Methodology

Creating an inclusive livelihoods taxonomy involves assigning human capital and skills to activities that are usually unseen, which comes with challenges.

Tabiya's work on the inclusive livelihoods taxonomy can be divided in two streams:

1. Adaptation of the Seen Economy. Making sure that the "seen" part of the pre-existing taxonomies such as ISCO and ESCO adequately fit local contexts. This work is highly specific to country contexts, and our rigorously tested approach in South Africa is described in details here.

2. Making Visible the Unseen Economy. Broadening existing taxonomies so that they include the unseen part of the economy, namely the activities that are typically not considered as productive and the skills that are associated with them.

In this section we detail our approach to the second workstream - our work expanding the map of the labor market.

Motivation of the Methodology

The challenge is the following: Tabiya aims at creating an inclusive taxonomy of livelihoods, while ensuring that this taxonomy is compatible with existing ones such as ISCO or ESCO. This allows us to ensure that the developed taxonomy can be used by institutions that rely on globally standardized and widely-used taxonomies. We chose to base our work on the European Skills, Competencies, Qualifications and Occupations (ESCO) taxonomy (reasons detailed here).

The first step, naturally, was to evaluate the inclusiveness of the existing ESCO taxonomy. The intellectual underpinning of this work builds upon the "Counting Women's Work" literature, that aims at assigning a monetary value to the tasks done by women, especially in their households. In Tabiya's work, we aim to highlight the human capital gained from these tasks more than assigning monetary values. Additionally, our work covers all job-seekers, not just women, although depending on local contexts they may de facto represent the majority of unseen job-seekers.

Counting Women's Work: The necessity to better understand sex inequalities in the labor market led to the finding that while both men and women work, their work is valued differently, and this differential valuation yields a perceived differential “productive characteristic endowment” amongst sexes that, in turn, drives sex wage disparities for the African case. In particular, men generally perform paid labor market activities, while women perform both paid labor market and unpaid home production activities (Dinkelman & Ngai, 2022). Hence, a literature that seeks to count women’s work has emerged. This literature relies on time-use data to attribute an equivalent labor market wage to home production activities done by women (Samarasinghe, 1997; Hoskyns and Rai, 2007; Donehower, 2018 and Abrigo & Francisco-Abrigo, 2019). For the South African case, this work’s results have found that if household work done predominantly by women were valued by its nearest specialized occupation, it would account for half of the nation’s aggregate labor income (Oosthuizen, 2018). Of course, if a given household activity can be equated to a specialized occupation, this implies that this activity comprises similar tasks to those performed in the specialized occupation. Then, by definition, the fact that tasks are an output of the application of a skill implies that at least some skills used outside of the market are comparable to those used in the market.

Making Visible the "Unseen Economy"

For the “unseen economy,” i.e. activities outside of the specific SNA production boundary, we rely on an existing classification of all time-uses and tasks one may gain human capital from - the International Classification of Activities for Time Use Statistics (ICATUS). This standard lists all time uses someone may have throughout the day. ICATUS represents the internationally applicable classifications of activities that people engage in during their 24-hour days.

ICATUS is made up of three levels. The first digit level of disaggregation (highest level of aggregation) is called the major division, the second digit level is called the division level, and the third digit level, which is the most granular level, is called the group level. We first start by comparing ICATUS with the System of National Account, to define the boundaries of the "seen" and the "unseen" economies.

Mapping of seen and unseen economy across the SNA production boundary and ICATUS categories, general and context-specific application used by the 2011 South African Time Use Survey.

From the mapping above, it is evident that countries use the ICATUS taxonomy as a skeleton that they use to build a locally-adapted time use survey based on. Hence, a key characteristic that positions the ICATUS Framework very well for our purposes is its amenability to local contexts’ time use surveys.

Based on the System of National Accounts, we therefore nominate the following ICATUS major division to encompass the unseen economy:

ICATUS Division 3	ICATUS Division 4	ICATUS Division 5
Unpaid domestic services for household and family members	Unpaid caregiving services for household and family members	Unpaid volunteer, trainee and other unpaid work
Excluding: 53. Unpaid trainee work and related activities.	Excluding: 9. Other unpaid work activities;	Excluding: All activities within ICATUS categories 3, 4 and 5 that include time allocated to waiting, traveling, or accompanying someone.

