Social Origins of Dictatorships: Elite Networks and Political Transitions in Haiti
←
→
Page content transcription
If your browser does not render page correctly, please read the page content below
American Political Science Review (2021) 115, 3, 900–916
doi:10.1017/S0003055421000289 © The Author(s), 2021. Published by Cambridge University Press on behalf of the American Political
Science Association. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://
creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the
original work is properly cited
Downloaded from https://www.cambridge.org/core. IP address: 46.4.80.155, on 27 Aug 2021 at 16:06:15, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055421000289
Social Origins of Dictatorships: Elite Networks and Political
Transitions in Haiti
SURESH NAIDU Columbia University
JAMES A. ROBINSON University of Chicago
LAUREN E. YOUNG University of California, Davis
E
xisting theories of democratic reversals emphasize that elites mount actions like coups when
democracy is particularly threatening to their interests. However, existing theory has been largely
silent on the role of elite social networks, which interact with economic incentives and may facilitate
antidemocratic collective action. We develop a model where coups generate rents for elites and show that
the effort an elite puts into a coup is increasing in their network centrality. We empirically explore the model
using an original dataset of Haitian elite networks that we linked to firm-level data. We show that central
families were more likely to be accused of participating in the 1991 coup against the democratic Aristide
government. We then find that the retail prices of staple goods that are imported by such elites differentially
increase during subsequent periods of nondemocracy. Our results suggest that elite social structure is an
important factor in democratic reversals.
INTRODUCTION 2008), extended to include social networks as modeled
B
by Ballester, Calvó-Armengol, and Zenou (2006).
etween 1960 and 2010, 51 countries experi- There are three types of agents: citizens, elites, and a
enced a total of 71 democratic reversals potential dictator.1 The economy features a fixed num-
(Acemoglu et al. 2019). Existing theories sug- ber of industries, each inhabited by a subset of elites.
gest that reversals occur when democracy threatens the The median voter, a citizen, determines policy in dem-
interests of elites who have the power to overthrow ocracy and prefers competitive markets. Elites, how-
it. When elites control a greater proportion of wealth or ever, prefer entry barriers that allow them to raise
are invested in activities that can be easily taxed, the prices. To achieve this they can exert effort toward a
policy choices of the masses under democracy are more coup to place a dictator in power. Elites are intercon-
likely to create economic incentives for elites to oppose nected via a social network, and we assume that their
democracy. actions are strategic complements. The incentive to
Ultimately, reversals take place when a group of mount a coup is that if democracy falls, the dictator
elites, whether military commanders, a political faction, levies “taxes” as barriers to entry to generate rents for
or the wealthy, collectively organize to overthrow or elites.
undermine a government. We argue that within these The model has an important implication that we take
groups, social networks are important for coordinating to the data. In particular, the incentive of an elite agent
activities or spreading information and that network to put effort into making a coup happen is an increasing
positions create variation in the amount of influence function of their network (Bonacich) centrality. Intui-
that individuals have over the behavior of others. Des- tively, the more central an elite is in the network the
pite the considerable focus on social networks in other more influence his actions have on the actions of others
areas of collective action, the role of elite social net- and the more likely it is that he can make a coup happen.
works in organizing resistance to democracy has so far We further show that industries in which the coup-
received little attention. participating elites engage should see their prices rise.
In this article we undertake to our knowledge the To test these hypotheses we constructed several ori-
first investigation of the role of social networks in ginal Haitian datasets, which we describe in the Section
coups. We develop a game theoretic model of coups titled “Data.” There were a number of motivations for
in the spirit of Acemoglu and Robinson (2001; 2006; testing the theory in Haiti. First, after the 1991 coup
against the democratically elected government of Jean-
Bertrand Aristide, the US Treasury Department pub-
Suresh Naidu, Professor, Department of Economics/SIPA, Columbia lished a targeted sanctions list that named individual
University, sn2430@columbia.edu. elites associated with the coup. This list was created
James A. Robinson , Professor, Harris School of Public Policy based on intelligence efforts by the US government
and Department of Political Science, University of Chicago, and thus gives us a rare list of people specifically accused
jamesrobinson@uchicago.edu.
Lauren E. Young , Assistant Professor, Department of Political
Science, University of California, Davis, leyou@ucdavis.edu.
Received: October 13, 2017; revised: February 19, 2020; accepted: 1
We use the terms “dictatorship” and “autocracy” to refer to any
March 29, 2021. First published online: May 21, 2021. state of nondemocracy.
900Social Origins of Dictatorships: Elite Networks and Political Transitions in Haiti
of contributing to a coup. Second, there are rich genea- analysis in political science (Cruz, Labonne, and Quer-
logical sources for Haiti that allow us to understand the ubin 2017; König et al. 2017).2 Finally, our argument
social networks of elite families and map elite family that the social cohesiveness of economic elites enables
Downloaded from https://www.cambridge.org/core. IP address: 46.4.80.155, on 27 Aug 2021 at 16:06:15, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055421000289
involvement in business and politics back to the nine- them to organize against majority interests has similar-
teenth century. Moreover, Haiti is sufficiently small that ities to arguments made about landed elites in India
there is some hope of constructing a relatively complete (Anderson, Francois, and Kotwal 2015).
network. Third, given our focus, it is advantageous that This article adds to our understanding of democratic
there is variation in regime type because of frequent reversals by highlighting the importance of elite social
coups and transitions. Finally, the fact that much of the networks in facilitating action against democracy and
Haitian elite’s wealth stems from imports gives us a rare redistribution. Classic research on social movements
view of much of the economy because it is easier to has highlighted the importance of social networks that
access data on international trade than on domestic link social movement organizers to important resource
commerce or production. bases and help overcome collective action problems by
We use these data in two primary ways. First we generating social benefits to participation (Diani and
estimate the probability that a particular elite was McAdam 2003; McCarthy and Zald 1977; Zald and
accused of contributing to the 1991 coup. Our data McCarthy 1987). Elites, however, are often assumed
allow us to examine the relationship between centrality not to have any problems organizing collectively to
and coup contribution (we drop “accused” from now resist democracy or other social movement goals
on) conditional on economic interests, social character- (Offe and Wiesenthal 1980). Theories that do focus
istics, and past political involvement. Our main result is on elite cohesion assume that elite splits stem from
consistent with the model: the probability that a family differences in preferences, such as a schism between
contributed to the coup is increasing in a range of hardliners and moderates, rather than from the lack of
centrality measures. While our analysis allows us to social ties that would facilitate coordination between
control for many plausible potential confounding fac- elites with shared interests (O’Donnell and Schmitter
tors, including a family’s “neighborhood” in the net- 1986).
