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Inequality, Protests, and
the Progressive Allocation
of Cash Transfers
in the Argentine Provinces
Ernesto Calvo
Lorena Moscovich
ABSTRACT
In the last 20 years, two broadly defined theories have sought to explain the rela-
tionship between economic inequality and redistribution. The well-known
hypothesis set forth by Meltzer and Richard (1981) states that larger income dif-
ferences between the median voter and the average income earner should increase
redistributive pressures in democratic regimes. Power Resource Theory (PRT), by
contrast, argues that income inequality breeds power inequality and should
dampen redistribution.Critical to both theories is the translation of redistributive
interest into policy signals. This article considers protests as signals that increase the
salience of inequality among voters. Results provide evidence that protests facilitate
more progressive cash transfers in highly unequal environments but have modest
effects in more egalitarian ones.
In the last 20 years, a wealth of scholarly research has sought support for a pur-
ported relationship between inequality, democratic competition, and redistribu-
tion. Taking as a point of departure the well-known hypothesis set forth by Meltzer
and Richard (1981) that larger income differences between the median voter and
the average income should increase redistributive pressures in democratic regimes,
scores of researchers have ventured into individual, national, and cross-national
datasets in search of evidence. This research generated considerable excitement as an
elegant theory connected democracy and progressive redistribution at a fundamental
level. Indeed, if electorally motivated parties have an incentive to reduce inequality
by addressing the preferences of the median voter, then democratic competition
should lead not only to desirable political outcomes but also to a more equitable dis-
tribution of income.
Results, however, were disappointing. From the outset, evidence was mixed at
best, often supporting the alternative hypothesis that more unequal societies were
also less likely to redistribute resources (Lindert 2004; Pontusson and Rueda 2010;
DOI: 10.1111/laps.12016
Copyright © 2017 University of Miami
Ernesto Calvo is a professor of government and politics at the University of Maryland.
ecalvo@umd.edu. Lorena Moscovich is an assistant professor of political science at the Uni-
versidad de San Andrés. lmoscovich@udesa.edu.ar
LAPS_Summer2017_LAPS_Fall13_copy.qxp 4/27/2017 11:31 AM Page 3
Huber and Stephens 2012; Ansell and Samuels 2014). As confirmatory evidence fal-
tered, scholars proposed amendments to the original theory, sorting out confound-
ing factors and adding ad hoc mechanisms to fit a variety of adjusted models of
inequality and redistribution.1
Much of the emerging research emphasized how issue salience and agency (e.g.,
parties, unions, and mobilization) interact with existing inequality to bring about
progressive redistribution. The leading challenge to the Meltzer-Richard hypothesis
came from the Power Resource Theory (PRT), which argued that greater inequality
is not necessarily brought to the attention of voters or acknowledged in political dis-
courses. Instead, as stated by Huber and Stephens (2012), a “greater distance
between the median and the mean income tends to be accompanied by a more
skewed distribution of political power and thus lower responsiveness to demands for
redistribution” (2012, 11).
Indeed, it is not enough for inequality to exist, but it has to be recognized as a
political priority as well. Challenges to the Meltzer-Richard model of inequality and
redistribution consequently focused on the mediating effects of belief systems, social
organizations, or political institutions (Alesina and Angeletos 2005; Lupu and Pon-
tusson 2011; Pontusson and Rueda 2010; Moene and Wallerstein 2001).2
The challenge from PRT to the proponents of the Meltzer-Richard model of
inequality and redistribution was twofold. Models should account for the mecha-
nisms that relay information of higher inequality to the voters and the political
actors, and models should distinguish economic incentives from political ones, as
higher inequality may increase distributive incentives but also demobilize voters.
This study tests for the effect of inequality on redistribution conditional on
social mobilization. It contends that protests raise the salience of inequality among
voters, signaling to political entrepreneurs the importance of redistribution (Lodola
2005). To this end, it provides an original measure of redistribution that considers
a variety of income sources, such as wages, rents, retirement benefits, and cash
transfers.
To test for the effects of inequality and protests on redistribution, this study
uses as its dependent variable the regressive-progressive allocation of government
subsidies to workers and nonworkers in Argentina (cash transfers).3It takes advan-
tage of cross-sectional time series income surveys by the Argentine Census Bureau
(INDEC) in urban conglomerates from 2003 through 2011. Using Gini decompo-
sition techniques on a variety of income sources (wages, rents, retirement benefits,
and cash transfers, among others), we estimate the contribution of each income
source to the overall Gini of voters in Argentina. Our analyses test for the direct
effect of inequality on redistribution as well as for the effect of social protests at dif-
ferent levels of prior inequality (e.g., the conditional effect of protests on inequality).
Findings align with research that describes a Robin Hood paradox in democratic
redistribution, wherein more unequal societies redistribute resources regressively
while more equal societies redistribute resources progressively. In the Argentine
provinces we confirm that in the absence of protests, inequality breeds more regres-
sive social spending.
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In the last 15 years, across most of Latin America, significant declines in income
inequality have been observed. Describing the particular case of Argentina, Lustig et
al. (2013) report significant gains in wages among employed workers and add,
“Within non-labor income, the changes in the marginal distribution of government
transfers accounted for the lion’s share of the decline in [inequality], and the main
contributing factor was the large expansion in coverage of government transfers”
(Lustig et al. 2013, 5).
