Regimes of the World (RoW): Opening New Avenues for the Comparative Study of Political Regimes

Abstract

Classifying political regimes has never been more difficult. Most contemporary regimes hold de-jure multiparty elections with universal suffrage. In some countries, elections ensure that political rulers are—at least somewhat—accountable to the electorate whereas in others they are a mere window dressing exercise for authoritarian politics. Hence, regime types need to be distinguished based on the de-facto implementation of democratic institutions and processes. Using V-Dem data, we propose with Regimes of the World (RoW) such an operationalization of four important regime types—closed and electoral autocracies; electoral and liberal democracies—with vast coverage (almost all countries from 1900 to 2016). We also contribute a solution to a fundamental weakness of extant typologies: The unknown extent of misclassification due to uncertainty from measurement error. V-Dem’s measures of uncertainty (Bayesian highest posterior densities) allow us to be the first to provide a regime typology that distinguishes cases classified with a high degree of certainty from those with “upper” and “lower” bounds in each category. Finally, a comparison of disagreements with extant datasets (7%–12% of the country-years), demonstrates that the RoW classification is more conservative, classifying regimes with electoral manipulation and infringements of the political freedoms more frequently as electoral autocracies, suggesting that it better captures the opaqueness of contemporary autocracies.

Full text

Politics and Governance (ISSN: 2183–2463)
2018, Volume 6, Issue 1, Pages 60–77
DOI: 10.17645/pag.v6i1.1214
Article
Regimes of the World (RoW): Opening New Avenues for the Comparative
Study of Political Regimes
Anna Lührmann *, Marcus Tannenberg and Staffan I. Lindberg
V-Dem Institute, Department of Political Science, University of Gothenburg, 405 30 Gothenburg, Sweden;
E-Mails: anna.luehrmann@v-dem.net (A.L.), marcus.tannenberg@gu.se (M.T.), xlista@gu.se (S.I.L.)
* Corresponding author
Submitted: 3 October 2017 | Accepted: 12 January 2018 | Published: 19 March 2018
Abstract
Classifying political regimes has never been more difficult. Most contemporary regimes hold de-jure multiparty elections
with universal suffrage. In some countries, elections ensure that political rulers are—at least somewhat—accountable to
the electorate whereas in others they are a mere window dressing exercise for authoritarian politics. Hence, regime types
need to be distinguished based on the de-facto implementation of democratic institutions and processes. Using V-Dem
data, we propose with Regimes of the World (RoW) such an operationalization of four important regime types—closed
and electoral autocracies; electoral and liberal democracies—with vast coverage (almost all countries from 1900 to 2016).
We also contribute a solution to a fundamental weakness of extant typologies: The unknown extent of misclassification
due to uncertainty from measurement error. V-Dem’s measures of uncertainty (Bayesian highest posterior densities) allow
us to be the first to provide a regime typology that distinguishes cases classified with a high degree of certainty from those
with “upper” and “lower” bounds in each category. Finally, a comparison of disagreements with extant datasets (7%–12%
of the country-years), demonstrates that the RoW classification is more conservative, classifying regimes with electoral
manipulation and infringements of the political freedoms more frequently as electoral autocracies, suggesting that it bet-
ter captures the opaqueness of contemporary autocracies.
Keywords
autocracy; democracy; democratization; regime; typology
Issue
This article is part of the issue “Why Choice Matters: Revisiting and Comparing Measures of Democracy”, edited by Heiko
Giebler (WZB Berlin Social Science Center, Germany), Saskia P. Ruth (German Institute of Global and Area Studies, Ger-
many), and Dag Tanneberg (University of Potsdam, Germany).
© 2018 by the authors; licensee Cogitatio (Lisbon, Portugal). This article is licensed under a Creative Commons Attribu-
tion 4.0 International License (CC BY).
1. Introduction
Classifying political regimes has never been more dif-
ficult. Most regimes in the world hold de-jure multi-
party elections with universal suffrage. In some coun-
tries, elections ensure that political rulers are—at least
somewhat—accountable to the electorate whereas in
others they are a mere window dressing exercise for au-
thoritarian politics. Therefore, we need to base regime
classification on the de-facto implementation of demo-
cratic institutions and processes. This is key to being
able to make a meaningful distinction between elec-
toral democracies and electoral autocracies. Such data
is provided by the Varieties of Democracy (V-Dem)
Project, which covers 177 countries from 1900 to 2016
(Coppedge et al., 2017a, 2017b). While V-Dem primar-
ily provides interval measures, many important research
questions require crisp regime measures. For instance,
categorical measures of regimes have been used in stud-
ies on democracy aid effectiveness (Lührmann, McMann,
& Van Ham, 2017), inquiries of democratic diffusion
(Gleditsch & Ward, 2006), backsliding (Erdmann, 2011),
Politics and Governance, 2018, Volume 6, Issue 1, Pages 60–77 60

sequencing (Wang et al., 2017), characteristics of au-
thoritarian regimes (Schedler, 2013), and regime survival
(e.g. Bernhard, Hicken, Reenock, & Lindberg, 2015; Prze-
worski, Alvarez, Cheibub, & Limongi, 2000; Svolik, 2008).
We use the V-Dem data to classify countries into four
regime categories. In closed autocracies, the chief ex-
ecutive is either not subjected to elections or there is
no meaningful, de-facto competition in elections. Elec-
toral autocracies hold de-facto multiparty elections for
the chief executive, but they fall short of democratic
standards due to significant irregularities, limitations on
party competition or other violations of Dahl’s institu-
tional requisites for democracies. To be counted as elec-
toral democracies, countries not only have to hold de-
facto free and fair and multiparty elections, but also—
based on Robert Dahl’s famous articulation of “Pol-
yarchy” as electoral democracy (Coppedge, Lindberg,
Skaaning, & Teorell, 2016; Dahl, 1971, 1998)—achieve a
sufficient level of institutional guarantees of democracy
such as freedom of association, suffrage, clean elections,
an elected executive, and freedom of expression. A lib-
eral democracy is, in addition, characterized by its hav-
ing effective legislative and judicial oversight of the exec-
utive as well as protection of individual liberties and the
rule of law.
Although the typology is widely accepted (e.g. Dia-
mond, 2002; Rössler & Howard, 2009; Schedler, 2013),
comprehensive, longitudinal measures have not been
available until now. Regimes of the World (RoW) closes
this gap by classifying virtually all country-years from
1900 to today based on this typology. In addition, we pro-
vide an innovative method to address a key weakness
in extant typologies: identifying ambiguous cases close
to the thresholds between regime types using V-Dem’s
measures of uncertainty. This additional information can
be integrated into quantitative analyses, for instance by
allowing scholars to conduct robustness checks which ex-
clude more ambiguous cases.
Section two discusses prior approaches to regime
types while the third section details the RoW typology.
Section four compares our regime typology to several of
the most frequently used extant measures.
2. Prior Approaches to Drawing the Line between
Regime Types
Longstanding conceptual and methodological discus-
sions include whether democracy is a best understood
as a multidimensional (Coppedge et al., 2011; Dahl,
1971; Vanhanen, 2005), continuous (Bollen & Jackman,
1989; Lindberg, 2006), polychotomous (Collier & Levit-
sky, 1997), or a dichotomous concept (Alvarez, Cheibub,
Limongi, & Przeworski, 1996; Cheibub, Gandhi, & Vree-
land, 2010), as well as debate the precise differentia-
tion between democratic and various types of autocratic
regimes (Geddes, Wright, & Frantz, 2014; Kailitz, 2013;
Wahman, Teorell, & Hadenius, 2013), including the exis-
tence of a “grey zone” (Diamond, 2002). We agree with
Collier and Adcock (1999) that the appropriate type of
regime measure depends on the nature of the research
question at hand. We seek here to provide a robust and
comprehensive regime type measure for research requir-
ing an ordinal or a dichotomous measure.
There are two main approaches to conceptualizing
and crafting dichotomous measures of democracy and
autocracy: as a difference in kind or as a difference in
degree, which are associated with qualitative and quan-
titative approaches to measurement, respectively (Lind-
berg, 2006, pp. 22–27). The in-kind/qualitative approach
typically proceeds in a Sartorian fashion by setting a num-
ber of necessary conditions that a regime must fulfill in
order to be coded as a democracy. For example, that
there are competitive, multiparty elections with suffrage
extended to a certain share of the population. The de-
gree/quantitative strand usually introduces a cut-off on
a continuous measure of democracy, coding countries
above the threshold as democratic and countries below
the threshold as being autocratic. In the following, we
provide details regarding how six of the most influential
datasets on regimes distinguish between democracies
and autocracies.
2.1. In-Kind/Qualitative Approaches
Cheibub et al. (2010) apply three criteria to distin-
guish democracies from autocracies: uncertainty, irre-
versibility, and repeatability.1Operationally, they iden-
tify democracies as regimes in which there are, first,
more than one legal party; second, a legislature elected
by popular elections, and a chief executive that is either
directly, or indirectly popularly elected; and finally, an al-
ternation of power must have occurred under the same
electoral rules that brought the incumbent into office.
While these clear and parsimonious coding rules mini-
mize the need for subjective judgments, they also come
at a cost. Two of these criteria raise concerns of con-
ceptual validity. The mere existence of two legal parties
hardly guarantees contestation, as understood in estab-
lished democratic theory (Dahl, 1971), and the alterna-
tion rule leads to both type I and type II errors. First,
as Wahman (2014) shows, it underestimates the num-
ber of democracies since incumbents often enjoy an elec-
toral advantage even in established democracies. Sec-
ond, even manipulated and un-democratic elections are
sometimes lost, which leads to the alternation rule over-
estimating the number of autocracies (Wahman, 2014,
p. 222). These errors have consequences. For example,
Knutsen and Wig (2015) demonstrate that the alterna-
tion rule leads to the underestimation of democracy’s ef-
fect on economic growth.
Geddes et al. (2014) sort all cases into either the
democratic or autocratic bin (before proceeding to clas-
1Their “Democracy and Dictatorship” dataset builds on earlier work by an overlapping group of authors (Cheibub, Przeworski, Limongi Neto, & Alvarez,
1996; Przeworski et al., 2000).
Politics and Governance, 2018, Volume 6, Issue 1, Pages 60–77 61

