Comparative Political Studies
2015, Vol. 48(12) 1526­–1562
© The Author(s) 2015
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DOI: 10.1177/0010414015582051
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Article
Electoral
Authoritarianism and
Human Development
Michael K. Miller1
Abstract
Do autocratic institutions matter for the welfare of average citizens? Despite
the large literature comparing democracies and autocracies, we know
little about how human development outcomes differ among autocratic
types. Contrary to conventional wisdom, this article argues that contested
autocratic elections promote human development by improving state
accountability and capacity. Using an instrumental variables setup, I show
that the presence and history of multiparty autocratic elections predict
significantly better outcomes on health, education, gender equality, and basic
freedoms relative to non-electoral autocracy. In fact, the effects on health and
education are as strong as the effects of democracy. In contrast, legislatures
and parties without multiparty elections produce slightly negative outcomes
because these institutions chiefly concern elite cooptation. The results have
major implications for the study of autocracy, the political economy of
development, and the welfare effects of international election promotion.
Keywords
non-democratic regimes, politics of growth/development, social welfare
programs
1George Washington University, Washington, DC, USA
Corresponding Author:
Michael K. Miller, George Washington University, Monroe Hall 440, 2115 G St. NW,
Washington, DC 20052, USA.
Email: mkm2@gwu.edu
582051CPSXXX10.1177/0010414015582051Comparative Political StudiesMiller
research-article2015
Miller	 1527
Introduction
Which political institutions promote responsive policy-making and positive
outcomes in areas like health and education? An extensive literature has
focused on democracy as synonymous with political accountability and, in
turn, social welfare provision. Indeed, there is overwhelming evidence that
democracies produce higher levels of social spending (e.g., Haggard &
Kaufman, 2008; Kaufman & Segura-Ubiergo, 2001; Stasavage, 2005) and
human capital (e.g., Gerring, Thacker, & Alfaro, 2012; Lake & Baum, 2001;
Sloan & Tedin, 1987).
However, this binary distinction between democracy and dictatorship
obscures a great deal of variation, as many autocracies have pursued expansive
social welfare programs. Perhaps the best-known example is Bismarck’s
proto-welfare state in 19th-century Prussia, but this is far from a unique case.
The Asian Tigers and Eastern European Communist regimes strongly
invested in education and basic health (Haggard & Kaufman, 2008). Brazil’s
military regime extended health insurance and social security to the rural
population in 1971, a reform that failed to pass under previous democratic
governments (Falleti, 2009). In fact, about two thirds of countries’ first adoptions
of old age, disability, and health insurance have occurred under authoritarianism
(Mares & Carnes, 2009).
Can political institutions account for this within-autocracy variation? For
instance, Malaysia and Swaziland are both middle-income autocracies, but
twice as many adults are illiterate in Swaziland and 14 times as many children
die before the age of 5. Is this connected to Swaziland’s lack of party
competition, whereas Malaysia has a 50-year history of contested elections?
Despite a growing literature on autocratic parties, legislatures, and elections
(e.g., Brownlee, 2007; Gandhi, 2008b; Geddes, 1999; Svolik, 2012), there
has been surprisingly little work comparing human development outcomes
across these institutions. What makes this oversight especially significant is
that international actors frequently pressure autocrats to adopt democratic
elements (Goldsmith, 2008; Levitsky & Way, 2010). As a result, about two
thirds of autocracies over the last 20 years have allowed multiparty elections.
Yet a critical question remains largely unexplored: Is this a good thing for
these countries’ citizens?
Using an instrumental variables (IVs) setup, this article shows that electoral
authoritarianism (EA) has a positive causal effect (relative to non-electoral
autocracy) on a wide range of human development outcomes, including
infant mortality, literacy, and gender balance in schooling. EA regimes are
defined as autocracies with legal multiparty competition in legislative elections.
Although contested, these elections are distinguished from the
1528	 Comparative Political Studies 48(12)
democratic type by unfree and unfair conditions that favor the regime. This
imbalance has led many scholars to see autocratic elections as insignificant or
even damaging to governance (Chauvet & Collier, 2009; Goldsmith, 2008;
Lust-Okar, 2006). Yet even when they are seriously manipulated, I argue that
autocratic elections can be sufficiently competitive to contribute to popular
pressure and governmental capacity.
Surprisingly, EA’s effects on health and education roughly match the
effects of democracy. As a result, this article relocates the social welfare
divide among regimes—the critical factor is not democracy, but contested
elections. However, democracy is maintained as the most advantageous system
given its clear superiority on civil liberties and state repression.
In further results, I find that legislatures and ruling parties in the absence
of multiparty competition predict slightly negative human development outcomes.
The recent literature on autocratic institutions has shown that legislatures
and parties promote regime durability (Brownlee, 2007; Magaloni,
2006, 2008; Svolik, 2012) and certain policy concessions (Gandhi, 2008b),
but the focus has instead been on elite cooptation. This article complements
this work by showing that social welfare policies are only promoted when
citizens and an opposition are granted voice, muffled as it may be.
For outcomes, I focus on four areas of human development: health, education,
gender equality, and basic freedoms. These outcomes are emblematic of
capable and responsive governance, and reflect a special concern with human
capital and long-run prosperity. As this article is the first to relate autocratic
institutions to several of these outcomes, the findings have important implications
for the political economy of development and the welfare effects of
international election promotion. This article also adopts two innovative
empirical strategies to address the potential endogeneity of EA: It distinguishes
the short- and long-term effects of institutions and uses the regional
diffusion of regime types and the inheritance of institutions from previous
rulers as IVs.
The following section overviews recent work on the policy and development
effects of democracy and autocratic institutions. The “Electoral
Authoritarianism and Human Development” section argues that EA regimes
should have superior human development outcomes compared with closed
(non-electoral) autocracies, based on three of the mechanisms commonly
associated with democracy. The “Determining the Causal Effect ofAutocratic
Elections” section lays out the endogeneity challenge in testing autocratic
institutions and defends my IV approach. The remaining sections overview
the data and empirical setup, followed by the empirical findings and a discussion
of their implications.
Miller	 1529
Past Work on Democracy and Autocratic
Institutions
Democracy and Human Development
An enormous literature has developed on the association between democracy
and human development, as well as economic growth, inequality, and
countless other outcomes.1 The central logic is that democracy provides
incentives for politicians to improve citizen welfare. Democracies are also
more effective at implementing policies, as they have higher quality of government
and lower corruption (Adserà, Boix, & Payne, 2003; Humphreys &
Bates, 2005).
There is strong evidence that democracy leads to greater public investment
in health and education (Brown & Hunter, 2004; Haggard & Kaufman,
2008; Lake & Baum, 2001; Stasavage, 2005; but see Mulligan, Gil, & Salai-Martin,
2004). Suffrage extensions, particularly for women and the poor,
have also been shown to increase social spending (Husted & Kenny, 1997;
Lindert, 2004). In turn, this spending translates into a positive association
between democracy and infant mortality (Besley & Kudamatsu, 2006;
Gerring et al., 2012; Lake & Baum, 2001; Zweifel & Navia, 2000), other
measures of public health (Gerring, 2011; Lake & Baum, 2001; Sloan &
Tedin, 1987; Wigley & Akkoyunlu-Wigley, 2011), educational attainment
(Brown, 1999; Halperin, Siegle, & Weinstein, 2010; Sloan & Tedin, 1987),
and gender equity in human development (M. Baum & Lake, 2003; Beer,
2009; Brown, 2004). However, the link between democracy and outcomes is
more often disputed (Carbone, 2009; Nelson, 2007; Ross, 2006). For instance,
Ross (2006) argues that democracy increases health spending targeted at the
middle class, but is unrelated to infant mortality.
Autocratic Institutions
The spread of autocratic institutions.  Despite the extensive literature on democracy,
there exists little work distinguishing human development outcomes
among autocratic types. This is a major oversight given the global spread of
autocratic institutions traditionally associated with democracy, such as legislatures,
parties, independent courts, and elections (Gandhi, 2008b; Schedler,
2006). Figure 1 shows the prevalence of closed autocracy, EA, and democracy
in each year from 1946 to 2007 (from Boix, Miller, & Rosato, 2013;
Cheibub, Gandhi, & Vreeland, 2010). Again, EA regimes are defined as
autocracies with legal multiparty competition for the legislature (e.g., Russia,
Malaysia, and Singapore). Closed autocracies either lack electoral institutions
(Saudi Arabia, UAE) or feature single- or no-party elections (North
1530	 Comparative Political Studies 48(12)
Korea, Swaziland), which are largely ceremonial in nature. EA regimes distinguish
themselves from democracies by manipulating electoral competition
to below democratic standards. As seen, EA is not entirely new, but has
recently become the large majority among autocracies.
