro-enterprise owners within their network. These FGDs were designed to identify the second set of generic entrepreneurial skills that might be relevant to microentrepreneurs in South Africa
. Ten percent people with disabilities were included in the sample. To encourage participation, a circular was disseminated, inviting eligible individuals to join the FGDs, with selected participants offered R450 for their involvement
Each session featured diverse entrepreneurial activities among participants, ranging from car washing and music production to tutoring, baking, goods selling, and hairdressing. The FGDs were thoughtfully designed as a series of group discussions coupled with individual exercises, aiming to gain insights into how young individuals perceive their general entrepreneurial skills.
As part of the FGDs, participants were provided with three lists of skills, sourced from existing collections of entrepreneurial skills identified by external organizations, among which the European Entrepreneurship Competence Framework (Entrecomp). In each list, participants were instructed to indicate skills they possessed, skills they did not possess but considered relevant, and skills they found unclear or irrelevant to entrepreneurs. Following the completion of the three lists, participants were asked to identify the list that resonated with them the most.
Overall, participants selected a considerable number of skills from all lists, implying a relatively good alignment of all three lists. However, the Entrecomp list emerged as the most preferred, with 16 out of 33 participants (48%) choosing it as the list they resonated with the most. Participants commonly cited the relatability of the Entrecomp list as the primary reason for its preference, noting that they could identify with most of the skills on that list. Other positive feedback highlighted its conciseness, clarity, and self-explanatory nature; emphasis on interpersonal skills related to business; and better inclusion of ideas, creativity, and motivation compared to the other lists.
Given the preference observed in the FGDs for the Entrecomp list of skills, it was chosen as the starting point for compiling a list of potential entrepreneurial skills applicable to microentrepreneurs in the informal economy. However, as the primary objective of the data collection exercise was to assess the relevance of the ESCO framework, each skill in the Entrecomp list was manually matched to the closest skill in the ESCO framework by members of the Harambee team. This list was then further enriched by incorporating skills from the ‘retail entrepreneur’ ESCO occupation, collectively serving as the list of potential entrepreneurial skills for the primary data collection.
The second step of our work with Harambee consisted in gaining insights into the income-generating activities undertaken by young individuals.
To do so, we developed a short online survey for individuals within the SA Youth network. The primary aim of the survey was to obtain accurate descriptions of the main micro-entrepreneurship activities individuals engaged in to earn income in the past 30 days. To achieve this, we included the following question: “Tell us about the main way you make money. What things or services do you sell? Write a short sentence or two explaining what you do”. The survey also gathered information on current contact details, the number of income-generating activities, time allocation to different activities, and a brief title for the respondents' primary activity.
The survey was programmed using Typeform, and the UCT Commerce Ethics Committee approved the research study (COM/00513/2023). Completing the survey was designed to be a brief task, taking individuals no more than 2-5 minutes.
The survey sample comprised of 35,000 individuals randomly drawn from Harambee’s data on the SA Youth platform, including 20,000 who had recently joined in the three months leading up to November 2023, and an additional 15,000 individuals previously identified through EJ data as being involved in micro-entrepreneurship. Each of these individuals received an SMS calling all youth who make their own money to answer the survey via a unique link. The unique link, generated using information from Harambee’s backend, enabled us to include details such as the individual’s name and date of birth to ensure accurate identification. This linkage allowed us to link responses with other information on SA Youth, such as demographics and location. Participants received R10 in airtime vouchers upon successful completion of the online survey.
The survey was sent out in early November and individuals had approximately one week to respond to the survey. A total of 6,670 individuals responded, yielding a response rate of 1.9%. Among these, 1,583 individuals reported not engaging in any income-generating activities in the past 30 days. Of the remaining respondents, 4,599 individuals answered the question describing their primary income-generating activity. However, a substantial number provided incomplete or nonsensical answers, and there were a number of duplicate entries. Additionally, many individuals were not working as micro-entrepreneurs but were either employed by others or were engaged in gambling for income. Lastly, 119 individuals were excluded as they were over 35 years old at the time of survey completion (SA Youth is for those aged 18-35). Ultimately, 3,259 young individuals provided complete descriptions of their main entrepreneurial activities.
The third step of the work on microentrepreneurs was to match individual's descriptions of their activities with existing ESCO occupations.
One option would be to perform this matching exercise manually, similar to the process for the formal economy. However, this would be a very labour-intensive exercise, as we had over 3,300 individual descriptions and 3,008 potential ESCO occupations. Furthermore, manual matching at this scale would be rather prone to human bias and error. To streamline the process and mitigate the risk of bias, we opted for a two-part, sequential matching procedure leveraging artificial intelligence.