sify sub-categories of the latter). They stipulate the fol-
lowing coding rules: a case is coded as democratic if the
executive achieves power through “reasonably fair com-
petitive” direct or indirect elections with suffrage exceed-
ing at least 10% of the population (Geddes, Wright, &
Frantz, 2013, p. 6). This requires a fair amount of judg-
ment by the coder. For example, relying on reports from
election observers to determine if an election was rea-
sonably “fair and competitive” can be problematic since
such organizations lack shared standards (Kelley, 2009).
It is not clear what a “competitive” election or “large”
party is by Geddes et al. (2014)’s standards (see Ged-
des et al., 2013, p. 6), nor is it clear how Geddes et al.
(2014) estimate the size of parties which did not enjoy
legal rights (Wahman et al., 2013).
Boix, Miller and Rosato (2013) provide a dichoto-
mous measure of democracy/autocracy from 1800 to
2010. Similar to Cheibub et al. (2010) and Geddes et al.
(2014), Boix et al. (2013) rely on a set of necessary condi-
tions. For a country to be coded as democratic, the ex-
ecutive must either be directly or indirectly elected in
“popular” elections and the legislature in “free and fair”
elections. They also require that a majority of the male
population has the right to vote. Boix et al. (2013) suffers
from a similar weakness as Geddes et al. (2014)—they
asses the freedom and fairness of elections without min-
imizing bias due to the potentially erroneous judgment
of the coder.
2.2. Degree/Quantitative Approaches
Other scholars apply a threshold on a continuous mea-
sure to distinguish between political regimes (Lindberg,
2016; Schedler, 2013; Wahman et al., 2013). The most
apparent difficulty with this approach is deciding where
to draw the line between democracies and autocra-
cies, which is inevitably, an arbitrary decision (Bogaards,
2012). Even for the most commonly used large-N data
sets—Freedom House and Polity—there is no consensus
in the literature on where to draw the line. Bogaards
(2012) identifies at least 14 different ways to use Free-
dom House ratings and at least 18 different ways to use
the Polity scores to classify democracies.
Freedom House itself uses its political rights and civil
liberty scores to label countries as “free”, “partly free”,
and “not free” (Freedom House, 2017). However, this
three-level ordinal scale evades the question of which
“partly free” country is a democracy and which not. Fur-
thermore, it neglects any necessary conditions—such
as free and fair elections—that are commonly found
in the literature. Similarly, the Polity project (Marshall,
Gurr, & Jaggers, 2014) provides various detailed assess-
ments of different aspects of regime quality, but refrain
from identifying an unambiguous cut-off point between
democracy and autocracy. Polity suggests using the com-
bined Polity score to cut the regime spectrum into three
parts: autocracies (−10 to −6), democracies (6 to 10),
and anocracies, with anocracies being between the first
two categories.2
Wahman et al. (2013) identify the cut-off point on a
combined Freedom House and Polity scale that best rep-
resents five qualitative democracy measures, such as the
ones we discussed above. They proceed by estimating
the mean score on the combined scale for the year be-
fore democratic breakdown and the year after transition,
as coded by the five measures. They then use the grand
mean of seven of these years as their empirical cut-off
point for democracy, while advising users to run robust-
ness checks using both the 6.5 and the 7.5 levels.
Scholars addressing the whole regime spectrum have
come to distinguish, typically, between closed and elec-
toral autocracies on one hand and liberal and electoral
democracies on the other hand (e.g. Diamond, 2002;
Rössler & Howard, 2009; Schedler, 2013) which has be-
come one of the most prolific typologies in the discipline,
as well as in the policy-practitioners’ world. Neverthe-
less, we lack comprehensive, longitudinal measures of
this four-fold regime typology.3Below, we suggest a way
to fill this gap while simultaneously avoiding the weak-
nesses of the current measures which have been out-
lined above.
3. The RoW Typology
Following this brief review of some of the extant regime
typologies, we endeavor to classify regimes into four
categories: closed autocracy, electoral autocracy, elec-
toral democracy and liberal democracy (Table 1). First,
we separate along the democratic and the autocratic
regime spectrum and then develop the democratic and
autocratic subtypes.4In a minimalist, Schumpeterian
sense, democracies are regimes that hold de-jure mul-
tiparty elections. However, many would agree with Pas-
tor (1999, p. 123) that “the essence of democratic gov-
ernment is accountability”. Such accountability can only
evolve if incumbents fear retribution at the ballot box
(Mechkova, Lührmann, & Lindberg, 2017a), and to this
end, mere de-jure multiparty elections are not enough
(e.g., Levitsky & Way, 2010; Schedler, 2013). We claim
that Dahl’s theory of polyarchy (1971, 1998) provides the
most comprehensive and most widely accepted theory
of what distinguishes a democracy based on six (1998,
p. 85—originally p. 8 in his 1971 book) institutional guar-
antees (elected officials, free and fair elections, freedom
of expression, alternative sources of information, associ-
ational autonomy, and inclusive citizenship). This concep-
tion requires not only free and fair elections but also the
freedoms that make them meaningful, and thus avoids
the electoral fallacy (Diamond, 2002; Karl, 1986). This al-
lows for demarcation between electoral autocracies and
2See http://www.systemicpeace.org/polityproject.html
3Typically, scholars use data from sources such as Freedom House and/or the Database on Political Institutions, which only starts in the 1970s.
4This strategy follows common advice for concept formation (e.g., Collier & Adcock, 1999, pp. 548–549; Goertz, 2006; Sartori, 1970).
Politics and Governance, 2018, Volume 6, Issue 1, Pages 60–77 62

