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Article
Party and Party System
Institutionalization: Which Comes First?
Fernando Casal Bértoa, Zsolt Enyedi and Martin Mölder
Parties and party systems are treated as separate phenomena in theory, but not in research practice. This is most clearly so in the
literature on the institutionalization of party politics, where the party level and the systemic levels are often analyzed through
combined fuzzy indices. We 1) propose separate indicators for measuring institutionalization at the party and at the party system
level, 2) demonstrate their different dynamics in twentieth and twenty-first century European countries, and 3) investigate the
direction of causality. Using a dataset that covers more than 700 elections, 800 parties, and 1,400 instances of government
formation in 60 different historical party systems across 45 European countries, we find that party-level institutionalization tends to
precede systemic institutionalization. The opposite pattern occurs only in a few countries.
The accepted wisdom in political science is that party
systems have a logic of their own, somewhat
detached from the life of individual parties (Ware
1996; Mair 1997; Randall and Svåsand 2002). There are
countries in which inter-party politics is characterized by
predictability in spite of the occasional merger, split,
disappearance, or emergence of individual parties. In other
countries the roster of individual parties and their electoral
support is relatively continuous, but parties frequently
realign. As an acknowledgment of two separate, though
obviously related, logics and arenas, the typical title of an
academic paper or of a university course on party politics is
“Parties and Party Systems”.
Given this background, one would expect the existence
of established separate measures for the two levels and
crystallized views on whether party system change leads to
A list of permanent links to Supplemental Materials provided by the authors precedes the References section.
Data replication sets are available in Harvard Dataverse at: https://doi.org/10.7910/DVN/SZ7JOO
Fernando Casal Bértoa is Associate Professor of Politics and International Relations, University of Nottingham (Fernando.
Casal.Bertoa@nottingham.ac.uk). He is co-director of REPRESENT: Research Centre for the Study of Parties and Democracy.
His work has been published in the Journal of Politics,European Journal of Political Research,Sociological Methods and
Research,Electoral Studies,West European Politics,Party Politics,European Political Science Review, and Democra-
tization among others. He was awarded the 2017 Gordon Smith and Vincent Wright Memorial Prize, the 2017 AECPA Prize
for the Best Article, the 2018 Vice-Chancellor Medal of the University of Nottingham, the 2022 AECPA Prize for the Best Book,
and the 2022 Routledge Area Studies Impact Award.
Zsolt Enyedi is Professor at the Political Science Department at Central European University (enyedizs@ceu.edu). He has (co)
authored two and (co)edited eight volumes and published numerous articles and book chapters, mainly on party politics and
political attitudes. His articles appeared in journals such as European Journal of Political Research,Political Studies,Political
Psychology,West European Politics,Party Politics,Europe-Asia Studies,Perspectives on Politics, and European Review.
He has received academic awards such as the 2003 Rudolf Wildenmann Prize; the 2004 Bibó Prize; and the 2020 Hungarian
Academy Award.
Martin Mölder is a Researcher in Comparative Politics at the University of Tartu, Estonia (martin.molder@ut.ee). He has
been working on the measurement of party positions; properties of party systems; public opinion; and voting advice applications, as
well as the analysis of political texts. He is teaching elections and political behavior and quantitative methods at the University of
Tartu and is a frequent commentator on Estonian politics in national media.
doi:10.1017/S1537592723002530
© The Author(s), 2023. Published by Cambridge University Press on behalf of the American Political Science Association. This is an Open
Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which
permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
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https://doi.org/10.1017/S1537592723002530 Published online by Cambridge University Press
party-level change, or vice versa. This is, in fact, not the
case. The indicators used to measure the two levels tend to
overlap and therefore no clear distinction or relationship
has been established between the two phenomena. While
there have been sporadic attempts at treating institution-
alization at the party-systemic level and at the party level
separately (e.g., Haughton and Deegan-Krause 2020),
through different indicators (we build particularly on
Casal Bértoa and Enyedi 2021), none of these attempts
aimed at establishing a causal sequence between the two
phenomena.
Identifying the differences between the dynamics of
parties and party systems is not only a theoretical necessity.
Through their differentiation we can capture better the
speed and character of de-structuration happening in
multiparty systems. Furthermore, the careful separation
of the two levels can help us in better responding to the
practical challenges of democracy promotion,
1
as the
contribution of the two levels to the quality or consolida-
tion of democracy may differ.
Most scholars from Huntington (1968) onwards
(cf. Mainwaring 1998; Morlino 1998; Tavits 2005) agree
that some level of institutionalization of party politics is
essential for a proper functioning of democracy, although
occasionally too much institutionalization is also suggested
to be problematic (Schedler 1995, Mölder, Enyedi, and
Casal Bértoa 2023; Yardimci-Geyikci 2015). If the indi-
vidual parties are institutionalized, then they have better
chances to become reliable conveyors of the preferences of
the citizens. Durable political parties can help voters to
reduce the multidimensional political world into a man-
ageable set of alternatives. Electoral promises can form the
basis of accountability exactly because of the longevity of
parties; citizens can exercise their right of rewarding or
punishing because those who made the promises at the
previous elections are still around and accept the verdict of
the supporters. Stable parties provide a framework for
politicians within which idiosyncratic ideological differ-
ences may cancel out each other, and a meaningful
electoral choice becomes possible.
The dominance of parties with a track record also
provides better conditions for linking the electoral, the
legislative, and the executive arenas. Across time, parties
get the chance to establish linkages to specific pressure
groups, social segments, geographic areas, and economic
sectors, representing the interests and values of these units
during the campaigns, legislative debates, coalition-
building, and governing. The citizens can realize that their
preferences expressed as votes translate not only into
political rhetoric but also into policies and governmental
regulations, and thereby their attachment to the political
system may solidify.
As far as the institutionalization of the party system is
concerned, the predictability of the alignments between
parties is primarily relevant in multiparty settings, where
the governments are often based on cooperation among
parties. Knowing which party is a “friend”with which
other party allows citizens to have rational expectations on
the character of the government. The coalescence of
parties into formal or informal alliances further simplifies
the political landscape, often reducing the number of
viable alternatives to two or three.
Since party alliances can fall apart at any minute, their
long-term survival signals underlying continuity in the
nature of political divisions. This continuity may stem
from stable social configurations, but given that conflicts
between parties may be outcomes of tensions within a
relatively narrow political elite, the stability of blocs of
parties also indicates intra-elite consensus on what political
competition is about.
Clearly, the contrast between parties and party systems is a
contrast between different levels of aggregation. But it is also
a contrast between two different logics. At the level of parties,
the question to be asked is whether they can maintain a
support base and achieve office. At the level of party systems,
the question is whether the inter-party relations and the rules
of competition and cooperations stabilize.