This diffusion has stimulated a growing literature on the causes and consequences
of autocratic institutions (Geddes, 1999; Levitsky & Way, 2010;
Schedler, 2006; Svolik, 2012). A dominant theme in this work is the strategic
value of institutions for regime survival, either through co-opting elites
(Blaydes, 2011; Geddes, 1999; Magaloni, 2006, 2008; Svolik, 2012) or
extending control over citizens (Lust-Okar, 2006; Magaloni, 2006).Autocratic
elections, for instance, allow regimes to signal dominance (Magaloni, 2006;
Simpser, 2013), disperse patronage (Lust-Okar, 2006; Magaloni, 2006), and
gather information on opponents (Gandhi & Lust-Okar, 2009; Magaloni,
2006; Miller, 2015).
Figure 1.  Distribution of three regime types by year.
The figure shows the distribution of three regime types by year from 1946 to 2007. Electoral
authoritarian (EA) regimes allow legal multiparty competition for the legislature (measured
from Cheibub, Gandhi, & Vreeland, 2010). Democracy is measured from Boix, Miller, and
Rosato (2013). Note the large fraction of EA regimes as far back as 1946 and their sharp rise
around the end of the Cold War.
Miller	 1531
If autocratic elections were only adopted based on such calculations, it
would be difficult to test their effects as they would be entirely endogenous
to regime strategies. However, there are several other motivations for regimes
to hold elections. The most widely recognized is international pressure,
which rewards countries for adopting electoral institutions through aid, trade,
and military benefits (Carothers, 1999; Levitsky & Way, 2010). Although
usually packaged as democracy promotion, the end result is often transition
to EA, as autocrats determine that they can profitably adopt the formal institutions
of democracy without the substance (Carothers, 1999; Goldsmith,
2008). Clear cases include Leopold Senghor’s late-1970s adoption of EA in
Senegal “to attract Western aid and investors” (Coulon, 1988, p. 157) and
Burma’s recent liberalization. Other factors encouraging EAadoption include
domestic protest, the country’s institutional history, post-civil war settlements
(often under international mediation), and regional diffusion, which I
expand upon below.
Autocratic institutions and policy.  Compared to regime survival, less work has
been done on how autocratic institutions influence policy. The most thorough
study in this vein is Gandhi (2008b), which argues that autocratic legislatures
serve as forums for policy compromises with elites. To test this, Gandhi
shows that legislatures predict greater civil liberties and lower military spending.2
Elsewhere, she relates legislatures to workers’ wages and strike behavior
(Kim & Gandhi, 2010). A separate current of work focuses on the power
of legislatures and parties to constrain the arbitrary rule of dictators. This
allows rulers to make credible promises, leading to more investment and economic
growth (Gandhi, 2008a; Gehlbach & Keefer, 2011; Jensen, Malesky,
& Weymouth, 2014; Wright, 2008).3
It is less clear that legislatures and parties by themselves will influence
social welfare policies. Within closed autocracies, these institutions primarily
involve deal-making among elites. If they succeed at this cooptation, legislatures
and parties magnify regime power and may reduce the need to appeal to
average citizens (Jensen et al., 2014; Wright & Escribà-Folch, 2012). Other
authors suggest that autocratic institutions act as political concessions that
substitute for public goods, implying that liberalized autocracies should have
worse human development outcomes (Desai, Olofsgård, & Yousef, 2008).
Perhaps for these reasons, Gandhi (2008b) does not find a relationship
between legislatures and social spending. Furthermore, the literature on legislatures
and parties has focused on the capacity of dictators to compromise
on policy rather than their incentives, which limits the causal significance of
these institutions. Critically, Gandhi’s (2008b) theory is that legislatures
enable policy concessions by providing a forum for bargaining and
1532	 Comparative Political Studies 48(12)
information-sharing. The motivation to compromise in her theory stems from
other factors, particularly the threat of armed revolt (see Pepinsky, 2014).
In contrast, I argue below that contested autocratic elections both motivate
regimes to improve social welfare and improve their capacity to do so. As a
result, contested elections are the critical institutions within autocracies for
generating human development. Past work has linked autocratic elections to
patronage (Blaydes, 2011; Lust-Okar, 2006) and budget cycles (Blaydes,
2011; Magaloni, 2006), which are among the array of tricks that ruling parties
use to control elections. However, many scholars remain skeptical that these
elections matter for substantive policy outcomes. Lust-Okar (2006), for
instance, contends that patronage “trumps by far any role of elections as arenas
for contests over the executive or critical policies” (p. 459). Yet evidence
is growing that multiparty autocracies are associated with distinct policy
choices. Conrad (2011) predicts calorie consumption and civil liberties based
on the legalization of opposition parties. Hankla and Kuthy (2013) show that
multiparty legislatures predict free trade, which they argue serves as a public
good. Finally, several studies find that Chinese local elections encourage
public goods provision and greater responsiveness (Martinez-Bravo, Padró i
Miquel, Qian, & Yao, 2012; O’Brien & Li, 2000; Wang & Yao, 2007).
This study extends this analysis to human development outcomes, the
clearest indicators of citizen welfare and policy responsiveness. Despite the
extensive work on democracy, studies of autocratic institutions have surprisingly
neglected core measures of human development. The closest is work on
public spending (Desai et al., 2008; Gandhi, 2008b) and calorie deprivation
(Blaydes & Kayser, 2011; Conrad, 2011). I demonstrate a strong causal effect
of EA on infant mortality, literacy, gender balance in schooling, and other
outcomes.
This article presents several further empirical advances. First, I differentiate
multiparty elections from other distinct, but correlated, institutions.
Gandhi (2008b) focuses on autocracies with legislatures, but only 66% of
these regimes qualify as EA. Following Geddes (1999), other studies compare
military, party-based, and personalist regimes (Lai & Slater, 2006;
Weeks, 2008; Wright, 2008). For a fuller picture of which institutions matter,
I compare multiparty elections to legislatures, parties, and the Geddes (1999)
categories.4
Second, I test both a country’s current regime type and its regime type history.
As Gerring (2011) argues, political institutions should influence human
development only over an extended time period. Variables like literacy and
life expectancy change slowly and political regimes’ effects permeate gradually
by transforming policy, bureaucratic effectiveness, and civil society.
Thus, Besley and Kudamatsu (2006), Gerring (2011), and Gerring et al.
Miller	 1533
(2012) generally find that health outcomes are positively related to the historical
stock of democracy, but not to its current level. I extend this analysis
to the history of EA and other autocratic institutions.
Third, to identify causal effects, I use the prevalence of regime types in a
country’s region and EA inheritance from previous rulers as a novel set of
instruments for EA. As discussed below, previous work has either ignored the
endogeneity problem or used instruments that likely fail the required exclusion
restrictions.
EA and Human Development
This section explains why EA regimes display superior human development
outcomes relative to closed autocracies. Human development is promoted by
effective public goods provision—especially in health services, education,
and environmental protection—and policies that promote broad social welfare.
Because such policies are widely popular, political features that incentivize
governments to appeal to citizens will produce better development
outcomes (Brown & Hunter, 2004; Lake & Baum, 2001). This case is easy to
make for democracy, which promotes responsive leaders by directly tying
their power to popular support.
I argue that EA regimes are also more motivated than closed autocracies
to respond to mass preferences. This follows from two mechanisms commonly
associated with democracy, but which I argue also apply to EA
regimes. The most critical is electoral pressure. Although initially adopted in
response to international incentives or to co-opt domestic actors, autocratic
elections can quickly transform into powerful sources of popular pressure.
Despite being manipulated, many of these elections are highly competitive
and thus force regimes to respond to mass demands. A secondary mechanism
is political openness, which provides another channel for popular pressure in
liberalized autocracies. Finally, I argue that institutionalized autocracies also
have advantages in governmental capacity and are thus more effective at
implementing policies that provide for basic needs and build human capital.
Electoral Pressure
By definition, autocratic elections are contested on an uneven playing field
(Magaloni, 2006; Schedler, 2006), but this does not eliminate uncertainty or
electoral turnover. In fact, autocratic elections can be highly competitive,
providing an opening for citizens to sanction regimes for poor policy outputs.