Table 1. Regime classification.
Closed Autocracy Electoral Autocracy Electoral Democracy Liberal Democracy
No de-facto multiparty, or free and fair elections, or De-facto multiparty, free and fair elections, and
Dahl’s institutional prerequisites not minimally fulfilled Dahl’s institutional prerequisites minimally fulfilled
No multiparty elections De-jure multiparty elections The rule of law, or The rule of law, and
for the chief executive for the chief executive liberal principles not liberal principles
or the legislature and the legislature satisfied satisfied
democracies, unlike minimalist definitions. In short, in
democracies rulers are de-facto accountable to citizens
through periodic elections and in autocracies they are
not.5Therefore, we approach de-facto multiparty and
free and fair elections as necessary, qualitative criteria
for labelling a regime as a democracy.
We distinguish between electoral democracies that
only achieve the basic criteria above, and liberal democ-
racies. We focus on this distinction because it is the most
common within the democratic regime spectrum (e.g. Di-
amond, 1999, 2002; Merkel, 2004; Munck, 2009). In ad-
dition to fulfilling the criteria for electoral democracy, lib-
eral democracies are characterized by an additional set
of individual and minority rights beyond the electoral
sphere, which protect against the “tyranny of the ma-
jority”; thus having limits on government is intrinsic to
democracy itself (e.g. Dahl, 1956; Hamilton, Madison, &
Jay, 1787/2009; cf. Coppedge, Gerring, Lindberg, Skaan-
ing, & Teorell, 2017d, p. 21; Lindberg, Coppedge, Gerring,
& Teorell, 2014). This is in Dahl’s words “Madisonian”
democracy (Dahl, 1956, p. 4). Core components thus in-
clude legislative and judicial oversight over the executive
providing checks and balances, as well as the protection
of individual liberties, including access to, and equality
before, the law. In particular, the rule of law is a funda-
mental prerequisite for the implementation of the liberal
principle as it ensures that decisions are implemented
(Merkel, 2004).
Autocracies are regimes where rulers are not ac-
countable to citizens by Dahl’s standards. The key differ-
ences along the authoritarian spectrum are whether the
office of the chief executive and seats in the national leg-
islature are subject to direct or indirect multiparty elec-
tions (Schedler, 2013, p. 2). In closed autocracies, the
chief executive and the legislature are either not subject
to elections, or there is no de-facto competition in elec-
tions such as in one-party regimes. Regimes with elec-
tions that do not affect who is the chief executive (even
if somewhat competitive) also fall into this category (fol-
lowing Brownlee, 2009; Donno, 2013; Rössler & Howard,
2009, p. 112).
In electoral autocracies, on the other hand, the chief
executive is dependent on a legislature that is itself
elected in de-jure multiparty elections (in parliamentary
systems), directly elected alongside a separately elected
legislature (in presidential systems), or a combination
of both (in semi-presidential systems). In an electoral
autocracy, these institutions are de-facto undermined
such that electoral accountability is evaded (Diamond,
2002; Gandhi & Lust-Okar, 2009; Levitsky & Way, 2010;
Schedler, 2002, 2013). They thus fall short of demo-
cratic standards due to significant irregularities, limita-
tions on party competition, or other violations of Dahl’s
institutional requisites. This conceptualization builds on
Schedler’s influential work on electoral authoritarianism
(2002, 2006, 2013) and the notion of competitive author-
itarianism developed by Levitsky and Way (2010).
3.1. Operationalization with V-Dem Data
We operationalize the RoW regime typology using data
from Varieties of Democracy (V-Dem).6Version 7.1 cov-
ers 178 countries from 1900 to 2016 (Coppedge et
al., 2017a, 2017b, 2017c; Marquardt & Pemstein, 2017;
Pemstein et al., 2017). Figure 1 portrays the step-
wise decision rules. To qualify as an (electoral) democ-
racy, regimes must fulfil three necessary conditions.
(1) De-facto multiparty elections as indicated by a score
above 2 on the V-Dem indicator for multiparty elections
(v2elmulpar_osp); (2) free and fair elections where mis-
takes and irregularities did not affect the outcome, as in-
dicated by a score above 2 on the respective V-Dem indi-
cator (v2elfrfair_osp);7and (3) following Lindberg (2016,
p. 90), a score larger than 0.5 on the V-Dem Electoral
Democracy Index (EDI, v2x_polyarchy) which explicitly
measures Dahl’s institutional de-facto guarantees, based
on 41 indicators (Coppedge et al., 2016, 2017a).8The in-
dex runs from 0 (not democratic) to 1 (fully democratic).
These coding rules strike a balance between two prin-
ciples in operationalization: substitutability and neces-
sity. In line with Coppedge et al. (2011), we treat Dahl’s
list of institutions as partly substitutable. A score larger
5This reflects the electoral principle of democracy (Coppedge et al., 2016, p. 3).
6This operationalization will be included in the V-Dem dataset version 8 under the variable name “v2x_regime“ (to be released in Spring 2018).
7The V-Dem measurement model converts expert scores to interval-level point estimates (Pemstein et al., 2017). We use a version of the data in which
these interval-level estimates were converted to the original 0–4 scale, which is indicated by the suffix _osp.
8The aggregation rule for the EDI allows for one strong sub-component to partially compensate for weaknesses in others, but also penalizes countries
weak in one sub-component according to the “weakest link” argument. Thus, the index is formed in one half by the weighted average of its component
indices and in the other half by the multiplication of those indices (Coppedge et al., 2016, 2017a).
Politics and Governance, 2018, Volume 6, Issue 1, Pages 60–77 63

Mulparty elecons
v2elmulpar_osp > 2
All regimes
Autocracy
Closed Autocracy Electoral Autocracy
Electoral Democracy Liberal Democracy
Democracy
Free and fair elecons
v2elfrefair_osp > 2
Yes
Yes
Mulparty elecons execuve
v2elmulpar_ex_osp > 1
Mulparty elecons legislature
v2elmulpar_leg_osp > 1
Access to jusce men/women
v2clacjstm/w_ops > 3
Transparent law enforcement
v2cmslw_ops > 3
Liberal Component Index cut-off
v2x_liberal > .8
Electoral Democracy Index cut-off
v2x_polyarchy > .5
YesNo
No
No
Yes
Yes
Yes
Yes
Yes
No
No No
No
No
Figure 1. Coding schema for the RoW typologies (for descriptions of variables see Coppedge et al., 2017a).
than 0.5 on the EDI, demonstrates that the balance of
potential weaknesses in one area is partly compensated
for by strengths in other areas to such a degree that
the regime may be classified as being more democratic
than not.9Yet, in the conceptualization above, given the
aggregation of 41 indicators, it remains possible that a
country could reach a level above 0.5 on the index while
still lacking two critical aspects: de-facto multiparty elec-
tions and the ability of such an election result to be re-
sistant to the effect of irregularities and unintentional
mistakes. We approach de-facto free and fair and mul-
tiparty elections as necessary conditions. Hence, even
while these two indicators are also part of the EDI among
the 39 other indicators, we ensure that the—admittedly
arbitrary—cut-off point on a continuous scale does not
lead to the misclassification of regimes as democracies
by combining it with the two key qualitative democ-
racy indicators.
Among dictatorships identified by their failure to
meet one or more of the criteria of democracies, elec-
toral autocracies are distinguished from closed dictator-
ships in that they subject the chief executive to elections
9For examples underscoring the empirical validity of these cut-off points, see the detailed discussion in section 4.
Politics and Governance, 2018, Volume 6, Issue 1, Pages 60–77 64