The functioning of democratic systems of representa-
tion may fail on either—or both—fronts. Parties may
remain ephemeral institutions with a short timespan or
may be unable to maintain unity and may fall apart into
various splinter groups. Alternatively, the coexistence of
parties may lack equilibria; the political community may
not reach an agreement about what are the principal
alternative teams. The latter is particularly likely if there
is no clear rank order between issue- and value-related
conflicts. The classical party systems of Scandinavian or
UK politics achieved such an equilibrium by giving pri-
ority to class-related interests, and by accepting the Labor/
Social Democratic parties as the principal spokespersons of
the working classes. On the Scandinavian right there has
always been more complexity, but the cooperation
between Agrarian, Conservative, Christian Democratic,
and right-wing Liberal forces allowed for a consolidation
of a bipolar system.
While the party-level and the systemic-level are neatly
separated in many theoretical studies, the most common
practice of measuring the institutionalization of party sys-
tems is to average the features of individual parties.
2
Some
scholars use, for example, the average party age (Schiller
2018; Schleiter and Voznaya 2018; Piñeiro Rodríguez and
Rosenblatt 2018 and the like) to pass judgment on the
institutionalization of party systems. This is a clear case of
using information calculated at one level—the parties—to
characterize another level—the system of parties. The
frequently used indicators of electoral volatility appear to
be more systemic in nature, but they are, in fact, also
aggregates of features of individual parties (in this case using
as input the change of their support from one election to
another).
2Perspectives on Politics
Article |Party and Party System Institutionalization
https://doi.org/10.1017/S1537592723002530 Published online by Cambridge University Press
We recognize that the listed measures tell us something
relevant about the nature of party politics (Haughton and
Deegan-Krause 2020). But none of them are truly systemic
indicators because they miss the very element that consti-
tutes a system: the interactions between the components.
In contrast, the essence of our proposition is to use party-
level measures for capturing the degree of party institu-
tionalization (PI), and interaction-related measures for
capturing party system institutionalization (PSI).
As far as the interactions among parties are concerned, we
suggest relying on the party system closure index (Mair
2001; Casal Bértoa and Enyedi 2021). The closure
approach considers party systems to be institutionalized if
a stable set of parties alternate in power following regular
coalition patterns. The strategy of relying on the closure
index is notwithout limitations as the empirical basis of this
measure is confined to the governmental arena. Information
on the relationships among all parties would provide a more
comprehensive picture. But the interactions of parties in
building governments are central to party relations in
general (Rokkan 1970;Smith1989). Furthermore, data
on the often-informal alliances of opposition parties are
rarely available. While the closure index misses changes
within the opposition, it allows for the analysis of long time
spans and a large number of countries.
We propose to consider parties to achieve a high degree
of institutionalization if they have a continuous existence
and if (legislative) elections are dominated by well-
established parties. This strategy of operationalization also
aims for an optimal balance between empirical reach and
validity. Specific intra-organizational characteristics are
not considered for the index as they are available only
for a limited time period.
The third limitation of the presented analysis is that it is
confined to Europe. Within this geographic scope, how-
ever, we can rely on an unusually large dataset, going back
to the nineteenth century and basing our conclusions on
the observation of up to 60 party systems, from the Second
French Republic, established in 1848, to Kosovo, inde-
pendent since 2008.
Exploiting the variation of a century and a half, includ-
ing into the analysis party systems that existed at one point
but have collapsed by now, and benefiting from cross-
national diversity, we are able to document the similarities
and differences between the temporal trends in the two
studied phenomena. Additionally, our goal is to investi-
gate the causal sequence between PI and PSI and to
establish whether we need institutionalized political
parties to achieve predictable patterns of inter-party com-
petition or whether the consolidation of relations among
parties is a precondition for the consolidation of the parties
themselves. Our ambition is not to provide a comprehen-
sive causal explanation for these two phenomena but to
highlight the differences between them and to confront
the fundamental question: What comes first?
One of the principal observations of the descriptive
analysis made possible by the new data and the new
indicators is that there is currently a drastic
de-institutionalization at the level of parties in Europe,
but a much more attenuated decrease in the stability of
party interactions in the governmental arena. The evi-
dence also leads us to conclude that one should think of
party-level institutionalization being the cause, and PSI
being the outcome. Institutionalized parties lead to more
stable party relations, but the opposite is mostly not true:
systems that develop predictable patterns of party relation-
ships do not necessarily enhance the institutionalization of
parties themselves.
In what follows, we discuss the conceptual and opera-
tional issues of PI and PSI and then the arguments justifying
particular causal sequences between the two. We next
introduce the data and the operationalization of the main
variables and thereafter present information on the cross-
temporal relationships between party and systemic institu-
tionalization. The following section investigates the causal
sequence between the two phenomena confirming our
main finding—PI is the prime mover. The article ends
with a summary of the main findings, including some
suggestions for future research.
Party and Party System
Institutionalization
In the analyses of party politics, PI and PSI are often
collapsed into a combined fuzzy syndrome (e.g., Kreuzer
and Pettai 2003; Lewis 2006; Meleshevich 2007; Moser
1999; Rose and Mackie 1988; Shabad and Słomczyński
1999). This is, on the one hand, understandable. Both
individual parties and the patterns of party competition
can become predictable, anchored, robust, impersonal,
and routinized, and there are strong reasons to expect
the institutionalization of individual parties and party
systems to be related (Lane and Ersson 2007; Rose and
Munro 2009; Sartori 1990). On the other hand, we will
never learn about their similarities and differences unless
we rely on separate empirical indicators.
Even when the party level and the systemic level are
treated separately, the features of the units (i.e., parties),
primarily their organizational strength and stability, are
used to characterize the whole system (e.g., Mainwaring
1998; Mainwaring and Scully 1995; Mainwaring and
Torcal 2006; Kuenzi and Lambright 2001; Tan 2006).
In other words, there is a mismatch between theory and
empirical strategy.
The confusion of the two levels can be minimized if one
conceptualizes the institutionalization of parties primarily
through organizational continuity and longevity (Levitsky
1998; Bolleyer and Ruth 2018; Scarrow, Wright, and
Gauja 2023), while thinking of systemic institutionaliza-
tion in terms of the stability of the structure of inter-party
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competition (Mair 2001). Since there is no deterministic
mechanical link between these factors, we allow for the
possibility that the patterns of partisan interactions may
solidify despite the discontinuity of individual parties or
that a substantive change in the dynamics of the system
may occur even without a drastic change in the support of
parties and without the appearance of new players on the
scene. At the opposite end of the spectrum, relationships
among parties may remain unpredictable and unstable
despite the persistence of party labels.