Our exploration of inequality in the Argentine provinces provides little support
for the Meltzer-Richard model of inequality and redistribution in its original form.
Like much of the current research, this study finds that—in the absence of social
protests—higher income inequality results in more regressive rather than more pro-
gressive allocation of government subsidies. However, our results find support for a
conditional effect of inequality on redistribution in the presence of social protests.4
That is, in highly unequal environments, protests yield larger gains than in more
egalitarian environments. Thus, in highly unequal provinces, social protests yield
larger redistributive gains than in more egalitarian provinces.
These findings align with those of Pontusson and Rueda (2007), who find that
social mobilization reduces wage inequality and does so more dramatically in more
unequal societies. However, our results differ from theirs in two very important ways.
Pontusson and Rueda consider unionization and turnout as signals of mobilization,
which, in our view, better describes labor strength. In the empirical section, we
implement a fixed effect autoregressive (AR1) model, which both is extremely con-
servative and takes the cross-district effects of unionization and turnout out of the
equation. Our results cannot be explained by unionization and turnout, which
remain relatively constant, but instead require observable shocks that vary within
provinces over time, such as protests. Second, and more important, results show that
overall protests have a larger redistributive effect than union protests taken separately.
Furthermore, by decomposing the different sources of inequality, results show that
protests have a larger effect on cash transfers than on the primary wages of workers.
In all, findings show that protests reduce overall inequality and, more important,
have a measurable effect on the progressive allocation of cash transfers. Therefore,
although our arguments bear a family resemblance to those of Pontusson and Rueda
(2007), both the proposed mechanisms and the estimation strategy differ.
The article is organized as follows. The next section presents survey data on
voters’ perception of inequality, which we consider a crucial determinant of redis-
tributive intent. Recent changes in inequality and social mobilization in the Argen-
tine provinces are described. Gini decomposition estimates for a variety of income
sources are presented, which allows for an assessment of the progressive or regressive
nature of cash transfers in the Argentine provinces. The following section estimates
the relationship between inequality and redistribution, conditioning on the level of
protests.
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INEQUALITY AND
REDISTRIBUTION
Recent studies of inequality and redistribution were heavily influenced by the model
proposed by Meltzer and Richard three decades ago. Their theory was elegant and
its implications far-reaching. Given that the income of the median voter is smaller
than the average individual income, a decisive median voter who favors redistribu-
tion should create incentives for parties to implement policies that lower income
inequality: “The basic intuition is that low income earners have more to gain and
less to lose from expansions of welfare spending than persons with high incomes”
(Moene and Wallerstein 2001).5
While economists and political scientists embraced the redistributive logic of
Meltzer and Richard, the implications of the model found no support in early
empirical studies. Instead, analyses of social spending and wage inequality in OECD
countries proved that more equal societies display larger levels of social spending
(Perotti 1996). Furthermore, individual-level income data proved that the median
voter was not a net beneficiary of redistribution in most democracies (Milanovic
2000).
Answering these challenges, authors such as Moene and Wallerstein (2001)
argued that a negative relationship between inequality and redistribution was the
result of an insurance logic that concealed the redistributive pressures of the
Meltzer-Richard models. Wealthier and less unequal societies, they argued, expand
social spending to insure voters against unemployment, health risks, and old age.
Consequently, the effect of inequality on redistribution is dampened by the insur-
ance function of welfare states.6Soon afterward, other rival theories were proposed.
Alessina and Angeletos (2005) argued that different belief systems across countries
affect the extent to which voters demand redistribution and welfare spending.
Iversen and Soskice (2006), Rueda and Pontusson (2007), Lupu and Pontusson
(2011), and Anderson and Beramendi (2012) incorporated leftist parties, social
mobilization, and electoral rules, which altered the workings of the Meltzer-Richard
model. Over all, the question raised by these models was whether inequality was
observed by voters and whether it led to policy change. Indeed, it was not enough
for income inequality to be present; it had to be recognized by the median voter as
well.
An alternative argument connecting inequality and redistribution, the Power
Resource Theory, argued that changes in income inequality also result in changes in
the organization of democratic politics (Huber and Stephens 2012). Given that
income inequality increases the disposable resources of the wealthy, it also provides
an increased capacity to invest resources, secure existing wealth, and improve the
economic position of the economic elites. In other words, inequality provides new
opportunities for the wealthy to augment their income. As previously noted, the
empirical question underlying Power Resource Theory was not whether higher
inequality is less preferred by the median voter but whether political incentives align
with those preferences. The comparison can be expressed in two hypotheses.
6 LATIN AMERICAN POLITICS AND SOCIETY 59: 2
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H1A . Meltzer-Richard: Higher inequality at t0increases the demand for redistribution,
leading to progressive redistribution at t1.
H1B . PRT: Higher inequality at t0increases the relative power of wealthy actors, leading
to regressive redistribution at t1.
Observing Inequality
The most important question underlying these arguments, however, is whether
inequality is observed by voters and dealt with by politicians. This is far from a set-
tled question. Survey data provide evidence that inequality is not always observed by
voters or described as a political priority in making voting decisions. Three recent
surveys in Argentina found that inequality was cited as the most important problem
by just 1 percent to 2 percent of all respondents (Lupu et al. 2015; ENPEA 2015;
Latinobarómetro 2015; Escolar 2016). The Latinobarómetro surveys report similar
findings for the years considered in this article, 2003 and 2009. In all seven surveys,
inequality is reported as the most important problem by less than 2 percent of the
respondents, not just in Argentina but in every country of Latin America. This is in
stark contrast to the top five most important problems listed by Argentine respon-
dents: crime, the economy, unemployment, low wages, and poverty. While it is true
that low wages and poverty have a direct effect on most measures of inequality,
respondents who favored low wages and poverty as the most important problems
were marginally more likely to report that “there is too much inequality” when the
question was asked.
