Government Survival the Italian Way:
the Core and the Advantages of Policy Immobilism during
the First Republic
Luigi Curini
Università degli Studi di Milano
Published in “European Journal of Political Research”, 50, 2011, 110-142
Abstract
During its nearly fifty years of history, the First Italian Republic has been characterized by the
highest rate of cabinet turnover in Western Europe. There are several convincing explanations of
this exceptional feature. Nevertheless, merely looking at the average figure risks overlooking the
variety in the Italian government experience. Focusing on the spatial determinants of Italian cabinet
duration, shows that the presence of a core party has a positive albeit conditional impact on
government duration, largely depending on the degree of intra-cabinet conflict. Moreover,
whenever the core is absent, the inability of cabinets to change the status quo appears to lengthen,
rather than shorten, their duration. This outcome appears in line with works stressing the substantial
policy immobilism of Italian governments throughout most of the post-war period. The analysis
relies on a new dataset based on a coding of the investiture debates of all the Italian cabinets. This
allows one to track the evolution of parties’ preferences in a policy space that can change between
(rather than only across) elections. The results show the importance of in-depth case studies to
better analyse some puzzles within the cabinet duration literature that might otherwise be averaged
out in large-N comparative analysis.
Keywords: cabinet duration; spatial theory of voting; Italian party system; event history analysis;
legislative speeches
1
Introduction
During its nearly fifty years of history, the so-called First Italian Republic (1946-94) had the highest
rate of cabinet turnover in Western Europe, at more than twice the regional average (Muller &
Strøm 2000). There are several convincing explanations for this exceptional feature (see, for
example, Mershon 1996). Nevertheless, merely looking at the average figure ignores the variety in
the Italian government experience: from the 77 days of the fifth Moro cabinet to the almost 3 years
of the first Craxi cabinet, the far from negligible variance in the duration of Italian governments is
worthy of analysis.
In the present study, I move beyond the aggregated data analysis so well developed in the
literature on cabinet duration, to a more detailed and case-specific analysis. One difficulty with the
large volume of research on cabinet duration is that a variety of system-level variables profitably
employed in the literature (specific institutional features such as the need of an explicit vote of
investiture or the type of party system; see Saalfeld 2008; Grofman 1989) are especially good in
explaining between-country variations, but are less helpful in accounting for variations in cabinet
length within a given country, given their viscosity at least in the medium term. In the latter
situation, particular attention must be devoted to variables that are more closely linked to the
context under study (on this point, see also Grofman & Van Roozendaal 1994).
Focusing on the spatial determinants of Italian cabinet duration shows that the presence of a
core party exerts a positive albeit conditional impact on government duration, largely depending on
the degree of intra-cabinet conflict. Moreover, whenever the core is absent, I find a surprising result
opposite from the ‘received wisdom’ in the literature: the inability of cabinets to change the status
quo appears to lengthen, rather than shorten, their duration. However, this outcome appears in line
with works stressing the substantial policy immobilism of Italian governments throughout most of
the post-war period (Cotta & Verzichelli 1996; Verzichelli & Cotta 2000).
Our analysis relies on a new dataset based on a coding of the investiture debates of all Italian
governments from 1946 to 1994. As explained below, this allows me to track the evolution of
parties’ preferences in a policy space that can change between (rather than just across) elections. In
the conclusion, I emphasize the importance of in-depth case studies to better analyse some puzzles
within the cabinet duration literature that might otherwise be averaged out in large-N comparative
analysis.
Spatial theories of cabinet stability: the Italian case and the (conditional) role of the core
A distinctive feature of the Italian political system during the so-called First Republic was the
extremely high level of cabinet turnover, at least when compared to other Western European
democracies.1 In spite of this well-established empirical feature, the determinants of government
turnover in post-war Italy are not very well understood (see Cioffi-Revilla 1984; Merlo 1998).
Figure 1 maps the kernel density estimate of cabinet duration (in days) for the 54 Italian
governments from 1946 to 1994.2 The median cabinet duration is 217 days (less than 8 months);
yet, as the distribution shows, there is significant variation: overall, 25 per cent of Italian
governments lasted less than 5 months, while another 25 per cent lasted at least 14 months (almost
twice the median).
Figure 1
2
I argue that spatial considerations can be particularly useful to explain this variance in
cabinet duration. In a spatial framework, the location of parties indicates their preferred or ideal
positions on the salient dimensions comprising the relevant policy space. The degree to which a
party favours any given policy (including the policy agreement pledged by a forthcoming
government) is therefore inversely proportional to the distance between that policy’s location and
the party’s ideal point. Various game theoretic models have been proposed to study government
duration. Some of them focus on the spatial attributes of government parties (in particular on their
ideological proximity) as well as the allocation of cabinet portfolios as the main determinants of
government stability (see Tsebelis 2002; Laver & Shepsle 1996).
These models rest on the crucial assumption that governments (or ministries within them)
have full control of the agenda. However, the institutional agenda setting that advantages the
government is not the same everywhere. For example, Doering (1995) shows that Italian
governments possess far less institutional leverage than the average European government to defend
their proposed changes to the status quo from being altered on the parliamentary floor during the
policy-making process. Doreing’s analysis is a snapshot of the situation during the 1980s, but
things were no different in earlier decades. Until 1971, to take another example, there was no
ceiling in either chamber on the number of bills that private members could propose (Mershon
1996), while prior to 1988 most votes in parliament were secret.
Another factor that negatively affected the ability of Italian cabinets to control the agenda
was the weakness of coalition discipline, as clearly evidenced by the high proportion of government
bills not passed by parliament, frequent bargains struck with the opposition, and the large number of
parliamentary amendments accepted by the government (Verzichelli & Cotta 2000). The interplay
among these institutional and political aspects resulted in cabinets that were particularly weak in
their relationship to parliament during the entire period considered here (Di Palma 1977).
To account for this phenomenon, it is therefore more promising to start with a theory that
does not assign any special role to the government as a political actor in the process of its formation
and stability, but instead focuses explicitly on parliamentary dynamics. The theory of the core party
(Laver & Schofield 1990; Schofield 1993, 1995; Schofield & Sened 2006) has this characteristic. A
core party is a party occupying a position in the policy space that cannot be defeated in a majority
vote. In one dimension, the party whose support coalition includes the median voter will be the core
party, and such a party will always exist. In contrast, in multiple dimensions, a core party will exist
only when all median lines (that is, lines presenting a majority in both closed half spaces created by
each line) intersect at one party’s ideal point, which for that reason constitutes the core party.
Moreover, a core party can be structurally stable or unstable. There is a structurally stable
core (or a strong core) when small changes in party locations do not affect its status. In general,
only the largest party in the parliament can aspire to become a structurally stable core. However,
this is a necessary but not sufficient condition (Schofield 1995). On the other hand, a structurally
unstable core will collapse if such movements are allowed. I will return later to the substantial
implications of this point.
Figure 2 presents two different situations taken from the Italian case analyzed here. Both the
policy space and party positions depicted are estimated using a methodology that will be explained
in detail in the following section.
