Conceptualization and Measurement of Democracy
Project Description for FRISAM project
PI: Håvard Hegre
Department of Political Science, University of Oslo
June 5, 2012
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Relevance: Ambiguous definitions, unclear conclusions?
Because democratic institutions are designed to place political power in the hands of the majority, we expect democracy to lead to outcomes in the interest of the majority of citizens:
economic growth, inequality reduction, peace, and the stability of the democratic institutions
themselves. However, such effects are not always easy to discern. India grows no faster than
China, Sri Lanka has had a long and bloody conflict, and Brazil has larger income inequality
than Venezuela. These examples are not atypical – research using cross-national data indicates that democracies on average perform only slightly better than non-democracies. This
is particularly true in low-income countries and countries that have democratic institutions
in combination with non-democratic traits.
Nevertheless, concluding that democratic institutions is not beneficial for the majority is
probably premature. In this project, we will investigate two possible reasons for the puzzling
lack of clear findings.
First, there is no consensus on how to define and operationalize democracy. Most theoreticians agree that democratic recruitment to positions of political power happens through
competitive elections. Beyond that, there is disagreement as to whether this is a sufficient
basis for defining democracy and, if not, what other political institutions and practices are
necessary to include. Despite this lack of consensus, cross-national studies employ only
a narrow range of proposed democracy measures, mostly with inadequate consideration of
whether the concepts underlying the measure is useful in their particular context, or whether
the measure makes use of the most relevant available data. This partly explains the absence
of clear findings.
Second, a question such as ‘is democracy good for growth’ is not sufficiently precise to
yield clear answers, even if we could agree on a good definition of democracy. Many different
institutional components go into a conception of democracy, and all of them may not be
important for growth. We will probably obtain more precise answers if we ask for instance
how growth is affected by the presence of institutions designed to limit decision-makers’
ability to allocate public funds to projects that benefit themselves and their core supporters.
For some outcomes, such institutions may be more important than whether decision-makers
are elected.
Both lines of investigation require us to look into the underlying components of democracy
and specific institutions within these components. In the Appendix, we identify seven components that cover most elements proposed as essential to democracy, and identify a set of
suggested operationalizations for each of these. The set of components is deliberately broad
in order to allow constructing a variety of democracy measures. This disaggregation allows
us to approach the problems mentioned above systematically, and to evaluate theoretically
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and empirically various suggested aggregation procedures. Through the remainder of this
proposal, we will refer to measures of ‘democracy’ as ‘indices’ or ‘aggregate measures’, and
to measures of sub-components of democracy as ‘indicators’.
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The research project
2.1
2.1.1
Background and status of knowledge
Defining democracy
There are several points of contention regarding how to define democracy. Is democracy
a dichotomous or continuous concept (Przeworski et al. 2000; Elkins 2000)? Should it be
defined ‘institutionally’ according to the existence of particular political institutions or ‘substantively’ according to some underlying principles (e.g. Schumpeter 1976; Przeworski et al.
2000; Beetham 1999)? Which elements should be included in, and excluded from, the concept? Are there necessary or sufficient requirements for democracy, or are there multiple,
but related, factors that can ensure democracy without any one factor being necessary or
sufficient (Gurr 1974; Goertz 2005; Gates et al. 2006)?
Different democracy definitions have different shortcomings. Minimalist definitions are
easier to operationalize (Przeworski et al. 2000), but may have less conceptual validity and
exclude relevant elements. The definition obviously affects classification of specific regimes
and also empirical studies of relationships between democracy and other variables. Przeworski et al. (2000, 15)’s ACPL measure defines democracy simply as a political regime in
which “those who govern are selected through contested elections”.
However, the equation of democracy and elections may make for a ‘fallacy of electoralism’
(Diamond 1999, 9). Several researchers argue there exist several ‘dimensions’ of democracy
(see e.g. Munck and Verkuilen 2002), where contestability of political elite selection is only
one. Some indices are built on a two-dimensional structure, with competition and participation being the two dimensions (Vanhanen 2000; Coppedge and Reinicke 1991; Gasiorowski
1996). Others, such as the Polity (Marshall n.d.) and MIRPS measures (Gates et al. 2006),
are based on three dimensions. These are also criticized for leaving out important elements,
such as political and civil rights (at the core of the Freedom House measure), accountability
(horizontal and vertical), rule of law, and political effectiveness. Our point of departure is a
range of elements grouped into seven components, detailed in the Appendix.