As Blofield and Luna note, “It is well established that Latin America has the high-
est income and wealth inequalities in the world. What has remained less well known
is how citizens perceive these inequalities” (2011, 147). The answer to this question,
as reported by the literature, seems to be rather mixed. While inequality remains con-
spicuously absent from the list of policy priorities, researchers have shown that Latin
American voters see inequality as being “too high” and tend to be supportive of poli-
cies that favor low-income workers and the poor (Morgan and Kelly 2010). A recent
Electoral Panel Study (Lupu et al. 2015) reported that 85 percent of Argentine respon-
dents agree or strongly agree that inequality is “too high” and 76 percent agree or
strongly agree that the state should seek to reduce income differences. Similar findings
are reported in the Argentina National Election Study (ENPEA 2015), wherein 55
percent of respondents agreed or strongly agreed with the statement “inequality has
increased in the last year” and 83 percent agreed or strongly agreed with the view that
the state should seek to reduce income differences. However, while a majority of
Argentines support redistribution and recognize that inequality is “too high,” the
number of respondents who give priority to this problem is negligible, and there is no
evidence that inequality has a significant effect on vote choice.
In all, Argentine voters consistently favor an active role for the state in reducing
inequality, but at the same time, do not consider income inequality a priority. Con-
sequently, while voters have clear preferences for policies that lower inequality, redis-
tribution is also a low-salience issue. Thereby we come to our second hypothesis:
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H2. Inequality at t0will increase the demand for progressive redistribution only if issue
salience can be increased among voters.
Protest and Issue Salience
There is a significant literature that analyzes whether protests raise the visibility of
demands and bring policy issues to the attention of politicians (Gormley 1986).
Beginning with William Gamson, sociologists and political scientists have argued
that social protests increase the chances for groups to advance their policy goals
(Gamson 1975). Protests signal likely alliances between nonincumbents and fac-
tions of the elite that may seek to unseat incumbents (Alcañiz and Scheier 2007;
Navarro Yáñez and Gutiérrez 2009). Protests also provide opportunities for issue
trespassing and issue capture by rising challengers (Norpoth and Buchanan 1992),
allowing parties to gain the support of new voters (Goldstone and Tilly 2001; Inclán
2009). It has been argued that protests signal that individuals and groups are willing
to invest resources to promote important issues (McCarthy and Zald 1977) and to
strengthen their organizations (Piven and Cloward 1977). Protests also provide a
narrative to attribute responsibility to politicians (McAdam 1999), which elicits
policy responses from incumbents (Benford and Snow 2000, 615).
Inclán argues that previous protests encourage and help define new demands,
raising the probability of political consideration (2009). Furthermore, if and when
institutions fail to translate demands into policies, protests provide an effective
venue to bypass political institutions and communicate social demands to voters
(Anderson and Mendes 2006; Machado et al. 2011; Scartascini and Tommasi
2012).
It is difficult to overstate the importance of social protests in Argentina. Argen-
tine unions are known for their combativeness and very high organizational capacity
(Murillo 2001; Torre 1990). Since the rise of Juan Domingo Perón in the mid-
1940s, unions have used their strength and numbers not only to negotiate collective
wages but also to drive party politics and challenge policies they disliked. Unions
were the backbone of the “Resistance” between 1955 and 1974, carrying the banner
of the party when Perón was exiled and the Peronism brand was under proscription.
The strength of the unions to negotiate collective wage agreements (paritarias) was
accompanied by very high levels of mobilization and protest. Between democratiza-
tion in 1983 and the beginning of the 2001 political and economic crisis, the Argen-
tine General Workers’ Union organized 22 general strikes and negotiated wage
increases for a majority of the formal employees.
With the rise of unemployment in the 1990s and the rapid increase in informal
sector work, a new social movement emerged that relied almost exclusively on
protests and pickets to advance its goals.
The piqueteros’ ability to make their demands heard rested on their form of protest:
blocking heavily traveled roads (typically vital commercial arteries in the countryside
and around the city of Buenos Aires) until provincial and/or national authorities were
forced to give in. Since the first picketing, the immediate objectives of this tactic have
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been to secure new jobs, access new government subsidies, or increase existing ones.
(Alcañiz and Scheier 2007, 160).
As described by Alcañiz and Scheier, the piqueteros used social mobilization to
increase and redirect resources toward their members, raising the visibility of a con-
stituency that was neither inserted in the labor market nor unionized. In effect,
social mobilization by unions and the piqueteros was critical to raising the policy
importance of social benefits in the aftermath of the 2001 crisis.
INEQUALITY AND PROTESTS
IN ARGENTINA
To test for the effect of prior inequality on redistribution in the Argentine
provinces, we test hypotheses H1A and H1B by measuring the progressive or regres-
sive allocation of government subsidies conditional on prior inequality. While we
focus on cash transfers and overall income inequality, we also measure the progres-
sive or regressive allocation of retirement benefits, rents, and a variety of other
sources of income.