Figure 2
On the upper panel I illustrate the policy space during the third cabinet of the Christian
Democratic Prime Minister Mariano Rumor, a government that started in February 1970 and lasted
for only four months. The two dimensions defining the space are economic policy (on the horizontal
axis), contrasting pro-state with pro-market attitudes, and social policy (on the vertical axis),
contrasting progressive with traditional views concerning moral values as well as anti- or proclerical positions. Party positions are represented as points in this space, and the utility a party gets
from a policy x is assumed to be a function of the Euclidean distance between x and xi, where xi
3
denotes the most preferred policy position of party i. In this sense, each party seeks to reach a policy
point as close to its ideal points as possible. The figure shows that, in the case of the Rumor III
cabinet, the median lines do not intersect at one point. In the absence of a core, my assumptions
lead to an expectation of instability. Because there is no undominated policy point in the space, any
majority coalition that forms around a given point can be upset by another majority coalition whose
members all prefer another policy point. In particular, it can be shown that, assuming that no policy
proposals will be made that render all members of a majority coalition worse off, any points in the
policy space that are Pareto optimal for every majority coalition can be solutions to the bargaining
game among parties. This space locus, called the cycle-set, is delimited in the figure by the
following parties: DC, PSI, and PLI.
In contrast, on the lower panel of Figure 2 I represent the situation during the fifth Rumor
cabinet, which took office in March 1974 and lasted twice as long as the Rumor III cabinet. As the
figure shows, in this case the two policy dimensions (economic and social policy) defining the
space remain the same as in Rumor III. Note that this is not always the case, given that the
substantial meaning of the policy space can change (see discussion below). In this policy space all
the median lines do intersect on the DC party, which as a result becomes a core party. This can also
be seen by noting that the DC now lies inside any Pareto set of all possible parliamentary majorities
that excludes it. Moreover, the DC is also a strong core party in this situation, given that it is not
vulnerable to slight shifts in party positions. When such a situation is encountered, negotiations
among parties will lead to a coalition government with the core party as a member and its ideal
point as a policy programme (Laver & Schofield 1990)3.
The core theory is mainly aimed at explaining the existence of policy stability. However,
Schofield and his co-authors (Schofield et al. 1988) argue that the presence of a core party also
enhances cabinet stability by giving the core party a strong bargaining position. The reason is that,
even though possible coalition partners of the core party are unable to influence the government’s
policy programme, the very unbeatability of core policies in the parliament, plus the non-policy
benefits of government membership, should generally discourage any defection from the coalition.
This results in extended cabinet duration (see also Warwick 1994 on this point).
Note, however, that until now no assumption has been made concerning the (expected)
electoral costs that parties endorsing the policies of a government will eventually have to bear.4
Still, party leaders are, to a varying degree, attached to their party’s policies. This concern with
policy is not necessarily sincere; parties may profess to care about policies simply because their
voters care about them. Precisely for this reason, the prospect of electoral unpopularity incurred
from continuing to support a government policy programme particularly distant from the one
favoured by a party’s own constituency could lead a party to move to the opposition. After all,
opposition parties do not have access to any office benefits deriving from participation in a majority
coalition, but at least avoid the (electoral) cost of endorsing policies that deviate (significantly) from
their declared positions (see Giannetti & Sened 2004: 489).
Thus, it is easy to imagine a situation in which, given sufficient ideological diversity among
cabinet members, the core party’s coalition partners become more and more dissatisfied with
respect to the policy equilibrium dictated by the core party itself, and increasingly frustrated for not
being able to affect it, given the asymmetric distribution of bargaining power within the cabinet.5
This will either a) induce them to leave the coalition, regardless of the non-policy benefits that they
lose, or b) compel the core party to substitute the recalcitrant government partners with more
acquiescent allies. By doing this, political stability is disturbed while policy stability is not affected.
Accordingly, I can develop the following conditional hypothesis:
Conditional Core Hypothesis: in the presence of a core party, the less intense
intra-cabinet conflict, the higher the cabinet stability.
4
The conditional hypothesis rests simply on the assumption that parties care about both office
holding and policy benefits and that they are ready to give up on policy benefits in exchange for
office holding, but only up to a certain degree (see also Sened 1995, 1996). To test if this hypothesis
accurately accounts for Italian cabinet duration, I first need to estimate the policy space (and its
evolution) over fifty years of the Italian First Republic, and then analyze my data with an
appropriate statistical technique.
The Italian policy space between 1946 and 1994: a new dataset
Our analysis relies on a new dataset based on a coding of all investiture debates during the Italian
First Republic. According to the Italian Constitution, the power to nominate the Prime Minister is
given to the President of the Republic. Usually the newly formed government goes to the
Parliament shortly after its formal nomination to seek investiture through a positive vote of
confidence. In particular, the Prime Minister, nominated but not yet inaugurated, has to deliver
official speeches in the Lower House (Camera dei Deputati) and the Upper House (Senato della
Repubblica) of Parliament.6 On both occasions, the premier expounds in detail the government’s
future policy proposals. After each speech, parliamentary debate is opened and various party
representatives are allowed to speak, discussing the wide range of issues mentioned by the Prime
Minister and concluding with a vote of confidence. I can therefore treat the investiture debates as a
set of comprehensive speeches addressing a wide range of policy issues, which disclose policy
proposals and expectations of both government and opposition parties (see also Curini & Martelli
2009, Ieraci 2008).
For each vote of investiture (from the second De Gasperi cabinet in 1946 during the
Constituent Assembly to the first Ciampi cabinet in 1993 during the Eleventh Legislature; see
Appendix 1) I selected and coded one speech from each party, for a total of 420 texts.7 Whenever
possible, I chose the speech of the party leader. Otherwise, I selected the most relevant MP for each
party among those who participated in the parliamentary debate.
To code the legislative speeches, I followed the method adopted by the Comparative
Manifesto Project (CMP), which analyzes the contents of party electoral programmes from a large
number of democracies including Italy (see Budge et al. 2001 for a detailed description). More
precisely, for each legislative speech I identified the number of quasi-sentences, which I treat as
coding units, and assigned them to a number of pre-established categories that form the
classification scheme.8 Based on this classification, I built a dataset that contains the percentage of
the total text of each legislative speech dealing with these categories. Moreover, I extended the
original 56 categories of the CMP dataset to 68 to take account of the Italian political context. For
example, I included extra categories to capture all positive and negative references made by parties
to the Catholic Church and the Soviet Union.
Second, following the literature (see Lijphart 1999; Laver & Hunt 1992; Farneti 1980), I
identified a priori eight policy dimensions that reasonably cover the principal aspects of Italian
party competition over the 50 years analyzed here. In addition to economic and social policies, I
also considered: foreign policy (contrasting pro- and anti-Western attitudes); democracy
(contrasting parties favouring a consensual vision of democracy; based on the deliberative role of
the Parliament, to those favouring a majoritarian conception, based on strengthened executive
power); environmental policy (contrasting emphases on economic growth and environmental
protection); centralization of decision making (that is, parties promoting or opposing
decentralization); institutions (contrasting parties supporting and criticizing the 1948 Constitution);
and, finally, justice (contrasting parties promoting the judicial independence with those underlining
the need of greater political control over the judiciary, see Guarnieri 1991).9
5
The association between categories and policy dimensions allows us to define first the
nature of the policy space for each investiture vote, and second party policy positions within this
space. Starting with the former, let Fiylx be the proportion of references party i makes during the
investiture vote y held in legislature l to the categories associated with the policy dimension x. By
+
−
+
definition, Fiylx = Fiylx
+ Fiylx
, where Fiylx
is the percentage of references to the categories associated
−
with the positive polarity of policy dimension x, and Fiylx
is the percentage for the negative polarity.
Moreover, let piyl be the share of legislative seats controlled by party i in legislature l during that
specific vote of investiture. The saliency of the policy dimension x during the vote of investiture y
will then be:
S ylx = ∑ Fiylx ⋅ piyl
(1),
i
where the (weighted) sum is extended to all parties. Following Laver & Hunt (1992) and Benoit &
Laver (2006), I take a weighted average of the saliency scores assigned to each dimension by each
party. This allows us to differentiate between the salience given to a particular dimension by large
and miniscule parties, therefore avoiding the possibility that a relatively small single-issue party
would exercise undue influence on the selection of the policy dimensions structuring the entire
party-system.