work, and assess robustness to reverse causality and We also contribute new evidence to arguments that
unobserved confounding, these results should ultim- democratic reversals are organized to protect the eco-
ately not be interpreted as conclusive evidence of a nomic interests of a wealthy elite. Several past studies
unidirectional causal relationship. have found evidence that coups have materialistic
Next we test whether coup contributions were motivations (Dube, Kaplan, and Naidu 2011; Mitra,
rewarded with economic rents under autocracy. We Thomakos, and Ulubaşǒglu 2002) and that elites bene-
use a dynamic panel data model to estimate the differ- fit economically from restrictions of democracy (Mitra,
ential effect of an autocratic spell from 2004 to 2006 on Thomakos, and Ulubasoglu 2002; Naidu 2012) and
the retail prices of products imported by families who suffer during expansions (Dasgupta and Ziblatt 2014).
contributed to the 1991 coup. We find robust evidence By showing how social networks are integral to the
that the prices of goods imported by coup contributors pursuit of those economic interests, our research sug-
increased relative to those of nonparticipants during gests that economic and social explanations of elite
autocracy. action against democracy are complementary. The
Though we only have rich data on elite networks in analysis that we present brings new micro-level empir-
Haiti the model does make predictions about the types ical evidence to help explain how elites are actually able
of elite social networks that would tend to enable to pursue their economic interests through the creation
democratic reversals. When elite centrality is highly of monopoly-granting autocratic regimes.
right-skewed, it should facilitate the organization of
coups, all else being equal. Intuitively, the larger the
total centrality of potential coup contributors, the more BACKGROUND ON HAITI
likely that a coup will happen.
Our article is related to several other contributions. Haiti is underdeveloped and unequal, with 48% of its
Our basic theoretical results on the connection between population below the poverty line and a Gini coeffi-
network centrality and coups are applications of ideas cient of 0.41 as of 2012 according to the World Devel-
first proposed by Ballester, Calvó-Armengol, and opment Indicators. Much of the wealth derives from
Zenou (2006) and Galeotti et al. (2010). Our model is dependence on international trade, the ownership and
also related to other models of coups, in particular control of which is very concentrated, something that
Acemoglu, Ticchi, and Vindigni (2010) who focus on dates back to its preindependence period as an extract-
the military. Although most of the literature on auto- ive slave society. Foreign merchants entered in the late
cratic persistence has focused on institutions, Carter nineteenth century, staying in Haiti as resident aliens to
(2014) shows how the president of Congo-Brazzaville maintain the protection of foreign governments, yet
manipulated elite social networks to maintain power. marrying into elite Haitian society to circumvent
Our approach to measuring the power of elite agents
builds on a rich tradition in sociology, including Padgett
and Ansell’s (1993) seminal study of the Medici family 2
While we focus on strategic interaction in networks, information
in medieval Florence (see also Puga and Trefler 2014). diffusion is another important channel by which networks matter, as
We also build on recent applications of network in García-Jimeno, Iglesias, and Yildirim (2018).
901Suresh Naidu, James A. Robinson, and Lauren E. Young
restrictions on foreign ownership of Haitian property violence and migrants, imposed sanctions on the junta
(Plummer 1988). According to a reference produced by and its economic backers. The names that Hallward
the US forces during the occupation in the 1910s and lists as coup supporters all appear on the sanctions list
Downloaded from https://www.cambridge.org/core. IP address: 46.4.80.155, on 27 Aug 2021 at 16:06:15, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055421000289
1920s, “The provisional heart, lungs and stomach of the where there are 16 members of the Brandt family, eight
Republic of Haiti, which means literally, agriculture, Mevs, seven Nadals, and André Apaid. Indeed, the
commerce and industries, from 1804 to 1915 were involvement of these families in coup plotting was not
largely foreigners: Germans, French, Syrians, Belgians new: as early as 1968 the Brandts, Nadals, and Légers
and English, with importance in the order named, who funded an attempted coup against Duvalier (Rotberg
cared very little what became of Haiti so long as they 1971, 254).
got their ‘bit’” (Jones 1919, 23). Aristide returned in 1994 to be replaced by René
The Duvalier dictatorship after 1957 largely pre- Préval in 1996. Aristide was reelected in 2001 but
served this concentrated economic structure. A long ousted by a second coup in 2004, again with the backing
list of industries became monopolies by presidential of economic elites. Although less is known about which
decree during the 1950s and 1960s: “mineral and pet- specific families participated in this coup, the top pri-
roleum exploration and exploitation, the construction vate sector backers were largely the same, and were led
and operation of television stations, the planting and by André Apaid, who had played a catalyzing role in
processing of kenaf, sesame, and ramie, the processing 1991. Apaid, along with his brother-in-law Charles
of guano, the manufacture of chocolate, a fertilizer Baker (also a sponsor of the 1991 coup), offered to
industry, the development of casinos and hotels, the pay gang leaders in Cité Soleil, a poor suburb of Port-
construction of a sugar factory, the improvement of the au-Prince, to turn against Aristide. One gang leader
telephone system, etc.” (Rotberg 1971, 210). By 1985, who took up the offer was reportedly paid $30,000
some 19 families held almost exclusive rights to import and offered a US visa (Hallward 2007; Podur 2013).
many of the most commonly consumed products in The elite also institutionalized their opposition to
Haiti. Though some of these families ultimately fell Aristide into a network called the G184 in 2002.