After testing for the effect of prior inequality on the progressive or regressive
allocation of different income sources, we provide an alternative specification that
considers the effect of protests, which we take as a proxy for raising the issue salience
of inequality. The alternative specifications tap into a different set of mechanisms
that depend critically on political agency. To test the proposed hypotheses, we use
individual income data from the Argentine Census Bureau (INDEC). We consider
survey respondents in 32 urban areas over a 9-year period.
Argentina is a federal country with 3 levels of government (federal, provincial,
and municipal), 23 provinces, and an autonomous city. There is enormous variation
in income, taxes, spending, partisan environment, and inequality in the Argentine
provinces. Although most revenue collection takes place at the federal level, revenue-
sharing rules provide governors with significant discretion to set spending priorities
and allocate subsidies.
In the last 20 years, the Argentine provinces have enjoyed a more prominent role
in the delivery of subsidies, as well as in the provision of basic services. Most social
services have been, since the 1990s, decentralized to provincial and municipal author-
ities (Falleti 2005, 2006). Health and education today are delivered by provincial
institutions and are subject to the availability of local resources, as provincial public
budgets today are equal to or larger than that of the federal government. Because tax
collection is carried out by the federal government while most spending takes place
at the provincial level, researchers have documented important common pool policy
traps that facilitate overspending (Spiller and Tommasi 2007; Rodden 2006).7
There is also significant variation in the prevalence of social protests in the Argen-
tine provinces. Over the last 20 years, Argentine scholars interested in contentious pol-
itics have documented significant province-level differences in the number of protests
(Pérez and Pereyra 2013; Svampa 2009; Delamata 2002; Scribano and Schuster 2001;
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Schuster et al. 2006). Nevertheless, according to the Americas Barometer, in 2010
more Argentines demanded policy changes from their government by participating in
protests than through any other active channel of participation, such as writing letters
or participating in political parties (Lodola and Seligson 2013). Among protest partic-
ipants, 57 percent attended two to three protests and 73 percent of the respondents
described their participation as worthwhile (Lodola 2013).
There is also ample evidence that politicians take notice of protests and imple-
ment policies in response to contentious events.8This has been noted by scholars
such as Szwarcberg (2015), who has documented linkages between social protests,
electoral mobilization, and clientelistic redistribution. Extensive subnational varia-
tion in spending, together with wide discretion to allocate income subsidies, allows
us to test for the relationship between inequality and redistribution.9
A Gini Decomposition Technique
to Explain Inequality in
the Argentine Provinces
To measure the progressive or regressive allocation of cash transfers (and other sources
of income) in the Argentine provinces, we implement a Gini decomposition tech-
nique. Gini decomposition is an estimation strategy that measures how different
sources of income shape overall income inequality. The results of the decomposition
analysis are interesting by themselves, but they will also serve as an intermediate prod-
uct to understand the progressive or regressive allocation of government subsidies.10
In their 2009 paper, Soares et al. implement a Gini decomposition strategy to
measure the effect of conditional cash transfer programs in Brazil, Chile, and
Mexico. In their analyses, Soares et al. provide evidence that conditional cash trans-
fer programs represent a small fraction of individual income but have a large effect
on reducing inequality. Furthermore, they note significant intercountry differences
in the inequality-reducing effect of cash transfers, although they do not systemati-
cally explain the origin of country differences.
Similarly, in an excellent article, Cont and Porto (2014) use Gini decomposi-
tion techniques to describe the effect of taxes and government spending on inequal-
ity. They find that overall, government spending in Argentina reduces inequality, a
combination of progressive spending that is able to offset slightly regressive taxation.
Cont and Porto note that provincial spending has a more pronounced progressive
effect than federal spending, “accounting for approximately 70 percent of change in
Gini coefficient” (Conto and Porto 2014, 572 ). They also find that most redistri-
bution takes place through social spending on government-provided services.
While Cont and Porto conclusively show that government spending reduces
overall inequality, they offer little discussion of the mechanisms that explain the
degree of progressivity across provinces. Indeed, their strategy does not allow us to
explain differences in observed inequality, assess the extent to which prior inequality
explains progressive redistribution, or consider the effect of other political variables.
We assume this task in what follows.
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The Data
Between 2003 and 2011, the Argentine Bureau of Statistics carried out quarterly
national-level surveys in the country’s 32 largest metropolitan areas. Each of the sur-
veys included between 45,000 and 65,000 respondents, for a total of 1,838,828
individuals. A total of 968,833 of those individuals received at least some income at
the time of the survey, providing us with large sample sizes by urban conglomerate
and province (see the appendix for descriptive information). While there has been
concern about data manipulation of the PCI index by the Argentine Census Bureau,
the National Income Survey has had a stellar record of data collection since it was
first implemented in 1974. The sample includes public and private sector employees
working part-time or full-time in the formal or informal labor market.
Although the national income surveys have been implemented since 1974, for
our analyses we pooled a standardized subset that includes an identical set of ques-
tions and variables. From 1974 through 2001, overall income inequality in
Argentina steadily rose. Inequality deepened through a combination of political and
economic shocks, such as the antilabor policies of the military regime (1976–83),
the high inflation shocks that followed the debt crisis in 1982, and the economic
contraction under the Currency Board after 1996, as well as the subsequent eco-
nomic meltdown of 2001. In all, overall inequality, as reported by Argentina’s Gini,
increased from .35 in 1974 to about .45 today, with peaks of .55 during the eco-
nomic crisis of 2001. Since 2003, fast-paced economic growth and large increases in
wages have been accompanied by a reduction in overall inequality. Most of that
reduction has resulted from gains in real wages (Lustig et al. 2013). This trend has
been verified nationwide, although significant variation is observed across provinces.