For measuring institutionalization at the systemic
level, we choose the party-system closure index (Mair
2001). Among the available empirical proxies for PSI
(e.g., fragmentation, electoral volatility, programmatic
stability, etc.) this is the one that focuses most unambig-
uously on the interactions among parties. Party-system
closure is considered high if the combinations of parties
constituting governments rarely change, if new parties
have a marginal presence in governments, and if govern-
ments are not based on the combination of hitherto
opposition and government parties. While the closure
scores are calculated using information obtained from the
governmental arena, they have been shown to reflect the
logic of party relations in general (Casal Bértoa and
Enyedi 2021). The reliance on the composition of gov-
ernments permits us to extend our investigation to a
particularly extensive large timespan.
As far as the party level is concerned, the same objective
can be reached by focusing on the age of parties and their
continuous electoral support. Other possible indicators of
PI (e.g., indices of party identification, membership, party
switching, party replacement, party nationalization,
bureaucratization, financial resources, etc.), are usually
available for a limited number of cases over time. Even
more importantly, age and electoral support are relevant
indicators of PI because they depend directly on the
organizational stability and social rootedness of the parties.
This operationalization strategy allows for the exami-
nation of the differences and similarities between party and
systemic institutionalization across time, and for establish-
ing the causal sequence between the two. In general, based
on the literature and on the arguments to be elaborated
further later, one should expect a positive relationship
between these phenomena. But this relationship is likely
to be less tight than assumed by the studies that mix
information from the two levels.
Party and Party System
Institutionalization: What Kind
of Relationship?
Despite the importance of both discussed notions, few
studies have probed into the causal relationship between
them. Within this relatively small literature, PI is mostly
assumed to be a cause of PSI (Roberts and Wibbels 1999;
Toole 2000), but some studies treat it as a consequence of
the latter (Tavits 2008).
3
Stable party interactions are
unlikely when political parties come and go and frequent
changes in party relations may hinder the ability of parties
to develop electoral roots and stable organizations. Thus,
intuitively, both models are conceivable.
The model according to which continuity in party
relationships anchors and stabilizes individual parties is
definitely plausible. This logic assumes that when parties
do not change partners, new party initiatives are dis-
couraged, and voters are reluctant to change partisan
preferences (Mair 1997). In contrast, if the electorate
sees parties colligating in an ad hoc and pragmatic
manner, making alliances out of convenience rather than
based on long-standing common interests and ideolog-
ical proximity, the loyalty of voters and politicians to
their party will diminish, making both electoral shifts
and organizational splits more likely (Tavits 2008). In
other words, uncertain party relations may weaken
political parties themselves.
The opposite model considers the institutionalization
of parties to be the more profound and more consequential
phenomenon and expects the systemic level to stabilize
only after political parties achieved considerable organiza-
tional continuity and gained a critical mass of loyal
supporters. We find the arguments in favor of the second
model to be more powerful, and therefore we expect PI to
precede PSI. The first argument is quasi-mechanic: pre-
dictable relationships between parties require some conti-
nuity in the basic building blocks of the system (Moser
2001, 36; Rose and Munro 2009). In theory, a center-left
party can be replaced by another center-left party that will
have the very same systemic role as its predecessor, but it is
highly unlikely that this logic will characterize every single
example of party discontinuity.
More substantively, PI implies routinized internal
processes for recruitment, deliberation, conflict resolu-
tion, and decision-making (Harmel, Svåsand, and Mjelde
2019). The establishment of conflict-solving mecha-
nisms reduces the room for intra-party factionalism and
dissent (Mader and Steiner 2019) and increases the
chances for internal cohesion to develop (Harmel and
Svåsand 2019; Basedau and Stroth 2008). In a political
system dominated by such parties, there is less reason for
voters to abandon parties and to consider newcomers
(Gherghina 2015; Tavits 2013). The smaller magnitude
of “homeless”and “wandering”voters is helpful for
systemic-level stability: abrupt shifts in electoral balance
from one election to another can easily undermine the
consolidation of inter-party competition (Ponce and
Scarrow 2022).
Furthermore, strong and recognizable party brands are
typically associated with relatively stable ideological plat-
forms (Lupu 2016, Rosenblatt 2018), promoting recur-
rent alliances and coalitions (Mainwaring and Zoco 2007).
In those systems where parties lack a secure core of
4Perspectives on Politics
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supporters, stable partisan relationships will be more
difficult to achieve, as parties will be more inclined to
change their ideological stances, confounding both voters
and politicians as to what they stand for.
The routinization of coalition preferences is also helped
by the fact that established parties are likely to be present
across the whole nation and to have professional staff
(Szczerbiak 2001). Professional politicians who are in party
office across longer time periods are more apt at striking
cross-party deals and at holding each other accountable.
To conclude, while the causal arrow running from the
systemic to the party-level also appears to be plausible, is
likely to be weaker and more indirect than the one running
from the party level to the systemic level. A party system
can be expected to institutionalize primarily when it has a
continuous core of parties. When that is not the case, we
can expect an open arena of government-building, and
constant coalitional innovations. Therefore, we hypothe-
size that in most cases the institutionalization of political
parties will lead to the institutionalization of the party
systems, and not the other way round.
Data and Operationalization
We make use of a new dataset comprising all European
countries that have had a meaningful experience with
democracy since 1848. A country is considered to be
democratic when 1) it has a score of ≥6 in the Polity IV
index, 2) universal (male) suffrage elections have been held
at least once, and 3) governments are formed with (and
rely on) parliamentary support rather than on the exclusive
will of the head of state (Casal Bértoa and Enyedi 2022).
The full dataset spans 171 years (from 1850 to 2021) and
60 different historical party systems across 45 countries
(refer to table 1 for details). The number of electoral cycles
varies between 1 (e.g., Greece’s post-World War II King-
dom or Poland’s First Republic) and 35 (Switzerland).
Partial and constitutional assembly elections are not taken
into consideration except when explicitly stated otherwise.
The number of cabinets per country varies between
2 (post-World War II Turkey and inter-war San Marino)
and 61 (France’s Third Republic). The full data set thus
covers 729 elections, 878 parties, and 1,475 instances of
government formation. All in all, this constitutes almost
the entire universe of cases for European democratic party
systems.
4
By default, the attributes of party relations of specific
(democratic) countries are used to characterize the party
system of that country. In this sense, countries and party
systems could be used as synonymous labels for our units
of analysis. But some countries had a ruptured history,
with democratic periods being divided by—often lengthy
—non-democratic spells, leading to a profound transfor-
mation of both party-political actors and their relations. In
such instances we talk about different “party systems”
nested in the history of a particular country. The temporal
boundaries of such party systems are provided by the
continuity of democratic arrangements, and the scores
refer to the (relational) features of party politics within
the uninterrupted democratic spells. In other words, our
actual units of analysis are democratic periods. Typically,
the entire democratic history of a country is one single
spell, but this is not always the case. This is why, for
example, we distinguish between four separate French
systems in table 1.