out with Duvalier, “outlasting all others were Though the group’s membership is opaque, G184
families B, C, D and J [in Appendix Figure A1]. They events featured the same families that had been sanc-
were the country’s principal exporters before, during, tioned for the first coup, most obviously the Apaid and
and after both Duvaliers” (Fass 1988, 27). One indica- Baker families, but also Benoît, Denis, and Gilles
tion of how wealthy these families are is that in 1960 (Hallward 2007, 192, 228). Civil society monitors
Osvald Brandt bought an entire issue of government describe the G184 as “a political platform led by the
bonds (Lundahl 1979, 347). country’s small private sector” (Arthur 2005, 1). Apaid
Democratization threatened the economic interests also apparently had control over the rebels who
of these elites. Jean-Bertrand Aristide won the 1991 advanced on Port-au-Prince in 2004: Colin Powell
election with almost 70% of the vote. Aristide had reportedly called Apaid after the rebels took control
campaigned on a platform of pro-poor redistribution, of Cap Haitien and asked him personally to restrain
and began putting in place policies to give the state a them (Hallward 2007, 224–225).
more “interventionist, dirigiste, and even protectionist Shortly after the 2004 coup, the collection of some
role in economic development” (Fatton 2002, 113). taxes paid by elites was suspended (Hallward 2007, 261;
During the first period of democracy, the Aristide Schuller 2008). Price controls were lifted, and the price
regime increased enforcement of tax collection, includ- of consumer goods skyrocketed, with the price of rice
ing import fees, and arrears (Hallward 2007, 33). As a doubling within five months (Hallward 2007, 261; Wei-
result, the Direction Générale des Impôts “registered a ner 2004). Appendix F includes a timeline of events that
historic increase in total revenues” (Dupuy 2007, 118). are relevant to our empirical strategy.
The Aristide government also increased the minimum
wage and introduced price controls on products such as
rice and wheat (Dupuy 2007; Farmer 1994; Hallward MODEL
2007).
The first coup occurred in September 1991, just eight Demographics, Preferences, and Production
months after Aristide took office and installed a mili- Structure
tary government under Raoul Cédras. The New York
Times reported that some wealthy Haitians offered as We develop a model to formalize the connection
much as $5,000 apiece to soldiers and police officers for between coup participation and network position. There
their participation in the coup (French 1991). Farmer are three types of agents that play roles in the model,
quotes one rich businessperson as saying that “every- citizens, elites, and a potential dictator. In a democracy
one who is anyone is against Aristide … except the the preferences of the citizens determine policy, but a
people” (1994, 150). Hallward (2007, 34) writes “Dur- dictator can set a different policy to create profits for
ing the summer of 1991 … the most powerful families in elites that can incentivize them to overthrow democracy.
the country—the Brandts, the Mevs, the Apaids, the Let and denote the sets of citizens and elites,
Nadals—began collecting the millions of dollars they respectively. There are E elites in total, so | |¼ E,
would need in order to pay the army to conduct another where jSj denotes the cardinality of set S, and we use
coup.” The US government, opposed to Aristide’s e ∈ to refer to a representative elite. Similarly, | | to
policies but nevertheless concerned with the political ensure that the median voter in a democracy will be a
902Social Origins of Dictatorships: Elite Networks and Political Transitions in Haiti
citizen. Citizen/consumers have a standard Cobb– We assume for simplicity that taxation is costless and
Douglas utility function defined over M different that the tax rate takes on only two values τ m ∈ f1, τ m g in
goods: sector m.
Downloaded from https://www.cambridge.org/core. IP address: 46.4.80.155, on 27 Aug 2021 at 16:06:15, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055421000289
Finally we assume that the potential dictator is
Y
M
Ui ¼ xαimm , (1) “Downsian” and gets exogenous rents D from holding
m¼1 office. At the start of the game he promises the elite a
tax vector (with commitment).
where xim is the consumption of good m by agent i and We can now write the indirect utility of a citizen in a
αm is the share of income spent on good m , where democracy as a function of the policy vector τ, to be
P M defined shortly, which is
m¼1 αm ¼ 1. Since it does not play an important role
in the analysis, we let αm ¼ α for all m, and thus α ¼ YM M1
1=M. Let xm be the aggregate demand for good m. The Y
W i ðτ Þ ¼ : (2)
only economic action that citizens take is to allocate m¼1
Mτ m κ
their exogenous income between the different goods.
Each agent maximizes this utility function subject to the The payoff to every elite member e in democracy is
P PM
budget constraint M m¼1 pm xim ≤Y, where pm is the price m¼1 wem ðτ m −1Þqκ, which is the sum across all sectors
of good m and Y is the income of citizen i in terms of the of the economy in which that elite member is active,
numeraire that we treat as exogenous and identical for taking into account the tax set in those different sectors.
all citizens. Standard arguments imply that the Mar-
shallian demand function for good m can be written as Political Regimes, Network Structure, and
LY
xm ¼ Lxim ¼ Mp because there is mass L of citizens. Transitions
m
Elites own firms distributed across the different
sectors and can also take actions to overthrow dem- There are two possible political regimes, democracy
ocracy and install the potential dictator. We assume and dictatorship. We assume that democracy is the
that each good is produced by a sector and that there default and applies unless a coup is attempted and
are multiple elites in each sector, but this varies across succeeds. In a democracy, we will assume that policy
sectors and is fixed. We assume that each good can be is chosen by the median voter, a citizen/consumer,
produced with a constant returns to scale technology whereas in a dictatorship it will be chosen by the
with fixed marginal cost κ. However, elite producers dictator.
are also capacity constrained and can produce in total Transitions between democracy and dictatorship can
qm units of output in a sector m . For simplicity we occur because the elite can use their de facto power to
assume qm ¼ q for all m. We assume later that for all induce a coup. In particular, suppose that elite e ∈ ℰ
sectors total elite supply is less than the total demand spends an amount ae ∈ ½0, 1 as a contribution to activ-
for that good, so we do not have to consider rationing ities to make a coup happen. We can interpret this
schemes across elites. action in different way—for example, it could involve
In addition to the elite producers in a sector, there is giving the dictator money to bribe the army or hire
also a competitive fringe of firms who have access to the paramilitaries directly, both of which have certainly
same technology. The equilibrium in each sector with- played a role in Haiti. If the elite take actions in this
out any government intervention therefore will involve way, then their aggregate “power” to place the dictator
elites limit pricing and setting their prices equal to κ, in power is
and profits are zero for each elite in each sector. !
