Exceptional Argentina Di Tella, Glaeser and Llach - Thomas Piketty

This change in inequality is also robust to the geographic coverage of the data.
Inequality series from 1974 can only be estimated for the Greater Buenos Aires, an
urban area containing around a third of Argentina’s total population. Notwithstanding
this limitation, the trends described in the previous paragraph can be extrapolated to
the whole urban population. Figure 9 suggests that inequality estimates for the
aggregate of all large urban areas in Argentina (available since 1992) do not differ
considerably from those of the GBA. 11
The trend in inequality can also be inferred from alternative data sources. Using
comparable methodologies for the 1985-1986 and 1996-1997 expenditure surveys,
Navajas (1999) reports Gini coefficients for the distribution of per capita expenditures
of 0.33 and 0.38, broadly compatible with the trend in income inequality in Figure 9.
Galbraith et al. (2006) find a large increase in inequality among formal workers
between 1994 and 2002, using microdata from the social security contribution
records.
It is also possible to complement indicators based on personal income with the
distribution of income between the factors of production, which can be inferred from
aggregate national accounts. While the share of wages was around 45 percent in the
early 1970s, the estimations for the mid 2000s range from 30 to 38 percent
(Lindemboim et al., 2005), suggesting again a substantial increase in inequality (see
Figure 7). 12
Finally, inequality statistics for the period after 1974 can also be derived from
administrative tax sources, as in the previous section of this chapter. Figure 1
presented an attempt to reconcile these sources with household survey data – while
not strictly comparable, the top income shares from administrative and survey data
presented roughly the same trends for the overlapping period available. These data
sources can also complement and correct some biases in inequality estimates derived
from incomplete household survey samples - see Figure 11 and a full discussion in
section 3.4 below.
The main reference points selected for Figure 8 depict the evolution of inequality in
the long run, but conceal the volatility that characterized Argentina’s income
distribution along this upward trend. Figure 9 displays the Gini coefficient for all the
years for which comparable data is available: there are short periods of relative calm,
and episodes of rapid surge in inequality. This volatility contrasts with the relative
11 See Gasparini and Cruces (2008) for more details.
12 In recent years, an increasing share of wages in aggregated income per se has ceased to be an indicator of
diminishing income concentration, since the rise of top wages in English-speaking economies has been a
driving force of the sharp increase in top income shares.