2.1.2
The outcomes of democracy
Growth The literature on democracy’s effect on economic growth mostly employ aggregate
democracy measures. Empirical studies differ considerably regarding democracy’s effect on
growth (Przeworski and Limongi 1993), although recent studies tend to find that democracy
enhances growth (e.g. Baum and Lake 2003). We argue that the inconclusive results are due
to some components of democracy having a positive effect on growth, whereas others do not.
Accordingly, different democracy measures give diverging results, since institutional components are weighted differently. Disaggregated approaches, when used, have yielded important
insights. Bueno de Mesquita et al. (2003) find that the most important components are the
absolute size of the winning coalition and its size relative to the selectorate. Lindert (2005)
argues that expansion of participation rights, rather than existence of competitive elections,
led to the expansion of growth-enhancing primary education systems in Western Europe and
North America. Persson and Tabellini (2003, 2004) indicate that the make-up of electoral
systems has important effects on economic variables like public spending, corruption, trade
openness and productivity growth.
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Stability With ‘stability’ we think of the ability of political systems to withstand radical
changes to their institutional setup. Several studies show that democracies are more stable
than autocracies, at least when average income is sufficiently high (Przeworski et al. 2000).
However, these studies tend to use minimalist definitions of democracy. Gurr (1974) demonstrates the importance of consistency across sub-components of political regimes, and Gates
et al. (2006) shows that such consistency is as important as income. There is also an ongoing debate on whether presidentialism increases the probability of democratic breakdown
(e.g. Linz 1990; Cheibub 2007). More detailed constitutional components, like constitutional
amendment procedures, may affect constitutional stability (e.g. Rasch and Congleton 2006),
and maybe even the probability of democratic breakdown (see Cheibub 2007). Beyond the
three components in Gurr (1974) and Gates et al. (2006) there is little systematic research
on how various components serve to stabilize each other.
Conflict Studies of democracy and interstate conflict show a clear relationship between
democracy and peace (Russett and Oneal 2001), but for internal conflict the relationship
is less clear. Hegre et al. (2001) and Fearon and Laitin (2003) find a curvilinear relationship – political systems that combine democratic and non-democratic elements are most
likely to experience civil conflict. However, exactly which combinations of democratic and
non-democratic components that increase conflict risk is unclear, as most studies use the
highly aggregated Polity index of democracy. Exceptions are Strand (2007), who shows
the importance of weak constraints on the executive in combination with elections – here
the fallacy of electorialism seems particularly detrimental. Vreeland (2008) concludes from
another ‘unpacking’ exercise that the curvilinear relationship is driven by the unfortunate
coding of ‘factionalism’ in the Polity project. A more detailed exploration of democracy’s
sub-components is likely to be fruitful.
Inequality The empirical literature finds no clear effect democratic institutions (Sirowy
and Inkeles 1990; Nielsen and Alderson 1995) – one study concludes that democracy increases
income inequality (Hegre, Gissinger and Gleditsch 2003), but ? and Lindert (2005) suggest
based on case studies that inequality falls after democratization. The statistical studies tend
to be somewhat aged, however, and mainly study aggregate indices. Moreover, these studies
tend to focus exclusively on vertical (inter-individual) inequality. Yet, there is growing
awareness that horizontal inequalities, i.e. systematic socioeconomic inequalities between
ethnic-, religious- or geographical groups, may be more important (see e.g. Stewart 2000;
Østby 2008b). Østby (2008a) find some evidence that the conflict potential of horizontal
inequality is contingent on regime type, but more research is needed to determine what
aspects of democracy may affect the link between horizontal inequality and conflict.
2.2
Approaches, hypotheses and choice of method
This brief review clearly indicates that research on democracy’s effects suffers from imprecise
and at best incompletely justified democracy indices. Most studies rely on a few ready-made
aggregations of democracy – primarily the Polity, Freedom House, and ACPL measures.
The project seeks to increase theoretical and empirical precision by 1) radically disaggregate
the democracy concept, 2) collect information on sub-components, and employ either 3) the
sub-components themselves or 4) some theoretically informed aggregation of them in studies
of the relationship between democracy and its potential outcomes. A considerable amount
of work has been done for point (2), but much research remains for the other three.