at least de-jure multiparty competition as indicated by a
score above 1 on the applicable V-Dem multiparty elec-
tions indicator (v2elmulpar_osp; see Appendix 1).
What distinguishes electoral and liberal democra-
cies is that the latter guarantee the three key as-
pects of the liberal dimension of democracy discussed
above. We operationalize this notion with three nec-
essary criteria. First, liberal democracies need to sat-
isfy three qualitative criteria focusing on the ultimate
guarantees of individual liberty: Scores above “3” on
the V-Dem indicators transparent and predictable law
enforcement (v2cltrnslw_osp), and secure and effec-
tive access to justice for men (v2clacjstm_osp) and
women (v2clacjstw_osp).10 While the non-arbitrary en-
forcement of laws is a prerequisite for the implementa-
tion of rules in the first place, access to justice gives in-
dividuals the chance to challenge arbitrary enforcement
patterns (Botero & Ponce, 2011). In order to further guar-
antee that no country is undeservedly classified as a lib-
eral democracy, we require a liberal democracy to over-
all satisfy the liberal principles of respect for personal
liberties and the rule of law, and judicial as well as leg-
islative constraints on the executive, as indicated by a
score above 0.8 on the summary V-Dem Liberal Com-
ponent Index (v2x_liberal).11 Corresponding to the dis-
tinction between democracies and autocracies, the in-
clusion of an aggregated index in the operationalization
rules allows for the substitution of weaknesses in one
area with strength in others. The threshold is naturally
arbitrary but setting it high, at the upper quartile of the
scale, seeks to ensure that the criterion adheres to the
fairly strict demands expressed in the literature in the lib-
eral tradition.
3.2. Accounting for Ambiguity: Lower and Upper Bounds
of Regime Categories
A principal objection leveraged against quantitative ap-
proaches to measuring regime types is that countries
close to thresholds between categories may be misclassi-
fied due to measurement error and uncertainty (e.g. Boix
et al., 2013). However, qualitative approaches face the
same issue (e.g. Alvarez et al., 1996). The only difference
is that we do not know how close or far away a case if
from the threshold since they are based on assessments
of—often individual—coders with unknown thresholds
and unreported uncertainty. The thresholds in quantita-
tive approaches are often more transparent and the con-
sequences of varying them can be tested (Lindberg, 2016,
p. 81), but without confidence intervals around point es-
timates, we still do not know which cases may be misclas-
sified regardless of threshold.
We suggest a major advance on current categoriza-
tions in this regard by incorporating into the RoW ty-
pology “grey-zone” categories of ambiguously classified
cases as indicated by confidence intervals from the un-
derlying Bayesian aggregation methods.12 The V-Dem
dataset provides not only point estimates for indices and
variables but also demarcates the interval in which V-
Dem’s custom-designed Bayesian item-response theory
measurement model places 68% of the probability mass
for each country-year score. These are calculated slightly
different at the indicator and index-level but provide the
rough equivalent of one standard deviation confidence
interval on either side of the points estimates.13
We use these intervals to identify cases that are close
to the thresholds between categories, those which are
ambiguously classified. If the V-Dem Bayesian highest
posterior density interval for an indicator or an index
used for the categorization into the four main regime
types, overlaps with the threshold of an adjacent cate-
gory, then the case is classified as ambiguous.
For example, Macedonia’s score on the EDI was 0.53
in 2016, slightly above the threshold for electoral democ-
racy (0.5). The values for the two qualitative criteria for
elections (multiparty, 3.9; and free and fair, 3.0) are also
above the thresholds electoral democracy. However, the
lower bound of the EDI score (v2x_polyarchy_codelow)
for Macedonia is 0.48 and thus falls within the range
of electoral autocracy. Hence, in the RoW typology, we
label the country as being “Electoral Democracy Lower
Bound”, to reflect this ambiguity. Our classification is cor-
roborated by credible reports that freedom of expres-
sion has been restricted in Macedonia in recent years.14
10 In an earlier version of this article (and in the V-Dem Data Set v7), we did not include these additional qualitative criteria for liberal democracies. As
a consequence, some countries with dubious respect for liberal principles met the threshold for liberal democracies (e.g. Hungary and Tunisia in 2016;
the United States prior to the improvements in civil rights in 1968). In order to make our measure of liberal democracy a more ambitious reflection of
democratic “completeness”—to borrow from Welzel (2013, p. 255)—we opted to include additional criteria.
11 This index gives the average of following indices on a scale from 0 (not at all satisfied) to 1 (satisfied): equality before the law and individual liberties
(v2xcl_rol), judicial constraints on the executive (v2x_jucon), and legislative constraints on the executive (v2xlg_legcon) (Coppedge et al., 2017a, p. 47).
12 This operationalization is included in the V-Dem Data Set v8 under the variable name “v2x_regime_amb“ (to be released in Spring 2018). We are
grateful to Valeriya Mechkova for suggesting this approach to using the Bayesian highest posterior density intervals.
13 For each indicator, V-Dem provides upper and lower bound estimates, which represent 68% of the highest posterior densities (distribution mass), i.e.,
a range of most probable values for a given observation. The intervals increase with the degree of ambiguity in the raw, expert-coded data. At the
indicator-level, mainly three factors influence the size of the intervals: high levels of disagreement between expert coders, a low number of coders,
and the presence of coders with relatively low estimated reliability (i.e., high stochastic error variance). V-Dem uses Bayesian Factor Analysis (BFAs
implemented with the R package MCMCpack) to aggregate indicators to mid-level indices, such as the Clean Election Index. In the BFA framework, the
size of the area covered by the 68 highest posterior densities of mid-level indices increases in size if underlying indicators show low levels of correlation.
The BFAs are run over 900 posterior draws from the indicators. As a result, uncertainty about indicators also influences the size of the interval in which
the modeling places 68% of the probability mass of the mid-level indices. Similar logic applies for top-level indices (such as the Electoral Democracy
Index, and the Liberal Component Index), which combine several mid-level indices (Marquardt & Pemstein, 2017; Pemstein et al., 2017).
14 On the recent developments in Macedonia see BBC (http://www.bbc.com/news/world-europe-36031417) and the EuropeanDigital Rights Association
(https://edri.org/huge-protest-against-corruption-surveillance-in-macedonia).
Politics and Governance, 2018, Volume 6, Issue 1, Pages 60–77 65