1 X
However, we allow the government to set a “tax” of ℰ −e
P ðae , a Þ ¼ ae þ ae0 , (3)
τ m that varies across sectors, which raises the marginal E e0 6¼e
cost of the fringe producers only, and this allows the
elite to increase the prices they can set. We interpret τ m where ae is the action choice of elite member e and a−e
as a generic entry barrier (e.g., privileged access to the vector of actions of elite members other than e, and
imports, government regulations), which makes it more P
the notation e0 6¼e ae0 means summation over all elite
costly for fringe producers to produce good m , thus agents except agent e . The scaling factor E1 is added
allowing incumbent elites to raise prices and extract simply to make sure we have a well-defined probability
rents. Thus with government intervention, the limit of a coup below because it guarantees that the sum of
price will be pm ¼ τ m κ ≥ κ and profits of a particular the actions is always between 0 and 1. There is a cost
elite member e who produces in sector m will be associated with action ae that is captured by the function
pm q−κq or ðτ m −1Þqκ ≥ 0 , and clearly profits of elite χ ðae Þ, which takes the specific form
agent e in sector m are increasing in the tax levied on
the fringe producers in that sector. The total profits of X a2e
the elite in sector m are π ðτ m Þ , and we define π e ¼ χ ðae Þ ¼ − ωee0 ae0 ae þ γae þ δ , (4)
PM e0 6¼e
2
m¼1 wem π ðτ m Þ, where wem is the share of total profits in
industry m that accrues to elite e. Total elite profits will
P PE PM where δ and γ are positive constants which are the same
be E e¼1 π e ¼ e¼1 m¼1 wem π ðτ m Þ. for all agents.
903Suresh Naidu, James A. Robinson, and Lauren E. Young
Equation 4 has a usual linear and quadratic term in problem of elites without altering the thrust of our
a2 argument (though obviously the details would change).
the own action of elite e, the term γae þ δ 2e , but it also
includes an interaction term so that if the action of
Downloaded from https://www.cambridge.org/core. IP address: 46.4.80.155, on 27 Aug 2021 at 16:06:15, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055421000289
player e increases, the marginal cost of exerting effort Timing of Events
for player e0 falls if the two agents are connected in the
elite social network. This is so if ωee0 6¼ 0, and we shall We now explain the timing of events. The beginning
assume that ωee0 > 0 for all ee0 , which guarantees that state is democracy, and there is an opportunity to
the action choices of the elite are strategic comple- transition to dictatorship.
ments. The E E matrix whose entries are the individ-
ual ωee0 is the (weighted) adjacency matrix, which shows 1. The potential dictator promises the elite the tax
the network interactions between the elites. The com- vector τ ∈ f1, τ m gM if a coup takes place.
bination of Equation 3 and Equation 4 means that our 2. Each elite agent e ∈ ℰ simultaneously chooses
model is an adaption of the preferences proposed by ae ∈ ½0, 1 and Pℰ ðae , a−e Þ , which is determined
Ballester, Calvó-Armengol, and Zenou (2006; see also according to Equation 3.
Jackson 2008, Section 9.5.2) to the technology for 3. The random variable θ is drawn from the distribu-
generating de facto political power. We assume this tion H, and PC is determined according to Equation
technology is the same in democracy and nondemoc- 5.
racy. The formula in Equation 4 brings out the network 4. If Pℰ ≥ PC , democracy collapses, the dictator takes
interactions between the actions of the different elite power, and the taxes chosen at stage (1) are imple-
members and the formula builds in that these actions mented; if Pℰ < PC , democracy survives and the tax
are strategic complements. We do not take a strong vector is chosen by the median voter. Taxation and
stand on the source of the complementarity in actions consumption takes place.
among the elite. Information flows, trust, or altruism
could all generate situations where elite actions were
strategic complements. In addition, interconnected Analysis of the Model
elites may internalize each other’s economic interests. We calculate the pure strategy subgame perfect Nash
Whether or not a coup succeeds depends on whether equilbrium of the game by backward induction.
the power of the elite is greater than the power of the Note first that if the attempted coup fails or there is
citizens (as in Acemoglu and Robinson 2008). Because no attempt, the median voter, a citizen, sets taxes in a
we assume that the citizens are too numerous to solve democracy. Since taxes increase the prices of consump-
the collective action problem, this power is not system- tion goods and are costly to raise, it is immediate that
atically organized, but nevertheless in idiosyncratic taxes are zero in a democracy and all elites make zero
circumstances the citizens may have some power. We profits. Indeed, it is easy to see that the indirect utility of
model this as a shock θ, which is drawn from a distri- citizens is strictly decreasing in τ.
bution function H with density function h on support Taking the postcoup tax vector as given and zero
½0, 1. Thus the power of the citizens is profits in a democracy, we move backward to the
decision by elites about how much effort to allocate
PC ðaÞ ¼ θ: (5) to inducing a coup. Given the tax rates that occur if a
coup occurs, the expected payoff for elite e is
Denote the probability that there is a dictatorship
next period by pðae , a−e Þ. This is the probability that the !!
1 X X
M X a2e
power of the elite is greater than the power of the H ae þ ae0 wem ðτ m −1Þqκ þ ωee0 ae0 ae −γae −δ :
E 2
citizens, or the probability that Pℰ ðae , a−e Þ ≥ PC ðaÞ , e0 6¼e m¼1 e0 6¼e
which is simply (6)
!!