Table 1
Party systems of democratic periods included in the dataset
Albania 2001-2021 Germany I 1919-1933 Norway 1903-2021
Andorra 1993-2021 Germany II 1949-2021 Poland I 1922-1926
Austria I 1920-1932 Greece I 1926-1936 Poland II 1991-2021
Austria II 1945-2021 Greece II 1946-1948 Portugal 1976-2021
Belgium 1919-2021 Greece III 1974-2021 Romania 1996-2021
Bulgaria 1991-2021 Hungary 1990-2021 Russia 1999-2006
Croatia 2000-2021 Iceland 1942-2021 San Marino I 1920-1923
Cyprus 1976-2021 Ireland 1923-2021 San Marino II 1945-2021
Czechia 1992-2021 Italy 1948-2021 Serbia 2000-2021
Czechoslovakia 1920-1938 Kosovo 2007-2021 Slovakia 1992-2021
Denmark 1910-2021 Latvia I 1922-1934 Slovenia 1992-2021
Estonia I 1920-1933 Latvia II 1993-2021 Spain I 1931-1936
Estonia II 1992-2021 Liechtenstein 1993-2021 Spain II 1979-2021
Finland I 1917-1930 Lithuania 1992-2021 Sweden 1917-2021
Finland II 1945-2021 Luxembourg 1919-2021 Switzerland 1896-2021
France I 1849-1851 Malta 1962-2021 Turkey I 1946-1953
France II 1876-1940 Moldova 1994-2021 Turkey II 1961-1979
France III 1946-1957 Montenegro 2006-2021 Turkey III 1983-2013
France IV 1968-2021 Netherlands 1918-2021 Ukraine 1994-2013
Georgia 2004-2021 North Macedonia 1990-2021 United Kingdom 1918-2021
5
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Operationalization of Main Variables
As mentioned earlier, PSI is measured by the closure index.
The empirical basis of the index is provided by data on the
party composition of governments and on the partisanship
of the ministers. The index has three components: alterna-
tion, formula, and access. The alternation sub-index shows a
low score if partial alternations are the rule, meaning that
some of the ruling parties continue in office while others do
not, and cabinets are a mix of parties from within the
previous government and from without. The formula sub-
index has low scores if there are frequent innovations in the
coalition formulae. Finally, the access sub-index has low
scores if new parties have easy access to government. Low
scores are taken as indicators of open, under-
institutionalized party systems. In contrast, we speak of
highly institutionalized (closed) systems if the incumbent
parties tend to leave office together or if governments tend
to remain in office across long time periods, if governments
are typically based on fixed alliances of parties and if they
consist of parties that have already governed in the past.
To indicate the degree of closure for a particular year, we
use a weighted average measure for each particular year that
takes the year in question as well as all previous years of the
party system into account. The weighted average closure for
year nof the party system takes all years from 1 to ninto
account. Weights for each year arethe year number divided
by the triangular number of n. This results in a linearly
decreasing weighting scheme, where the more recent years
are given more weight and the weights would reach
0 beyond the beginning of the party system.
5
To capture the level of PI, we introduce two variables. The
first is the average age of parties, widely used in the literature
(see Dix 1992; Huntington 1968;KuenziandLambright
2001; Mainwaring and Scully 1995;Mainwaring1998;
Roberts and Wibbels 1999;Tan2006). In order to calculate
this indicator, we have collected data on the year of founda-
tion of political parties from multiple sources, including party
statutes and official websites. While party mergers are con-
sidered cases of organizational rupture (e.g., Liberal Demo-
crats in the UK, Christian Democratic Appeal in the
Netherlands, Freedom Union in Poland), simple name
changes (e.g., People’s Party in Portugal and Spain) are not.
Inthecaseofsplits,theageofthesplintersstartsfromthe
moment of the split, while any successor party will not have its
age re-started. We consider all those parties that obtained at
least 3% of the national vote at least once in their lifetime.
6
Capturing organizational continuity exclusively through
average age gives an advantage to older democracies. Addi-
tionally,a simple average is not sensitiveto the fact that some
parties are more important than others. In order to make up
for these deficiencies, the employed PI measure also includes
the Established Party Domination (EPD) index (Casal
Bértoa and Enyedi 2021, 150-151). The index has a high
score if voters tend to cast their vote for parties that were
established at the beginning of the party system. Each party
contributes to the index withits vote share plus 5%
7
for each
year since the party first participated in elections. The index
calculates a reference score and an actual score for each
election. The reference score for an election assumes that all
parties have endured since the founding elections,
8
while the
actual score takes their actual durations into account. The
EPD index is the ratio of the two.
Considering the vote share of a party implies a contrast
between the analyzed party and the total vote. This may
sound like bringing in the systemic level, but the goal is
simply to capture the relative weight of the party in the
electorate and not to tap the relations among parties.
Because EPD is calculated differently than party age, it
allows for tapping a different layer of PI. It can be high
even in a situation where the average party age is relatively
low, for example in those newly democratized party
systems in which the very same parties are returned to
the legislature election after election.
We use the mean of the standardized values of both
components, average party age and established party dom-
ination as an overall indicator of PI.
The descriptive statistics for the indices and their com-
ponents across all the years and countries in our full data set
(n=2400) (Casal Bértoa, Enyedi and Mölder, 2023)are
provided in table 2 and their correlations are shown on
Table 2
Descriptive statistics
Variable mean SD min max density
PSI 91 7.6 41 100
alternation 87 13 8.3 100
formula 91 9.3 18 100
access 95 6.4 31 100
PI 0.024 0.75 −3.1 2.2
established party domination 84 13 22 100
party age 34 20 1 98
6Perspectives on Politics
Article |Party and Party System Institutionalization
https://doi.org/10.1017/S1537592723002530 Published online by Cambridge University Press
figure 1. The correlation between PI and PSI is 0.42. This
indicates that the overlap between the two phenomena may
be smaller than often assumed, at least using the previously
introduced indices. If we look at the components, we see
that the relationship is driven by average party age being
related to the formula- and access-component of party
system closure. Established party domination and alterna-
tion play a lesser role in the overall association between party
and systemic institutionalization.
Differences across Time and across
Systems
The temporal extent of our data set allows us to trace the
co-evolution of party and systemic institutionalization in
European democracies over more than a century. Figure 2
looks at the two levels of institutionalization aggregated by
5-year periods from 1900 (the earlier nineteenth-century
data are too sparse for identifying trends) to 2021. The
trajectory of PI across this period has an inverted-U shape
with a steep increase followed by an equally steep decline.
These data demonstrate, dramatically, the advent and the
wane of the mass party era. Political parties were central
institutions in the class-dominated politics of the 1950s
and 1960s, but the subsequent social transformations led
to the appearance of new forces, mergers, and splits of the
established actors, and a general appetite for experimen-
tation on behalf of voters.
The process of de-institutionalization is not an exact
mirror-image of institutionalization. The latter process
was part of social modernization and democratization.
De-institutionalization does not require a rejection of
the norms of modernity and liberal democracy. On some
aspects these norms may even be supported by the decline
of bureaucratic mass organizations.