Similarly, Poland lost its status as a liberal democracy
in 2013 when the point estimate for one of the quali-
tative indicators (the transparent law enforcement indi-
cator; v2cltrnslw_osp) dropped below the threshold of
3.0, while the upper bound remains above the threshold.
It is therefore classified as an “Electoral Democracy Up-
per Bound”.
The RoW typology thus represents a more trans-
parent ordinal measure of regime types than prior ap-
proaches, reflecting the estimates of uncertainty of the
underlying data calculated by state-of-the-art Bayesian
models. We argue that this is a major advance on extant
regime typologies—quantitative or qualitative—which
do not report how certain we should be about each classi-
fication. This brings together conceptual validity and pre-
cision with transparent and systematic incorporation of
uncertainty with four “pure” regime types and six upper
and lower bound regime categories.
4. Opening New Perspectives in Regime Studies
RoW also provides us with unique opportunities to
answer new questions. For example, we can analyse
changes over time with regard to the share of countries
in these grey zones between the “pure” regime types. Fig-
ure 2 demonstrates that almost all countries were unam-
biguously classified at the beginning of the last century
(light-grey line on top of the graph). The level of ambi-
guity (black dashed line) started increasing from around
1960 and peaked during the 1990s—coinciding with the
height of the third wave of democratization identified by
Huntington (1992). By 2016, almost 30% of all countries
were in one of the ambiguous categories, and 12% fell in
the critical grey zone between democracy and autocracy.
This is a significant result in itself.
There are two but distinct developments driving this
trend. First, an increasing number of countries are in the
ambiguous regime categories because they have de-jure
democratic institutions, but simultaneously undermine
their effectiveness. The share of unambiguous regimes
dropped from above 94% in 1950 to 70% in 2016. Sec-
ond, the average distance between the upper and lower
bounds of the V-Dem indicators and indices have in-
creased in recent decades, reflecting among other things
greater disagreement among coders. This also suggests
that it has become harder to unambiguously assess coun-
tries’ states of affairs, even on the very discreet issues
that V-Dem ask country experts to rate. The world is be-
coming opaquer in terms of regimes.
Figure 3 shows the development over time of the
RoW regime types (tinted colors indicate ambiguous cat-
egories). Our data allow us to show how the number
of regimes in the ambiguous categories has increased
over recent decades. Several commentators have also
recently expressed concerns about potential backslid-
ing among liberal democracies. This is captured in the
RoW measure with the number of liberal democracies
declining in the last few years. Furthermore, we can iden-
tify two pronounced developments associated with the
second half of the third wave of democratization, from
around 1990. First, the two intermediate categories be-
tween electoral democracies and autocracies have both
grown wider. Second, the number of closed autocra-
cies declined sharply. Electoral autocracies and electoral
democracies have replaced this regime type. An impor-
tant implication of these two developments is that an
increasingly greater number of countries risk being mis-
classified by extant measures, thus opening the spectre
of biased, or even misleading results. RoW can help us
solve that problem.
1900
Ambiguous Unambiguous Ambiguous between Democracy and Autocracy
0%
20%
40%
60%
80%
100%
1910
Percet of all Countries
1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020
Figure 2. The development of regime ambiguity in the world from 1900 to today.
Politics and Governance, 2018, Volume 6, Issue 1, Pages 60–77 66

1900 1910 1920 1930
Liberal Democracy
RoW Regime Type
1940 1950 1960 1970 1980 1990 2000 2010 2020
0%
20%
40%
60%
80%
100%
Percet of all Countries
Liberal Dem. Lower Bound
Closed Aut. Upper Bound
Closed Autocracy
Electoral Dem. Upper Bound
Electoral Democracy
Electoral Dem. Lower Bound
Electoral Aut. Upper Bound
Electoral Autocracy
Electoral Aut. Lower Bound
Figure 3. Regimes of the World (RoW) 1900–2016. Source: Coppedge et al. (2017b).
In addition to such descriptive analysis, we recom-
mend the use of ambiguous categories for robustness
checks in quantitative analysis. For instance, in demo-
cratic survival analyses it makes sense to repeat the
analysis varying the in- and exclusion of the ambigu-
ous cases from both the democratic and autocratic
regime categories.
5. Comparing RoW to Dichotomous Measures of
Democracy
The distinction between democracy and autocracy is ar-
guably the most important aspect of a regime typology.
The RoW typology lends itself also to research that re-
quires a dichotomous measure since both the two cat-
egories of democracy and autocracy can be collapsed.
The lower bounds of (electoral) democracy and the up-
per bounds of (electoral) autocracy still apply and can
be used in combination with the pure regime types in
the same fashion as discussed above. In this section, we
compare RoW’s distinction between democracy and au-
tocracy to the most relevant extant measures, namely
those provided by Boix et al. (2013), Cheibub et al. (2010),
and Geddes et al. (2014); and Freedom House (Freedom
House, 2017), Polity (Marshall et al., 2014), and Wahman
et al. (2013).
RoW Regime Type
Electoral Democracy
Liberal Democracy
Closed Autocracy
Electoral Autocracy
Figure 4. Regimes of the World (RoW) 2016. Source: Coppedge et al. (2017b).
Politics and Governance, 2018, Volume 6, Issue 1, Pages 60–77 67

The purpose of this appraisal is two-fold: First, it
helps to assess the convergent validity of the RoW mea-
sure, one of the most commonly used strategies for new
regime type measures (Adcock & Collier, 2001, p. 540).
Second, and in line with the spirit of this thematic is-
sue, we seek to make clear what the empirical conse-
quences of the measurement choices are for users of the
RoW typology.
A comparison with extant measures, unfortunately,
means we have to disregard the ambiguous and pure
regime classifications in the RoW measure. Figure 3 first
illustrates the distribution of regime types in the world
in 2016. Most regimes are in the democratic spectrum
(56%): 62 countries qualify as electoral democracies and
35 as liberal democracies (of 174 countries). 56 countries
(32%) are electoral autocracies and 21 (12%) are closed
autocracies. For a complete list see Appendix 2.
Table 2 compares RoW to the most commonly used
measures in the literature. One striking difference is the
coverage of RoW, which is matched only by Boix et al.
(2013) and Polity, in that it includes all countries and
semi-independent territories (including most colonies)
from 1900 until the present, and will continue to be up-
dated annually. Cheibub et al. (2010) and Geddes et al.
(2014) start in 1946, Wahman et al. (2013) in 1970 and
none of them provide data after 2010. While Boix et
al. (2013) starts in 1800, it is not updated so the last
seven years are not covered. Polity has a longer time se-
ries and is updated annually but does not cover semi-
independent countries and territories. The fourth col-
umn shows that the rate of agreement is relatively high,
varying between 88.5% (Cheibub et al., 2010) and 93.1%
(Wahman et al., 2013). Excluding the cases which our ty-
pology qualifies as ambiguous, the level of agreement
varies between 91.7% (Cheibub et al., 2010) and 93.5%
(Geddes et al., 2014). When there is disagreement be-
tween RoW and other measures, our classification tends
to be more conservative and sets a higher bar for what
counts as a democracy, i.e., by classifying certain coun-
tries as autocracies whereas others place them in the
democratic regime spectrum.
The four different panels in Figure 5 display the
RoW count of democracies over time compared with the
other measures. Three other measures have data prior
to 1970—Boix et al. (2013), Cheibub et al. (2010), and
Geddes et al. (2014).
The overlap of observations between our RoW mea-
sure with Boix et al. (2013) (11, 262 cases) is the sec-
ond largest, with a rate of agreement on classification
in 90.8% of these observations (Figure 5 [A]). The level
of agreement increases to 93.5% if we exclude observa-
tions that fall into the ambiguous categories according
to RoW. In general, Boix et al. (2013) has a lower thresh-
old for democracy: 84% of disagreements on the clas-
sification of country-years are due to Boix et al. (2013)
classifying them as democracies while they are coded
as autocracies by RoW. For example, Boix et al. (2013)
code Chile between 1909 and 1949 as democratic even
though only 25 to 35% of the adult population were en-
franchized due to a lack of female suffrage. Another ex-
ample is Guatemala, which Boix et al. (2013) and Cheibub
et al. (2010) code as democratic following the general
election in 1958 up until the onset of civil war in 1981.
RoW classifies it as an electoral autocracy. We think the
RoW classification has greater face validity since it cap-
tures the absence of de-facto minimum level of institu-
tional requirements of democracy in this case: Illiterate
women were banned from voting up until 1966 (Organi-
Table 2. Comparison of six dichotomous measures to the RoW democracy threshold.
Country Coverage Country-Year Agree with RoW Autocracy RoW Democracy
Years Overlap with RoW RoW Other Democracy Other Autocracy
RoW 17140 1900–2016
Boix et al. (2013) 16988 1800–2010 11,262 90.8% 7.7% 1.5%
(93.5%) (5.8%) (0.7%)
Polity 16826 1800–2016 11,394 92.1% 5.4% 2.5%
(94.3%) (4.1%) (1.6%)
Cheibub et al. (2010) 19117 1946–2008 18,187 88.5% 8.5% 2.9%
(91.7%) (6.4%) (1.9%)
Geddes et al. (2014) 17956 1946–2010 17,688 90.2% 7.4% 2.4%
(92.8%) (5.7%) (1.4%)
Wahman et al. (2013) 16279 1970-2010 16,277 93.1% 2.8% 4.0%
(96.8%) (1.3%) (1.9%)
Freedom House 16277 1973–2016 16,275 88.8% 1.7% 9.6%
(93.3%) (0.9%) (4.6%)
Note: Numbers in brackets are calculated excluding the cases we identified as ambiguous (see section 2). Source: RoW, Coppedge et al.
(2017b); Boix et al. (2013); Cheibub et al. (2010); Geddes et al. (2014); Freedom House (2017), Polity (Marshall et al., 2014) and Wahman
et al. (2013).
Politics and Governance, 2018, Volume 6, Issue 1, Pages 60–77 68