Finally, the two most salient dimensions (according to (1)) are taken as the dimensions that
define the relevant policy space for each particular investiture vote (which I treat as fixed until the
next vote).10 Appendix 1 reports the party composition, the two dimensions associated with the
policy space, and the possible presence of a core party for each Italian cabinet (see below).
The evolution of the policy space fits studies of post-war Italian political history (Farneti
1980; Mastropaolo & Slater 1992; Curini & Martelli 2009). The economic policy dimension always
structures the relevant policy space (except in three cases). Foreign policy emerges as a relevant
dimension with the start of the Cold War in 1947, before declining at the end of the 1960s, in
coincidence with the increasing relevance of the social policy dimension which continues to be
important today. On the other hand, the democracy dimension appears to have an intermittent
influence on inter-party dynamics for a decade beginning in the latter half of the 1970s, lasting until
the second Craxi cabinet and the failure of the first Bicameral Commissions in charge of drafting
institutional reform in 1985.
If one assumes that the parties’ latent ideological stance influences which issues would
receive highest priority in legislative speeches, then one can estimate their policy positions by
treating these differences of emphasis as reflecting underlying ideological dissimilarities (Budge et
al. 2001).11 Following the standard way the CMP group computes parties’ policy positions, I
estimated the policy scores of parties along the two dimensions comprising the policy space as the
+
−
difference between Fiylx
and Fiylx
. Moreover, to allow a direct comparison of party positions within
the same policy space and across time, I normalized the previous measure by the salience of each
policy dimension. That is, I define the position Piylx of party i during the investiture debate y within
legislature l along the dimension x as:
+
−
Piylx = ( Fiylx
− Fiylx
) / S ylx
(2).
Normalization is necessary given that the salience of each dimension imposes strict
arithmetic limits on the party position scores that can be estimated (Benoit & Laver 2007). For
example, if the salience of a given dimension increases dramatically across two investiture debates,
a party that presents a radical but constant ideological position along that dimension will obtain a
larger score in the second debate compared to the first one, simply because in the second debate this
6
+
−
dimension records a higher number of references. Normalizing ( Fiylx
− Fiylx
) by S ylx neutralizes this
problem.12
As an illustration, Figure 3 plots the evolution of policy positions of the three main Italian
parties (in terms of both vote share and political relevance) along the economic dimension. The
figure shows that the dynamics of parties is quite convincing as far as face validity is concerned
(see Farneti 1980; Galli 1994). For example, I nicely capture the DC’s clear movement since May
1947 towards a moderate position under the leadership of Alcide De Gasperi, which not only put a
halt to its previous alliance with left parties during the first year of the Constituent Assembly, but
also neglected the largely pro-state positions advocated by the influential left-wing faction led by
Giuseppe Dossetti. The DC only departed from this centrist position at the beginning of the 1980s
when the party placed greater emphasis on a pro-market position under the leadership of Ciriaco De
Mita, before returning to more moderate stances under the subsequent leadership of Forlani and,
most notably, Martinazzoli in the early 1990s. In contrast, the PCI always stands on the left (prostate) side of the scale. However, the radicalism of its ideological stance appears to decline
markedly since the end of the 1960s, coinciding with the leadership of Enrico Berlinguer. After the
brief interlude of his successor Alessandro Natta (1984-1988), the PCI resumed its movement
toward a moderate position in the late 1980s under the leadership of Achille Occhetto, in
coincidence with the transformation of the PCI into the Democratic Party of the Left (PDS). The
Socialist party, on the other hand, mimics the movement of the PCI until Bettino Craxi assumed its
leadership in the second half of the 1970s, after which the PSI shifted towards a more moderate
economic position. 13
Figure 3
In addition to face validity, the convergent validity of my scales also appears to be
satisfactory. I report in Figure 4 policy scores for those parties included in the Laver and Hunt
expert-survey (Laver & Hunt 1992) and the corresponding policy positions (averaged over the last
25 years of the First Republic14) as shown in my analysis with respect to three of the four
dimensions identifying the various policy spaces of Italian governments (policy scores are
standardized to allow direct comparison)15. While a number of flaws can be identified with expert
surveys (see Mair 2001), my purpose is to compare my policy scales with well-known and widely
used benchmarks (for a similar approach, see Gabel & Huber 2000; Laver et al. 2003). As a further
check, I also report the corresponding policy scores found in the CMP dataset.16 The correlations
are consistently high, with my scores providing a better estimate than the Manifesto scores. Thus,
my methodology adequately captures the Italian party policy positions.
Figure 4
Knowing the two-dimensional configuration of parties’ positions (as well as their relative
size), I am able to check for the presence of a core party in each of the governments analyzed. The
results are reported in the last two columns of Appendix 1. Contrary to Schofield (1993, 1995), I
found that the DC was not always a core party. Indeed, in my dynamic policy space, the DC was a
core party in only 19 out of 54 occasions.17
In column (H), moreover, I distinguish between a strong and a weak core. Recall that a
structurally stable core party means that small changes in party locations do not affect its status.
Given that one is always uncertain (to a varying degree) about the precision of estimates of party
policy scores, checking for this is crucial to be sure about the empirical implications of spatialbased theoretical models. This becomes even more important once one recognizes how the method
7
employed here (as with the CMP data; see Benoit et al. 2009) does not naturally involve a measure
of statistical uncertainty, given that I have only one measure for each party on each occasion.
Finally, the well-known (and well-documented) fractionalization of various Italian parties
(Zuckerman 1979) adds to the importance of taking into consideration the uncertainty surrounding
party policy positions, given that the presence of fractionalized party(ies), by itself, increases the
measurement error of my estimates.
To take these problems into consideratiom, I add random disturbance terms to the estimated
party policy positions. More precisely, the random disturbance term added to each policy position
on each dimension was independently drawn for a normal distribution with a mean of zero and a
standard deviation of .05, so that most altered policy positions were on average within 10 per cent
of their original value.18 I simulated this disturbance a thousand times for each core position
reported in column (G), and for each simulation I recorded the size of the corresponding cycle set
(zero when a core party is present, and greater than 0 otherwise). I treat a core as structurally stable
if after a thousand simulations, the mode of the distribution of all the cycle sets for that particular
case is 0 and the median value is less than .05.19 As a result, I am left with 18 stable core parties,
while the only structurally unstable core occurs during the Amato cabinet.
The importance of between-elections dynamics
Compared to the widely used CMP dataset, using a dataset based on investiture debates rather than
electoral programmes presents three main advantages, at least where the Italian case is concerned.
First, whenever a party split or merger modifies the legislative party systems between elections
(Laver & Benoit 2003) I am still able to produce party policy scores for the new entities (provided
an investiture debate occurs after this occurrence, which is likely given the high rate of cabinet
turnover in Italy). This problem is highly relevant in the cases examined. Indeed, in 5 of the 12
periods analyzed here (11 legislatures plus the Constituent Assembly period), the party system
actually changed following an election as a result of party splits and/or mergers.