As figure 1 shows, inequality held relatively low and steady in San Luis and
Santa Cruz provinces. It also remained high and unchanged in Tucumán. Very large
reductions in inequality in Chaco and Salta contrast with mild declines in La Rioja
and Neuquén. It is interesting that there is little relationship between mean provin-
cial income and inequality (Cont and Porto 2014). Inequality in the poor province
of La Rioja is roughly similar to the well-off province of Mendoza. Low Gini scores
in the high-income province of Santa Cruz are comparable to those in the relatively
poor province of San Luis. Indeed, unlike most other income indicators, Gini esti-
mates display little regional clustering.11
DECOMPOSING INEQUALITY
IN THE ARGENTINE PROVINCES
As we have seen, individual incomes are composed of different sources, such as
wages, rents, severance payments, owed income, retirement benefits, subsidies, and
so on. In Argentina, between 60 percent and 80 percent of personal income is col-
lected from the respondent’s main employment (see figure 6 in the appendix for
provincial details). Each of these different income sources contributes, to a different
extent, to the overall income of respondents as well as to overall inequality.
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12 LATIN AMERICAN POLITICS AND SOCIETY 59: 2
Figure 1. Inequality (Gini) by Province, 2003–2011
Source: Authors’ estimates from EPH surveys.
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The Gini decomposition technique measures the relative contribution of each
income source to overall inequality. Each income source contributes to overall
inequality according to its share of the individual’s total income and as a function
of progressivity (the extent to which it increases or reduces inequality).
Lerman and Yitzhaki (1985) propose a strategy to decompose Gini coefficient
Gas a function of three terms: describing the contributions of a collection of
incomes kto total income Sk; the source Ginik; and the correlation Rkbetween each
income and the source Gini Gk.
G = K
k=1SkGkRk(1)
The different parameters of the model in equation 1 describe the contribution
of each income source to inequality and present information on the relationship
between each income source kand overall inequality. The substantive interpretation
of the three parameters allows us to assess how important the effect of an income
source is (i.e., how large the income share, Sk), how unequal the allocation of that
source is (i.e., what is the Gini of the composite source, Gk), and what the correla-
tion is of this income source with the overall Gini, Rk.
Consider, for example, figure 2, which plots the overall Gini (G) on the hori-
zontal axis and the decomposed Gini for the primary wage of the respondent (Gwage)
CALVO AND MOSCOVICH: CASH TRANSFERS IN ARGENTINA 13
Figure 2. Overall Gini vs. Main Wage Gini by Urban Conglomerate and Period,
2003–2011
Source: Authors’ estimates from INDEC data.
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on the vertical axis for all quarterly estimates by metropolitan region in Argentina.
We also add a 45-degree reference line to show that overall inequality (Gini) grows
faster than wage inequality (Gwage). Indeed, Gwage is highly correlated with overall
inequality G, given that it is the largest source of income. Other sources of income,
such as investment (stocks and bonds) or rental properties, tend to increase overall
inequality, while fellowships, cash grants, and retirement benefits tend to lower
mean inequality.
We decompose the Gini coefficient using all 14 different sources of income
listed in the Argentine National Household Survey: summer bonuses (Aguinaldo),
alimony, children’s income, fellowships, investments, wages (main occupation),
other wages, other cash income, owed income, property rentals, social security (jubi-
laciones), severance payments, social subsidies (beneficios sociales), and unemploy-
ment benefits.
The correlation between each of the income sources and overall inequality is
reported in table 1, which shows that cash transfers are, on average, negatively
related to overall inequality while most other income sources correlate positively
with the source (overall) inequality.
A negative correlation indicates that an income source reduces overall Gini.
Correlations near zero indicate that the income source does not correlate with the
overall Gini and consequently provides moderate levels of redistribution. Further-
more, a high correlation indicates that the income source further contributes to
higher levels of inequality. When inequality in the allocation of government subsi-
14 LATIN AMERICAN POLITICS AND SOCIETY 59: 2
Table 1. Correlation (Rk) Between Source Income kand overall Gini (G)
Mean SD of
Source Income Correlation (Rk) Correlations Minimum Maximum
Summer bonus 0.746 0.239 –0.758 1.000
Alimony 0.555 0.153 –0.266 0.915
Child’s employment 0.309 0.542 –0.906 0.999
Fellowships 0.193 0.508 –0.942 0.992
Investments 0.814 0.322 –0.975 1.000
Wages (main occupation) 0.910 0.025 0.806 0.988
Other cash 0.581 0.492 –0.976 1.000
Wages (secondary occupation) 0.637 0.106 0.102 0.958
Owed income 0.873 0.225 –0.744 1.000
Rental property 0.818 0.150 –0.571 1.000
Retirement 0.712 0.121 0.213 0.986
Severance payments 0.436 0.567 –0.898 1.000
Government cash transfers –0.065 0.310 –0.769 0.968
Unemployment benefits 0.285 0.447 –0.905 1.000
Note: Gini decomposition correlation means by urban conglomerate and trimester, estimated in
Stata 12 using Descogini. Vectors were stored, and entries report mean correlations (Rk) between
each source income and overall inequality.