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2.2.1
Data Collection
The first task is to review, assemble, and supplement data for a wide range of indicators and
indicators of democracy’s components. A large number of indicators have been proposed and
(partly) coded – a preliminary overview is given in the Appendix. We will supplement this
body of data, and obtain and organize it within a common and publicly available database
framework. The Quality of Government Institute in Gothenburg (QGI) (represented by Jan
Teorell’s participation in the project) will provide a very useful point of departure. The
Kellogg Institute for International Studies, University of Notre Dame (KIIS) will employ a
large number of country experts to collect data on a wide range of institutional indicators
for the 1900–2010 period to supplement the coverage. This data collection effort will take
place in collaboration with our project and with joint funding. Data collected through the
RCN project 196850/V10 at PRIO on power-sharing institutions will also contribute to our
body of data.
Our goal is to cover all independent states in the world for the 1960–2010 period. Some
indicators may also be coded back to 1900. Reviewing existing sources, we will systematically
identify where data coverage is poor and supplement where feasible. Several indicators, for
example from Polity, systematically lack data on small countries. Other indicators are coded
only for some years. We should be able to expand coverage for indicators that are coded
according to clear coding rules.
A preliminary review indicates that extension is particularly needed in two areas:
Institutions of horizontal accountability Polity’s XCONST measure has broad coverage and some face validity (see Gleditsch and Ward 1997), but its coding rules are very
non-transparent and the level of aggregation is high; it is unclear which institutions are
required to achieve a top score. Some indicators relevant to this sub-component will be
coded by country experts. We will also supplement the Judicial checks and balances (2004)
data on judicial checks and balances. This is an excellent source, but covers only 71 countries for a single period. We also intend to collect data on how constitutions are protected,
and if possible on institutions that secure transparency in budgeting and public expenditure
processes.
The freeness and fairness of elections Data sets such as ? measure the extent of
participation using the most readily avaiable source, namely the official election results.
Electoral fraud, however, is a frequent phenomenon that often invalidates the official source
for the data. Fraud can be institutionalized through gerrymandering or disenfranchisement;
it can happen during elections through for instance ballot-box stuffing; or it can occur after
elections through fraudulent counting. We will produce a corrected version of the Vanhanen
dataset (for a limited time frame) based on own collected data, KIIS country expert codings,
Lindberg (2006), and other sources. We will also employ information on the regularity of
political leader changes from the Archigos data set (Goemans, Gleditsch and Chiozza 2009).
2.2.2
Mapping various conceptualizations of democracy
Partly in parallel with the data collection, we will review, systematize and evaluate various
conceptualizations of democracy. Since there is no clear consensus on a definition of democracy, there is no consensus on the appropriate list of sub-components/indicators, nor on
how they interact theoretically. The review will look into the tradeoff between the necessarily subjective assessments of broad democracy conceptions and more objective but thinner
measures.
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Disaggregation allows identifying a number of more easily measurable indicators that
together form a broad picture of democracy. This endeavor, however, requires a clear theoretical specification of which indicators are salient, how they interrelate, and how they
should be re-aggregated to form meaningful indices. This task involves specifying the logical
structure of various suggested democracy concepts, relating them to each of our seven components, and formulating how various conceptualizations translate into specific rules for how
to combine indicators into valid aggregate measures. Outlines of such specifications exist
(see e.g. Goertz 2005; Diamond and Morlino 2005), but more explicit and detailed work
along these lines is needed.
Likewise, we will work out theoretical specifications for each of the seven components
partly to guide our data collection, partly to underpin the discussion in Section 2.2.4, partly
as input to the conception of democracy itself.
2.2.3
Aggregating democracy indicators and evaluating previous aggregate measures
Aggregation Moving from aggregate democracy measures to specific indicators will give
more leverage for specific research questions, and such indicators should often be used in
place of aggregate measures. However, researchers and policy makers will not stop asking
how ‘democracy’ affects for example inequality and conflict – there is a demand for unidimensional aggregations of political regimes’ sub-components. Moreover, although it makes
sense to divide ‘democracy’ into several components, it is clear that several of these are
reinforcing each other, and are correlated. We are thus open for aggregating our components
into one (or a few) meaningful measures of democracy.