1 X Assuming there is an interior equilibrium, the result-
−e
pðae , a Þ ¼ H ae þ ae0 ing first-order condition for elite agent e is
E e0 6¼e
" #
X 1 XM
For simplicity and to maintain a linear quadratic ωe e ae −γ−δae þ
0 0 wem ðτ m −1Þqκ ¼ 0: (7)
structure of payoffs we assume that H is uniform with e0 6¼e
E m¼1
constant unit density. Shortly it will be useful to use the
notation pðaÞ for pðae , a−e Þ , with a referring to the Now we can write Equation 7 for all elite agents as a
vector of elite action choices. matrix equation
We do not observe ae in the data, only whether or not
an elite ends up on the sanctions list, discussed below in 1
a ¼ Π þ ωa,
the data section. Therefore we think of ae as a latent δ
variable and posit a strictly increasing function F :
½0, 1 ! ½0, 1 , which is the probability that an elite where a ¼ ða1 , ::, aE Þ is a column vector of action
who took action ae ends up on the sanctions list. We choices by active elites, ω is the adjacency matrix, and
do not assume that being sanctioned leads to any costs, Π is the (weighted) active elite net profit vector defined
though this could be introduced into the optimization as
904Social Origins of Dictatorships: Elite Networks and Political Transitions in Haiti
!
1 XM XM We can express this formally as the sample covari-
Π w1m ðτ m −1Þqκ−γ, ::, wEm ðτ m −1Þqκ−γ : ance between the vector of tariffs and the ownership-
δE m¼1 m¼1 weighted vector of coup participation.
Downloaded from https://www.cambridge.org/core. IP address: 46.4.80.155, on 27 Aug 2021 at 16:06:15, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055421000289
(8) There are two things to note about this result. First is
that this result is not a mechanical result of higher
We can write the solution to Equation 7 in matrix incentives (via τ m ) resulting in higher effort by elites.
notation as Instead, the effort of elites is increasing in their expos-
−1 ure to promised tariff despite the fact that the elite
1
a ¼ I− ω Π, (9) effort depends on the effort of their neighbors in the
δ network. Second is that while we present a transparent
sufficient condition below, in Appendix C.1 we provide
where I is the identity matrix. Note that because of the a weaker sufficient condition for the covariance to be
network structure, the optimal choice of ae depends on positive.
the tax rate set in a particular sector not just via own
−1
profits but also through the profits of elite agents who Proposition 2: If I− 1δ ω is positive definite and
are connected to e in the adjacency matrix. the average maximum tariff E ½ τ M1 > 1 is sufficiently
As Ballester, Calvó-Armengol, and Zenou (2006) P
close to 1, then Cov τ, e wem ae > 0.
show (Theorem 1 and Remark 1), this implies that
the action choice of agent e can be written as their
weighted Bonacich centrality, with weights given by Proof: Let W denote
the E M matrix of ownership
−1
weighted profits as in Equation 8. shares, and Ω I− 1δ ω . Multiply both sides of the
Finally, to complete the analysis, moving back to the equilibrium condition (Equation 9) by the transpose of
initial node of the game, because the dictator is Down- Π ¼ W ðτ−1M Þqκ − γ1E to get
sian, his objective in choosing the tax vector is to
maximize the probability that a coup happens, which ðW ðτ−1M Þqκ−γ1E Þ0 ΩðWðτ−1M Þqκ−γ1E Þ
P
is E a
e¼1 e . Because taxation is costless, it is clear that he ¼ ðW ðτ−1M Þqκ−γ1E Þ0 a:
will offer the maximal tax vector.
There remain several technical issues to address. Note that the left-hand side is greater than 0 by Ω
First we need to make sure that the choice of ae is being positive definite. We can then expand the right-
interior. It is sufficient to show that the matrix I− 1δ ω, or hand side to get
equivalently its inverse, is positive definite, and thus it is
sufficient to show all its eigenvalues are positive (since 0 < W ðτ−1M Þqκ−γ1E Þ0 a ¼ qκτ 0 W 0 a−qκ1M ’W 0 a−γ10E a,
ω is symmetric). This would follow if the maximal
eigenvalue of ω, which we denote λ, is less than δ, which which implies
we empirically impose below. Second we need to guar-
antee that no elite producer is unincentivized by tariff γ 0
0 < τ 0 W 0 a−1M 0 W 0 a− 1 a:
benefits because they are already providing the max- qκ E
imum level of effort a ¼ 1. We discuss this condition in
the Appendix. Now by assumption, if E½τ is sufficiently close to
From this the first result, which is a direct conse- 1, we will have
quence of Ballester, Calvó-Armengol, and Zenou
γ 0
(2006), Theorem 1, follows 0 < τ 0 W 0 a−1M 0 W 0 a− 1 ae < τ 0 W 0 a−E½τ ð1M 0 W 0 aÞ
qκ E
Proposition 1: The equilibrium action of elite agent
e is increasing in his weighted Bonacich centrality. ¼ M Covðτ, W 0 aÞ,
From this and the structure of our model, we have
our main result which we take to the data. where we recall that the sample covariance of two
vectors x and y is Covðx, yÞ ¼ E½xy−E½xE½y ¼
Corollary 1: The probability that an elite agent e is xy ð1M xÞ ð1M yÞ
sanctioned for participation in the coup is increasing in M − M M , the result.■
In the second set of empirical tests, we test this
his weighted Bonacich centrality.
proposition.
Corollary 1 is the main theoretical result we can test
with our data in the first set of empirical tests. It is also
interesting to consider what the model tells us about the DATA
payoffs to elites from making a coup happen. In the
model, the incentive to take actions to induce a coup is To test the predictions of our model, we constructed a
that elites get entry barriers so that they experience dataset that brings together information on families,
higher prices after the coup. firms, and products from more than 15 different
A natural conjecture would be that those who were sources. We draw on genealogical data going back to
sanctioned by the US would receive the most favorable the mid-nineteenth century, contemporary firm-level
treatment after the coup because they likely put more data, and information on ownership of hundreds of
effort into it. businesses. We describe the data assembly process in
905Suresh Naidu, James A. Robinson, and Lauren E. Young
detail in Appendix A, and in this section we detail the elite sample has 15 recorded marriages out of 21 family
construction of the two most distinctive variables: coup members recorded between 1850 and 1975.