As Levitsky and Way (2010) argue, “Government officials fear a possible
opposition victory (and must work hard to thwart it) . . . In competitive
authoritarian regimes, incumbents are forced to sweat” (p. 12).
1534	 Comparative Political Studies 48(12)
Contrary to what many assume, autocratic elections feature dramatic and
often unexpected swings in support. In each legislative election under EA, a
one-standard-deviation shift in the ruling party’s seat share is about 19%,
slightly higher than within democracies.5 Examples of unanticipated electoral
shocks under EA include Mexico in 1988, Singapore in 1991, Morocco
in 2007, and Russia in 2011. As a result, electoral turnover is a real threat.
Using Hyde and Marinov’s (2012) data, I find 51 elections since 1946 in
which an EA regime’s incumbent party lost, with another 55 in which the
incumbent leader left office due to the election. Together, these constitute
nearly 1 in 5 national elections under EA. Either event roughly doubles the
likelihood of democratization within 2 years (using Boix et al., 2013), as
occurred in Benin in 1991, Guyana in 1992, and Mexico in 2000. Furthermore,
a majority of the turnover cases experienced “regime failure” as defined by
Geddes, Wright, and Frantz (2014). To avoid this fate, regimes spend copiously
on election campaigns, clientelism, bonuses for public workers, and
public goods to placate citizens, none of which would occur if elections were
truly pre-ordained.
Even when ruling parties do not immediately risk losing power, several
features of contested autocratic elections encourage policy responsiveness.
First, even when they control elections in the present, autocrats are constantly
reminded that complacency risks defeat in the future. It is tempting to make
the faulty inference that because many autocratic elections are won by large
margins, they cannot motivate regimes to provide public services. However,
this is akin to arguing that because a champion boxer consistently wins his
fights, he must not feel the need to train very hard. This foresight retains parties’
sensitivities to popular demands, while lengthening their time horizons,
leaving them more inclined to invest in education and long-term development
(Gehlbach & Keefer, 2011; Olson, 2000; Wright, 2008). Ruling parties
can also benefit from successful development even after democratization, as
most remain electorally competitive post-transition (Wright & Escribà-Folch,
2012). For instance, the ruling legacies of Mexico’s PRI and Taiwan’s
Kuomintang (KMT) were central to their regaining power under democracy.
Second, even when national parties are highly secure, individual politicians
may not be. For instance, between 1984 and 2005, reelection rates for Egyptian
legislators varied from 19% to 42% (Blaydes, 2011). Local leaders also use
strong electoral results to signal their competence and rise up the party hierarchy
(Blaydes, 2011; Brandt & Turner, 2007). This electoral pressure motivates
politicians to improve citizen welfare, at least in their local constituencies.
Third, besides the fear of outright losing, ruling parties seek to maximize their
winning margins to project strength and deter elite defections (Magaloni, 2006;
Simpser, 2013). Fourth, even semi-competitive elections can function as dangerous
focal points for opposition collective action, especially if there is a
Miller	 1535
widespread perception of fraud (Fearon, 2011; Magaloni, 2006; Svolik, 2012).
About one in three EA elections feature significant protests, riots, or violence
surrounding the election (Hyde & Marinov, 2012). This vulnerability encourages
regimes to at least temporarily reduce citizen discontent.
A final question is why many autocrats choose social welfare policies and
public goods to defuse this popular pressure, rather than exclusively relying
on fraud, repression, or vote buying. Although many EA regimes rely on
some mix of these strategies, public goods often prove to be the safest option.
Fraud and repression risk triggering protest, a loss of legitimacy, and international
punishment, thereby forgoing the central benefits for which elections
are adopted. Vote buying and patronage can control elections, but can also be
exceedingly costly, especially for large, wealthy populations (Gandhi &
Lust-Okar, 2009; Hicken, 2011).6 When clientelism does occur, it often consists
of an informal bargain in which local public goods are traded for electoral
support.7 As a result, when constructing electoral coalitions, EA regimes
are naturally drawn to the poor as they are more easily co-opted by state
assistance (Blaydes, 2011; Gandhi & Lust-Okar, 2009; Hicken, 2011).8 In
turn, this leads many EA regimes to strategically emphasize social assistance
and basic development outcomes.
Numerous cases show that even minimally competitive elections can
motivate EA regimes to improve social welfare policies.9 Nelson (2007)
points to a positive effect of competitive elections on education reform in
autocratic Malawi, Uganda, Tanzania, Kenya, and Mexico. In several detailed
case studies, Haggard and Kaufman (2008) identify autocratic elections as
key to increased public goods provision and social assistance in Taiwan,
Brazil, Mexico, Peru, and Venezuela. We can also find evidence of withinregime
policy shifts: In a study of 86 EAregimes, electoral declines for ruling
parties predict post-election increases in education and social spending and
decreases in military spending (Miller, 2015).
A clear example of autocratic electoral pressure promoting human development
is Taiwan’s path to universal health care in 1995. As late as 1980,
only 16% of Taiwanese were insured and they spent a miniscule US$78 per
capita on health care (Chiang, 1997). After the ruling KMT allowed opposition
competition in 1986, the Democratic Progressive Party (DPP) strongly
emphasized social welfare reform and garnered unexpected electoral support
in 1986 and 1989. The KMT quickly pivoted to an expansion of social programs
due to this newfound political pressure (Chiang, 1997; Haggard &
Kaufman, 2008; Son, 2001). In particular, the KMT moved to nullify one of
the DPP’s chief policy demands by passing health insurance for farmers in
1988 and proposing a National Health Insurance (NHI) system by 2000.10
Although the KMT remained electorally dominant, the DPP was steadily
1536	 Comparative Political Studies 48(12)
gaining support, creeping up to 31% of votes in 1992. Anticipating the
rematch in 1995 and facing mounting pressure to deliver on social demands,
the KMT fast-tracked the NHI, implementing it 9 months before the election
(Son, 2001). By February 1996, 92% of the population was insured, with a
big expansion in health care utilization (Chiang, 1997).
Civil Liberties and Political Openness
An alternative perspective is that direct popular engagement with politicians
is more effective at engendering responsiveness than electoral pressure
(Cleary, 2007; Verba, Schlozman, & Brady, 1995). Protests, strikes, personal
appeals, and civil society movements all motivate governments by providing
information on policy demands and threatening to develop into electoral or
violent challenges if left unaddressed. In turn, the ability of citizens to effectively
pressure the government depends on a number of political factors,
often termed the “political opportunity structure” (Kitschelt, 1986). I focus
on two such factors: individual civil liberties and the openness of the political
space to rival groups. Although democracies provide the freest environments
by far, EA regimes are at least freer than closed autocracies and thus motivate
their leaders to provide more extensive public goods.
First, protected rights to speech and association are critical to popular
pressure.11 Here, the evidence is clear that EA regimes lie about midway
between closed autocracies and democracies, using either the Freedom House
(2010) rating of civil liberties or the Cingranelli–Richards (CIRI) data set’s
rating of freedom of speech (Cingranelli & Richards, 2010; see Online
Appendix Figure A1.) The freedom advantage of EA over closed autocracy is
confirmed in the empirical section, which further shows that legislatures and
parties by themselves are negatively related to civil liberties.
Second, political openness gives room to rival organizations that can pressure
the ruling party or help to provide social services themselves (Lake &
Baum, 2001; Gerring et al., 2012). By definition, EA regimes allow opposition
parties, and they tend to also tolerate outside groups like unions, nongovernmental
organizations (NGOs), and civil society movements, albeit
begrudgingly. Political openness can particularly influence development outcomes,
as popular challenges often focus on the inadequate delivery of public
services. In 1970s Brazil, for instance, an ideational movement within the
state bureaucracy known as the sanitaristas coalesced around the goal of
decentralizing and modernizing public health care (Falleti, 2009). In Russia,
civil society groups such as Health Care for Children have organized around
public health grievances, prompting a US$900 million government initiative
to improve health care delivery (Englund, 2011).
Miller	 1537
Governmental Capacity
It is not enough for leaders to want to improve citizens’ lives—they must
have the capacity to do so. A government’s ability to translate policy goals
into outcomes encompasses a range of political qualities, including bureaucratic
capacity, the rule of law, corruption, and territorial control by the state.
Whereas democratic systems necessitate a variety of institutions that can
effectively implement policies (Adserà et al., 2003; Humphreys & Bates,
2005), closed autocracies often exercise power through personal ties, military
hierarchies, or ruling families. In particular, closed regimes often invest little
in professionalized bureaucracies, which are costly and potentially threatening.