Furthermore, other events can occur during the life of a legislature that carry relevant
consequences for the political environment in which a government must survive, but which the
CMP methodology cannot capture. First, party policy positions can change due to intra-party
dynamics. This can happen either when a new leader imposes a new policy agenda, or when a new
equilibrium is reached between different factions within a party.20 In the same vein, sudden
political events can change the relative salience of key policy issues (Laver & Shepsle 1998). In this
case, what is modified is the structure of the relevant policy space in which parties interact
strategically rather than party ideal points. Returning to the Italian case, the Soviet invasion of
Hungary in 1956 greatly increased the salience of foreign affairs in the following years for all
parties, and the same happened with social issues just before and after the referenda on divorce in
1974 and on abortion in 1981 (data available upon request).21
With an average of more than four votes of investiture per Legislature, examining the Italian
First Republic is valuable since it allows us to track on an almost annual basis the evolution of
parties’ preferences in a dynamic policy space. Moreover, any estimate reached through my data
will reflect the views of party leaders, and captures legislative, rather than electoral, party
configurations. Given my interest in cabinet survival, that is, in a political outcome that reflects
legislative party configurations, my data collection method represents a further advantage.
Control variables
8
In the following analysis, I draw on the large empirical literature on cabinet survival and control a
number of variables related to party system and government attributes, which have been shown to
be statistically significant in cross-country analyses (see Laver & Schofield 1990; Warwick 1994).
With respect to the former, I consider:
• Party fractionalization: the Laakso-Taagepera index of the effective number of
parliamentary parties.
• Polarization: following Powell (1982), I measure the proportion of parliamentary seats
controlled by extremist or antisystem parties.
Besides the existence of a core party, which I treat separately, both party system attributes listed
above influence the complexity of the bargaining environment in which the cabinet performs, and
thus its expected duration. In particular, the higher the party fractionalization and/or polarization,
the shorter the cabinet duration, since any slight perturbation would have considerable effect on the
distribution of bargaining power in the party system (Laver & Schofield 1990: 157).
With respect to cabinet attributes, I consider:
• Ideological heterogeneity: an index of the ideological compatibility of cabinet members that
I approximate by using the range of government parties on each dimension and calculating
their average (see Tsebelis & Chang 2004). Ideologically compact coalitions should find it
easier to reach agreement in the first place on how to change the existing legislative status
quo, and have more possibilities to agree on possible responses when new political issues
arise (Tsebelis 2002). Therefore, I expect a negative relationship between ideological
heterogeneity and cabinet duration. Note that this variable allows us to test the conditional
hypothesis relating to the presence of a core with cabinet duration (see below).
• Government fractionalization: the absolute number of cabinet parties. As the membership of
the government grows, both the potential transaction costs of managing conflict and of
reaching agreement among cabinet parties and the chances of a government breakdown
should increase.22
• Returnability: the proportion of parties represented in the current government that were also
represented in the previous cabinet. Although the literature generally agrees on the
importance of this variable, there is some disagreement on its expected sign. For Warwick
(1994), the more members from the previous government who participate in the next one,
the smaller the expected cost to any one party from government collapse, and the more
likely the government is to fall. Therefore, the expected relationship is a negative one.
However, high Returnability also implies the continuation of successful cooperation among
the government parties, meaning that those parties can take advantage of already established
mutual trust and high levels of information about one another, thus reducing any perceived
commitment problems (Saalfeld 2008). If these factors are present, they should provide
better conditions for cabinet longevity than cases where a political partnership is still
untested, implying a positive relationship between Returnability and cabinet duration.
• Crisis duration: the number of days before a new government formed.23 As in the previous
case, there is also some disagreement in the literature concerning this variable. For Strøm
(1988) and Merlo (1998), delays in government formation act as a selection mechanism, and
therefore longer negotiations allow parties to form relatively more stable governments. In
contrast, for King et al. (1990), the expected relationship is negative, given that a longer
crisis indicates an environment rich in possible alternative coalitions.
• Caretaker status: a dummy variable coded 1 if the government is a caretaker one, and 0
otherwise. I expect that the duration of such cabinets, which take office during difficult
periods on an interim basis until a regular government can be formed or new election held,
should be much shorter.24
9
Government duration and event dependence
I test my model using Cox’s partial likelihood survival model. The central concept in survival
analysis is the hazard rate, h(t), that is the rate at which units fail (or duration ends) by t given that
the unit had survived until t (Box-Steffensmeier & Jones 2004). Thus, the hazard rate is a
conditional failure rate.25 The hazard rate has two components. The first is the set of covariates that
are hypothesized systematically to affect the timing of an event. The second is the baseline hazard
rate h0(t), which indicates the underlying probability of cabinet termination over time when the
vector of all covariates is zero. The hazard rate typically has the following form:
h ( t x ) = h0 ( t ) e∑
β k X ik
(3).
In my case, the xβ part of the hazard rate is specified as:
Government Duration = βC CORE + β I IDEOLOGICAL HETEROGENEITY
+ βCI CORE x IDEOLOGICAL HETEROGENEITY + β k (control party-system attributes)
+ β j (control government attributes)
(4).
The conditional nature of the relationship between the presence of a core party and
government duration can be easily controlled according to the previous equation. If the conditional
relationship assumed in my hypothesis is true, then the marginal effect of CORE
∂Government Duration
(
= β C + β CI IDEOLOGICAL HETEROGENEITY ) must be significant and
∂CORE
decrease as a function of the value of the Ideological Heterogeneity variable.
Following common practice in the literature, governments whose termination occurred
within 12 months of the date mandated for new elections and was not provoked by a government
collapse or other political crisis were censored. Such censored records remain in the analysis and
are essentially treated as cases for which the actual failure time is unknown.
Notice that a cabinet termination is an event that can repeat itself during the life of a
legislature. The consequences of this possibility are not trivial. The occurrence of a cabinet
termination may affect the likelihood of additional cabinet dissolutions within a legislature, simply
because prior events force actors down a path where options become limited, creating what is called
event (or occurrence) dependence (see Box-Steffensmeier et al. 2007). I am theoretically agnostic
about the possible results of event dependence in my case. Still, to the extent that second and
subsequent events are likely to be influenced by, and therefore different from, the first event, the
correlation produced by event dependence may be quite high. This implies that the process of
cabinet termination can be deemed dynamic and should be modelled as such. The failure to do so
could lead to biased and inconsistent estimates (Box-Steffensmeier et al. 2007: 238).
The methodological solution to event dependence is stratification by event number to allow
the baseline hazards to vary within risk pools (as opposed to treating them as if they are identical).26
In my dataset, there are a total of 54 events (that is, cabinet terminations) with each legislature
experiencing an average of 4.5 events, while the event strata range from 1 to 7. To avoid poor
estimates for strata with a relatively small number of cases, I collapsed the event strata such that
strata greater than 4 were set equal to 4.
Results
10
Table 3 presents the results of the two Cox survival models estimated. In the first model, I calculate
a simple additive model, in which equation (4) is estimated without the interaction term between
CORE and IDEOLOGICAL HETEROGENEITY, while in the second model I directly test my
conditional hypothesis.
In Model 1, the unconditional impact of CORE significantly reduces the risk of cabinet
termination. Specifically, the negative coefficient of 1.096 for the core variable suggests that the
presence of a core party results in a lower hazard rate (and higher survival time) than otherwise. In
percentage terms, when the DC (which was always the largest parliamentary party) constitutes the
core, cabinets are 67 per cent less likely (i.e., 1-exp(-1.096)) to collapse at any given time (given
that they are still in charge until that time) than cabinets without a core party.27
Table 3
It is worth noting that the other two party system attributes (party fractionalization and
polarization) do not exert any significant effect on the likelihood of cabinet termination, once the
core effect is controlled for. In other words, what really matters in determining the bargaining
complexity of the environment in which cabinets must survive is the strategic nature of parties’
spatial interactions. Overlooking this aspect would generate misleading conclusions.28
Regarding the cabinet control variables, being a caretaker government significantly
increases the risk of cabinet breakdown, while a longer negotiation before a new government is
formed actually decreases it. The Returnability variable displays a negative coefficient, meaning
that sharing a common membership in the preceding government reduces the hazard rate of
government termination. As is well known, the Italian First Republic was characterized by the
existence of ‘government formulas’, that is, regularities in the outcomes of coalition formation
processes (Mershon 1994).29 The negative sign for Returnability implies that stabilization (and
therefore strengthening) of these formulas translated into longer cabinet duration. Finally, neither
government fractionalization nor ideological heterogeneity (at least in Model 1) is statistically
significant.