participation and network centrality. The use of family ties to operationalize a social
Downloaded from https://www.cambridge.org/core. IP address: 46.4.80.155, on 27 Aug 2021 at 16:06:15, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055421000289
The information on coup participation comes from network is basic to most network analysis. In a country
the US Treasury Department’s targeted sanctions list, like Haiti, where the state is weak and small, the natural
which named individual official and unofficial leaders way to organize many activities is through kinship
in the coup government in power during the early (Henrich and Henrich 2007). Therefore, scholars such
1990s. The US had sanctions against Haiti from 1991 as Padgett and Ansell (1993) begin their analyses by
until the restoration of democracy in 1994 based on an constructing kinship and marriage networks. The use of
executive order by President Bush and populated with kinship networks is also common in recent political
specific individuals by the Office of Foreign Assets economy studies of the influence of social networks
Control. Participation in coups is an illicit activity that on politics (e.g., Cruz, Labonne, and Querubin 2017).
most participants prefer to hide, and the existence of Nevertheless, elite social networks are formed not only
this list is one reason we chose to test our general theory through marriages but also through participation in
in Haiti. educational, occupational, and social institutions. In a
The sequence of events suggests that this list repre- case like Haiti, where family firms dominate, family
sents the US government’s best information on which networks are a reasonable proxy for a wide range of
elites were instrumental to installing and supporting the strong social ties and are also likely to shape additional
coup government.3 Being added to the sanctions list interactions.
meant that an individual’s US assets were frozen, they An important variable in our model is Пe, the profits
were barred entry into the US, and they were unable to of an elite family e under dictatorship. As an imperfect
trade with US partners. From this list, we create a proxy, we use the sum of values of imports across
binary measure of coup participation by family. products p and across businesses j, with the latter
We do not have a similar list for the second coup in divided by the number of owners nownj, π e ¼
2004, but the historical literature suggests that the main P P valueejp
j nown j . Ideally, we would calculate П based on
e
instigators and supporters were the same and that many p
were connected by kinship and social ties. Many elite data from before the 1991 coup. However, we only have
families identified as supporters of the second coup also data linking elite families to firms and products for
appear on the 1991 sanctions list, including the Apaids, 2009–2011 and thus rely on the assumption that ship-
Bakers, Benoits, Denis, and Gilles (Hallward 2007; ping interests have been stable over time. This assump-
Podur 2013). Therefore, we use the same list of elites tion is supported by the historical literature, which
when we examine the consequences of the documents how many of the families who show up as
second coup. having high trade values in our data were also promin-
Our data on the social structure is taken from the ent economic players in the 1990s. For example, a 1996
Association Généalogique d’Haïti, a nonprofit effort to Dow Jones report quoted in Sprague-Silgado (2018, 5)
collect genealogical data from Haitian and American reported that “well-known local names such as Mevs,
archives and the personal records of Haitian families Bigio, Brandt, Madsen and Acra have run the economy
run by a business leader in Haiti.4 We use the Collective since the early days of this century. They control much
Genealogy of Haitian Families, which includes infor- of Haiti’s industry and trade; its supplies of petroleum,
mation on more than 64,000 individual members of telephones, sugar, flour, plastics, soap, cooking oil,
Haitian families beginning in the seventeenth century. cement, steel, iron.”
We restrict this data to more complete cohorts born Nevertheless, to check this assumption we test the
between 1850 and 1975 and collapse it into a network of extent to which the value and volume of a good
marriage links between families. Individuals are iden- imported by a specific family in 2009 and 2011 are
tified as being part of a family based on their last names, correlated. This is a relatively tough test given that
with women entered into the dataset under their Haiti experienced a catastrophic earthquake in January
father’s name.5 Direct marriage ties, including second 2010 that destroyed the port and massively disrupted
and subsequent marriages, are coded based on the trade. Appendix A.2 shows that for the products that
recorded spouses of individuals associated with each we use in our analyses, the correlations are 0.51 to 0.56.
family name. This results in a network with nodes We calculate several network statistics implied by
representing families, where the average family in our our theory, varying the weight placed on close versus
distant ties. The most general expression of the cen-
trality measures that we use is the weighted Bonacich
3
The text of the Executive Order establishing the sanctions defines it centrality, corresponding to Equation 9 above:
to target those within the regime who provided support to the regime
or who obstructed efforts to negotiate a settlement. One Haitian −1
1 1
academic told us that the criteria for inclusion were (a) public state- B , Π, ω ¼ I− ω Π,
ments from those individuals, (b) open affiliation with the coup δ δ
leaders, (c) open support to the anti-Aristide rebels, and (d) human
rights reports that documented their involvements.
4
Accessible at http://www.agh.qc.ca/.
where ω is the adjacency matrix, 1δ determines the
5
97% of women in our dataset have the same last name as their emphasis on close versus distant nodes, and Πis defined
father. as above. We use a version of the adjacency matrix
906Social Origins of Dictatorships: Elite Networks and Political Transitions in Haiti
where links between families are weighted by the size reference price (Rauch 1999), and complexity
of each family such that links to a large family with (Hausmann et al. 2013). When families import more
many potential marriages contribute less to centrality than one product, these characteristics are aggregated
Downloaded from https://www.cambridge.org/core. IP address: 46.4.80.155, on 27 Aug 2021 at 16:06:15, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055421000289
than a link with a small family.6 Each element of the up to the family level weighted by the value of the
1
adjacency matrix is multiplied by sizee size m
, where sizee family’s import portfolio that each product comprises.