As a result, their ability to deliver public services may be limited, even
when so motivated.
In contrast, EA regimes establish a similar set of formal institutions as
democracies. Even when manipulated, they contribute to bureaucratic development,
specialization, and information-sharing, promoting governmental
effectiveness in the long run (Charron & Lapuente, 2011). Looking at
Malaysia, Indonesia, and the Philippines, Slater (2008) concludes that autocratic
elections can spur institutional capacity by forcing regimes to develop
competent parties and extend state control to marginal populations. EA may
also help to select more skilled and technocratically competent leaders, who
must rise through a party hierarchy (or found it) and win contested elections
(Svolik, 2012). Other autocrats rule by virtue of birth or military leadership,
which has little connection to governing ability.
Finally, EA regimes have an advantage in that autocracies are typically
less constrained in implementing their policy goals. Democratic leaders face
strong incentives for social reform but can be stymied by powerful interest
groups (such as unions and bureaucracies) and legislative gridlock (Brown &
Hunter, 2004; Nelson, 2007; Olson, 1984). In contrast, ruling parties in EA
regimes usually dominate the legislature and face limited opposition from
within the public sector (Levitsky & Way, 2010; Magaloni, 2006). Thus, EA
regimes advantageously combine electoral incentives with political
centralization.
Determining the Causal Effect of Autocratic
Elections
The Endogeneity Problem
The central problem with testing the effect of EA is the endogeneity of regime
type. Elections are adopted by autocrats who simultaneously determine
1538	 Comparative Political Studies 48(12)
governing strategies and policies. A variety of factors could mutually influence
these decisions. For instance, strong opposition movements may lead autocrats
to accede to elections and policy concessions. Simple correlations cannot therefore
determine the causal effects of autocratic institutions. Unfortunately, most
work in this area has ignored the endogeneity problem, with Gandhi (2008b) a
notable exception. Although the problem also applies to democracy, it is less
severe given that democracy is typically not chosen by the same rulers who
determine policies. Endogeneity concerns are partly addressed here by testing
regime history, which is driven by institutions up to 60 years in the past, lessening
the confounding from near-term political factors.
IVs provide a fuller approach to the endogeneity issue. IVs are used to
demonstrate that an endogenous variable X causes variation in an outcome Y.
To recover a causal effect, we use a set of instruments Z that must satisfy two
conditions: (a) They must be sufficiently predictive of X and (b) each instrument
must satisfy an exclusion restriction whereby it only influences Y
through its effect on X (net of any controls). The second condition, often
ignored in empirical work, is critical: Only if we can substantively support
the claim that Z does not directly influence Y can we infer the causal
effect of X.
In at least three studies, Gandhi (2008a, 2008b; Kim & Gandhi, 2010) uses
IVs to account for the endogeneity of autocratic legislatures. However, as
noted in Pepinsky (2014), the choice of instruments is problematic, as none
clearly satisfy an exclusion restriction.12 I now turn to an original IV strategy
that more plausibly meets the exclusion restrictions.
The IV Strategy: Diffusion and Inheritance of Autocratic
Elections
This study uses two sets of instruments for EA. Both are derived from theoretical
reasons that regimes hold contested elections, independent of their
general cooptation strategies: international diffusion and institutional inheritance.
First, countries are known to be more likely to adopt and sustain
democracy if higher fractions of their region and neighborhood are democratic
(Gleditsch & Ward, 2006; Starr, 1991). I find the same diffusion effect
for EA, implying that the regional and neighborhood prevalence of EA and
democracy can serve as exogenous instruments for EA (Miller, 2014). This
parallels a similar strategy in Acemoglu, Naidu, Restrepo, and Robinson
(2014), which uses regional diffusion to instrument for democracy.
Why are autocracies more likely to adopt elections when nearby countries
include them? Most simply, surrounding regime types proxy for region-specific
Miller	 1539
international pressures (Levitsky & Way, 2010). Furthermore, there are at least
four reasons that EA and democratic neighbors directly influence EA adoption:
learning and emulation by autocratic leaders (Simmons, Dobbin, & Garrett,
2006), an absence of support for similar neighboring regimes from powerful
closed autocracies (Ambrosio, 2010; Levitsky & Way, 2010), increased popular
pressure for elections when citizens witness them in neighboring countries
(Bratton & van de Walle, 1997; Gleditsch & Ward, 2006), and a desire by autocrats
to avoid looking like illiberal outliers (Whitehead, 1996). For instance,
Julius Nyerere instituted multipartyism in Tanzania based on a belief that the
wave of liberalizations in early-90s sub-Saharan Africa “would inevitably catalyze
pressures for similar changes in Tanzania” (Hoffman & Robinson, 2009, p.
125). Based on this theoretical setup, I include four instruments: the fraction of
democracies and EA regimes in each country’s region (excluding the country
itself) and among its neighbors.13
Second, I leverage the inheritance of EA from previous rulers. Multiparty
competition is very sticky, even after a change of leadership. When an autocratic
executive loses power, the new ruler retains multiparty elections 93%
of the time. As Pepinsky (2014) notes, the number of parties inherited from
the previous regime is the most convincing instrument used in Gandhi
(2008b). Jensen et al. (2014) use an identical instrument. Similarly, I use two
dummies for EA under the previous leader and the previous autocratic
regime.14 When testing regime type history, I instead use weighted histories
of the six variables as instruments.
As detailed below, diagnostic tests clearly indicate that these variables
satisfy the two requirements for instruments. The first stages of the IV models
show that they are highly predictive of EA and its history, well exceeding
standard benchmarks for strong instruments.15 In addition, I use the limitedinformation
maximum likelihood (LIML) IV estimator, which is more robust
to weak instruments than two-stage least squares (2SLS; Stock & Yogo,
2005).
The exclusion restrictions are also likely to be satisfied. First, it is
improbable that external regime types directly influence development outcomes.
A possible alternative causal channel is through policy diffusion,
whereby external countries’ regime types predict their policies and they
diffuse to the country’s own policies. To account for this possibility, all
models control for the regional average of the dependent variable. This
effectively blocks the causal pathway through policy diffusion (see Pearl,
2009 and Online Appendix Figure A2), as well as many other potential
confounders. I also control for aid to account for direct intervention. Thus,
for the exclusion restrictions to fail, there must be an omitted factor that
predicts a country’s development outcomes and its neighbors’regime types,
1540	 Comparative Political Studies 48(12)
but not it’s neighbors’ development outcomes, which is unlikely.16 The case
for EA inheritance is even simpler. As discussed in Jensen et al. (2014),
instrumenting with inherited institutions eliminates the confounding due to
leaders who establish contested elections and may also pursue distinctive
policy strategies.17
Second, given the multiple instruments, overidentification tests can further
support the exclusion restrictions. These tests calculate whether the
residuals from the outcome equation are correlated with the instruments. If
so, this is evidence that the instruments violate the exclusion restrictions. For
all models, the overidentification tests support the validity of the six
instruments.18
Although caution is warranted for any IV strategy, this represents the most
thoroughly supported IV approach to testing autocratic institutions, both theoretically
and diagnostically. The choice of instruments is also guided by the
judgments of Pepinsky (2014), Jensen et al. (2014), and Acemoglu et al.
(2014). Furthermore, the findings are highly robust to different choices of
instruments. The online appendix shows the results for infant mortality and
literacy after alternatively dropping the EA inheritance, regional, and neighbor
instruments, as well as dropping each of the six instruments individually.
For regime history, 18 of 20 tests are significant (at the .10 level).19 Finally,
the results hold across different samples and IV techniques, and consistently
match the results testing regime history without IVs.
Empirical Approach and Data
Dependent Variables
For outcome variables, I focus on four areas of human development: health,
education, gender equality, and basic freedoms. I address infant mortality in
the greatest detail, as it is an ideal indicator of inequality, development, and
state effectiveness (Gerring et al., 2012; Ross, 2006). I then turn to two
closely related measures: the mortality of children under 5 and overall life
expectancy. For education outcomes, I look at literacy and school enrollment,
as well as the gender balance in both these variables. Unless noted otherwise,
the measures are taken from World Bank (2011).
All of these variables are directly affected by public policies and indicate
responsive governance and general social welfare. Furthermore, they are
well-represented in existing work on democracy, facilitating comparisons
with this established literature. I focus on outcomes rather than spending for
two reasons. First, public spending measures are often unreliable in autocracies.