De-institutionalization is primarily related to phenom-
ena like the personalization of party politics, the profes-
sionalization of party elites, the rise of the “party in public
office”at the expense of the “party in central office”and of
the “party on the ground,”and the extension of public
funding of parties (Katz and Mair 2018). These phenom-
ena amplified instability and sped up the process of the
voters’withdrawal from the electoral arena (Mair 2013;
Ignazi 2017; Scarrow, Webb, and Poguntke 2018).
Socially rooted parties were replaced by entrepreneurial
parties (Bolleyer 2013). The rise of populism also contrib-
uted to the spread of fluid and personalistic organizational
style (consider Podemos, Five Stars Movement, Brexit
Party, or the Czech ANO). Together, these processes led
to a sharp decline of PI, especially after the 2008 Great
Recession.
Party-system closure shows less dramatic changes.
Between the 1920s and the 1980s the trend was towards
(moderate) growth. The turbulence of the 1990s affected
closure negatively, but afterwards systemic institutionali-
zation proved to be more resistant against the forces of
destructuration than PI. Having said that, the last half
century produced less predictable party systems than the
previous one. This trend applies whether the new post-
communist party systems are excluded or not from the
analysis.
As it follows from table 3, stability in parties and in
party relations need not go hand in hand. About one
quarter of the cases are characterized either by relatively
institutionalized parties but not systems, or the other way
round. The configuration of chaotic inter-party relations
despite the existence of socially rooted and organization-
ally continuous parties is well exemplified by Finland.
During the interwar period virtually all combinations
Figure 1
Correlations between PSI and PI and their
components
Figure 2
Average party and party system
institutionalization over time (1900-2021).
−0.6
−0.3
0.0
0.3
1900 1925 1950 1975 2000 2025
standardized values
party institutionalization party system institutionalization
7
https://doi.org/10.1017/S1537592723002530 Published online by Cambridge University Press
among the Socialists, the Agrarians, the Communists, the
Liberals, the Conservatives, and of the party of the Swedish
minority, were tried. Most governments relied on the
right-wing and centrist parties, but the Socialists were also
able to form a government. Politics changed significantly
after World War II, but the logic of complex
re-combinations of well institutionalized parties contin-
ued. The same applies to the French Third Republic,
where the individual parties achieved a high level of
institutionalization, but the system remained unstable.
With the exception of the Communists all major political
forces participated in coalition-making. Out of the 61 gov-
ernments only 15 had a familiar party combination.
At the opposite end of the spectrum, in Fifth Republic
France, Hungary, the Netherlands or post- World War II
San Marino, to name a few, the splits and disappearance of
individual parties did not undermine the development of
meaningful systemic level patterns, providing these cases
with relatively high closure scores and low PI scores.
The relatively weak correlations, the occasionally
diverging temporal trends, and the existence of cases that
excel on one dimension but lag behind on the other one
indicate that PI and PSI, while related, are still different
phenomena. However, can one of them be considered to
be the cause of the other? This is a question we address in
the following section.
Parties or Party Systems: The Chicken or
the Egg?
In general, we test for what is known as Granger causality
(Granger 1969)—whether the past values of one time
series are able to predict the future values of another time
series. This approach has its weaknesses (e.g., Freeman
1983) as it is only able to establish mechanical temporal
precedence that should be interpreted through theoretical
expectations. Temporal precedence does not prove cau-
sality, but it constitutes a major and empirically verifiable
precondition of it.
We first test for Granger causality in panel data using
the method suggested by Dumitrescu and Hurlin (2012)
and implemented in the “plm”(Croissant and Millo 2008)
package in R (R Core Team 2022). The method imple-
ments a series of Granger tests per unit (country) and
provides a hypothesis test for whether there is evidence for
Granger causality in the panel as a whole. This can mean
that there is evidence for causality for some of the units,
but not necessarily all. We run the test for the aggregated
indices using lags from 1 to 5 years (which limits the party
systems that we can include in this particular analysis to
those that have more than 20 observations—i.e., 36 party
systems).
We then test for the causal sequences across years within
party systems using a fixed-effects panel model with lagged
dependent variables to account for serial correlation and
lagged predictors. That is, we test if the variation of PI
within party systems is associated with subsequent varia-
tion of PSI or vice versa. We use one-, two-, and five-year
lags for the predictors in our models to allow for the
potential causal effect to play out over various periods
of time.
In general, we follow the logic suggested by Beck and Katz
(2011) for the analysis of time-series cross-section data. As
the units of analysis are countries that constitute the whole
population and as we are not aiming to draw direct conclu-
sions beyond our population, a fixed-effects model is pref-
erable over a random-effects model (Hsiao 2014,48-49).
Our dependent variables are correlated over time and this
introduces serial correlation into the model, which can be
addressed by including lagged dependent variables. We are
aware that in a fixed-effects panel model this introduces bias
into the estimates, but also that this bias is mitigated as the
number of over-time observations per unit (democratic
periods of party system) is considerable (Beck and Katz
2011,342).Wefit the models using the “plm”package
(Croissant and Millo 2008)inR(RCoreTeam2022), using
partysystemaswellasyearofdemocracyfixed effects to take
into account the fact that levels of PI and PSI might differ for
Table 3
Party and party system institutionalization across 60 political systems
Institutionalized Parties Non-Institutionalized Parties
Institutionalized systems Austria II, Denmark, Germany II, Greece
III, Liechtenstein, Luxembourg, Malta,
Norway, Portugal, Spain II, Sweden,
Switzerland, UK
Albania, France IV, Georgia, Hungary,
Iceland, Ireland, Montenegro,
Netherlands, San Marino II
Inchoate systems Austria I, Belgium, Cyprus, Finland I & II,
France III
Andorra, Bulgaria, Croatia, Czechia,
Czechoslovakia, Estonia I & II, France I &
II, Germany I, Greece I & II, Italy, Kosovo,
Latvia I & II, Lithuania, Moldova, North
Macedonia, Poland I & II, Romania,
Russia, San Marino I, Serbia, Slovakia,
Slovenia Spain I, Turkey I, II & III, Ukraine
8Perspectives on Politics
Article |Party and Party System Institutionalization
https://doi.org/10.1017/S1537592723002530 Published online by Cambridge University Press
different party systems and that there might be a pattern of
variation that depends on the time that a party system has
been democratic (e.g., PSI tends to be lower in the earlier
years of the system). A fixed-effects model like this analyzes
associations with respect to the time or panel unit means,
i.e., the variables are effectively centered around the unit
means. Variation between countries or regions is thus taken
out of the picture. Finally, we use robust standard errors as
suggested by Beck and Katz (1995).
In order to illustrate the full effect of our variables of
interest in the panel models with lagged dependent vari-
ables, we show the long-term effects of the predictors that
take into account how the effect carries on through the lag
of the dependent variable (Beck and Katz 2011, 336) as
well as the confidence intervals for these long-term effects
calculated using the delta method as implemented in the
“msm”package (Jackson 2011) in R (R Core Team 2022).