However, the hypothesis introduced in the first section is a conditional one. Therefore, in my
second model I also include the interaction term between CORE and IDEOLOGICAL
HETEROGENEITY, as shown in equation (4). The results are intriguing.
As is well known, the appropriate test for an interacting model is to look at the specific
shape of the confidence interval of the marginal effects in which I am interested (see Brambor et al.
2006). Figure 5a shows how the presence of a core party affects the hazard rate of cabinet survival
across the observed range of government ideological difference. The positive consequences of the
presence of a core party on cabinet duration decline as intra-cabinet ideological heterogeneity
increases. Moreover, the significant impact of the CORE variable on the hazard rate disappears
when ideological heterogeneity exceeds 1.2 (a condition satisfied by the 22 per cent of my
observations).
Thus, it appears that the non-policy benefits of government membership accruing to the
coalition parties (others than the core party) are sufficient to compensate for their lack of influence
on the policy equilibrium of the government only when potential intra-cabinet tensions are limited.
On the contrary, when ideological diversity within the government grows, the strong bargaining
power of the core party increases the willingness of its coalition partners to threaten the survival of
the cabinet, given the latter’s inability to influence government policies. As a result of this intracabinet conflict, the presence of a core party ceases to facilitate longer government duration.
Figure 5
11
Figure 5b shows symmetrically the marginal effect of ideological heterogeneity depending
on the presence or absence of a strong core party. As the figure shows, when the core party is
absent, the hazard rate decreases substantially as ideological heterogeneity increases from one
standard deviation below the mean to one standard deviation above the mean. Contrary to
expectations, there is a positive relationship between ideological heterogeneity and cabinet duration.
On the other hand, when a core party is present, the marginal impact of ideological heterogeneity on
cabinet survival is not significant.
Summing up, the results demonstrate that the core and ideological heterogeneity variables
do not exert a cumulative impact on cabinet survival. Recall that as the ideological range within a
government increases, its ability to change the existing legislative status quo is expected to decrease
(Tsebelis 2002). As a result, during the Italian First Republic a cabinet had a higher probability of
survival either when 1) the Christian Democrats enjoyed such a dominant bargaining position to be
able to effectively impose its own ideal point as the policy equilibrium of the government (and in
the legislature), given a low level of intra-ideological heterogeneity, or 2) cabinet parties were
ideologically quite different, given the absence of a core party. In contrast to results generally
reported in the comparative literature, these two alternative scenarios (particularly the latter) capture
a relevant, and well-studied, aspect of the Italian post-war political history.
Italian policy making up to 1992 has been described as characterized by cycles, in which
(relatively) few moments involving reforms at the meso-level (policies concerning important
aspects of economic, social, or foreign policy) were largely overwhelmed by the implementation of
massive distributive policies (see Cotta & Verzichelli 1996; Verzichelli & Cotta 2000). The reasons
for this outcome, and in particular for the paucity of meso-policy reforms, have been linked to the
particular structure of the Italian party system which, by involving anti-system oppositions,
polarization, and fragmentation, compelled parties to claim their choices more at the meta-level of
the policy process (which concerned the very nature of the political regime as well as the position of
Italy in the international alliance system) (Ieraci 2008).
The main consequence of this situation was that all political coalitions, finding their glue
principally in choices concerning meta-level policy, often needed to overlook their ideological
differences at the meso-level. Besides the meta-level confrontation, the only space left was for
micro-policies seeking to satisfy sectional interests. These could to some extent compensate for the
failure to agree on and implement significant reforms. In this sense, parties and party leaders did not
engage in active policy making. Instead, they acted as guardians of the status quo who reacted
rather than initiated, while ensuring that policy initiatives coming from other actors (including
lower-level party leaders or the government itself) did not endanger the coalition of interests which
the party, often internally divided, aggregated with a great effort (Cotta & Verzichelli 1996: 188).
Of course, this does not imply that relevant meso-policy changes were never enacted during
five decades of Italian politics. However, reforms were usually confined to the beginning of each
new coalitional formula (see earlier and n. 29). This is true in particular for the first years of the
centrist coalition, the centre-left coalition, and national solidarity (see Cotta 1996). Quite
interestingly, but not surprisingly, in each of these periods the DC was a strong core party in a
situation where intra-cabinet conflict was reasonably low: this was the case from the De Gasperi IV
to De Gasperi X cabinets, and during the Fanfani III, Fanfani IV, and Andreotti IV cabinets (see
Appendix 1). On each of these occasions, the DC was able to effectively influence the status quo
through its strategic power, at same time lengthening cabinet duration.
In all other cases, intense intra-cabinet ideological heterogeneity appears to favour
government longevity. Given the particular institutional and political context characterizing the
everyday life of Italian governments (as discussed above), I suspect that this is true because it
allowed cabinet to send a (credible) message to Parliament, to their own supporting parties, and to
the respective backbench members,30 signalling that nothing was really going to change to put
under stress a coalition usually characterized by weak discipline. This consequently increased the
12
duration of the government. The signal was perceived as credible precisely because an ideologically
heterogeneous coalition faces greater difficulty in changing the status quo than a unified one.
As recently noted by Lupia & Strøm (2008: 57), to reap the benefits of governing, all
members of a governing coalition must satisfy two requirements simultaneously: 1) form and
maintain agreement with other parties, and 2) please voters. It seems therefore that in the Italian
political context, the former requirement was mainly satisfied in a negative way, through policy
immobilism (whenever the core was absent) rather than government effectiveness, while micropolicies played an important role in meeting the latter requirement.
As a final step in the analysis, Figure 6 plots the estimated survival functions by event
number of Model 2. The graph provides evidence for the presence of event dependence, given that
the survival functions for each stratum are distinct. In particular, the risk of having a third and,
especially, a fourth event (cabinet breakdown) decreases after experiencing the first two events,
while the largest risk is associated with the first event. Assuming a data generation process that
presents baseline hazard rates that vary for each event therefore seems appropriate in my case.
Figure 6
Conclusion
The in-depth study of one country enables an analyst to move closer to decision-making processes
and to filter through a variety of evidence, in ways not possible in cross-national observations
(Mershon 2001: 559). Because the Italian record of cabinet survival was (at least up until 1994) so
different compared to the other Western Democracies, the empirical analysis of government
duration in this case holds theoretical promise. This Italian peculiarity risks being averaged out in
cross-national analyses common in the literature on cabinet survival. For example, the empirical
literature distinguishes between party-system attributes and cabinet attributes. Warwick’s (1994)
important work on this issue shows that cabinet attributes generally hold greater explanatory power
than party-system ones. However, his results are based on a pool of countries. As I stressed, there
are good reasons to assume that parliamentary dynamics plays a much more relevant role in
explaining cabinet duration in Italy than in other countries, given the relatively low institutional
agenda setting power enjoyed by the Italian cabinets. I therefore selected a theory and a concept
(that of the core party) that explicitly focus on parliamentary dynamics. I tested the micro-political
theory of cabinet dissolution using a new dataset that takes between-election dynamics into account.