What goes on the books as social spending may in reality be diverted to
Miller	 1541
patronage. Second, regimes vary greatly in their capacity to translate spending
into outcomes, which are of course what we ultimately care about.
I also test four measures of political rights, two concerning civil liberties,
one women’s political rights, and the last an indicator of physical repression
by the state. Besides their normative importance, political freedoms are critical
to human development and economic productivity. Furthermore, the
results on civil liberties can be compared against Gandhi (2008b) and Conrad
(2011). Summary statistics are shown in Online Appendix Table A1.
Definitions of Regime Types
Democracy is measured using Boix et al.’s (2013) dichotomous coding,
which requires competitive elections and a minimal level of suffrage.
Although highly correlated with other measures of democracy, this coding is
advantageous in that it explicitly differentiates democracies from EA regimes
based on the freedom and fairness of elections.
EA regimes are defined as autocracies in which multiple political parties
exist and legally compete in legislative elections (from Cheibub et al., 2010).
Thus, they tolerate organized opposition and provide citizens a regular, legal
route to pressure the government. About 90% of these regimes experienced a
full legislative election within the previous 5 years (using Hyde & Marinov,
2012).20 This definition has the advantage of concreteness, as it is based on a
formal legal requirement. In contrast, concepts like competitiveness are
worth testing, but are more subjective and will suffer from reverse causation
if development outcomes influence electoral behavior.
Empirical Setup
I test four distinct panel models for each outcome variable Y. As a baseline, I
first run ordinary least squares (OLS) with dummy variables for EA and
democracy (lagged by 1 year):
	 Y EA D R Yit it it it t it+ + += + + + + + +1 0 1 2 3 1 1α α α α α γ ε( ) ,4 itX 	(1)
where EAit and Dit are indicators of EA and democracy for country i in year t.
Closed autocracy is the omitted category. R(·) stands for the regional average
(excluding the country i), Xit is a set of control variables, the γt are year fixed
effects, and ε is an error term.
Although useful, this approach cannot demonstrate the causal effect of
regime type. The second model thus instruments for EA using four measures
of external regime types and two of institutional inheritance. Democracy is
1542	 Comparative Political Studies 48(12)
assumed to be exogenous, but violations of this should not affect inference on
EA. The first-stage equation is thus the following:
	
EA R EA R D N EA N D
R Y
it it it it it
it
= + + + +
+ ++
β β β β β
β β
0 1 2 3 4
5 1
( ) ( ) ( ) ( )
( ) 66
7
EA PreviousLeader
EA PreviousRegime t it
( )
( ) ,+ + + +β β γ µ8 itX
	(2)
where N(·) stands for the neighbor average and µ is an error term. The IV
models are calculated using the ivreg2 command in Stata (C. F. Baum,
Schaffer, & Stillman, 2010). I use the LIML form of the IV, which has attractive
robustness properties (Stock & Yogo, 2005). I also check the results
using 2SLS and the generalized method of moments (GMM)IV estimator.
The third and fourth models test the cumulative, historical effects of
regime types, mirroring the approach in Gerring et al. (2012). For each country,
I calculate the weighted average of each regime type back to 1946. As in
Gerring et al., I apply a 1% annual depreciation to the weight. In contrast, I
normalize the weighted history to the same scale as an average, so that the
three measures sum to 1. For instance, EA History is measured as,
	
EAHistory
EA
it
i t
= ≥
−
≥
∑
∑
0 99
0 99
0
0
.
.
,
,
τ
τ
τ
τ
τ 	(3)
and similarly for Democracy History. This approach captures long-term
experience, but unlike a stock variable, avoids conflating it with the time
period and years of independence. The third model type replaces the regime
dummies in equation (1) with the history measures. The fourth, which I consider
the benchmark model, instruments for EA History using weighted histories
of the instruments.
In the main results, the sample is limited to 158 countries from 1960 to
2007, although this varies by dependent variable. The main models use robust
standard errors clustered by country. As a robustness check, I use DriscollKraay
standard errors, which account for multiple lags of serial correlation
and contemporaneous correlation across units.
Control Variables
For each outcome Y, the models control for the regional average of Y (excluding
the country itself) in the same year. This accounts for distinct regional
characteristics, as well as shocks specific to time and region, such as the diffusion
of medical innovations.
Miller	 1543
The models include a common set of further control variables, which are
lagged by 1 year. First, I account for Foreign Aid (official development assistance
as a percentage of gross national income, from World Bank, 2011).
While obviously influencing outcomes like infant mortality, aid is often tied
to political reform and so represents a potential confounder.
Second, I control for five economic variables: logged Gross Domestic
Product (GDP) per capita (in real 2000 dollars, from Haber & Menaldo,
2011; World Bank, 2011), Economic Growth (the percentage change in
GDP/capita), Resource Dependence (fuel and metal revenues as a percentage
of GDP, from Haber & Menaldo, 2011), Economic Inequality (Gini,
from Galbraith & Kum, 2003; United Nations University–World Institute
for Development Economic Research, 2005; World Bank, 2011), and a
Communist dummy. Government resources and the level and distribution of
income strongly condition human development. Haggard and Kaufman
(2008) show that Communist regimes have highly distinct policy
platforms.21
Third, I control for several socioeconomic characteristics that affect the
ease of delivering public services: Population (logged, from Heston,
Summers, & Aten, 2011), Urbanization (the percentage living in cities of
100,000+, from Correlates of War Project, 2010), and Ethnolinguistic
Fractionalization (ELF, from Roeder, 2001). Fourth, because domestic conflict
can disrupt government services and impede human development, I control
for Political Violence (a 0-10 rating of domestic civil and ethnic violence,
from Marshall, 2010).
Finally, to account for variation across time, I include year fixed effects. I
do not include country fixed effects, which problematically negate the influence
of the 57 countries that do not vary by regime type. Whereas the purpose
of country fixed effects is to account for country-level omitted variables, I
rely here on instruments and regime history to obtain causal estimates.
However, the online appendix shows that the infant mortality results are
robust to including fixed or random effects (Online Appendix Table A5). In
other checks, I control for region fixed effects and the Geddes autocracy categories
(military, party-based, and personalist).
Empirical Results
I now present the main results, with full regressions shown for infant mortality
and the key findings shown for the remaining outcomes. I then discuss
several robustness checks for infant mortality and literacy, and finally compare
the effect of EA with legislatures and parties for several outcomes.
1544	 Comparative Political Studies 48(12)
Main Results
Infant mortality. Table 1 displays results predicting Infant Mortality (per
1,000 live births). Models 1 and 2 test EA and Democracy, while Models 3
and 4 test their historical averages. Models 2 and 4 instrument for EA and EA
History, respectively.22 Again, Model 4 is the benchmark model. All four
models show superior outcomes under both EA and democracy, with all eight
coefficients significantly negative for infant mortality. The results are particularly
strong in the IV models, implying a large causal effect of EA on
health. According to Model 4, a long-term EA regime has about 27 fewer
infant deaths per 1000 live births compared with closed autocracy. This is
equivalent to the estimated effect of shifting from Vietnam to Sweden on
average income. For democracy, the effect is nearly identical.
The table also displays the two primary checks for the validity of the
instruments. The weak identification test addresses whether the instruments
explain a sufficient amount of variance in the endogenous variable (EA or EA
History). The specific test shown is the Kleibergen–Paap F statistic (measured
against the Stock–Yogo critical values), where the common rule of
thumb is a threshold of 10 to be considered valid. In both models, the instruments
exceed this threshold. The overidentification test (the Hansen J statistic)
calculates whether the instruments are correlated with the error term in
the outcome equation, violating the exclusion restrictions. A rejection of the
null questions the validity of the instruments, but the test is insignificant in
both models. The two checks are virtually identical for the other dependent
variables because the only variation in the first stage is the regional DV
average.
Results for the control variables are largely expected. Higher income is
strongly negative for infant mortality, whereas a higher regional average is
positive. Consistent with Haggard and Kaufman (2008), Communist regimes
feature fewer infant deaths. More populated and less urbanized countries
have higher rates, reflecting a difficulty in delivering public health services.
Surprisingly, no relationship with inequality or resource dependence is
evident.
Other health outcomes.  Table 2 summarizes results for two other health outcomes
and four education outcomes. The four model types are identical to
those in Table 1, but results for the controls are omitted. Each pair of coefficients
(for EA and Democracy) represents a separate regression. A total of 24
are shown in Table 2. Again, the third and fourth models test EA History and
Democracy History.