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dies runs counter to overall inequality, it indicates that cash transfers disproportion-
ately target populations as their relative income declines.12 While cash transfers, on
average, are negatively related to overall inequality, figure 3 shows significant varia-
tion within districts and over time. In particular, we see more progressive allocation
of government cash transfers after 2005.
THE ALLOCATION OF CASH TRANSFERS
IN THE ARGENTINE PROVINCES
We take as a dependent variable two main variables: the Gini coefficient, which has
been extensively used as a general measure of inequality; and the progressive or
regressive allocation of cash transfers by urban conglomerate and trimester, as cap-
tured by the correlation terms RCashTransfers in the Gini decomposition model. This
provides a total of 908 observations, each of which takes a value ranging from –1 to
1. As noted, a negative RCashTransfers < 0 indicates that cash subsidies are being dispro-
portionately allocated to offset overall inequality. By contrast, RCashTransfers > 0 indi-
cates that cash transfers fail to reduce existing inequality. As figure 3 shows, govern-
CALVO AND MOSCOVICH: CASH TRANSFERS IN ARGENTINA 15
Figure 3. Correlation (RSocial Benefits) Between Distribution of Social Subsidies and
Overall Gini (G)
Note: Points describe the estimate of the correlation between the source income (RSocial Benefits) and
the overall Gini by urban conglomerate and trimester.
LAPS_Summer2017_LAPS_Fall13_copy.qxp 4/27/2017 11:31 AM Page 15
ment subsidies are generally progressive, with negative correlations on average in an
overwhelming majority of districts.
To explain the progressive or regressive allocation of government subsidies at
the district level, we consider a range of independent variables. They include the
mean inequality in the previous trimester (G[t–1]), the progressive or regressive allo-
cation of cash transfers in the previous trimester (RCT [t–1]), the log of the provincial
population, the log of the population with unsatisfied basic needs, and the log of the
number of workfare programs allocated in the province. We also consider a number
of political and institutional variables, including the log of number of protests in the
previous year, the log of protests by unions in the previous year, a dummy variable
that indicates whether the current governor comes from the same political party as
the president (PJ), and a dummy variable that indicates whether the current mayor
comes from the same political party as the governor.13 In the unrestricted specifica-
tions we also consider the interactions between the lagged inequality and protests,
G[t–1]) * ln (Protests), as well as the interaction between the lagged cash transfers and
protests, RCT[t–1] * ln (Protests). These last interacted terms measure the conditional
effect of prior inequality on redistribution, conditional on the level of protests,
which raise the visibility of inequality.
Table 2 presents the results of eight different specifications. The first four
models measure the effect of prior inequality (lagged Gini and rk) and protests on
current inequality. All models present autoregressive specifications with fixed effects
by survey and urban unit, although a variety of alternative models (random effects,
moving average, AR[2], etc.) yield substantively similar results.14 Table 2 presents
the most conservative estimates, with fixed effects that eliminate cross-sectional con-
founding effects and lagged values for the dependent variable that eliminate con-
founding variables within units.
In all models, higher inequality is described by the mean Gini at t–1 or the
prior correlation between each source of income and Gini (where higher correlation
means that the allocation of the income source increases inequality). The higher the
prior inequality, the less progressive the allocation of subsidies. Results are robust
within and across urban conglomerates, across specifications, and when sampling
provinces with different levels of development. The protest variables in the first four
models are negative, indicating that the greater the number of protests, the lower the
Gini (models 1 and 2). Similarly, the greater the number of protests, the more pro-
gressive (lower regressive rk) of social benefits (models 3 and 4). Because the corre-
lation between overall protests and union protests is .82, it is not surprising that sta-
tistical significance drops when both terms are introduced simultaneously. It is
interesting that in all specifications we can see that overall protests reduce inequality
to a larger extent than union protests. The effect is particularly significant in model
4, with larger numbers of overall protests yielding a more dramatic reduction in the
regressive allocations of social benefits. In all, results show that an increase in the
number of protests (LN) results in a statistically significant and substantive decline
in inequality. In other words, protests result in a more progressive allocation of gov-
ernment subsidies.
16 LATIN AMERICAN POLITICS AND SOCIETY 59: 2
LAPS_Summer2017_LAPS_Fall13_copy.qxp 4/27/2017 11:31 AM Page 16
CALVO AND MOSCOVICH: CASH TRANSFERS IN ARGENTINA 17
Table 2. The Effect of Protests and Prior Inequality on Current Inequality by Income Source, Argentina 2003–2007
(1) (2) (3) (4) (5) (6) (7) (8)
Overall Overall Social Social Main Retirement Severance Unemployment
Inequality Inequality Benefits Benefits Occupation Benefits Payments Benefits
Gini Gini (rk) (rk) (rk) (rk) (rk) (rk)
Union protests (Count-LN) –0.00466* –0.00305 –0.0818*** –0.0554* –0.00205 –0.00439 0.112 0.00245
(0.00277) (0.00284) (0.0288) (0.0291) (0.00171) (0.00952) (0.140) (0.0825)
Overall protests (Count-LN) –0.00539* –0.0919*** –0.00350** –0.00845 –0.126 –0.0818
(0.00292) (0.0297) (0.00172) (0.00950) (0.202) (0.108)
Gini (LAG) 0.276*** 0.250***
(0.0466) (0.0485)
rk (LAG) 0.341*** 0.357*** 0.116** –0.0627 –0.361** –0.00101
(0.0536) (0.0542) (0.0500) (0.0515) (0.153) (0.124)
Constant 0.345*** 0.367*** 0.161*** 0.345*** 0.824*** 0.838*** 0.929* 0.696**
(0.0229) (0.0258) (0.0419) (0.0735) (0.0469) (0.0463) (0.515) (0.326)
Fixed effects YES YES YES YES YES YES YES YES
Observations 408 394 360 346 394 392 64 93
R-squared 0.098 0.104 0.129 0.174 0.040 0.008 0.118 0.010
Number of urban units 30 29 30 29 29 29 19 26
LogLik 866.2 844.9 –53.15 –37.60 1046 367.1 –15.64 –8.309
Standard errors in parentheses.