1970
40
60
80
100
1980
C — Wahman, Teorell and Hadenius
RoW
WTH
Number of Democracies
1990 2000 2010
20
0
40
60
80
100
120
1980
D — Freedom House
RoW
FH (free)
FH (partly + free)
1990 2000 2010
1900
40
20
0
60
80
100
1920
A — Boix, Miller and Rosato
RoW
BMR
Number of Democracies
1940 1960 1980 2010
20
40
60
80
1950 1960
B — Cheibub, Gandhi and Vreeland;
B — Geddes, Wright and Franz
RoW
CGV
GWF
1980 19901970 2000 2010
Figure 5. Visual comparison of other measures to RoW. Note: Each panel is limited to the time period and cases of the
dataset with least coverage.
zation of American States, 2008), and parties faced se-
vere obstacles to establish themselves and to their partic-
ipation in elections. Furthermore, electoral intimidation
was common throughout the period, and civil society or-
ganizations were not free to form or operate. Boix et al.
(2013) also codes Czechoslovakia (1939–1945), Norway,
Belgium, the Netherlands (1940–1945), and Denmark
(1943–1944), as democratic during the years of German
occupation whereas RoW does not. Out of the few Boix
et al. (2013) autocracies that are coded as democracies in
RoW, half are classified as ambiguous cases. Among the
unambiguous democracies, RoW captures the dramatic
shift from an absolute monarchy to democracy that took
place in Bhutan following its first parliamentary elections
in 2007/2008, and coded the country as being demo-
cratic from 2009 onwards. This is in line with case study
evidence (Turner & Tshering, 2014).
Cheibub et al. (2010) provide regime classifications
for 9,117 country-years; 8,187 observations overlap with
RoW, and the rate of agreement is 88.5% (Figure 5 [B]).15
Out of the 933 disagreements, 75% (N =696) are
country-years that Cheibub et al. (2010) code as demo-
cratic and RoW classifies as autocratic. This discrepancy
may be due to Cheibub et al. (2010) using a lower thresh-
old for democracy than RoW. For instance, Cheibub et
al. (2010) classifies Kyrgyzstan (2005–2008) and Armenia
(1995–2008) as democracies whereas the V-Dem expert-
coded de-facto indicators capture severe shortcomings
in terms of the most basic requirements of democracy
such as the freedom and fairness of elections. When
RoW classifies countries as democracies which Cheibub
et al. (2010) codes as autocratic, it is due to Cheibub
et al. (2010)’s controversial alternation rule. For exam-
ple, Botswana, South Africa, and Namibia are autocra-
cies according to Cheibub et al. (2010) for all years cov-
ered, because only one party has been in power since
the introduction of multi-party elections. The V-Dem in-
dicators build on indicators that do not require alterna-
tion in power, leading to their classification as liberal
democracies in the late 1990s. This result is in line with
the conclusions of prominent observers (e.g., Diamond,
1999, pp. ix–xxvi).
The RoW measure covers all but 168 of Geddes et al.
(2014)’s 7,956 observations,16 and out of the overlap-
ping country years, the level of agreement of the two
measures is 90.2% (92.8% excluding ambiguous cases).
15 Cheibub et al. (2010) cover 973 observations that are not in the RoW measure. These are mainly microstates not included in the V-Dem Data set: Lux-
emburg; Andorra, Antigua and Barbuda, Bahamas, Bahrain, Belize; Brunei; Grenada; Kiribati; Lichtenstein; Malta; Marshall Island; Micronesia; Nauru;
Palau; Samoa; San Marino; St. Kitts and Nevis; St. Lucia; St. Vincent and the Grenadines; Tonga; Tuvalu; United Arab Emirates. Additionally, Cheibub
et al. (2010) covers Oman 1970–1999; Cameroon 1961–1963; and Mozambique 1975–1977, which are not included in V-Dem.
16 These are the two small states Luxemburg and United Arab Emirates and individual years in Oman (1946–1999), Cameroon (1961–1963), and Mozam-
bique (1976–1977), which are not included in the V-Dem data.
Politics and Governance, 2018, Volume 6, Issue 1, Pages 60–77 69

The measures diverge in particular prior to the 1970s
and in the early 2000s. Again, when classifying a coun-
try as democratic, RoW is more demanding than Ged-
des et al. (2014) (Figure 5 [B]). For example, Geddes
et al. (2014) code Sierra Leone (1999–2002) as demo-
cratic even though the then ongoing civil war drastically
undermined rules and procedures (Harris, 2014). Simi-
larly, they rate the Central African Republic (1993–2003),
Burundi (2005–2010), and Nepal (1991–2002) as demo-
cratic, whereas V-Dem’s expert-based indicators indicate
severe violations or grave deficiencies in the institutional
requisites of democracy. In contrast, a number of coun-
tries in which V-Dem experts report relatively strong
democratic institutions, both de-jure and de-facto, are
coded as autocracies by Geddes et al. (2014): Botswana
(1967–2010), Burkina Faso (1993–2010), Ghana (1996–
2000), Namibia (1991–2010), and Senegal (1983–2000).
The V-Dem coding is consistent with academic assess-
ments of the state of democracy in Ghana (Abdulai
& Crawford, 2010), Botswana and Namibia (Diamond,
1999), although some observers of Senegal denote the
time period as one of “transition to a fully demo-
cratic state” and prefer to label the country as “semi-
democratic” (Coulon, 1988; Vengroff, 1993, p. 23). RoW
reflects this ambiguity, classifying Senegal as an unam-
biguous democracy only after the improvements follow-
ing the 1993 election.
RoW covers all observations in the Wahman et al.
(2013) data set with the exception of Mozambique from
1975–1977. Out of all measures compared in this article,
Wahman et al. (2013)’s has the highest level of concor-
dance with RoW (Figure 5 [C]; 93.1% or 96.8% exclud-
ing ambiguous cases). Wahman et al. (2013) is based on
the Freedom House and Polity ratings (see discussion in
section 1). When defining only countries that Freedom
House codes “free” as democracies the agreement falls
to 88.8% or 93.3% when excluding the cases classified
as ambiguous in RoW (see Figure 5 [D]). The bulk of the
disagreements stem from countries that we classify as
democracies but that are “partly free” according to Free-
dom House. However, lowering the dichotomous thresh-
old to include all “partly free” countries as democracies
reduces the concordance to 75.5%, indicating that a ma-
jority of countries that Freedom House code as partly
free are coded as autocracies in RoW. Hence, overall the
agreement between the RoW and Wahman et al. (2013)
datasets is greater than when comparing RoW to either
Freedom House or Polity separately.
Polity IV is the data source with the greatest num-
ber of country-years overlapping with RoW (11,394).
Following Marshall et al. (2014)’s suggestion to treat
countries above and equal to 6 on the combined Polity
scale as democracies, classification agreement with RoW
is 92.1%, or 94.3% when excluding ambiguous cases.
Most disagreements are once again due to RoW autoc-
racies being coded as democracies in Polity. For exam-
ple, Polity codes Sweden (1916–1919) and the United
States (1900–1919) as perfect democracies (score 10)
when women were disenfranchised. RoWclassifies these
cases as electoral autocracies. In recent years, Burundi
(2005–2013), Malawi (1994–2013), and Malaysia (2008–
2012) are democracies according to Polity while V-Dem
experts observe severe obstacles to democracy. There
are also disagreements of other sorts. For example,while
Polity codes Suriname as just short of being a democracy
(score of 5) since 1991, V-Dem’s indicators rate the coun-
try as a liberal democracy for the same time period. Fig-
ure 6 shows the share of countries coded as RoW democ-
racies for each value on the combined Polity scale. In gen-
eral, higher values on the Polity scale correspond to a
higher share of RoW democracies. The spike in the polity
score of 0 is driven by Burkina Faso (2001–2014) and
Uruguay (1939–1951), which are classified as democra-
cies in RoW. According to V-Dem coders Burkina Faso had
Polity Score
Percent of RoW Democracies
–10
0%
20%
40%
60%
80%
100%
–5 0 5 10
Figure 6. Percentage of RoW democracies by Polity score. Note: The dotted vertical lines mark Polity’s suggested thresholds
of autocracy (≤ −6) and democracy (≥6), with anocracy in between (Marshall et al., 2014). Cases of foreign interruption,
interregnum or anarchy, and transitions (polity codes: −66, −77, and −88) are excluded from this comparison.
Politics and Governance, 2018, Volume 6, Issue 1, Pages 60–77 70