is the number of individuals in family e and sizem is the Finally, in some specifications we include a community
number of individuals in family m. Bonacich fixed effect that we calculate based on the network data
(1987) using a fast-greedy community detection algorithm
suggests that 1δ take the value in the range 0, 1λ , where
(Clauset, Newman, and Moore 2004). These fixed
λ is the largest eigenvalue of the adjacency matrix ω, in
effects represent a flexible way to control for endogen-
a network with complementarities. This ensures that
ous network formation by estimating the effect of
λ < δ , and so the matrix I− 1δ G is positive definite, centrality within subgraphs of nodes that should have
which was required for our theoretical results above. similar unobserved characteristics to the extent that
Our primary measure of network centrality is the connections are endogenously formed. The top panel
Bonacich centrality where 1δ ¼ 5λ1 ¼ 0:1 , because the of Figure 1 shows that coup participants are spread
largest eigenvalue of G is approximately λ ¼ 2, but we throughout many network neighborhoods. The bottom
also show that our results hold when we parameterize panel shows that the distribution of centrality is right-
the Bonacich centrality with values in the range skewed, particularly for coup participants, and that for
1
δ ∈ 1
, 9
10λ 10λ . We can use the data to provide an aux- the importer sample in particular there are more high-
iliary check on the magnitude of 1δ by regressing a density coup participants than nonparticipants.
family’s coup participation on the coup participation of
its direct connections, recovering an estimate of the
direct spillovers. We find that the coefficient on direct
spillovers from this regression, shown in Appendix D.1, RESULTS
implies a value of 1δ equal to 0:2, close to our baseline
Who Participates in Coups?
and well within the range of our robustness exercises.
The method of calculating Bonacich centrality that is In this section we test our prediction that central elites
implied by our model identifies a set of central families are more likely to organize against democracy. Figure 2
who correspond with the historical literature on Haiti. plots the proportion of elites who participated in the
The Acra, Brandt, Baker, and Bigio families, known coup in the importer-only and all-elite samples, broken
both for their dominance in import markets and coup down into 10 equally sized deciles of centrality. In the
participation, are near the top of our list of central importer sample, 29% of elites in the lowest centrality
families. Appendix Table A1 presents information on decile participated in the coup, compared with 55% in
the 25 most central families in our dataset using our the highest. In the all-elite sample, 18% in the lowest
preferred operationalization of centrality. decile participated compared with 43% in the highest.
In addition to these variables, we constructed a Figure 2 shows that there is indeed a correlation
number of control variables representing social and between elite centrality and coup participation. Is this
economic factors that might be related to coup partici- correlation driven by omitted variables, or does it hold
pation and centrality. To create controls for other social up to the inclusion of controls for other social, political,
characteristics, we digitized dictionaries of public offi- and economic characteristics of families? To assess the
cials and immigration histories constructed by a Haitian relationship between centrality and coup participation
sociologist to create indicators of whether a family was conditional on other relevant characteristics, we esti-
a political or military elite from Haiti’s independence to mate the following specification:
the end of the Duvalier dictatorship, as well as indica-
tors of whether their ancestors immigrated to Haiti Coupi ¼ βCentralityi þ ηFamilySizei þ Social0i θ
after independence (Supplice 2001; 2009). To create þ Economic0i γ þ εi ,
controls for economic factors, we draw on eight differ-
ent sources. We create a measure of the consumption
share (a proxy for inelasticity) from Jensen, Johnson, where Coupi is an indicator for whether a family
and Stampley’s (1990) data on household consumption participated in the 1991 coup. Centralityi is a measure
in Haiti, and the value of trade is from a Haitian trading of a family’s weighted centrality in the marriage net-
association called AGEMAR. The product measures work. Sociali is a vector of social characteristics of each
cover five characteristics, described in the data appen- family including historical military and political service
dix, that have been found in other contexts to affect the and migration history. We also control for family size.
vulnerability of economic actors to government preda- Economici is a vector of characteristics that define the
tion and taxation. They include divisibility, bulkiness economic interest of a family in a coup.
(de la Sierra 2020), time sensitivity (Hummels 2007), We use two separate datasets at the family level for
this analysis: one that includes all elites, meaning any
family that appears in our records of historical political
6
It is standard practice in analysis of network data to correct for the or military service or in one of our business ownership
“garrulousness,” or overall number of connections, of nodes (Bailey databases, and one that covers only importers. Our
et al. 2018). model, which assumes that elites want to participate
907Suresh Naidu, James A. Robinson, and Lauren E. Young
FIGURE 1. Visualizations of Network Data
Downloaded from https://www.cambridge.org/core. IP address: 46.4.80.155, on 27 Aug 2021 at 16:06:15, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055421000289
(a) Network of importers (b) Network of all elite
Neighborhood Coup
Neighborhood Coup
1 5 9 13 17 21 55 117 151 Participant
1 4 7 10 13 16 19 22 Participant
2 6 10 14 18 22 59 124 168 Nonparticipant
2 5 8 11 14 17 20 55 Nonparticipant
3 7 11 15 19 29 72 138 170
3 6 9 12 15 18 21 146
4 8 12 16 20 34 90 146
(c) Distribution of importer centrality (d) Distribution of all elite centrality
Distribution of log centrality of coup plotters (black) Distribution of log centrality of coup plotters (black)
and nonplotters (grey) and nonplotters (grey)
0.20
0.35
0.30
0.15
0.25
0.20
Density
Density
0.10
0.15
0.10
0.05
0.05
0.00
0.00
0 2 4 6 8 −5 0 5 10
Bandwidth = 0.5 Bandwidth = 0.75
Note: The top panel in this figure shows marriage network ties among importing elites and all elites, with families clustered based on their
neighborhood. The bottom panel shows kernel density plots of log centrality among the coup participant and the non-coup-participant
families.
in coups to gain tariff protections under autocracy, is some specifications to take into account the fact that
tested most directly in the importer sample. In the all- families may cluster based on unobserved factors. We
elite sample, it is less evident that our assumptions calculate these fixed effects using the fast-greedy algo-
about elites’ incentives are descriptively true. rithm, which identifies dense subgraphs within the full
One concern in this analysis is the risk of bias due to network (Clauset, Newman, and Moore 2004). Later in
omitted variables. In Appendix B, we examine the this section, we describe additional robustness checks
correlates of centrality and find that obvious determin- to assess the risk of omitted variable bias.
ants of coup participation, such as military or political Table 1 presents the results of these regressions.
elite status, are uncorrelated with family centrality Columns 1–6 show the results using data from our
conditional on covariates. Nonetheless we control for importer sample, whereas Columns 7–10 use the full
many possible observable determinants of centrality. elite sample. Columns 1 and 7 show the bivariate rela-
We also include network neighborhood fixed effects in tionship between coup participation and centrality.