In the first phase, we designed an algorithm capable of identifying up to three relevant ESCO occupations for each provided description. In the second phase, we reviewed these matches manually to evaluate the accuracy of these matches. Adjustments were made if a match was deemed inadequate or if we believed that an apparent occupation match had been overlooked.
We considered various approaches - including Word2Vec, Doc2Vec, and BERT - but, ultimately, the easiest and most applicable approach for this first exercise was to make a simple prompt to OpenAI’s GPT models. Using the individual descriptions, the algorithm tasked OpenAI’s GPT model with evaluating all possible ESCO occupations and categorizing the description. The algorithm could offer multiple categories if there were several potential matches, but it was instructed not to provide more than three matches. Zero matches were also allowed. We restricted the potential ESCO matches to the 4.1-digit level of the ESCO taxonomy. This limitation aimed to allow for detail but minimize the risk of asking about occupations and skills that are highly specialized and unlikely to generalize beyond our sample.
In total, 3,236 individuals (99%) were successfully matched to at least one potential ESCO occupation. There were 23 individuals for whom no applicable ESCO occupation match was identified. These individuals engaged in activities related to:
Informal lending of money for interest,
Running errands for people (e.g., renewing licenses, fetching medication, arranging home affairs appointments),
Making photocopies of documents for people in the community.
Finally, we assessed the applicability of the ESCO taxonomy for informal microentrepreneurs. To achieve this, we designed a phone survey with three primary objectives:
Verify if the ESCO occupations accurately represent individuals' work and if they would willingly identify themselves with these labels.
Evaluate the relevance of the ESCO skills associated with each matched occupation.
Assess the relevance of the identified list of general entrepreneurial skills.
To address the first objective, participants were presented with each matched ESCO label and its description. They were then asked to consider whether these applied to their main way of making money. . Lastly, to test the third objective, five general entrepreneurial skills identified during the previous process were randomly selected for each participant. The complete questionnaire can be found here.
For each skill or knowledge tag, we designed several questions in order to determine its relevance to individuals’ work. These included whether individuals considered the skill as essential or optional, their perceived proficiency in the skill, their perception of how well other entrepreneurs in similar roles perform the skill, the importance of the skill to their own work, its importance to other entrepreneurs engaged in similar activities, and the perceived importance of the skill in a formal sector job akin to their work.
In addition, we incorporated a section aimed at identifying potential skill omissions from the ESCO taxonomy for informal micro-entrepreneurs. This section prompted participants to indicate if there were any other skills that were essential for their work that we had not inquired about.
Data collection in details:
We contracted the Southern African Labour and Development Research Unit (SALDRU) to carry out the primary data collection for the phone survey, with Dr. Jacqueline Mosomi as the PI. . Data collection was conducted via telephone, assisted by computer-assisted telephonic interview (CATI) software, and the research study received approval from the UCT Commerce Ethics Committee (COM/00513/2023). The objective was to achieve 1,500 successfully completed interviews from the specified sample. Respondents were offered a R50 incentive to encourage survey completion, and the survey was designed to take approximately 20 minutes.
Data collection took place between November 15 and December 8, 2023. To enhance the likelihood of participants completing the interview, SALDRU sent a pre-interview SMS to inform the sampled young individual that they will be contacted for an interview. Trained and experienced CATI interviewers conducted the interviews and, to ensure data quality, SALDRU implemented various checks, including listening to 10% of the completed questionnaire recordings. This process ensured that interviews were conducted professionally, and that the data was accurately captured.
The primary reason for non-response (45.8%) was the participant being uncontactable despite multiple attempts. Another 4.1% requested a call back but did not answer, and only 2% refused to participate in the survey.
The results of the microentrepreneurship survey seem to corroborate our approach, especially by highlighting the absence of systematic bias regarding own skill evaluation between different subgroups in the data. The full results of the survey can be found here.
The analysis of the survey's results is ongoing. The analysis of alternaive skills suggested by respondents should be added shortly.
Importanly, young South African on average consider that they are more skilled than the rest of job-seekers. This is positive, as it means that they are confident in their own skills.
Contrary to what one may expect, the data does not highlight any statistically significant difference in the estimation of respondents' own skills between males and females. If anything, it shows that female respondents tend to deem their own skills as more advanced, compared to their male counterparts.
Finally, there is no statistically significant difference between respondents' own skill evaluation based on wether or not they matriculated (finished high school).