relatively strong democratic institutions, both de-jure
and de-facto during those years. While Uruguay did not
guarantee full political freedoms in the first three years
following the dictatorship of Gabriel Terra (1933–1938),
the country can indeed be considered a democracy fol-
lowing the introduction of its new constitution in 1942.
Similarly, the relatively high value of -1 on the Polity scale
is driven largely by Senegal (1983–2000), which accord-
ing to V-Dem coders had both de-jure and de-facto demo-
cratic institutions.
Overall the new RoW typology relatively closely
tracks the classification of country-years as either demo-
cratic or autocratic by major extant binary measures of
democracy. This is a good sign of convergent validity.
However, there are substantial differences concerning
a significant number of cases, primarily where de-facto
practices deviate from de-jure standards. We argue that
the RoW typology does a better job than others in these
instances, discriminating “real” from “fake” democracies.
For example, most other measures code Kenya
as democratic17 in the years following the crisis that
erupted after president Kibaki was accused of stealing
the December 2007 election (Rutten & Owuor, 2009).
Politically-motivated (Kagwanja & Southall, 2009)—
and allegedly state-sponsored—violence left more than
1,000 people dead and up to 500,000 people displaced
(Human Rights Watch, 2008). RoW picks up this politi-
cal turbulence, with Kenya being classified as autocratic
from 2007 until the freer and fairer elections of 2013.
While Cheibub et al. (2010), Geddes et al. (2014), and
Boix et al. (2013) code Sri Lanka as democratic between
2005 and 2009, RoW captures the limitations to democ-
racy that existed before and during the 2008/2009 civil
war and classify it as autocratic. Similarly, Cheibub et al.
(2010), Geddes et al. (2014), Boix et al. (2013), and Polity
code Burundi as democratic following the presidential
election of 2005, whereas RoW classifies Burundi as au-
tocratic reflecting, among other things, that there was
no de-facto multiparty competition and president Nku-
runziza ran unopposed. RoW also categorizes Nigeria as
an electoral autocracy prior to 2011, a reflection of the
widespread electoral manipulation that marred all Nige-
rian elections until 2011 (Lewis, 2011), whereas Cheibub
et al. (2010) and Geddes et al. (2014) classify Nigeria as
a democracy from 2000. While Polity, Freedom House
and Wahman et al. (2013) also place Nigeria on the auto-
cratic spectrum prior to 2011, the democratic improve-
ments in 2011 are not noted in their coding, which is
static up until 2015. Another example is Albania, which
Boix et al. (2013), Cheibub et al. (2010), and Geddes et
al. (2014) code as democratic from 1991 or 1992 and
onwards even though the main opposition leader Fatos
Nano was jailed from 1993 to 1999 on politically moti-
vated charges (Abrahams, 1996). In contrast, RoW codes
Albania as democratic only from 2002 onwards.
Many fewer country-years are classified as democra-
cies in RoW when most or all other measures code them
as autocratic. This applies for example to Namibia (1991–
2010) where free and fair multiparty elections in combi-
nation with freedom of expression and association qual-
ify Namibia as a democracy based on the assessment of
the V-Dem experts, whereas most other data sets (Boix
et al., 2013; Cheibub et al., 2010; Geddes et al., 2014; and
Polity) disagree. In line with RoW, Freedom House clas-
sifies Namibia as “free” from the 1990’s onwards, and
Larry Diamond (1999) describes it as a “liberal democ-
racy”. Similar disagreement can be observed for Zam-
bia (1994–2007), Burkina Faso (1993–2010) and Mexico
(1995–1999).
6. Conclusions
Many research questions require that scholars use a dis-
crete regime variable, either on the right- or left-hand
side. Extant approaches to this task are laudable, but
are often either limited in their temporal or geographi-
cal coverage, not fully transparent in their coding proce-
dures, or have questionably low thresholds for democ-
racy. None of them provide measures of measurement
error or other sources of uncertainty to help identify am-
biguous cases situated close to thresholds. In this article,
we propose a new regime typology—RoW—covering al-
most all countries from 1900 to 2016. We build on theory
conceptualizing democracy as embodying the core value
of making rulers responsive to citizens, achieved through
electoral competition for the electorate’s approval under
circumstances when suffrage is extensive; political and
civil society organizations operate freely; elections are
clean and not marred by fraud or systematic irregulari-
ties; and where elections affect the chief executive of the
country. In between elections, democracy requires free-
dom of expression and an independent media capable
of presenting alternative views on matters of political im-
portance. We hence classify countries only as democratic
if a minimum level of Dahl’s (1971) famous institutional
requisites are fulfilled in terms of freedom of expression
and alternative sources of information, freedom of as-
sociation, universal suffrage, free and fair elections, and
the degree to which power is de-facto vested in elected
officials. Furthermore, we distinguish between demo-
cratic (liberal and electoral democracy) and autocratic
subtypes (closed and electoral autocracy). Earlier ver-
sions of our typology have already been used in scholarly
work on democratic backsliding (Mechkova et al., 2017b),
the Sustainable Development Goals (Tosun & Leininger,
2017), and political culture (Welzel, 2017), which further
underscores the usefulness of the new RoW measures.
Our threshold for democracy is more demanding
than in all extant data sets because we base our typol-
ogy not only the existence and quality of elections but
also on Dahl’s notion of Polyarchy. Some extant data sets
are limited to de-jure rules and other indicators that are
directly observable. Other data sets only focus on the
implementation of elections in a narrow sense, such as
17 Except for Freedom House (2017), which classifies Kenya as “Partly free” since 2002.
Politics and Governance, 2018, Volume 6, Issue 1, Pages 60–77 71