No existing aggregate democracy indexes are without serious validity or reliability problems (Munck and Verkuilen 2002; Goertz 2005). Broad measures like Polity and the Freedom
House Index are often problematic, largely because aggregation procedures do not reflect how
the democracy concept is logically structured (see e.g. Munck and Verkuilen 2002; Goertz
2005). Scores on the various questions are simply added together with minimal justification. Paying attention to the various nuances of a multi-dimensional democracy concept is
useless in the absence of a suitable aggregation procedure. Some good attempts at linking
aggregation procedures to their theoretical argument exist (e.g. Inglehart and Welzel 2006),
but may still be too simplistic (Knutsen 2010). Moreover, widely used aggregation methods
often fail to account for the inherent uncertainty in the aggregation process resulting from
the fact that indicators are noisy signals of the actual location of countries on underlying
dimensions (Kaufmann and Mastruzzi 2004; Høyland, Moene and Willumsen 2009).
We will systematically develop and evaluate aggregation procedures based on the review
of conceptualizations and a range of statistical techniques. For example, we will use latent
variable measurement techniques from a Bayesian Markov-Chain Monte Carlo framework
to evaluate the empirical overlap between various conceptually identified aspects of democracy (see e.g. Bollen 1993; Jackman 2009; Høyland, Moene and Willumsen 2009; Treier and
Jackman 2008).
Even with our planned data collection efforts, we will have missing values for indicators
in many cases. In addition to dealing with uncertainty in indicator scoring, one advantage
of the Bayesian framework is that it allows for model specific imputation of missing values.
In combination with the compilation of a wide range of alternative indicators we expect to
be able to produce aggregate measures with nearly complete coverage.
Validation We will carry out a systematic analysis of divergences between our suggested
measures and other aggregate democracy measures, in accordance with the recommendations
of Adcock and Collier (2001). The analysis of the relationship between democracy measures
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and our four outcomes may provide a useful nomological validation of our aggregates, particularly in combination with parallel studies of how theoretically relevant sub-components
relate to the outcomes.
We intend to carry out a number of case studies and small-n comparative studies to
illustrate the scoring of the various indicators and aggregate measures, particularly for cases
where we argue existing aggregates produce poor codings. These evaluations will also indicate whether the components are weighted appropriately in our measures.
Case-based evaluations often reveal interesting differences between various measures, especially on countries that are not very democratic nor very dictatorial. The scoring of these
intermediate regimes is sensitive to what dimensions and indicators are included, and how
they are weighted. For example, according to the Freedom House Index (and Russia observers, e.g. McFaul and Stoner-Weiss 2008), Russia became less democratic after Putin
took over the presidency from Jeltsin, whereas the Polity Index indicates the exact opposite.
Other interesting cases that may be considered for study are Botswana, Kenya, Mongolia,
Nigeria, Singapore and Venezuela.
2.2.4
Reanalyzing empirical relationships in four fields, using disaggregated and
aggregated democracy measures
The third task is to use the new disaggregated and aggregated data, and the associated theoretical rationales, to further the study of how democracy affects growth, inequality, conflict
and stability. We expect to improve theoretical specifications and contribute to theory development in these fields by 1) substituting ‘democracy’ as an independent variable with more
directly relevant components of democracy or particular institutional sub-components, and
2) employing better aggregation procedures. Some theoretical contributions on democracy’s
effects are quite specific (see e.g. Boix 2003), but many others fail to be explicit as to which
democracy components matter for the outcome of interest. Clearer theoretical specifications
will also allow more precise empirical estimation.
For growth, for instance, institutional structures that make it more difficult to pass
comprehensive reforms may reduce growth rates (see e.g. Knutsen 2011). We will study the
effect of constitutional rules such as requirements for parliamentary supra-majorities and the
executives’ opportunities for dissolving parliament (Franchino and Høyland 2009). We will
also study how institutions of horizontal accountability affect growth through their impact on
property rights protection (North and Weingast 1989; North 1990). For inequality, we will for
instance look at how the extent of political participation affects inequality and redistribution
(?), and how institutions such as the constitutional protection of minorities affect intergroup (‘horizontal’) inequality – systematic exclusion of minorities from power is likely to
be important (Cederman and Girardin 2007). For conflict, we will in particular explore
the importance of institutions of constraints in semi-democratic regimes. For stability, we
will for example consider how constitutional rules affect the stability of constitutions and
political regimes, and whether institutions of horizontal accountability are more important
in majoritarian systems than in PR systems. A study on how specific combinations of
electoral rules and types of legislative-executive relations affect democratic breakdown may
be a concrete output.
