Who live in the poor neighborhoods of the City of Buenos Aires? What do they do? What is the job they have access to? Under what conditions does it develop? What is the popular economy? A survey on the labor trajectories of those who live in working class neighborhoods to understand how it works and what are the characteristics of the working class economy in the City of Buenos Aires.
Fundar, together with Eduardo Levy Yeyati and the Centro para la Evaluación de Políticas Basadas en Evidencia (Center for the Evaluation of Evidence-Based Policies or CEPE) of the Torcuato Di Tella University, carried out a mapping of the labor skills and career paths of individuals in the popular economy of the City of Buenos Aires for the Ministry of Human Development and Habitat of the Government of the City of Buenos Aires.
About the research
The research consisted of:
- An original 79-question survey designed to:
- Identify eligible individuals within the surveyed household (those currently or previously employed by the popular economy);
- Randomly select the person to be surveyed from among the eligible individuals in the household;
- Survey their current employment situation;
- Survey the level of subjective satisfaction based on different aspects of their current job;
- Survey a set of the individual’s job skills;
- Survey their career paths and the level of satisfaction with their previous occupation;
- Survey career education through courses and training, and interest in taking new courses.
- The survey of 1800 cases was carried out with a probabilistic sample of the target population in informal housing neighborhoods of the City of Buenos Aires (communes 4, 7, 8 and 9) and the most vulnerable sectors of the same communes excluding informal housing neighborhoods, (i.e., the 33% of households with the highest percentage of unfulfilled basic needs according to the 2010 Census).
- The subsequent analysis and processing of the survey to characterize the socioeconomic and labor situation, skills, subjective satisfaction, profiles and training of the popular economy population.
- An analysis of the career paths of the popular economy population based on the Permanent Household Survey (EPH) to analyze upward occupational mobility (people who have moved out of the popular economy).
25 in-depth Interviews to target population explored work histories, skills, and factors explaining upward occupational mobility in selected cases.
A closer look at the members of the popular economy by branch of activity and occupational category reveals that the most common occupations are fixed-point salespersons (in the “Popular trade and work in public spaces” segment), janitorial positions (in the “Personal services and other trades” segment), jobs in clothing and textile industry (in the “Manufacturing industry” segment) and bricklayer/durner (in the “Construction” segment).
Although cooperatives are usually considered an important sector of the popular economy, less than 10% of respondents (in both informal housing and formal housing neighborhoods) reported working in a Cooperative as their main occupation.
We also found that the percentage of people who have ever been hired through an interview, selection process or application is low, with a high preponderance of individuals getting jobs through personal contacts, referrals, or on their own.
In terms of skills, most survey respondents do not use tools in their current jobs, with the number of workers using tools increasing with education level. When broken down by occupation, there are industries such as “Construction, social infrastructure, and environmental improvement” and “Manufacturing”, where most workers use tools.
Most respondents lack computer skills or have very limited computer skills. Few respondents have used a computer on a regular basis in any of their jobs, and few have frequently used social media to promote their products.
The vast majority of respondents reported that they had not completed any training, with the most common courses being digital, cosmetology/aesthetics, gastronomy, personal care, and electrical maintenance/installations. However, nearly 80% of respondents were interested in taking courses or training in the future.
Income and working conditions
The proportion of the population that is formally employed and whose employer pays the applicable payroll and social security taxes is quite low (14.3%). There is also a small number of individuals enrolled in the simplified individual tax regime (monotributo), but a very small number with labor risk insurance benefits (ART).
About 70.6% of the workers in the sample reported earning less than the minimum wage (about ARS 90,000 as of June 2023). The workers with the lowest average monthly compensation are in the “Recovery, Recycling and Environmental Services” segment, while those with the highest compensation work in “Transportation and Warehousing”.
Most individuals with a government subsidy are beneficiaries of the Potenciar Trabajo program, and most program beneficiaries are required to perform some work in exchange for the benefit (60.2% report working in exchange for the benefit, while 17.1% report working and studying in exchange for the benefit).
Thirty-five percent of the surveyed population receives some form of subsidy, the most common being the Universal Child Allowance (AUH).
Most claim to be satisfied with their current job (their relationships with clients, bosses and colleagues are good, they do not have to commute long distances to get to work), but they also consider their working day to be tiring and too long, and claim to be dissatisfied with their income.
Most respondents have had a previous job, but the percentage of those who report a previous job in the same sector is low. In other words, job changes mainly involve a change in industry.
Most respondents say they would like to change jobs. When it comes to choosing a new job, formality is what they value most.
Only 4% of the sample show upward occupational mobility, and they tend to be those with higher education or skills (71%) and predominantly residents of the city’s formal neighborhoods.
There are also few respondents with downward mobility (8% of the sample), most of them from informal housing neighborhoods and also in the higher-skilled segment (48%).
We used machine learning techniques to recognize specific segments within the target population. In this way, we identified four segments (or clusters) that can be distinguished by their level of formal education, skills (trade skills, computer skills), previous job experience obtained through an application or interviews, and age range. We identified four groups:
- A first group, characterized by a majority with a trade and a higher average age;
- A second group of individuals with a higher level of education, younger age, computer skills and who have obtained jobs through interviews;
- A third group of older people, with no jobs and a lower education level;
- A fourth group, with a large number of young people, most of them without a high school degree.
Each of these segments presents important differences in terms of average reported income, access to employment programs and subsidies and interest in receiving training.