Given an appropriate setting that models the dynamic nature of cabinet dissolution (in particular the
existence of event dependence), the results show not only the importance of the core party for
cabinet duration, but also the conditional relationship between this presence and the degree of intracabinet conflict. Moreover, whenever the core is absent, cabinet ideological heterogeneity
lengthens, rather than shortens, government duration. This last result stands in stark contrast to
findings in the existing empirical literature. But this seemingly bizarre result becomes much more
understandable when taking into consideration the particular features of the process of policy
making in Italy up to the very end of the First Republic. Summing up, the present analysis shows
that existing comparative studies on cabinet durations are not immune to ‘ecological fallacy’, at
least concerning the Italian case. In this sense, my analysis confirms the warning (see Grofman
1989; Grofman & Van Roozendaal 1997) regarding the need to develop better understanding of the
within-country variation in cabinet durability.
13
Acknowledgments
I would like to thank Marco Giuliani, Willy Jou, Fabio Franchino, Joseph Godfrey and three
anonymous EJPR referees for helpful comments. I also gratefully acknowledge the financial
assistance of the Italian Ministry of Education, University and Research, Prin 2007, prot.
2007SCRWT4, “I luoghi del legislativo, i luoghi delle politiche. Giochi, veti, reti nell’Italia
dell’alternanza”. All data to replicate this study, including the list of speeches coded, the categories
employed and the codebook, are available at: http://www.sociol.unimi.it/docenti/curini/papers.html.
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19
Table
Table 1. Cox survival models of the Italian cabinet duration (assuming event-dependence):
1946-1994
Model 1
Model 2
Party system attributes
PARTY FRACTIONALIZATION
0.061 (0.329)
0.048 (0.326)
POLARIZATION
2.754 (1.705)
2.463 (1.554)
CORE
-1.096*** (0.350)
-1.730*** (0.527)
Cabinet attributes
GOVERNMENT FRACTIONALIZATION
-0.013 (0.178)
-0.017 (0.159)
IDEOLOGICAL HETEROGENEITY
-0.350 (0.333)
-0.670* (0.344)
CORE*IDEOLOGICAL HETEROGENEITY
1.011** (0.404)
RETURNABILITY
-1.581*** (0.556)
-1.454** (0.590)
CARETAKER
2.036** (0.825)
1.913*** (0.867)
CRISIS DURATION
-0.023*** (0.007)
-0.022** (0.006)
N
54
54
Log-likelihood for model
-71.90
-70.54
Wald test
158***
140***
AIC
159.80
157.08
BIC
175.71
172.99
Note. Significance (two tailed): * .1; ** .05; *** .01. Standard errors clustered on Legislature in parentheses. The Efron
method is employed for handling ties.
20
Figures
Figure 1. Kernel density estimate of cabinet duration: Italy 1946-94
0
.0005
Density
.001
.0015
.002
Kernel density estimate
0
300
600
900
Cabinet Duration in Days
Source: Woldendorp, Keman & Budge (2000).
21
1200
Figure 2. Absence (upper panel) and presence (lower panel) of a core party
(in brackets the seats controlled by each party in the Lower Chamber – my elaboration)
(a) Rumor III cabinet (1970)
(b) Rumor V cabinet (1974)
Note. Party Acronyms. DC: Christian Democracy; PCI: Communist Party; PSI: Socialist Party; PSDI: Social
Democratic Party; PRI: Republican Party; PLI: Liberal Party; PSIUP: Socialist Party of Proletarian Unity; MSI: Social
Movement; PDIUM: Democratic Party of Monarchist Unity.
22
De Gasperi 2
De Gasperi 3
De Gasperi 4
De Gasperi 5
De Gasperi 6
De Gasperi 7
De Gasperi 8
De Gasperi 9
De Gasperi 10
De Gasperi 11
Pella
Fanfani 1
Scelba
Segni 1
Zoli
Fanfani 2
Segni 2
Tambroni
Fanfani 3
Fanfani 4
Leone
Moro 1
Moro 2
Moro 3
Leone 2
Rumor 1
Rumor 2
Ruomor 3
Colombo 1
Colombo 2
Andreotti 1
Andretti 2
Rumor 4
Rumor 5
Moro 4
Moro 5
Andreotti 3
Andreotti 4
Andreotti 5
Cossiga 1
Cossiga 2
Forlani
Spadolini 1
Spadolini 2
Fanfani 5
Craxi 1
Craxi 2
Fanfani 6
Goria
De Mita
Andreotti 6
Andreotti 7
Amato
Ciampi
-2
-1
0
Economic Policy
1
Figure 3. The evolution of the three main Italian parties along the economic policy dimension
Cabinets 1946-1993
DC
PCI/PDS
23
PSI
2
Pearson's r LH-Leg.Speeches: .91
Pearson's r LH-CMP: .67
-2
Social Policy
-1
0
1
Pearson's r LH-Leg.Speeches: .93
Pearson's r LH-CMP: .87
-2
Economic Policy
-1
0
1
2
Figure 4. Scatter plot of party policy positions according to Laver & Hunt (1992) expert survey, to
CMP data and to Legislative Speeches. Pearson’s r also reported
DP
PCI
PSI
PR GREENS PSDI
PRI
DC
PLI
MSI
DP
Parties
PSI
PR GREENS PSDI
PRI
DC
PLI
MSI
Parties
Leg.Speeches
CMP
Laver-Hunt
Leg.Speeches
CMP
Pearson's r LH-Leg.Speeches: .79
Pearson's r LH-CMP: .55
-2
Foreign Policy
-1
0
1
2
Laver-Hunt
PCI
DP
PCI
PSI
PR GREENS PSDI
PRI
DC
PLI
MSI
Parties
Laver-Hunt
Leg.Speeches
CMP
Sources: CMP policy scores come from my elaboration on the original CMP dataset (Budge et al. 2001). Both the CMP
scores and the Legislative Speeches scores are averaged over the last 25 years of the Italian First Republic (1968-1993).
To facilitate the comparison I reported the standardized scores of each scale.
24
Figure 5. Marginal Effects Plots of the interaction
between CORE and IDEOLOGICAL HETEROGENEITY
3
2
1
0
-1
Marginal Effect of Strong Core Party
4
(a) Marginal Effect of Strong Core Party on Cabinet Survival
0
.5
1
1.5
2
2.5
3
Ideological Heterogeneity
2
1.5
1
.5
0
-.5
-1
Marginal Effect of Ideological Heterogeneity
(b) Marginal Effect of Ideological Heterogeneity on Cabinet Survival
0
1
Strong Core Party (0=absent; 1=present)
90% Confidence Interval
Note. The marginal effect plots are constructed using parameter estimates for Model 2 from Table 1. The confidence
intervals are calculated via simulation using 10,000 draws from the estimated coefficient vector and variancecovariance matrix.