*** p < 0.01, ** p < 0.05, * p < 0.1
LAPS_Summer2017_LAPS_Fall13_copy.qxp 4/27/2017 11:31 AM Page 17
The results with all covariates are presented in table 3. As expected, the results
show a more progressive allocation of subsidies in more populous districts (negative
coefficient for the log of the district population) and in districts with larger numbers
of individuals with unsatisfied basic needs. More interesting, as shown in table 3,
model 2 and in figure 4, is that the effect of social protests on subsidies is largest
when the prior allocation of resources is regressive, but has no statistically significant
effect when resources were already distributed progressively at t–1.
18 LATIN AMERICAN POLITICS AND SOCIETY 59: 2
Table 3. Regressive Allocation of Social Subsidies RSB
as a Function of Covariates
(1) (2)
Overall Gini Social Benefits (rk)
Protests (LN-LAG) –0.00720 –0.0725***
(0.0143) (0.0264)
Gini (LAG) 0.294***
(0.0902)
Protests (LN-LAG) * Gini (LAG) 0.00783
(0.0310)
rk (LAG) 0.549***
(0.0952)
Protests (LN-LAG) * rk (LAG) –0.0944***
(0.0327)
Population (LN) –0.0131* –0.158**
(0.00696) (0.0669)
Unsatisfied basic needs –0.0196*** –0.188***
(0.00590) (0.0573)
Number of workfare programs allocated 0.0168*** 0.171***
(0.00388) (0.0373)
Mayor same party as governor –0.0117 0.218
(0.0174) (0.166)
Peronist governor –0.0153 –0.0856
Population (LN) (0.0131) (0.124)
Constant 0.420*** 1.225
(0.111) (0.972)
Observations 427 385
R-squared 0.240 0.277
Number of urban centers 28 28
LogLik 937.2 –21.78
Standard errors in parentheses.
*** p < 0.01, ** p < 0.05, * p < 0.1
LAPS_Summer2017_LAPS_Fall13_copy.qxp 4/27/2017 11:31 AM Page 18
CONCLUDING REMARKS
Despite a significant amount of research, little support has been found for the
Meltzer-Richard model of inequality and redistribution. Consistent with the find-
ings of Lindert (2004) and Pontusson and Rueda (2007), this article shows that
more unequal districts are more likely to distribute cash transfers in a regressive way.
Using very large income surveys from the Argentine Bureau of Statistics (INDEC),
we find no “virtuous” democratic mechanism that reduces inequality through elec-
toral mechanisms.
Results are more interesting, however, when we decompose inequality and ana-
lyze the effect of prior inequality and protests on the regressive allocation of social
benefits. The findings show that protests reduce inequality and, more important,
that they do so more extensively when prior inequality is high. That is, the more
unequal the district, the more progressive the allocation of resources induced by
protests.
CALVO AND MOSCOVICH: CASH TRANSFERS IN ARGENTINA 19
Figure 4. Effect of Social Protest on Progressivity, Conditional on
Prior Allocation of Cash Transfers
Source: Estimated from table 2, model 6.
Note: Higher numbers on the horizontal axis rk[n–1] describe more regressive allocation of cash
transfers. Because rk captures the correlation between cash transfers and Gini, positive numbers
indicate that it increases Gini values (therefore it contributes to higher inequality). Positive values
on the horizontal axis indicate that cash transfers reinforce inequality, while negative numbers indi-
cate that they reduce inequality.
LAPS_Summer2017_LAPS_Fall13_copy.qxp 4/27/2017 11:31 AM Page 19
Consider, for example, the cases of Tucumán and Neuquén, two provinces
with similar levels of social protest but vastly different levels of inequality. Findings
in this article do not simply show that protests yield a reduction in inequality, but
more important, that this reduction will be larger in the highly unequal Tucumán
than in Neuquén. Furthermore, the results show that increasing protests should
yield negligible reductions in inequality in Santa Cruz and large reductions in Salta.
To explain the effect of protests on redistribution and their conditional effect,
we consider how protests increase the salience of inequality as an important issue.
As we have noted, Argentine voters are aware that inequality in Argentina is high,
but at the same time, they do not consider such inequality an important policy issue
to be dealt with. Protests, we argue, raise the visibility of inequality as an important
policy issue and provide signals to politicians to invest public resources. The higher
the existing inequality and the more numerous the protests, consequently, the more
progressive politicians’ investment to deal with this issue.
