Exceptional Argentina Di Tella, Glaeser and Llach - Thomas Piketty

even when the number of well-off individuals may be regarded as very small with
respect to the economy as a whole, they cannot be neglected for distributive analysis.
If an infinitesimal (in term of members) richest group owns a finite share S of total
income, then the Gini coefficient can be approximated as G ≈ S + (1-S) G*, where G*
is the Gini for the rest of the population. 36
Data from Argentina also illustrate the limitations of household surveys, as opposed
to tax reports, as a source of information on high and very high income recipients. 37 A
comparison between tax tabulations and household income surveys reveals that it is
not an exaggeration to assume that the top 1% (or even the top 5%) income earners
are not considered in the survey. Under this assumption, let G* be the survey-based
Gini. One can then compute G by applying the estimates of top income shares to the
approximation mentioned above. For Greater Buenos Aires, we can compute G by
using the estimates of top income shares from Alvaredo (2011) and the survey-based
Gini coefficient. Results are presented in figure 11, where G1 and G2 are the Gini
coefficient G under the assumption that the top 0.1 percent and the top 1 percent,
respectively, are not represented in the surveys. Two facts are noticeable. First, G can
be several percentage points above G*. For instance, in 2004 G* was 0.487, while G1
was 0.523 and G2 was 0.573. Second, not only can levels be different, but also the
trends of G and G* can diverge. According to survey results, G* displays almost no
change when 2001 and 2003 are compared, going from 0.511 to 0.509 in those years.
However, G2 was 0.574 in 2001 and 0.592 in 2003. 38 That means that even when
survey-based results seem to indicate that inequality between those years was stable,
overall inequality might have risen because the share of top incomes not captured by
surveys increased substantially. This means that when the participation of the rich in
total income is important (no matter how small this group is), changes in their income
shares are relevant in explaining changes in overall distribution.
3.5. Changes in income inequality in a comparative perspective, 1970s to
2000s
The increase in inequality in Argentina from the mid-1970s to the mid-2000s was
comparatively large by international standards. This section documents the pattern of
36 This explanation follows Atkinson (2007); for a formal proof see Alvaredo (2011).
37 See Alvaredo (2010) for Argentina and Székeley and Hilgert (1999) for a general view of Latin
America. Burkhauser and others (2009) shows, for the United States, that the top 1 percent share
measured by the internal Current Population Survey (CPS) is consistently lower than the top 1 percent
income share measured by tax data, mainly because the CPS does not record important income sources
at the top (realized capital gains and stock option gains) and because the CPS records top incomes by
means of codes instead of actual income figures.
38 Determining whether those estimates of the Gini coefficient are statistically different or identical
isbeyond the scope of this analysis.