Miller	 1545
Table 1.  IV and OLS Regressions Predicting Infant Mortality.
OLS IV OLS IV
DV = Infant mortality (1) (2) (3) (4)
EA −7.319* −18.253*  
  (−2.15) (−2.07)  
Democracy −13.089*** −18.561**  
  (−3.62) (−3.19)  
EA history −13.982* −26.612**
  (−2.57) (−2.77)
Democracy history −20.902** −26.835***
  (−3.23) (−3.55)
Infant mortality 0.418*** 0.425*** 0.412*** 0.425***
  (Regional average) (4.93) (4.81) (4.91) (4.82)
Foreign aid 0.387** 0.371* 0.290* 0.233†
  (2.76) (2.48) (2.38) (1.86)
GDP/capita (ln) −15.132*** −15.175*** −13.776*** −13.346***
  (−7.29) (−7.08) (−6.68) (−5.87)
Economic growth −0.141* −0.114† −0.125† −0.099
  (−2.00) (−1.67) (−1.77) (−1.50)
Economic inequality 0.125 0.087 0.117 0.112
  (0.93) (0.63) (0.86) (0.77)
Resource dependence 0.161 0.133 0.116 0.081
  (1.30) (1.03) (0.88) (0.77)
Communist −14.991*** −12.805*** −17.037*** −15.079**
  (−4.14) (−3.62) (−3.96) (−3.16)
Urbanization −0.181* −0.154† −0.200* −0.177*
  (−2.28) (−1.92) (−2.58) (−2.25)
ELF 3.107 3.871 4.857 5.024
  (0.48) (0.58) (0.74) (0.75)
Population (ln) 2.643** 2.480* 2.459** 2.260*
  (2.95) (2.54) (2.75) (2.34)
Political violence −0.140 −0.120 0.113 0.125
  (−0.19) (−0.16) (0.18) (0.19)
Year dummies? Y Y Y Y
n 4,435 4,237 4,455 4,257
Countries 151 144 152 145
Adjusted R2 .798 .790 .805 .798
Weak identification (F) 30.99*** 12.95***
Overidentification (χ2) 10.28 7.50
The table displays models predicting infant mortality from regime type. Model 1 uses OLS to compare EA
regimes and democracies with closed autocracies. Model 2 instruments for EA. Model 3 uses OLS to test
histories of EA and democracy. Model 4 instruments for EA History. In each model, both EA and democracy
are significantly negative for infant mortality. Years are 1960 to 2007. t statistics (based on robust standard
errors clustered by country) are shown in parentheses. IV = instrumental variables; OLS = ordinary least
squares; DV = dependent variable; EA = electoral authoritarianism; ELF = ethnolinguistic fractionalization.
†p < .10. *p < .05. **p < .01. ***p < .001.
1546	 Comparative Political Studies 48(12)
Table 2.  IV and OLS Regressions for Health and Education Outcomes.
Regime Level Regime History
  OLS IV OLS IV
  (1) (2) (3) (4)
Under-5 Mortality
 EA −14.03* −35.82* −26.52** −53.51***
  (−2.43) (−2.51) (−2.78) (−3.49)
 Democracy −20.56** −31.25** −34.36** −47.10***
  (−3.34) (−3.18) (−3.06) (−3.50)
Life Expectancy
 EA 1.30† 2.32 2.31* 6.12**
  (1.90) (1.17) (2.07) (3.00)
 Democracy 2.80*** 3.06* 4.41** 6.18***
  (3.61) (2.57) (3.07) (3.66)
Literacy
 EA 2.51 12.30* 10.12* 24.78**
  (0.99) (2.09) (2.47) (2.62)
 Democracy 6.53* 12.02** 15.03** 23.64**
  (2.32) (2.66) (3.06) (2.95)
Schooling
 EA 2.06 9.52 7.76* 20.77**
  (0.97) (1.60) (2.10) (2.76)
 Democracy 3.95† 7.94† 8.60* 14.91**
  (1.68) (1.91) (2.20) (2.78)
Literacy Equality
 EA −0.01 0.22* 0.09* 0.23*
  (−0.23) (2.37) (2.28) (2.29)
 Democracy 0.01 0.17* 0.11* 0.20*
  (0.51) (2.33) (2.51) (2.36)
Schooling Equality
 EA 0.04* 0.16** 0.10** 0.18*
  (2.03) (3.27) (2.80) (2.38)
 Democracy 0.05* 0.12** 0.10* 0.14*
  (2.34) (3.09) (2.57) (2.34)
The table summarizes models predicting health and education outcomes from regime type. The six
dependent variables are listed in the first column. Four models are then shown for each dependent
variable. Model 1 uses OLS to compare EA regimes and democracies to closed autocracies.
Model 2 instruments for EA. Model 3 uses OLS to test histories of EA and democracy. Model 4
instruments for EA History. The standard controls are included, but not shown. t statistics (based
on robust standard errors clustered by country) are shown in parentheses. IV = Instrumental
variables; OLS = ordinary least squares; EA = electoral authoritarianism.
†p < .10. *p < .05. **p < .01. ***p < .001.
Miller	 1547
Under-5 Mortality (per 1,000 live births) is a slightly broader measure of
basic health compared with infant mortality. Life Expectancy (in years) is
broader still, but heavily influenced by child mortality. For both variables,
EA and democracy are strongly associated with better outcomes (although
EA misses significance at the .05 level for Life Expectancy in Models 1-2).
According to Model 4, a long-term EA regime produces 53.5 fewer child
deaths per 1,000 births and 6.1 additional years of life compared with closed
autocracy. For democracy, the effect is 47 fewer deaths and 6.2 additional
years of life.
Education.  Table 2 also features four measures of education. The first is
Literacy (as a percentage of adults, from Banks, 1976; Norris, 2008;
World Bank, 2011), which is positively related to democracy and EA in
both IV tests. The effects are particularly strong for the historical measures,
which is sensible given that literacy needs to build up over time
within a population. A similar pattern is found for Schooling, the percentage
of age-appropriate children enrolled in primary and secondary education
(called the gross enrollment ratio). From Model 4, long-term EA
regimes increase literacy by 25% and schooling by 21%, each about one
standard deviation.
Finally, I test Literacy Equality and Schooling Equality, respectively the
gender ratio of literacy (UNESCO Institute for Statistics, 2012) and Schooling.
Higher values indicate more equal outcomes across genders. EA and democracy
are significantly positive for both using the historical measures and in
the IV tests. This makes sense given that the equal vote women receive in
modern electoral regimes substantially boosts their political power relative to
closed autocracy.
In sum, EA and democracy yield better outcomes for all seven measures
of health and education. In particular, both are significant (at the .05 level) in
all 14 regime history models, validating the theoretical approach of Gerring
et al. (2012). Supporting a causal interpretation, 12 of 14 IV estimates of EA
are significant. Furthermore, a sensitivity analysis of the non-IV tests (shown
in the online appendix) suggests that omitted variables are unlikely to account
for the significant EA History findings.23
Political rights.  The four dependent variables listed in Table 3 measure basic
freedoms and political rights. All are scaled to run from 0 to 1, with 1 highest
in freedom. Civil Liberties is from Freedom House (2010) and Free Speech
from Cingranelli and Richards (2010). For both, democracies are much freer
than closed autocracies, whereas EA regimes lie in between. However, EA
History is only weakly related in the IV tests. This may be because long-lived
1548	 Comparative Political Studies 48(12)
democracies experience a consolidation process of democratic deepening,
whereas EA regimes do not—liberties always remain at the mercy of the ruling
party’s interests.
The Women’s Rights variable (Cingranelli & Richards, 2010) relates
positively to EA and democracy and, unlike for civil liberties, results are
similar in magnitude. Finally, EA is unrelated to Physical Integrity, an
Table 3.  IV and OLS Regressions Predicting Political Rights.