Finally, as robustness checks we also present the results
of models that focus on the components of the indices, as
well as models containing additional covariates that could
help to explain variation in both party and systemic
institutionalization. We also run the primary analysis
using an alternative approach for serially correlated data
—the Prais-Winsten estimator for AR(1) serial correlation
(Prais and Winsten 1954). This method estimates the
serial correlation (ρ), transforms the data accordingly,
and fits an OLS model to the data.
The overall Granger causality tests in the panel between
PSI and PI indicate that there is evidence of causality
moving from PI to PSI (Z-tilde = 9.22, p-value < 0.001),
rather than from PSI to PI (Z-tilde = 1.36, p-value = 0.17).
This suggests that for at least some of the party systems in
the data set there is indication for a temporal sequence in
the data. Changes in PI help to predict subsequent changes
in PSI and not the other way around. Malta, Germany,
and Italy illustrate well the causal pattern. In Malta the
predictable two-party system could build on the well-
entrenched political organizations of Labour and of the
Nationalists, with very strong social roots dating back,
respectively, to “the Riformisti, who favored British policy,
and the anti-Riformisti, who upheld Italian language and
culture,”political movements in the late nineteenth cen-
tury (Carammia and Pace 2022, 113). In Germany, party
relations became routinized after the Christian Democrats
achieved their final shape through mergers and absorp-
tions. In Italy, the seven main political parties
(i.e., Communists, Socialists, Social Democrats, Republi-
cans, Liberals, Christian Democratic, and neo-Fascists)
were socially rooted and organizationally stable well before
Sartori’s(1976) polarized pluralist pattern of inter-party
competition, with the Christian Democracy making gov-
erning coalitions with all major parties except the Com-
munists and the neo-Fascists, consolidated in the early
1960s. Italy illustrates well the typical logic of
de-institutionalization too: it was the dissolution of six
of those seven political parties in the mid-1990s that led to
the collapse of the party system and the appearance of
socially less anchored and organizationally weaker political
forces.
The data suggest that in only three cases—Andorra,
Denmark, and North Macedonia—was the institutional-
ization of parties preceded by the consolidation of the
party system. Out of the three, Andorra is the most
extreme case: the current-day protagonists of the party
system (the Democrats for Andorra and the Social Dem-
ocratic Party) were established only at the beginning of the
twenty-first century, following a long period of predictable
party politics structured around the Liberal Party, a party
of “notables”(Minoves 2022, 80).
Table 4, showing results of panel data regressions,
provides further evidence for PI preceding PSI. Both
one-, two-, and five-year lags of PI indicate a positive
association to PSI at time t, while for PSI there is no
association for the one- and two-year lagged values. We do
see a positive association with PSI at t-5 and PI at t, but
compared to the effects of PI on PSI, this association is
with much more uncertainty.
The corresponding standardized long-term effects that
consider how a change carries forward in time through the
lagged DV are shown in figure 3. Note that even though
the instantaneous effect of PSI (t-5) on PI (t) is smaller
than the effects of PSI on PI, the fact that the serial
correlation for PI is much stronger means that the long-
term effects are comparable. But even so, there is clearly
more evidence for potential causality running from PI to
PSI than vice versa.
In order to test the robustness of these findings, we
repeated the analysis substituting our indicators for other
suggested measures of party and systemic institutionaliza-
tion. We used electoral volatility and parliamentary frag-
mentation as substitutes for closure and the Varieties of
Democracy (VDEM) (Coppedge et al. 2021) party institu-
tionalization index (v2xps_party) as well as two of its
components, the party organization index (v2psorgs) and
the party linkages index (v2psprlnks), as substitutes for our
PI index. The party organizations index captures the extent
to which parties have permanent organizations and the party
linkages index measures the extent parties have program-
matic, as opposed to clientelistic, linkages to constituents.
In our yearly data set, closure has a correlation of -0.3
with parliamentary fragmentation and -0.43 correlation
with electoral volatility. The negative correlations reflect
that for both of these alternative measures of PSI, higher
values should indicate less institutionalization. The
VDEM overall party institutionalization index has a cor-
relation of 0.32 with our indicator of PI, the party
organizations index has a correlation of 0.26 (0.44 with
party age) and the party linkages index has a correlation of
0.22. In other words, the associations are weaker, but they
are all positive and significant.
9
https://doi.org/10.1017/S1537592723002530 Published online by Cambridge University Press
Substituting fragmentation for closure (figure A4 in the
online appendix) we see that PI at time t-1 is related to
fragmentation at time tin the expected direction, but the
coefficient was not significant with the other two time lags.
Substituting volatility for closure (figure A5 in the online
appendix), we found that PI predicted electoral volatility
in all three-time lag specifications. Replacing our PI
measure with the VDEM indicators (figures A6–A8 in
Table 4
Two-way fixed effects panel models with lagged dependent variables (DV) and lagged
predictors (standardized coefficients)
Dependent variable:
PSI (t) PI (t)
(1) (2) (3) (4) (5) (6)
DV (t-1) 0.634*** 0.639*** 0.736*** 0.931*** 0.928*** 0.929***
(0.020) (0.019) (0.017) (0.009) (0.009) (0.009)
PI (t-1) 0.062*** —————
(0.018)
PI (t-2) —0.067*** ———
(0.017)
PI (t-5) ——0.036* ———
(0.015)
PSI (t-1) ———–0.011 ——
(0.006)
PSI (t-2) ————–0.007 —
(0.006)
PSI (t-5) —————0.013*
(0.006)
Observations 2,400 2,393 2,239 2,400 2,340 2,168
Adjusted R
2
0.420 0.439 0.572 0.866 0.865 0.869
Note: *p<0.05; **p<0.01; ***p<0.001
Figure 3
Long-term effects between PI and PSI
closure (t) PI (t)
PI (t−1) PI (t−2) PI (t−5) closure
(t−1)
closure
(t−2)
closure
(t−5)
−0.2
0.0
0.2
0.4
cause
long−term effect
10 Perspectives on Politics
Article |Party and Party System Institutionalization
https://doi.org/10.1017/S1537592723002530 Published online by Cambridge University Press
Figure 4
Long-term effects of components of PI on PSI
alternation (t) formula (t) access (t)
EPD (t−1)
EPD (t−2)
EPD (t−5)
party age (t−1)
party age (t−2)
party age (t−5)
EPD (t−1)
EPD (t−2)
EPD (t−5)
party age (t−1)
party age (t−2)
party age (t−5)
EPD (t−1)
EPD (t−2)
EPD (t−5)
party age (t−1)
party age (t−2)
party age (t−5)
−0.2
0.0
0.2
0.4
0.6
cause
long−term effect
11
https://doi.org/10.1017/S1537592723002530 Published online by Cambridge University Press
Figure 5
Long-term effects of components of PSI on PI
EPD (t) party age (t)
alternation (t−1)
alternation (t−2)
alternation (t−5)
formula (t−1)
formula (t−2)
formula (t−5)
access (t−1)
access (t−2)
access (t−5)
alternation (t−1)
alternation (t−2)
alternation (t−5)
formula (t−1)
formula (t−2)
formula (t−5)
access (t−1)
access (t−2)
access (t−5)
−0.4
−0.2
0.0
0.2
0.4
cause
long−term effect
12 Perspectives on Politics
Article |Party and Party System Institutionalization
https://doi.org/10.1017/S1537592723002530 Published online by Cambridge University Press
the online appendix), we received significant results only
in one instance: VDEM’s party organizations index at time
t-5 helped to predict closure at time t.