The empirical research will largely utilize statistical techniques. However, we intend
to complement this research with small-n comparative studies and case studies, primarily
studying the countries listed above. We expect the case studies to help understand and illustrate specific mechanisms and processes that may be hard to identify in statistical studies.
We consider the large- and small-n as complementary to achieve a proper understanding of
the effects of democracy.
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2.2.5
Other data
We will use a range of sources for data for our four outcome variables, such as World Bank
(2010) and ?. Regime stability data will be derived from our democracy data sets.
2.3
Project plan, management, organization and cooperation
The project will extend from July 2011 to June 2014. The sequencing of the project is laid
out in the milestones section of the grant application form. This section summarizes the
organization of the project.
The core team – the PI, three of the researchers (the post-doc, Gudrun Østby, and Bjørn
Erik Rasch), RAs and master students – will be located at the Department of Political
Science (ISV), University of Oslo.
The project will collaborate with two institutions. The Kellogg Institute of International
Studies, University of Notre Dame, will use country experts to code a wide range of indicators
for all countries globally for the 1900–2010 period, under the direction of Professor Michael
Coppedge.1 Associate Professor Jan Teorell, University of Lund, will also participate in this
activity. Coppedge, Teorell and their co-investigators will also contribute to the theoretical
and empirical work on disaggregating and aggregating democracy indicators. Both have
made significant contributions to the measurement of democracy.
Scott Gates and Håvard Strand at the Peace Research Institute, Oslo, will collaborate
both on measurement of democracy and on studying the stability and war outcomes. The
Centre for the Study of Civil War will contribute with matching funds.
In addition, the following researchers will participate in the project: Professor Sabine
Carey (University of Mannheim), Assistant Professor Hanne Fjelde, Uppsala University,
Professor Kristian S. Gleditsch (University of Essex), Senior Researcher Bjørn Høyland (CICERO).2
The post-doc researcher will be recruited to work on the measurement of democracy and
at least one of the outcomes – in particular on democracy’s effect on growth, the outcome
where the team has (relatively) weaker competence.
Together, the team has extensive research experience on the measurement of democracy, on the required research methods, and on how political institutions relate to the four
outcomes. All have published extensively in high-ranked journals.
Collaboration will take the form of three workshops at the University of Oslo and submissions of panels to conferences such as the ISA, APSA, and ECPR joint sessions. Workshop 1
will address measurement of democracy and its disaggregated components, Workshop 2 the
effects of democracy and its components on economic growth, inequality, conflict and political stability, Workshop 3 the aggregation of democracy’s components and how aggregated
measures relate to the four outcomes.
The project will collaborate with the Research Programme on Democracy (RPD) at
the University of Oslo [http://www.demokrati.uio.no/], led by Bjørn Erik Rasch. The data
collection and measurement work will be of interest to other researchers in RPD, and our
project will benefit from contact with some focal RPD areas such as the relationship between
majorities and minorities in democracies, and the global economic and political challenges
for current democracies.
We intend to recruit RAs from the large pool of master students at the ISV, and also to
invite master students to write master theses as part of the project. The RAs will primarily
work on collecting data on the constraints and election indicators (see Section 2.2.1)
1
2
The country expert coding has financing from other sources, including the Kellogg Institute itself.
Some of these are fully funded at own institutions and only require travel funds.
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3.1
Perspectives and compliance with strategic documents
Compliance with strategic documents
This project complies with key points in the University of Oslo’s strategic document ‘Strategi
2020’ through its focus on publication of results in high-ranking journals, extensive international collaboration, and dissemination outside the research community. The project’s focus
is highly complementary to the University’s inter-facultary RPD discussed above. Finally,
the project is in line with the ISV’s explicit focus on democracy and governance.
3.2
Relevance to society
The four outcomes under study are all beneficial to societies at large. To the extent that the
research succeeds in identifying institutions that promote these outcomes, and actors take
steps to put such institutions into effect, societies will benefit.
3.3
Environmental, ethical, and gender perspectives
The project has no direct, negative environmental impacts nor any conflict with the Research Council of Norway’s Research Ethics Checklist. Any individual data collected will
be properly anonymized. This also applies to informants in case-studies if there is a risk of
retribution from their government or others. Three of the project’s eleven core participants
are female researchers. We expect at least 50 percent of the master students to be female,
reflecting the slight dominance of female students at ISV.