25
1.0
Figure 6. Estimated survival function for each event number for Model 2 of Italian Cabinet survival
0.6
0.4
0.2
0.0
Survival Estimates
0.8
Event 1
Event 2
Event 3
Event 4-7
0
200
400
600
Time (Days)
26
800
1000
Appendices
Appendix 1. Italian Governments (1946-1994)
Legislature (A)
Costituent Assembly
Costituent Assembly
Costituent Assembly
Costituent Assembly
First Legislature
First Legislature
First Legislature
First Legislature
First Legislature
Second Legislature
Second Legislature
Second Legislature
Second Legislature
Second Legislature
Second Legislature
Third Legislature
Third Legislature
Third Legislature
Third Legislature
Third Legislature
Fourth Legislature
Fourth Legislature
Fourth Legislature
Fourth Legislature
Fifth Legislature
Fifth Legislature
Fifth Legislature
Fifth Legislature
Fifth Legislature
Fifth Legislature
Fifth Legislature
Government (B)
De Gasperi II
De Gasperi III
De Gasperi IV
De Gasperi V *
De Gasperi VI
De Gasperi VII *
De Gasperi VIII
De Gasperi IX *
De Gasperi X
De Gasperi XI
Pella
Fanfani I
Scelba
Segni I
Zoli
Fanfani II
Segni II
Tambroni
Fanfani III
Fanfani IV
Leone I
Moro I
Moro II
Moro III
Leone II
Rumor I
Rumor II
Rumor III
Colombo I
Colombo II *
Andreotti I
Date Formed
(C)
Jul-46
Feb-47
May-47
Dec-47
May-48
Nov-49
Jan-50
Apr-51
Jul-51
Jul-53
Aug-53
Jan-54
Feb-54
Jul-55
May-57
Jul-58
Feb-59
Mar-60
Jul-60
Feb-62
Jun-63
Dec-63
Jul-64
Feb-66
Jun-68
Dec-68
Aug-69
Feb-70
Aug-70
Mar-71
Feb-72
Parties in Cabinet (D)
DC, PCI, PSIUP, PRI
DC, PCI, PSI
DC, PLI
DC, PLI, PSLI, PRI
DC, PLI, PSLI, PRI
DC, PLI, PRI
DC, PSDI, PRI
DC, PRI
DC, PRI
DC
DC
DC
DC, PSDI, PLI
DC, PSDI, PLI
DC
DC, PSDI
DC
DC
DC
DC, PSDI, PRI
DC
DC, PSI, PSDI, PRI
DC, PSI, PSDI, PRI
DC, PSI, PSDI, PRI
DC
DC, PSU, PRI
DC
DC, PSI, PSDI, PRI
DC, PSI, PSDI, PRI
DC, PSI, PSDI
DC
27
First Dimension
(E)
economic policy
economic policy
economic policy
economic policy
social policy
social policy
economic policy
economic policy
foreign policy
economic policy
economic policy
economic policy
foreign policy
economic policy
foreign policy
foreign policy
economic policy
economic policy
social policy
economic policy
economic policy
economic policy
economic policy
economic policy
economic policy
economic policy
economic policy
economic policy
economic policy
economic policy
economic policy
Second Dimension
(F)
Core (G)
social policy
social policy
foreign policy
core
foreign policy
core
foreign policy
core
foreign policy
core
foreign policy
core
foreign policy
core
economic policy
core
foreign policy
social policy
foreign policy
economic policy
core
foreign policy
economic policy
core
economic policy
core
foreign policy
core
foreign policy
economic policy
core
foreign policy
core
foreign policy
social policy
foreign policy
foreign policy
social policy
core
foreign policy
core
democracy
social policy
democracy
democracy
social policy
-
Strong Core
Party (H)
strong core
strong core
strong core
strong core
strong core
strong core
strong core
strong core
strong core
strong core
strong core
strong core
strong core
strong core
strong core
-
Sixth Legislature
Andreotti II
Jun-72
DC, PSDI, PLI
economic policy
democracy
Sixth Legislature
Rumor IV
Jul-73
DC, PSI, PSDI, PRI
economic policy
social policy
core
strong core
Sixth Legislature
Rumor V
Mar-74
DC, PSI, PSDI
economic policy
social policy
core
strong core
Sixth Legislature
Moro IV
Nov-74
DC, PRI
economic policy
social policy
Sixth Legislature
Moro V
Feb-76
DC
economic policy
social policy
Seventh Legislature Andreotti III
Jul-76
DC
economic policy
democracy
Seventh Legislature Andreotti IV
Mar-78
DC
social policy
democracy
core
strong core
Seventh Legislature Andreotti V
Mar-79
DC, PSDI, PRI
economic policy
social policy
Eighth Legislature
Cossiga I
Aug-79
DC, PSDI, PLI
democracy
social policy
Eighth Legislature
Cossiga II
Apr-80
DC, PSI, PRI
social policy
economic policy
Eighth Legislature
Forlani
Oct-80
DC, PSI, PSDI, PRI
social policy
economic policy
Eighth Legislature
Spadolini I
Jun-81
DC, PSI, PSDI, PRI, PLI
economic policy
social policy
Eighth Legislature
Spadolini II
Aug-82
DC, PSI, PSDI, PRI, PLI
economic policy
social policy
Eighth Legislature
Fanfani V
Dec-82
DC, PSI, PSDI, PLI
economic policy
social policy
Ninth Legislature
Craxi I
Aug-83
DC, PSI, PSDI, PRI, PLI
economic policy
social policy
Ninth Legislature
Craxi II
Aug-86
DC, PSI, PSDI, PRI, PLI
economic policy
democracy
Ninth Legislature
Fanfani VI
Apr-87
DC
economic policy
social policy
Tenth Legislature
Goria
Jul-87
DC, PSI, PSDI, PRI, PLI
economic policy
social policy
Tenth Legislature
De Mita
Apr-88
DC, PSI, PSDI, PRI, PLI
social policy
economic policy
Tenth Legislature
Andreotti VI
Jul-89
DC, PSI, PSDI, PRI, PLI
social policy
economic policy
Tenth Legislature
Andreotti VII
Apr-91
DC, PSI, PSDI, PLI
economic policy
social policy
Eleventh Legislature Amato
Jun-92
DC, PSI, PSDI, PLI
economic policy
social policy
core
Eleventh Legislature Ciampi
Apr-93
DC, PSI, PSDI, PLI
social policy
economic policy
Note. * Government formed as a result of a cabinet reshuffle in party composition, without a formal resignation (and therefore without a new investiture debate). In this case, the
relevant policy space is that of the previous government
28
Appendix 2. Association between Policy Dimensions and Categories
Policy Dimensions
Categories
Foreign Policy
Pro-Western Polarity (+):
Anti-Western Polarity(-):
Foreign Special Relationship (USA and
Foreign Special Relationship (USA and
NATO): Positive
NATO): Negative
Anti-Imperialism
Military: Positive
European Community: Positive
Military: Negative
Foreign Special Relationship (USSR and
Peace
others socialist countries): Negative
European Community: Negative
Foreign Special Relationship (USSR and
others socialist countries): Positive
Economic Policy
Pro-Market Polarity (+):
Pro-State Polarity (−):
Free Enterprise
Market Regulation
Incentives pro-market
Economic Planning
Protectionism: Negative
Controlled Economy
Economic Orthodoxy
Keynesian Demand Management
Welfare State Limitation
Protectionism: Positive
Trade Unions: Negative
Nationalization
Marxist Analysis
Social Justice
Welfare State Expansion
Trade Unions: Positive
Entrepreneurs: Negative
Social Policy
Traditional Polarity (+):
Progressive Polarity (−):
National Way of Life: Positive
National Way of Life: Negative
Traditional morality: Positive
Traditional morality: Negative
Catholic Church: Positive
Catholic Church: Negative
Multiculturalism: Negative
Multiculturalism: Positive
Law and Order: Positive
Law and Order: Negative
Involvement of citizens and movements in
decision-making
Environmental
Materialist Polarity (+):
Post-Materialist Polarity (−):
Policy
Productivity
Anti-Growth Economy
Environmental Protection
Centralization of
Centralization Polarity (+):
Decentralization Polarity (−):
decision making
Centralization
Decentralization
Democracy
Consensual Polarity (+):
Majoritarian Polarity (-):
Parliament and Representative Institutions
Political Authority
Institutions
Pro-Institutions Polarity (+):
Anti-Institutions Polarity (−):
Constitutionalism: Positive
Constitutionalism: Negative
Justice
Independence Polarity (+):
Responsibility Polarity (−):
Judges: independence
Judges: political control
29
Notes
1
In a typical comparative study on cabinet duration of Western European democracies, Italian cases
provide around 15 per cent of observations in the entire sample.