To summarize the robustness checks, they largely con-
firmed the pattern found with our measures, but the
results were typically less strong and less clear (refer to
the online appendix for more detail).
We ran the same analyses that are reported in table 4
also on the components of the two indices separately and
the long-term effects from these models are shown in
figures 4 and 5(refer to tables A1-A5 in the online
appendix). These results give us further details about the
structure of potential causality between party and systemic
institutionalization. We see that both established party
domination and the average age of parties are positively
related to subsequent PSI on the dimensions of formula
and access. This is equally true for 1-, 2-, and 5-year lags
for the predictors. Alternation, however, seems to capture
something different as alternation at time tis not related to
the components of PI across all time lags.
If we look in the other direction, as shown in
figure 5, we see that the positive association between PSI
and PI is driven by established party domination at time t
being related to formula and access at time t-5. We see a
positive association also for alternation at t-5, but the
confidence interval for that association narrowly crosses
0. There is no association between average party age at
time tand the components of PSI at times t-1, t-2 and t-5.
Following the existing literature on the institutional-
ization of party politics (see especially Bolleyer and Ruth
2018;Lupu2016;Tavits2005,2008;2013,Mainwar-
ing and Bizzarro 2018; Casal Bértoa and Enyedi 2021),
we modeled our main variables (PI & PSI and their
components) and the potential causal associations
between them also through models that included various
institutional, economic, and political variables tradition-
ally used to represent different aspects of the environ-
ment of party politics as contemporaneous predictors,
namely:
a) the electoral system, whose impact is operationalized
through Gallagher’s(1991) the least-squares index of
disproportionality;
b) economic development, measured using the logarithm
of GDP per capita of the election years (Gapminder
2021);
c) fragmentation, calculated through the Laakso and Taa-
gepera (1979)effective number of parliamentary
parties index; and
d) polarization, captured by the percentage of votes for
anti-political-establishment parties
9
(cf. Karvonen and
Quenter 2002; Powell 1981).
The detailed results of these analyses are reported in
tables A6 and A7 in the online appendix. In none of the
models did the results reported here change substantially
(only the uncertainty related to the estimates increased, as
expected).
Finally, we also tested for the potential causal sequence
using the Prais-Winsten estimator, which is reported in
table 5. The results for this model echo what was shown
earlier—that past increases in PI help to predict future
increases in PSI and not vice versa. One major notable
difference here is that the model shows a negative associ-
ation between PSI at t-2 and PI at time t. But this only
strengthens the overall conclusion that increased PI is
more likely to eventually lead to increased PSI and not
the other way around.
Conclusions
We started our article with the expression of unease con-
cerning the fact that systemic institutionalization is often
measured by phenomena that pertain to individual parties
and have little to do with the systemic level of party politics.
Conceptually, change in parties does not necessarily mean
party-system realignment, and the reconfiguration of inter-
party relations may happen leaving the roster of parties intact.
Building on Casal Bértoa and Enyedi (2021), but
considering a longer period of time and using a different
methodology, we have confirmed that the empirical sep-
aration of the institutionalization of political parties and
the institutionalization of party systems reveals the exis-
tence of dynamic processes that run in parallel in some
periods (between the 1930s and the 2000s) of European
history, but diverged in others (1900–1930, 2000–2020).
But the major novelty of the current exercise is the
establishment of a temporal sequence.
The analysis led us to conclude that out of the two
phenomena, PI is the prime mover. In order to achieve a
predictable system, it seems that one needs to stabilize the
parties first. Mair (1997) suggested the opposite logic: that
disloyalty among parties will trigger the infidelity of voters
to their favorite party, and thereby party system change
will undermine the stability of individual parties. Our
results do not deny the possibility of such scenarios, but
the prevailing model appears to be the opposite: an
increase in the stability in party relations is predicated on
increasing the stability of individual parties.
In the context of European politics, our analyses have
shown that there is an overall tendency of deinstitution-
alization, as suggested by many observers, but this ten-
dency is much stronger at the level of parties. At the level of
party relations, the signs of disintegration are less obvious.
Considering, however, what we have found in terms of the
causal sequence between PI and PSI, there are good
reasons to expect a shift towards openness at the systemic
level in the near future.
From an academic point of view, the fundamental
recommendation of our article is to measure systemic
institutionalization through indicators of party interactions
13
https://doi.org/10.1017/S1537592723002530 Published online by Cambridge University Press
and not by aggregating the features of individual parties.
This empirical strategy opens the door to establishing and
comparing the causes of the two types of institutionaliza-
tions, an exercise that requires further work.
Such a separation is necessary, because PSI and PI may
be relevant for different political outcomes. Our study
showed that PSI is not a good predictor of institutionalized
parties, but Ridge (2022), for example, recently found that
it increases satisfaction with democracy, irrespective of the
levels of party affection. The systemic level appears to be
crucial for the survival of democracy (Casal Bértoa 2017),
but too-predictable party relations may dampen the qual-
ity of democracy under certain conditions (Casal Bértoa
and Enyedi 2021; Mölder, Enyedi, and Casal Bértoa
2023). PI, on the other hand, has been identified as factor
behind partisan mobilization (Ponce and Scarrow 2022),
successful anti-corruption efforts (Schleiter and Voznaya
2018), economic development (Bizarro et al.2018), and
more extensive and universal welfare (Rasmussen and
Knutsen 2021). These results suggest not only that we
need to care about these phenomena, but also that we need
to systematically distinguish between them.
Our findings have further relevant practical implications.
It seems that practitioners and democracy promotion insti-
tutions interested in higher degrees of institutionalization
should invest primarily into party building. The establish-
ment of socially rooted parties is not only conducive to
healthy linkages between teams of representatives and their
voters, but in time it also leads to transparent relations
among parties and predictable government-building. Our
findings cast doubt on the focus on institutional factors
whose primary role is to create stable governments, clear
governmental responsibility, and stable alternation in
power. These features may be beneficial for the consolida-
tion of democracies, but they do not foster the development
of robust, institutionalized political parties. They put the
cart before the horse. If parties are strengthened and
consolidated, however, then we do not only forge a con-
nection between citizens and the state, but we also increase
the likelihood that regular interactions develop among the
government-oriented political parties.