their de-jure competitiveness. RoW is based on V-Dem’s
high standards in the aggregation of expert-coded data
and recruitment of expert coders, which make the data
more reliable and allows us to assess the de-facto imple-
mentation of institutions as opposed to simply their de-
jure existence.
Finally, RoW is the only measure of discrete regime
types that explicitly addresses a fundamental challenge
for all typologies: classifying political regimes involves
some amount of measurement error and other sources
of uncertainty. Therefore, we have designed RoW to in-
corporate V-Dem’s Bayesian intervals indicating where
68% of the probability mass for each country-year score
is located. We use these intervals to identify the cases
which are close to the thresholds between categories
and which are as a result ambiguously classified. Thus,
the main RoW measure puts country-years in categories
reflecting either certain regime types (closed dictator-
ships, electoral autocracies, electoral democracies, and
liberal democracies), or ambiguous cases in lower and
upper bounds of these regime types. This innovation
opens up research avenues for incorporating such uncer-
tainty in empirical analyses, thus avoiding biased and po-
tentially misleading results.
Acknowledgements
We are grateful to Valeriya Mechkova for the idea of build-
ing a RoW typology capturing ambiguously classified cases.
For helpful comments, we also thank Philip Keefer, Beth
Simmons, Ariel I. Ahram, Josh Krusell, Kyle Marquardt,
Rick Morgan, Dag Tanneberg, the editors and anonymous
reviewers; and participants of the V-Dem Research Con-
ference (May 2017), the APSA General Conference (Au-
gust 2017), the Varieties of Autocracy workshop at the
University of Gothenburg (June 2017; funded by Riks-
bankens Jubileumsfond) and the Empirical Study of Autoc-
racy workshop at the University of Konstanz (September
2017) where earlier versions of this article was discussed.
This research project was supported by Riksbankens Ju-
bileumsfond, Grant M13-0559:1, PI: Staffan I. Lindberg, V-
Dem Institute, University of Gothenburg, Sweden; by Knut
and Alice Wallenberg Foundation to Wallenberg Academy
Fellow Staffan I. Lindberg, Grant 2013.0166, V-Dem Insti-
tute, University of Gothenburg, Sweden; as well as by in-
ternal grants from the Vice-Chancellor’s office, the Dean
of the College of Social Sciences, and the Department of
Political Science at University of Gothenburg.
Conflict of Interests
The authors declare no conflict of interests.
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About the Authors
Anna Lührmann is a Senior Research Fellow at the Varieties of Democracy (V-Dem) Institute (Univer-
sity of Gothenburg). She received her PhD in 2015 from Humboldt University (Berlin). Her articles on
regime change, autocracies, democracy aid, and elections have appeared in the Journal of Democracy,
Electoral Studies, and International Political Science Review.
Marcus Tannenberg is a PhD candidate at the Varieties of Democracy (V-Dem) Institute at the de-
partment of political science, University of Gothenburg. Marcus’s work focuses on politics and public
opinion in autocratic regimes, and survey methodology.
Politics and Governance, 2018, Volume 6, Issue 1, Pages 60–77 74

Staffan I. Lindberg is the director of the Varieties of Democracy (V-Dem) Institute and Professor of
Political Science at the University of Gothenburg. He is a Wallenberg Academy Scholar, a member
of the Young Academy of Sweden and recipient of an ERC consolidator grant as well as numerous
other grants and awards for his research. He is the author of Democracy and Elections in Africa (John
Hopkins University Press, 2006) and editor of Democratization by Elections (John Hopkins University
Press, 2009).
Politics and Governance, 2018, Volume 6, Issue 1, Pages 60–77 75

Appendix
1. Threshold between Closed and Electoral Autocracies in Detail
The V-Dem data set includes specific indicators for legislative and executive elections (v2elmulpar_osp_leg/v2elmulpar_
osp_ex). To identify which of the two should be used for assessing if the Head of the Executive is subject to de-jure mul-
tiparty elections, we need to take the relative power of the Head of State (HoS) and the Head of Government (HoG) and
the appointment procedures into account. The V-Dem variable v2ex_hosw identifies if the HoS (v2ex_hosw =1) or HoG
(v2ex_hosw <1) is the chief executive. If the HoG is the chief executive, the variable v2expathhg indicates whether the HoG
is directly (8) or indirectly (7) elected or appointed by the HoS (6). In the first case, we take the multiparty variable for exec-
utive elections (v2elmulpar_osp_ex), in the second case for legislative elections (v2elmulpar_osp_leg) and in the third case
the score for HoS as follows. If the HoS is the chief executive, the variable v2expathhs indicates whether the HoS is directly
(7) or indirectly (6) elected. In the first case, we take the multiparty variable for executive elections (v2elmulpar_osp_ex),
in the second case for legislative elections (v2elmulpar_osp_leg). (see Coppedge et al., 2017a).
2. RoW by Country for 2016.
Liberal Democracy Electoral Democracy Electoral Autocracy Closed Autocracy
Albania Bhutan +Comoros +Turkmenistan +
Australia Cape Verde +Fiji +Kuwait +
Austria Chile +Guinea +Vietnam +
Belgium Ghana +Haiti +
Canada Guyana +Honduras +China
Costa Rica Israel +Iraq +Cuba
Cyprus Lithuania +Madagascar +Eritrea
Denmark Mauritius +Mozambique +Jordan
Estonia Moldova +Niger +Laos
Finland Panama +Papua New Guinea +Libya
France Poland +Serbia +Morocco
Germany Senegal +Somaliland +North Korea
Iceland Seychelles +Oman
Ireland Slovakia +Afghanistan Palestine/Gaza
Japan South Africa +Algeria Qatar
Netherlands São Tomé & Príncipe +Angola Saudi Arabia
New Zealand Trinidad & Tobago +Armenia Somalia
Norway Tunisia +Azerbaijan South Sudan
Portugal Vanuatu +Bangladesh Swaziland
Spain Belarus Syria
Sweden Argentina Bosnia & Herzegovina Thailand
Switzerland Bolivia Burma/Myanmar Yemen
United Kingdom Brazil Burundi
United States Bulgaria Cambodia
Uruguay Burkina Faso Cameroon
Colombia Chad
Barbados −Croatia Dem. Rep. of Congo
Benin −Dominican Rep Djibouti
Botswana −Ecuador Egypt
Czech Republic −El Salvador Equatorial Guinea
Italy −Georgia Ethiopia
Latvia −Greece Gabon
Namibia −Guatemala Gambia
Slovenia −Hungary Iran
South Korea −India Kazakhstan
Taiwan −Indonesia Malaysia
Ivory Coast Maldives
Jamaica Mauritania
Politics and Governance, 2018, Volume 6, Issue 1, Pages 60–77 76

Liberal Democracy Electoral Democracy Electoral Autocracy Closed Autocracy
Lesotho Montenegro
Liberia Nicaragua
Mali Pakistan
Mexico Palestine/West Bank
Mongolia Rep. of the Congo
Nepal Russia
Nigeria Rwanda
Paraguay Singapore
Peru Sudan
Philippines Tajikistan
Romania Tanzania
Solomon Islands Turkey
Sri Lanka Uganda
Suriname Ukraine
Timor-Leste Venezuela
Togo Zambia
Zanzibar
Central African Rep. −Zimbabwe
Guinea-Bissau −
Kenya −Uzbekistan −
Kosovo −
Kyrgyzstan −
Lebanon −
Macedonia −
Malawi −
Sierra Leone −
Note: The “+” and “−“ denotes an ambiguous case. “+” indicates that some evidence suggests that the country might be better placed in
the next higher category. “−“ indicates that the country might be better placed in the next lower category. For more detail see section 3.
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Politics and Governance, 2018, Volume 6, Issue 1, Pages 60–77 77