Regime Level Regime History
  OLS IV OLS IV
  (1) (2) (3) (4)
Civil Liberties
 EA 0.11*** 0.20*** 0.13*** 0.15*
  (5.33) (4.00) (3.64) (2.33)
 Democracy 0.38*** 0.43*** 0.38*** 0.39***
  (15.57) (12.24) (10.41) (8.19)
Free Speech
 EA 0.12*** 0.18* 0.10† 0.11
  (3.41) (2.29) (1.92) (1.32)
 Democracy 0.36*** 0.41*** 0.36*** 0.35***
  (10.13) (7.13) (6.58) (5.31)
Women’s Rights
 EA 0.06** 0.06 0.05 0.14*
  (2.66) (0.99) (1.65) (2.13)
 Democracy 0.07** 0.08* 0.11** 0.18***
  (3.10) (1.98) (3.06) (3.55)
Physical Integrity
 EA 0.00 0.03 −0.01 0.03
  (0.07) (0.48) (−0.35) (0.45)
 Democracy 0.11*** 0.13** 0.11** 0.14**
  (4.54) (3.01) (2.89) (3.15)
The table summarizes models predicting basic freedoms and women’s rights from regime
type. The four dependent variables are listed in the first column. Four models are then shown
for each dependent variable. Model 1 uses OLS to compare EA regimes and democracies to
closed autocracies. Model 2 instruments for EA. Model 3 uses OLS to test histories of EA
and democracy. Model 4 instruments for EA History. The standard controls are included, but
not shown. t statistics (based on robust standard errors clustered by country) are shown
in parentheses. IV = Instrumental variables; OLS = ordinary least squares; EA = electoral
authoritarianism.
†p < .10. *p < .05. **p < .01. ***p < .001.
Miller	 1549
index of freedom from torture, killings, and physical repression by the state
(Cingranelli & Richards, 2010), whereas democracy is strongly positive in
all four tests. This presents an interesting contrast with EA’s positive relationship
with civil liberties. A possible reason is that EA regimes feature a
high degree of contention relative to closed autocracies. Thus, their legal
recognition of civil liberties may be balanced by their needs to suppress
opposition activity (Vreeland, 2008). In comparison, closed regimes facing
quiescent populations do not need to resort to widespread physical
repression.
Robustness Checks
Table 4 summarizes eight sets of robustness checks for the IV results on
infant mortality and literacy, with the baseline results included for comparison.
The table shows the IV estimates for EA (Models 1 and 3) and EA History
(Models 2 and 4). Each coefficient represents a separate regression.As clearly
seen, the regime history results are highly robust, remaining significant at the
.05 level in all 16 models. For regime level, results remain significant in 11
of 16 models, narrowly missing in another 3.
The first check includes two alterations taking into account possible spatial
dynamics. First, I control for the neighbor average of the outcome in
addition to the regional average. Second, I use Driscoll-Kraay standard
errors, which are robust to three lags of serial correlation and arbitrary correlations
across countries. EA’s significance increases in all four tests.
The second check controls for the autocracy categories coded in Geddes
et al. (2014). For Models 1 and 3, I add dummies for military and partybased
regimes, with personalist dictatorships and monarchies as the base
category. For Models 2 and 4, I instead test their historical averages. The
Geddes categories are unrelated to both outcomes (see Online Appendix
Table A7).
In the next two checks, I replace the LIML IV estimator with 2SLS and a
GMM estimator, with little effect on the findings. The fifth check adds region
dummies. In the sixth check, I limit the sample to autocracies. The level models
necessarily omit Democracy, but the history models still include
Democracy History. In the seventh check, I remove cases of state failure
(from Marshall & Jaggers, 2010) because these are over-represented among
closed autocracies. In the final check, I remove Economic Inequality and
Foreign Aid as controls, as they have the most missing data. To compare with
Table 1, Model 2’s sample size increases to 5,645 (with 150 countries). For
the literacy models, the sample is expanded to 1946-2007. The IV estimates
for EA become slightly stronger.
1550	 Comparative Political Studies 48(12)
Other Autocratic Institutions
How does EA compare with other institutions that have become widespread
in autocracies? Studies of autocracy have focused the greatest attention on
legislatures and parties, but there is a shortfall of work explicitly comparing
these different institutions.24 I therefore compare EA with legislatures and
parties (measured from Cheibub et al., 2010) in the absence of multiparty
competition. Because EA incorporates all three elements, it is not yet clear
which is really doing the work. As a robustness check, I also test the effect of
Table 4.  IV Robustness Checks for Infant Mortality and Literacy.
Infant Mortality Literacy
  Level History Level History
  (1) (2) (3) (4)
Baseline −18.25* −26.61** 12.30* 24.78**
  (−2.07) (−2.77) (2.09) (2.62)
Spatial dynamics −11.89*** −20.96*** 5.17** 13.58***
  (−4.50) (−11.12) (2.78) (4.95)
Geddes types
added 
−18.20† −27.76** 13.83* 29.12*
(−1.83) (−2.60) (2.08) (2.47)
2SLS −15.83* −24.53** 9.02* 18.22**
  (−2.18) (−2.86) (2.15) (2.96)
GMM-IV −16.12* −22.32** 5.00 11.52*
  (−2.22) (−2.71) (1.35) (1.97)
Region FE −16.79* −21.14* 7.23 18.13*
  (−2.00) (−2.03) (1.00) (1.98)
Autocracies only −17.35† −33.36** 13.37† 42.59**
  (−1.91) (−3.07) (1.77) (3.04)
No state failure −18.44* −26.02** 11.82* 24.21**
  (−2.06) (−2.72) (1.99) (2.58)
Inequality/aid
omitted 
−22.64** −33.66*** 17.86** 29.73***
(−2.93) (−4.05) (3.16) (4.55)
The table summarizes several robustness checks for the IV models predicting infant mortality
and literacy. Only the results for EA and EA History are shown. The first column lists the
model checks, which are described in the text. Models 1 and 3 instrument for EA and test the
effect of regime level. Models 2 and 4 instrument for EA History and test the effect of regime
experience. t statistics (based on robust standard errors clustered by country) are shown in
parentheses. IV = instrumental variables; EA = electoral authoritarianism; 2SLS = two-stage
least squares; GMM = generalized method of moments; FE = fixed effects.
†p < .10. *p < .05. **p < .01. ***p < .001.
Miller	 1551
a Multiparty Legislature, which differs from EA in additionally requiring that
multiple parties are seated in the legislature. About 80% of EA regimes satisfy
this requirement.25 I expect the two measures of multiparty contestation
to have similar effects.
To make the comparisons, I adapt the third model type, namely, a non-IV
test of regime type histories. Ideally, an IV setup would be used, but I lack a
reliable set of instruments for legislatures and parties.26 For each outcome
variable, I run four separate regressions, testing historical averages of the
four alternative institutions. Each regression includes the standard controls
and Democracy History.
Figure 2 graphically displays the estimated coefficients (with 95% confidence
intervals) predicting Infant Mortality, Literacy, Literacy Equality, and
Civil Liberties. As discussed, EA History produces superior outcomes for all
four measures. Results are virtually identical for Multiparty Legislature.
However, the effects of legislatures and parties by themselves are opposite in
direction for all four outcomes, albeit inconsistently significant. Thus, legislatures
and parties without multiparty competition are associated with higher
infant mortality and lower civil liberties.
This result conflicts with theories, such as Gandhi’s (2008b), that legislatures
in isolation can induce political concessions. Rather, legislatures and
parties by themselves may only serve to increase regime power by co-opting
elites who would otherwise pressure the government. Multiparty elections, in
contrast, motivate regimes to promote citizen welfare. This calls into question
many of the empirical findings on legislatures and parties, which may be
driven by the large share of regimes with these institutions that additionally
feature multiparty competition.
Conclusion
Autocratic elections matter. Relative to closed autocracy, EA regimes perform
better on health, education, gender equality, and civil liberties. Furthermore,
the IV models identify these effects as causal and the regime history models
find a particularly strong cumulative effect of EA on health and education. In
contrast, legislatures and parties in the absence of multiparty competition display
slightly negative outcomes. This points to the acceptance of multiparty
elections as the most politically significant feature of autocracy.
The results have a number of important implications. First, the findings
contribute to the political economy of development literature. A continuing
theme in this field is the importance of institutions but without a clear picture
of which institutions matter. Greater attention should be given to autocratic
electoral institutions, especially their role in generating accountability and
1552	 Comparative Political Studies 48(12)
Figure 2.  Effects of autocratic institutions on human development.
The figure compares the effect of electoral authoritarianism (EA) with other autocratic
institutions. The dots are regression coefficients (shown with 95% confidence intervals)
estimating the long-term effects of different institutions on four development outcomes. EA
and legislatures with multiparty representation lead to better outcomes for all four measures.
Legislatures and parties in the absence of multiparty elections yield negative effects.