APPENDIX
Figure 5. Inequality (Gini) by Province, Boxplot
20 LATIN AMERICAN POLITICS AND SOCIETY 59: 2
Source: Authors’ estimates from EPH surveys.
LAPS_Summer2017_LAPS_Fall13_copy.qxp 4/27/2017 11:31 AM Page 20
NOTES
We thank Germán Pérez and Melchor Armesto, who facilitated data on protests. Exten-
sive comments were provided by Pablo Beramendi, Charles Munnell, María Victoria Murillo,
Carlos Scartascini, Richard Snyder, Mariano Tommasi, and Rebeca Weitz-Shapiro on differ-
ent versions of this manuscript. We also thank the participants of workshops at Brown Uni-
versity, Oxford University, and the Universidad de San Andrés. Lorena Moscovich thanks the
Center for Latin American and Caribbean Studies at Brown University, the financial support
of the LASA-Mellon Seminar Funds, and the BIARI program.
1. See Ansell and Samuels 2014 for a more general review of the literature.
2. Electoral rules are critical intervening variables that affect how extensively inequality
is translated into redistributive pressures. For example, malapportionment, majoritarian
biases, or proportional allocation of seats are not equally likely to give voice to the median
income earner (Iversen and Soskice 2006; Schneider and Soskice 2009; Ardanaz and Scar-
tascini 2013); a disenfranchised and demobilized poor may result in a decisive median voter
who is wealthier than the actual median income earner (Anderson and Beramendi 2012); and
wealthier societies with lower inequality may be able to expand social insurance, confounding
the distributive pressures anticipated by the theory (Moene and Wallerstein 2001).
3. In this article, a regressive allocation of subsidies is defined as one that increases over-
all (Gini) inequality, and a progressive allocation of subsidies is defined as one that reduces
(Gini) inequality. To this end, we implement a decomposition technique that allows us to
measure the contribution of different income sources to overall inequality.
CALVO AND MOSCOVICH: CASH TRANSFERS IN ARGENTINA 21
Figure 6: Overall Annual Number of Protests (LN) by District
Source: Pérez and Armesto 2012.
LAPS_Summer2017_LAPS_Fall13_copy.qxp 4/27/2017 11:31 AM Page 21
4. For analyses of the relationship between protests and redistribution see Garay 2007;
Weitz-Shapiro 2006; and Giraudy 2007.
5. Extensions of Meltzer and Richard have been incorporated into a range of influen-
tial analyses, explaining why economic elites resist democratization while the poor promote
it (Acemoglu and Robinson 2005; Boix 2003); why majoritarian electoral rules were aban-
doned (Cusak et al. 2007); and the expansion of welfare policies (Alesina and Angeletos
2005).
6. In a recent article, Barber et al. (2013) find experimental support for these two
incentives, although the effects were moderate and voters had difficulty distinguishing the
distributive and insurance function of transfers.
7. Most resources are collected by the federal government and delivered to provinces
according to a federal revenue-sharing law. Some resources are also delivered discretionally or
through federal policies (infrastructure or social aid).
8. Examples include statements from prominent governors such as Felipe Solá of
Buenos Aires province (Lucesole 2004) and Eduardo Fellner of Jujuy (Noro 2003).
9. Such subnational variation has made the Argentine provinces the object of numer-
ous analyses by political scientists and economists, studying a range of phenomena that
includes differences in the degree of subnational democracy (Gibson 2005; Gervasoni 2010;
Giraudy 2010); spending (Spiller and Tommasi 2007); income and inequality (Cont and
Porto 2014; Porto and Cont 1998); protest (Arce 2010; Garay 2007; Giraudy 2007;
Machado et al. 2011; Moscovich 2012; Weitz-Shapiro 2006); and partisan competition
(Calvo and Escolar 2005; Leiras 2007).
10. A description of inequality measures can be found in Mahler and Jesuit 2006. These
include the Gini coefficient, still the most widely used; net and disposable income; fiscal
spending; and tax transfers. While many cross-national datasets exist, we are not aware of any
that include time series comparative subnational data. In the Argentine case, Gini decompo-
sition data that account for posttax income were estimated in Cont and Porto 2014 for a
single wave of the EPH, which is why we decided to use the progressive or regressive effect of
different income sources on the Gini coefficient. We consider this a reasonable approxima-
tion of the effect of different income sources on inequality.
11. The boxplot in figure 5 in the appendix facilitates a comparison of inequality for
the entire period, describing median Gini estimates by province with a solid line inside each
bar and describing the 75/25 range in Gini estimates for the entire period. As can be
observed, Gini coefficients display significant variation across provinces and over time, with
Salta, Tucumán, and Corrientes displaying the highest inequality scores, compared to Santa
Cruz and San Luis with the lowest scores.
12. We also estimated an alternative specification using overall change in Gini by gov-
ernment subsidies. Both models yield similar results.
13. Variables describing the number of protests by district are from Pérez and Armesto
2012. The dataset collects national media reports, which underestimate provincial protests
and treat the Buenos Aires metropolitan area events as “local.” Reporting biases, however,
should remain relatively constant over time. We thank Germán Pérez and Melchor Armesto
for sharing these data.
14. Alternative models and replication materials may be downloaded at http://gvpt
sites.umd.edu/calvo.
22 LATIN AMERICAN POLITICS AND SOCIETY 59: 2
LAPS_Summer2017_LAPS_Fall13_copy.qxp 4/27/2017 11:31 AM Page 22
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