There is nothing in our argument that would limit the
presented logic to a specific time period, specific region, or
constitutional order, but such variations are, of course,
possible. Within Europe, geographical regions do not
diverge, and the one presidential country (Cyprus)
behaved like the parliamentary countries from the point
of view of the established temporal pattern. Nevertheless,
further studies, working with larger geographical scope, are
required to provide us with firm conclusions in this regard.
Our analysis focused on the sequence between the
institutionalization of parties and party systems. Obvi-
ously, the relation between these two phenomena is nested
into an environment that contains factors that constrain
Table 5
Results from Prais-Winsten AR(1) model (standardized coefficients, panel corrected standard
errors)
Dependent Variable:
PSI (t) PI (t)
(1) (2) (3) (4) (5) (6)
intercept –0.358 –0.279 –1.329 –0.026 –0.019 –0.085
(0.501) (0.336) (0.280) (0.342) (0.345) (0.355)
PI (t-1) 0.092* —————
(0.034)
PI (t-2) —0.116** —— — —
(0.036)
PI (t-5) ——0.088*** ———
(0.024)
PSI (t-1) —— —–0.001 ——
(0.009)
PSI (t-2) —— — —–0.020** —
(0.008)
PSI (t-5) —— — — —–0.008
(0.009)
Country FE Yes Yes Yes Yes Yes Yes
Time FE Yes Yes Yes Yes Yes Yes
Rho 0.58 0.59 0.75 0.94 0.94 0.94
Observations 2,400 2,393 2,239 2,400 2,340 2,168
Adjusted R
2
0.28 0.29 0.27 0.07 0.07 0.07
Note: *p<0.05; **p<0.01; ***p<0.001
Standardized coefficients, panel corrected standard errors
14 Perspectives on Politics
Article |Party and Party System Institutionalization
https://doi.org/10.1017/S1537592723002530 Published online by Cambridge University Press
both. An effective and autonomous state, for example, is
likely to be a precondition for both, while the emergence
of new social cleavages may undermine party organizations
and party alliances equally. While existing research has
uncovered many of the potential causal factors, more work
is needed that systematically and symmetrically separates
the party and the systemic levels. Which of these levels is
more vulnerable to social upheavals, to the changes in the
communication technologies or to the institutional
reforms? We believe that these questions need to play a
central role in the agenda of party politics research.
Finally, we focused on the “what comes first’question,
but the interaction between the two analyzed levels has
many further, here unexplored, aspects that we can only
speculate on. The cross-temporal positive correlations
allow for the possible existence of virtuous and vicious
cycles of institutionalization, but they also leave some
room for occasional functional trade-offs. It is imaginable,
for example, that in certain historical periods a country can
“afford”the frequent replacement of parties because the
alliance structures (left versus right, isolationist versus
expansionist, urban versus rural and the like) are relatively
stable, and therefore the continuity of the political system
is not threatened by the dis/appearance of specific actors.
Equally, the disturbance stemming from a shift of alle-
giance (e.g., a hitherto right-wing liberal party becoming
part of the leftist bloc) may be less damaging due to the
robust continuity at the party level. In order to study the
working of such functionalist logics one would need to
climb further on the ladder of abstraction, and to analyze
the political system as a whole, establishing the role of
parties and party systems within the political system.
Supplementary Material
To view supplementary material for this article, please visit
http://doi.org/10.1017/S1537592723002530.
Acknowledgments
The authors would like to express their gratitude to the
four reviewers of this paper. Their insightful and demand-
ing comments helped to considerably improve this paper.
Notes
1 International aid can focus on strengthening political
parties (Burnell and Gerrits 2012) or on the stabiliza-
tion of the party systems (Casal Bértoa 2017), or both.
2 Birnir (2005) provides a rare example of the opposite
practice: she used a systemic level phenomenon (elec-
toral volatility) to characterize party institutionalization.
3 Some even discuss party stability as a component of
systemic stability (Chiaramonte and Emanuele 2017;
Mainwaring 2018).
4 Our particular analyses, depending on the lags that we
use for the variables, will have a slightly shorter temporal
duration.
5 Casal Bértoa and Enyedi (2016, 269-270; 2021, 34-45)
provide further details on the calculation of the closure
index.
6 This threshold allows us to cover almost all European
parliamentary parties as most electoral thresholds (with
the exception of the ones in the Netherlands and
Denmark) are at or above 3%.
7 EPD is a modified version of Lewis’s(2006)Party
Stabilization Index. That index increased a party vote
share at each election by 20%, assuming that the time
between elections is equal (e.g., four years). To bring the
calculus closer to real-life dynamics (in real life the time
span between electionscan vary from a couple of months
to a couple of years), and to make the results comparable
to the results of Lewis, we have decided to increase the
vote share of a party by 5% per every single year (20%
divided by the average assumed number of years between
elections). If this parameter in the equation is decreased
to 0, the index is reduced to the sum of the vote shares of
the parties that are taken into account. The higher the
parameter, the more the value of the index depends on
large parties that have been around since the beginningof
the party system. Simulations of the index on our data set
showed that there are marginal changes in the value of the
EPD index if the parameter is increased beyond 5%.
8 Following Casal Bértoa and Mair (2012), we exclude
most 1) constitutional assembly elections (e.g., Austria
in 1919; Bulgaria in 1990; Estonia in 1919; France in
1848, 1871, and June 1946; Italy in 1946; Latvia in
1920; Luxembourg in 1918; Poland in 1919; Portugal
in 1975; and Spain in 1977); 2) “breakaway”
(i.e., regime referendum) elections (e.g., Poland in
1989, Czechoslovakia in 1990) and pre-independence
elections (e.g., Estonia, Latvia, Lithuania, Moldova,
North Macedonia, Slovenia, or Ukraine in 1990).
9 An anti-political-establishment party is a party that
fulfills the following criteria: “a party that challenges the
status quo in terms of major policy issues and political
system issues; a party that perceives itself as a challenger
to the parties that make up the political establishment; a
party that asserts that there exists a fundamental divide
between the political establishment and the people. It
thereby implies that all establishment parties be they in
government or in opposition are essentially the same.”
(Abedi 2004, 12). We take the list of anti-political-
establishment parties from Casal Bértoa (2022). As
opposed to the closure and PI indices, this index of
polarization is not adopted because of its theoretical
superiority over other—e.g., ideology-based—mea-
sures, but because it is available for more countries and
more time periods. The anti-establishment index cor-
relates with Dalton’s(2008) left-right polarization
15
https://doi.org/10.1017/S1537592723002530 Published online by Cambridge University Press
index at 0.7 across party systems (Casal Bértoa and
Enyedi 2021).
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