908Social Origins of Dictatorships: Elite Networks and Political Transitions in Haiti
FIGURE 2. Proportion of Elites Who Participate in the Coup by Deciles of Centrality
Downloaded from https://www.cambridge.org/core. IP address: 46.4.80.155, on 27 Aug 2021 at 16:06:15, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055421000289
(a) Importers (b) All elite
1.00 1.00
0.75 0.75
Coup Participation
Coup Participation
0.50 0.50
0.25 0.25
0.00 0.00
10
10
1
2
3
4
5
6
7
8
9
1
2
3
4
5
6
7
8
9
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Q
Centrality Centrality
Note: This figure shows the percentage of families who appear on the OFAC list by our weighted centrality measure.
Columns 2 and 8 add a control for family size, military family. The estimates in Column 6 imply that
and Columns 3–6 and 9–10 add four other social an elite family at the average level of the control
characteristics—namely, whether a family has any his- variables has a 45% probability of coup participation
torical military and political service, whether a family at the mean level of centrality, increasing to 62% with a
migrated to Haiti after independence, and whether they one-standard-deviation increase in centrality.
migrated from the Middle East. Columns 4–6 include We also test whether the relationship between
our two most important measures of economic interest: centrality and coup participation is robust to other
the value of a families’ trade and a proxy for demand measures of network centrality. As discussed in the
inelasticity. Columns 5–6 include five other product description of our data, our preferred measure of cen-
characteristics. Columns 6 and 10 include the network trality is a case of Bonacich centrality where the 1δ
neighborhood fixed effects. Models are estimated using parameter that sets the weight of close over distant ties
OLS with robust standard errors in parentheses. For our is equal to 5λ1 ¼ 0:1, which is similar to our estimate of
main coefficient of interest, we also present a second the relationship between coup degree and coup partici-
estimate of the standard errors that is clustered by the pation in Appendix D.1. In Figure 3, we recalculate
network neighborhood in square brackets. centrality allowing this parameter to approach the
Table 1 is consistent with the theoretical result that largest eigenvalue in theadjacency matrix by allowing
central families are more likely to participate in coups. 1 9 1
δ to vary in the range of 10λ , 10λ . This puts increasing
This result is robust to the inclusion of a wide range of weight on close over distant connections. Figure 3 plots
economic measures that should make a family more the coefficient on centrality using the specification in
interested in autocracy. The centrality coefficient Columns 1 and 7 of Table 1. All estimates are well
remains significant with all the social controls in the within the confidence intervals of our original estimate.
importer sample, but falls in magnitude and loses sig- A second check tests whether our results are robust to
nificance with these added in Column 9 in the all-elite down-weighting data that appears to be lower quality.
sample. The relationship between centrality and coup We created family-level datasets by assuming that indi-
participation is stronger and more robust in the viduals who share the same last name are part of the
importer sample, which is consistent with our theoret- same family. Thus, one possible source of measurement
ical argument that network ties facilitate and incentiv- error comes from misattributing family ties to unrelated
ize collective action by an economic elite with the individuals who share the same last name. As a measure
purpose of protecting monopolies. of data quality, we therefore calculate the probability that
Substantively, we find that a one-standard-deviation there is a path in the individual-level genealogical data
increase in centrality is associated with a 9–21-percent- between individuals with the same last name. Results in
age-point change in the probability of participating in Appendix D.2 show that estimates are robust to weight-
the coup. This is roughly double the effect of being a ing observations by this measure of data quality.
909Downloaded from https://www.cambridge.org/core. IP address: 46.4.80.155, on 27 Aug 2021 at 16:06:15, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0003055421000289
910
Suresh Naidu, James A. Robinson, and Lauren E. Young
TABLE 1. Coup Participation
Dependent variable:
Coup
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)
Centrality 0.188*** 0.178*** 0.199*** 0.127* 0.136* 0.169** 0.209*** 0.193*** 0.099 0.086
(0.060) (0.058) (0.065) (0.072) (0.073) (0.071) (0.055) (0.054) (0.064) (0.064)
[0.038] [0.06] [0.044] [0.066] [0.015] [0.119] [0.066] [0.025] [0.052] [0.126]
Family size 0.066*** 0.065*** 0.055** 0.052** 0.057* 0.045*** 0.035*** 0.036***
(0.022) (0.022) (0.026) (0.026) (0.031) (0.012) (0.013) (0.014)
Value −0.014 −0.016 0.003 −0.007
(0.030) (0.030) (0.036) (0.044)
Consumption 0.025 0.023 0.017 0.012
Share (0.051) (0.046) (0.050) (0.056)
All inputs −0.029 0.002 0.176 0.201
(0.141) (0.145) (0.185) (0.200)
Political elite 0.074 0.071 0.067 0.067 0.062
(0.084) (0.084) (0.090) (0.045) (0.047)
Military elite 0.079 0.088 0.080 0.126*** 0.101***
(0.100) (0.104) (0.106) (0.037) (0.038)
Business elite 0.057 0.057
(0.044) (0.045)
Middle Eastern 0.168 0.171 0.149 0.249*** 0.224**
(0.121) (0.125) (0.140) (0.096) (0.102)
Immigrant 0.086 0.096 0.085 0.062 0.074
(0.096) (0.097) (0.106) (0.059) (0.061)
Constant 0.433*** 0.263*** 0.314** 0.191 0.083 0.185 0.427*** 0.313*** 0.138** 0.200***
(0.044) (0.066) (0.135) (0.146) (0.163) (0.178) (0.042) (0.050) (0.067) (0.077)
Product chars. ✓ ✓
Community FE 25 36
Sample Importers All elites
Observations 217 217 217 217 217 217 716 716 716 716
R2 0.033 0.069 0.074 0.113 0.132 0.232 0.016 0.033 0.071 0.112
Note: Robust standard errors in parentheses. Standard errors clustered by fast-greedy neighborhood in square brackets. *p < 0.10, **p < 0.05, ***p < 0.01.You can also read