2
Following Woldendorp et al. (2000), I define a government as any administration that is formed
after an election and continues in the absence of: a change of Prime Minister; a change in the party
composition of the Cabinet; a resignation in an interelection period followed by re-formation of the
government with the same Prime Minister and party composition. As in King et al. (1990), I also
consider cabinets that failed investiture votes in my analysis.
3
Party positions in Figure 2 provide a rather coherent picture of the overall Italian party system in
two different historical moments according to the common perception. See next section for a more
systematic test concerning the validity of my estimated party positions.
4
The attempt to properly link the four stages of a typical multiparty parliamentary systems (that is,
the preelection stage, the election stage, the coalition bargaining and the legislative stage) within the
same theoretical model has been only recently advanced in the literature. See in particular Schofield
& Sened (2006). For an application to the ‘Second Italian Republic’ case (i.e., Italy post-1994
election), Giannetti & Sened (2004).
5
I assume that parties cannot assess with certainty whether a core exists or not in the legislative
arena. In this sense a party can decide to join a coalition with a core party while realizing only expost its substantial inability to affect the cabinet policy programme.
6
The estimation of parties’ policy positions according to their legislative speeches would generate
biased results whenever the linkage between government and the parliamentary majority influences
what parties say during a vote of investiture. The weak cohesion of Italian coalitions (see earlier),
together with the fact that what is coded are verbal expressions rather than concrete behaviour,
makes this risk less relevant in this case. Notice, moreover, that government parties are usually
dispersed in the estimated policy spaces (see Fig.2 above). This clearly contradicts the idea that
parties conceal their true policy preferences during investiture debates to avoid exacerbating intracoalition conflicts.
7
I focused my analysis on investiture debates in the Lower House, with the exception of the first
and fifth Andreotti governments, which only delivered an official speech in the Upper House before
being defeated in a vote of confidence.
8
The coding procedure was carried out by two trained coders. Inter-coder reliability is .83.
9
I used 49 out of the 68 categories comprising the classification scheme to discriminate among
opposite polarities of each dimension (see Appendix 2). I assessed the internal coherence of the
categories comprising each dimension through a principal component analysis (as done in Laver &
Budge 1992). Supplementary analysis confirms that the categories employed in each dimension
indeed measure the same latent dimension.
10
I observe that the two most salient dimensions cover on average the 62 per cent of all the codified
quasi-sentences associated with the 8 policy dimensions, and their variance across votes of
investiture is relatively small (s.d. .07). Therefore, using a two-dimensional space to model party
competition within the Italian legislative arena seems appropriate. On this same solution, see Budge
et al. 1987; Laver & Schofield 1990; Laver & Hunt 1992.
11
The CMP coding system - and the coding system employed here - is based on saliency
assumptions. For this reason, its ability to estimate the position of parties has been questioned (see
Laver 2001). For a convincing counter-argument see Budge (2001).
12
+
−
The alternative to (2) would be to normalize the difference Fiylx
− Fiylx
with the salience that each
party i assigns to dimension x (Kim & Fording 1998). Note, however, that this ratio measure can
30
produce large swings in parties’ positions for any small difference of emphasis on the categories
defining a given dimension whenever the party’s references to those categories are relatively few.
This does not happen with (2) due to the presence of the factor 1/Sylx. Given that the aforementioned
problem is present in my data, I opted to normalize party policy positions according to (2).
13
The temporal dynamics of parties along other policy dimensions is also quite convincing in terms
of face validity. I omitted the analysis for space reasons.
14
Using a longer or shorter period does not affect my findings. In performing this correlation, we
consider the expert survey policy scores as capturing the long-term reputation of a party; see Budge
et al. (2001).
15
Unfortunately, nothing similar to my democracy dimension is included in the Laver-Hunt expert
survey.
16
In the CMP case, the three policy scales are built using the same categories employed for
estimating my scales. This allows to maximize comparison between the results from the CMP
dataset and my own.
17
Schofield reports this result using the two-dimensional space that Mastropaolo & Slater (1987)
obtained through a two-stage factor analysis of the CMP data from 1946 to 1979. Replicating their
analysis on the CMP data from 1946 through 1992, shows that the DC was not a core party in the
Constituent Assembly during the 1950s and since the mid-1980s. Second, and more important, in
Mastropaolo and Slater’s analysis the two dimensions defining the Italian policy space are fixed
over the entire period. This is however an artifact produced by the statistical method employed. It is
precisely because I believe that, in terms of party-system interactions, a change in the meaning of
the dimensions comprising a policy space is no less important than a change in the party positions
within that space, that I avoid applying any data reduction method (as a factor analysis) to the data.
This of course does not dismiss the utility of such strategy whenever the researcher is interested in
extracting one single dimension, such as a general left-right scale, that it is assumed stable enough
across time and countries (see Gabel & Huber 2000). The results of the replication of Mastropaolo
and Slater’s analysis are available upon request from the authors.
18
Implicitly this assumes that the parties’ policy scores are estimated with a 10 per cent margin of
error.
19
Given the scale employed in my estimated policy spaces (ranging from -3 to +3 on both axes),
this value appears sufficiently miniscule. The simulation has been carried out using CyberSenate
software.
20
For example, all 17 secretaries of the DC, 13 out of 14 secretaries of the PSI and 4 out of 5
secretaries of the PCI were appointed between elections. On the importance of intra-party politics in
Italy, see Mershon (2001).
21
A third possible event that can influence the political environment in which government and
parties interact is related to a public opinion shock that changes the electoral expectations of key
parties and possibly increases incentives to bring down a government (Lupia & Strøm 2008).
22
I also estimated party fractionalization by taking into consideration the relative sizes of parties.
This does not change my results.
23
The data on crisis duration are taken from Pasquino (1997).
24
Controlling for cabinet type (i.e., a minority cabinet or not) or the size of the government’s
majority do not affect my main estimates. I also controlled for the existence of single-party
cabinets, given their relative large number (15 out of 54), and given that a single-party cabinet does
not present any level of government ideological heterogeneity. Once again, the results do not
change.
25
Individual and global tests of the Schoenfeld residuals indicate that the proportional hazard
assumption underlying the Cox model is not violated.
26
Although a separate baseline hazard is estimated for each stratum, I assume the covariate effects
to be constant across the strata. See Box-Steffensmeier et al. (2007).
31
27
As expected, if Model 1 is replicated using the structurally unstable cores instead of stable ones,
the estimated coefficient of CORE decreases (from -1.096 to -0.909).
28
The relationship between the core variable and cabinet survival is not affected by the unusual
scenario of the first Legislature (1948-53), during which the DC actually controlled a majority of
seats in both Chambers (becoming, by default, a strong core party). Indeed, if the analysis is
repeated dropping this Legislature, the core variable retains its significance with a slightly higher
coefficient.
29
Five government formulas can be devised in the post-war Italian politics: national unity (from
1944 to 1947, in which the DC governed with the PSIUP and the PCI); centrist coalition (from 1947
to 1960, in which the DC allied with the PSDI, PRI, and PLI); centre-left coalition (from 1960 to
1976, in which the PSI replaced the PLI in government coalitions); national solidarity (from 1976 to
1979, in which the PCI also supported the government); and finally, the five-party coalition since
1979 (which became a four-party coalition after the PRI’s defection in 1989) until the end of the
First Republic following the 1992 elections (in which the DC allied with the PSDI, PRI, PLI, and
PSI).
30
On the relationship between party leadership and backbenchers, and on the strategies that leaders
can pursue in this regard to maintain party unity despite divergent interests, see Kam (2009).
32