Miller	 1553
promoting specific political models of development. For instance, the general
pattern found for EA closely corresponds to the East Asian developmental
model associated with Taiwan, Singapore, and South Korea. Like EAregimes
generally, the “Asian Tigers” featured large public investments in education
and health, middle levels of civil liberties, and low redistribution (Haggard &
Kaufman, 2008).27 As the Asian Tigers were EA regimes during their key
periods of development, this may suggest a natural affinity between EA and
this particular economic model.
Second, several scholars have questioned the welfare effects of democracy
promotion given that it often stalls at EA (Goldsmith, 2008; Lust-Okar,
2006; Regan & Bell, 2010). In contrast, this article implies that the international
encouragement of elections is a net positive for citizen welfare, even
when the end result is short of democracy. Unexpectedly, EA regimes perform
as well as democracy in the IV tests for health and education. On balance,
however, the results still support democracy as the most advantageous
system, as it maintains a clear superiority on civil liberties and physical
repression. In fact, the results demonstrate a lack of tension between political
freedom and government performance. Thus, the encouragement of contested
elections should continue with added vigor, favoring democracy as the ultimate
goal but still recognizing EA as clearly superior to closed autocracy.
Finally, the results provide further evidence that scholars should move
beyond the democracy-autocracy dichotomy when predicting political outcomes.
Lumping autocracies together as one large group overlook a great
deal of variation due to autocratic institutions. In particular, future work can
extend this article’s IV strategy for EA to other outcomes, such as economic
growth and conflict behavior. It is critical that we further our understanding
of how autocratic regimes choose policies and how elections influence these
decisions. Given that the majority of the developing world remains under
autocracy, continued insight into how autocratic politics can improve human
development bears on the welfare of a large part of the world’s population.
Acknowledgment
Thanks for helpful comments to Editors Ben Ansell and David Samuels, several anonymous
reviewers, Jeff Colgan, Sarah Bush, Michael McKoy, Macartan Humphreys,
and audience members at Midwest 2012, ISA 2012, APSA 2013, Australian National
University, and University of Melbourne.
Declaration of Conflicting Interests
The author declared no potential conflicts of interest with respect to the research,
authorship, and/or publication of this article.
1554	 Comparative Political Studies 48(12)
Funding
The author received no financial support for the research, authorship, and/or publication
of this article.
Notes
 1.	 For more thorough overviews of this literature, see Haggard and Kaufman
(2008), Carbone (2009), and Halperin, Siegle, and Weinstein (2010).
 2.	 In empirical testing, Gandhi (2008b) uses a three-valued measure where 0 =
no legislature, 1 = a single-party legislature, and 2 = a multiparty legislature.
However, her theory focuses on the existence of a legislature.
  3.	 Scholars have also related autocratic institutions to democratization (Brownlee,
2009; Geddes, 1999; Wright & Escribà-Folch, 2012), torture (Vreeland, 2008),
terrorism (Aksoy, Carter, & Wright, 2012), civil war onset (Regan & Bell, 2010),
and conflict behavior (Kinne & Marinov, 2013; Lai & Slater, 2006; Weeks, 2008).
  4.	 Several studies analyze countries at middle values of the Polity democracy score,
often called anocracies (Blaydes & Kayser, 2011; Regan & Bell, 2010), but this
lumps together highly disparate regimes. For instance, only 42% of the anocracies
in Blaydes and Kayser (2011) are EA regimes. Bueno de Mesquita, Smith,
Siverson, and Morrow’s (2003) selectorate theory argues that larger winning
coalitions predict public goods provision. However, it’s unclear whether an EA
regime’s winning coalition is large (the electoral majority) or small (the party’s
inner circle).
  5.	 Of course, this partly reflects the smaller margins of party control within democracies.
The data are taken from Keefer (2010) and cover 1975-2010.
  6.	 The same logic that Bueno de Mesquita et al. (2003) use to connect democracies
to public goods—their cost efficiency relative to individual payoffs for large
electorates—also applies to EA regimes.
  7.	 For instance, Blaydes (2011) finds that opposition-supporting areas in Mubarak’s
Egypt were less likely to receive connections to public sewer and water lines.
  8.	 Reversing the democratic pattern, the poor are often more likely to vote in autocratic
elections and support the ruling party (Blaydes, 2011; Magaloni, 2006).
 9.	 The accountability of EA regimes should not be overestimated, either. These
regimes routinely violate norms of free and fair competition and use state
resources and coercion to retain power. However, the same violations are only
multiplied in closed autocracies.
10.	 This was in conjunction with an increased emphasis on primary education and a
general reorientation of spending toward average citizens (Kosack, 2014).
11.	 Wigley and Akkoyunlu-Wigley (2011) also argue that rights protections promote
health outcomes directly (i.e., not through policy) by increasing autonomy, selfesteem,
and social capital. Also see Chandra and Rudra (2015) on public deliberation
in autocracies.
12.	 Kim and Gandhi (2010), for instance, use seven instruments for an autocratic legislature:
dummies for military and civilian dictatorship, resource exports, size of
Miller	 1555
the manufacturing workforce, counts of leader changes and purges, and the global
share of democracies. They then use the instrumented likelihood of a legislature to
predict workers’ wages and strike activity. However, resource wealth and the size
of the manufacturing workforce could clearly affect wages directly. Military dictatorship
and political instability also directly influence policies. The world’s share
of democracies most plausibly satisfies an exclusion restriction, but may simply be
picking up the effect of time (which is omitted from the outcome equation).
13.	 Tests were also run using trade partners’regime types (weighted by dyadic trade,
from Barbieri & Keshk, 2012), but these were not found to be consistently related
to a country’s regime type. Neighbors are countries that share a land border or are
separated by no more than 24 miles of water (Correlates of War Project, 2007).
14.	 Data on leader changes come from Goemans, Gleditsch, and Chiozza (2009).
The previous regime is defined as that existing before the most recent regime
breakdown in the Geddes, Wright, and Frantz (2014) data.
15.	 Regional regime types also predict transitions to EA (Miller, 2014).
16.	 One possibility is that autocracies feel increased popular pressure from neighboring
regime types and respond with policy concessions, possibly as an alternative
to liberalizing (Desai, Olofsgård, & Yousef, 2008). If so, then we should
find a direct effect of local regime types within the set of countries that remain
closed autocracies. However, none of the four diffusion variables are predictive
of infant mortality in this sample, either in combination or singly (see Online
Appendix Table A3).
17.	 Past institutions could affect past outcome values, which then influence current
values, but because this assumes that the causal link is present, it does not
directly question the findings.
18.	 A related check is to test whether the instruments predict the outcome after controlling
for the endogenous variable. If not, this suggests the exclusion restrictions
hold. The instruments are indeed non-predictive: For the infant mortality
tests, none of the six instruments are significant when tested individually, nor are
they jointly significant (using an F-test).
19.	 See OnlineAppendix TableA4.All 40 total tests are of consistent sign.As should
be expected, the weakest results come after dropping the most predictive instruments,
the neighbor variables.
20.	 Recoding the remaining 10% as closed autocracies leaves the results unchanged.
21.	 Results are unchanged after also adding a post-Communist dummy.
22.	 The first stages from the IV models are shown in Online Appendix Table A2.
23.	 Following Altonji, Elder, and Taber (2005), this analysis calculates how strongly
omitted variables would need to predict EA to explain the findings, then compares
this to how strongly observed variables predict EA. Generally, a ratio of 1
or more implies that the relationship is unlikely to be due to omitted variables.
For EA History, six of the seven tests for health and education are above 1, with
the sole exception at 0.91.
24.	 An exception is work on democratization (Brownlee, 2009; Wright & EscribàFolch,
2012).
1556	 Comparative Political Studies 48(12)
25.	 In the remaining 20%, either the ruling party wins every seat (e.g., Singapore
1968-1983) or the regime is in a period between legalizing competition and seating
the election winners.
26.	 I investigated using regional and neighbor averages of these variables, but the
resulting instruments were too weak to be considered valid.
27.	 As shown in Online Appendix Table A8, EA regimes are indistinguishable from
closed autocracies on income redistribution. In addition, this article’s results
hold when the Tigers are removed from the sample (Online Appendix Table A7).
Thus, the similarities are not being driven by the Tigers themselves.
Supplemental Material
The online appendix is available at http://cps.sagepub.com/supplemental
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Author Biography
Michael K. Miller is an assistant professor of political science and international
affairs at George Washington University. His research focuses on democratization
and the role that autocratic elections play in regime change and policy setting. He has
published articles in the American Journal of Political Science, British Journal of
Political Science, Journal of Conflict Resolution, and elsewhere.