Matching "Unseen" ICATUS activities to the ESCO framework

Once ICATUS activities have been associated with the "unseen" part of the economy, the challenge is to make sure the unseen part of our inclusive taxonomy follow the same structure as the existing ESCO taxonomy. Namely, we need to assign skills to the ICATUS activities forming the unseen part of the economy. Therefore, Tabiya conceptualizes a framework that links the most granular level of unseen economy ICATUS activities (3-digit level) to a set of non-exhaustive candidate ESCO skills and knowledge tags per ICATUS Activity.

ICATUS structure: ICATUS 3 digit level activities comprise more specific activities that lie within ICATUS Divisions 3,4, and 5. For example, “Preparing meals/snacks'' is a Group Level Activity that falls within the Division 3 of ICATUS, namely Unpaid domestic services for household and family members. At the Group Level, ICATUS includes a definition of each activity, and a non-exhaustive list of the tasks that each activity includes and does not include, and at least one example of each Group Level Activity.

ESCO structure: The ESCO taxonomy is made up of a set of occupations at level five or lower that are derived from the four ISCO-08 occupations hierarchy. For the purpose of the Tabiya Framework, we use only ESCO occupations at level five or lower for our analysis, since this provides the desirable granularity and metadata to adequately link ESCO to ICATUS. The ESCO taxonomy provides a brief description of each occupation it comprises, the occupation’s alternative labels as well as access to regulatory information pertaining to the occupation.

The ESCO taxonomy is particularly valuable because of how it structures the full set of skills required by an occupation: every occupation consists of "skills/competencies" and "knowledges" required, and each of these skills/competencies/knowledges are further assigned to being essential or optional to the occupation.

Mapping ICATUS x ESCO

ICATUS Group Level activities are used as one of the inputs and ESCO occupations and skills, competences and knowledge (skills, competences and knowledge will be referred to as skills henceforth for simplicity) are used as the other input for the matching procedure.

First, each ICATUS Group Level activity is manually matched to at most four ESCO occupations by a team of researchers. ICATUS, even at the Group Level, is more broad than ESCO occupations and so, to ensure comprehensiveness in the Tabiya matching procedure, up to four ESCO occupations were potentially matched to each ICATUS Group Level activity. Since the ESCO taxonomy assigns skills to occupations, these ESCO-assigned skills then form the initial list of candidate assigned skills per ICATUS Group Level activity.

The assignment of ESCO occupations to ICATUS activities is based on the relative similarity definitions between ICATUS Group Level activities, and ESCO occupations. Comparing definitions of ICATUS activities to ESCO occupations is relatively easy to do amongst a team of researchers, since activities and occupations are similar in nature, and in turn, in the manner that each of these are defined.

Once at most four ESCO occupations are matched to each ICATUS Group Level activity by a team of at least two researchers, these matches are then reviewed by another independent researcher. Throughout this process, there were no instances where the independent researcher disputed an occupation without mutual agreement from the pair of researchers who initially made the match. The process ensures that person-specific biases do not prevail during the matching process.

While we endeavor to minimize biases and human error through this process, we cannot completely rule out the possibility that other (group level) biases and errors may have occured. Over time, as Tabiya accumulates more data and learns from this, the framework will use these learnings to improve and ultimately, not succumb to any currently prevailing biases and errors.

After the ICATUS to ESCO occupations match is done and verified, the next stage of the Tabiya framework formulation can commence. By design, the ESCO taxonomy pre-assigns skills to each ESCO occupation at disaggregation level five and below. Thus, we exploit this structure for the Tabiya framework. In particular, once ICATUS activities are matched to ESCO Occupations, we adopt the pre-assigned ESCO skills as the first set of candidate skills assigned to each unseen economy ICATUS activity. After duplicate skills are removed, each ICATUS activity now has a comprehensive list of skills assigned to it. The procedure is shown below:

Matching process from ICATUS activities to ESCO skills

Reducing the List of Skills

The skills taxonomy obtained following this method is hardly usable: each ICATUS activity ended up being associated with numerous skills. In order to provide a manageable list to job seekers when they are selecting skills, the team concluded that the list of skills needed to be condensed. Reducing this also allowed to addressed the transferability and signaling issues inherent to the unseen economy.