Properly understanding how various democratic institutions function may have positive,
indirect effects on various environmental and gender aspects. Democratic institutions, have
for instance been shown to improve the educational situation of women and reduce certain
forms of environmental degradation.
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Communication with users and utilization of results
Most dissemination will be through leading international journals. For details, see the grant
application form.
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Appendix: Seven components of democracy
Competition With no competition for elected offices,
popular control over public decision making suffers greatly.
Przeworski et al. (2000) provide perhaps the most stringently operationalized measure on whether offices are obtained
through competitive elections. Other sources are the competition components in the Polyarchy measure of ?, the executive recruitment components in Polity (Marshall n.d.) and
in the measures of Arat (1991); Bollen (1980); Coppedge and
Reinicke (1991); Coppedge, Alvarez and Maldonado (2008);
Gasiorowski (1996); Hadenius (1992). Some of the sources
have limited temporal scope, and supplementing data by original coding may be necessary. Components of the Archigos
dataset (Goemans, Gleditsch and Chiozza 2009) – the extent
to which political leaders gain or lose power through regular
means also provide information on this dimension.
istence of formally guaranteed political and civil rights and
liberties. These are vital for ensuring citizens’ ability to control political debates and processes (e.g. Diamond and Morlino
2005; Inglehart and Welzel 2006). Freedom House provides two
broad, relevant indexes (Freedom House 2010), and also has a
separate indicator on press freedom. Bollen (1980) include indicators on press freedom and freedom of group opposition.
Moreover, the CIRI Human Rights Data Project provide detailed data on various civil liberties. Other operationalizations are found in Gasiorowski (1996); Hadenius (1992), and
in datasets that record the extent of human rights violations
(Cingranelli and Richards 1999; Poe, Tate and Keith 1999;
Wood and Gibney 2010).
Horizontal Accountability Institutions that ensure political accountability are vital for democracy, as they ensure
that elected officials follow the interests of constituents, rather
than personal interests. Horizontal accountability are ensured
by institutions such as strong parliaments, general auditors,
independent judiciaries, etc. Polity (Marshall n.d.) codes a
‘constraints on the executive’ indicator. Other operationalizations are suggested by Judicial checks and balances (2004);
Djankov et al. (2003). Fish and Kroenig (2009) include detailed data on national legislatures.
Participation and Political Inclusiveness The most
common additional democratic attribute is the degree of “participation” in political processes (e.g. Dahl 1971). The democracy measures of ?Coppedge and Reinicke (1991); Coppedge,
Alvarez and Maldonado (2008); Gasiorowski (1996); Bueno de
Mesquita et al. (2003) and the participation component of
Polity (Marshall n.d.) provide data.
Political and Civil Rights A third aspect is the ex-
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Vertical Accountability Accountability is also ensured
through a more direct interaction between politicians and citizens. Institutions that faciliate this are rules that secure transparency concerning budgeting, legislation, and implementation. A free press is essential for vertical accountability van
Belle (e.g. 1997). Other systematic data are scant for this
component.
Rule of Law Formal rights and liberties, like constitutionally guaranteed free speech, count for little if not guaranteed in practice, and this is strongly related to existence of rule
of law (e.g. Inglehart and Welzel 2006). Also effective competition and participation require that political elites obey the law,
for example when it comes to ensuring free and fair elections
(see e.g. Schedler 2002). Elections can be manipulated for example through systematic violence and imprisonment of opposition candidates (see e.g. Schedler 2002; Lindberg 2006). Such
indicators are also included in the CIRI data. The World Governance Indicators (Kaufmann, Kraay and Mastruzzi 2007) includes a rule of law indicator. ICRG (nd) also produces relevant data for this component. Disaggregated measures from
other sources tap various sub-components of rule of law (e.g.
Djankov et al. 2003; Judicial checks and balances 2004).
Political Effectiveness As discussed by e.g. Munck and
Verkuilen (2002), it matters whether those elected exercise
power over agenda setting and decision making. If, like in
present Iran, a non-elected entity dominates important areas
of political life, democracy is but a façade. This aspect could
be called an “effectiveness aspect”, and is reflected in some
democracy measures (Bollen 1980; Arat 1991; Hadenius 1992;
Marshall n.d.). The Polity project used to code a ‘scope’ variable along the same lines, but this has not been updated since
1986.
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