More Equal Than Others

A brief exploration of income inequality and social stratification in Argentina

Inequality 101: the Gini Coefficient

Graph 1: Gini coefficient of per capita family income over time, compared to three other countries in the Americas. Figures in one line can be compared, but figures in different lines cannot (except for the yellow and purple ones).

Income inequality is generally measured by what’s known as the Gini Coefficient. It measures distribution by the difference between the amount of money each percentile actually has against the proportional amount (i.e. top 1% gets 1% instead of, say, 5% or whatever). So this means 0 is perfect equality - everyone has the same amount of stuff; 1 is absolute inequality, since nobody has anything except 1 person (or 1 percentile, or one decile or quartile or whatever) that owns everything.

Income inequality increased in the late 80s due to high inflation (that affects the poor more) and lackluster labor market performance. During the 90s, as the economy liberalized, it went down from its hyperinflation peak, but steadily increased as poverty worsened and the winners of (especially trade) liberalization (importers and exporters, highly educated workers, service firms) saw rapid gains while the losers (manufacturing, public employees) got the short end. As the system boiled over in a massive recession, a shock stabilization plan that quadrupled the exchange rate and had price increases of 40% (the highest since 1990 and until 2018), inequality peaked again.

As the more statist wing of the Peronist Party took over, and the economy improved, strong wage and employment growth reduced inequality. Unlike what’s stated by the official data, this decline took place over most of the decade, and not three years - and can be explained by strenghtened unions, labor intensive growth, and expansive fiscal policy. However, the reckless macroeconomic policies the government undertook also steadily increased inflation, leading to a notable deceleration throughout the 2010s as real wage growth slowed and the economy entered stagflation (this coincided with sluggish reductions in poverty). The recession of 2018 and 2019, plus disparities resulting from the recent COVID crisis, have undone about 9 years of progress in that front.

This follows, although much more starkly, the same pattern as the rest of Latin America: the pro-business reforms of the 90s “overshot” their targets, leading to higher inequality and social tensions; the good external conditions (high commodity prices), positive long-term trends in family planning and education, and expansions of welfare reduced inequality in the 2000s. By the following decade, however, negative international factors, and in many cases outcomes of bad policies, led to tepid growth and a slowdown in inequality reductions. This pattern holds across growth levels, political leanings, and policies - and seems to mostly stem from the demand for unskilled vs skilled labor. In fact, the wage premium for tertiary education grew 1.8% annually in the region, and 3.5% in Argentina; in the following decade, it dropped 2.8% regionally and 2.4% locally.

Stratification and mobility

A second dimension of analysis could be the controversial division of society in classes. How do we define class? Away from the traditional Marxist “means of production” shtick, we can say that they’re divided by the access to certain goods, services, or positions, while at the same time that access is reproduced and modified within and between generations. This points to class mobility, or the ability of a given person to change classes; and it comes in two flavors: intergenerational, meaning between different generations (so, the children of a poor person become rich) or intragenerational (so, a single person goes from poor to rich in their lifetime). The clearest distinction to be made is that class is not only defined by income, but also by educational attainment and by career path (among other factors).

This creates two dimensions of analysis: the first is how high mobility actually is, and the second is whether or not there are significant constraints on it by the relative positions of the classes (so mobility could be high but because living standards got much lower, for example).

So which classes are there? We will define 5 of them. The first is the service class, whose members are high level professionals and managers, plus the most qualified technicians. Compared to the average person, they make 52% more income, and 47.6% of its members have a university degree (vs 15% of the population). The second class is the routine workers class, mostly made up of more or less qualified office workers - with wages 4% higher than the average, and being just 9% university-educated. The third class are small business owners, making 16% less income than the average person and with just 7% holding higher education degress. The fourth class are qualified laborers, mostly low level clerk and qualified manual workers; their salaries are 13% lower than average, and only 3% have a degree. Finally, the fifth and final class are unqualified laborers, which make 38% less than average and basically none have a university degree.

Mobility between the classes is not low, with just 33% remaining in the one they inherited. Of the remaining two thirds of mobility, nearly a majority (49.5%) can be pinned down to intergenerational mobility, the vast majority of which (30.3% of the total) had been upwards. The rest (26.2%) can be explained by intragenerational mobility. A problem is that the process is not equitable: just 22% of people of the lowest two classes can make it to the top, while 35% of the service class is self-recruiting and a futher 41% comes from the middle two classes. Mobility into those classes is also low, with only 40% of their members coming from the bottom two. The reverse dynamic happens at the bottom classes - pointing to the fact that, while mobility is possible, it tends to only happen between closely adjacent classes.

In fact, the aforementioned dynamics obscure how hard it is to break into the higher ranks of society. Members of the service class are over twice as likely than expected to remain there compared to a perfect mobility scenario, and routine workers are 38% more likely - compared to all other classes, that have worse odds. On the flip side, members of the top two classes are only likely to trade positions with each other if they become downwardly mobile - and upwards mobility in the lower classes only happens to the ones immediately above it, with permanence the most likely outcome. There are also gender differences: while men are overrepresented at the top, low class men are only half as likely as their female counterparts to improve their position.

People in the highest classes, and the ones that break into them, have the highest personal wealth and per capita income (both 50% greater than the average population), enjoy 4 additional years of education (almost 16, vs 11.9 for the general populace), and have the best outcomes in mental wellbeing and health; the opposite happens for those at the bottom, i.e. those who either stay at the worst off strata or even descend into the outer layers of society. And the risk of members of either group to be low income (below 150% of the poverty line), in poverty, or in extreme poverty is different as well, with all that it entails.

Using a slightly different definition of class, where members of the service class and certain routine workers are lumped into the “professional middle class”, the rest of the routine workers and small business owners form the “non-professional middle class”, and the other two categories are more or less the same but renamed to “integrated laborers” and “marginal laborers” respectively, we can get more detailed information about their specific living conditions (plus poverty and extreme poverty rate, as a comparison). Unlike the previous chart, all figures correspond to households and not individuals (meaning they aren’t comparable to each other).

Conclusions

We have already mentioned education multiple times in this post - it is highly correlated with upwards mobility and higher incomes. During the 2020 pandemic, there was an estimated hike of 16% in students dropping out of school, and in most cases, they are not expected to return. A majority of teenagers aged 15-17 are expected to not continue their education after 2020 either. Given restrictions on personal movement and the insistence on virtual learning, this has exposed some glaring inequalities - 67% of lower class children don’t have access to the internet, and an equal proportion don’t have a computer in their homes.

The horrendous handling of education during the pandemic points to a lack of concern about longstanding inequities in educational and career outcomes, which will only heighten existing disparities between the classes and will make mobility into the top ranks even less possible.

Sources