We do this in two stages for our first use-case in the South African labor market: first, the Tabiya team proceeded with a first round of skill selection in order to delete skills that were deemed obviously not consistent with the definition and description of ICATUS activities. For the skills list that come out of this first stage filtering, a panel validation approach involving South-African labour market experts was adopted. An expert panel structured as a series of validation exercises would generate context-specific insights from a wide range of stakeholders, making it possible to compensate holders' biases pertaining to the transferability and credibility of skills.

Below we describe the 4 principles used in the first stage skills reduction by Tabiya's researchers. The panel at Harambee is described in details here.

1. Isolating knowledges and retaining only skills/competencies: The ESCO classification distinguishes between "skills" - that all describe an action - and "knowledges". For instance, the occupation "cook" is associated with the skill "use cooking techniques" and the knowledge "cooking technique". As a first step, we chose to isolate knowledges and to mainly focus on skills. However, we chose to let the panel decide to keep certain knowledges when they brought important new informations. For instance, "common children's diseases" may be deemed an essential knowledge when one claims to have experience raising children.

The decision to isolate knowledges also relies on the observation that knowledges assigned with ESCO occupations are usually redundant with skills, i.e. their presence in the list does not bring new information content. For instance, if a young job seeker "uses cooking techniques", this implies that they to know "cooking techniques".

1. Deleting irrelevant skills:

   In ICATUS, each activity is associated with a definition, and explicit list of tasks included in the activity, a list of tasks that are not included, and one or more examples. ESCO is built similarly. However, ICATUS activities are typically not only broader, but conceptually different from ESCO occupations. For example, "Budgeting, planning, organizing duties and activities in the household" is not a formal sector activity that is included in ESCO. Therefore, to assign ESCO skills to this ICATUS activity, it was matched to "Office clerk", "Accountant", "Bed and breakfast operator", three ESCO occupations that encompass all tasks involved in "Budgeting, planning, organizing duties and activities in the household". The issue is that they encompass a lot more work than what budgeting and planning for a household would entail. For example, because of "bed and breakfast operator", the skill "serve beverages" ended up being associated to "Budgeting, planning, organizing duties and activities in the household", even though serving tasks are not included in the description of the ICATUS activity. When we came across such cases, we decided to exclude these skills.

The difficulty when applying this rule came from our expectation of how young job seekers would use the Harambee platform. Indeed, when selecting the ICATUS activity "preparing meals and snacks", one might mean that they prepare meals, serve them, and clean after. In ICATUS, those are three different activities, that are associated with different tasks, and thus skills. For version 0.1 of the Harambee platform, we chose to strictly fit the descriptions of each ICATUS activity, and to expect users to chose all relevant ICATUS activities. This choice was motivated by the observation that a more flexible approach would make a taxonomy inoperative, and make it more difficult to match job seekers to relevant job offers.

1. Deleting skills that are deemed too formal: Some of the skills associated with ESCO occupations directly refer to situations or tasks only imaginable in the seen economy, whether it is formal or informal. For instance, "maintain customer service" cannot be appropriately associated with "serving meals and snacks", as it describes serving meals and snacks to one's own children/family members.

Applying this rule is entails having a very literal interpretation of ICATUS activities and the skills involved. For instance, one may argue that ensuring the satisfaction of family members when serving a meal or a snack may allow someone to develop customer service skills.

1. Deleting redundant skills: ESCO occupations are typically associated with numerous skills, and each ICATUS activity was associated with multiple ESCO occupations. The lists of skills from each ESCO activity was added to a list of skills for each ICATUS activity, with deletion of duplicate instances of skills. For instance, "Outdoor cleaning" was associated with both "prune plants" and "prune hedges and trees". We considered that associating both skills to "outdoor cleaning" did not bring new information.

Applying this rule proved tricky, as it highlighted the complexity of the ESCO taxonomy. For instance, "prune plants" does not contain the subsoil "prune hedges and trees", even though hedges and trees are obviously plants. However, it contains the subskill "perform hand pruning". This shows that the organization of ESCO itself is not straightforward, and that cases exist where two skills conceptually very similar.

This makes up the generalizable unseen economy framework methodology. From this candidate list of skills associated with each unseen economy ICATUS activity, differing contexts can begin to localize this framework.