ELECTORAL COMPETITION AND CRIMINAL VIOLENCE IN ITALY
(1983-2003)
Salvatore Sberna
Istituto Italiano di Science Umane - Florence
[email protected]
Paper presented at the ECPR Joint Session Conference
Workshop on “Political Institutions and Conflict”
St. Gallen - 2011
ABSTRACT
Do criminal organizations use strategically violence for electoral purposes? This
research aims at analyzing the relation between criminal violence and elections in
southern Italy (1983-2003) where four regionally-based organized crime networks
operate. In this study, criminal-electoral violence is defined as any organized act or threat
by criminal organizations that occur during an electoral process, from the date of
nomination for political offices to the date of elections, to intimidate, physically harm,
blackmail, or abuse a political stakeholder in seeking to influence directly or indirectly
an electoral process. The empirical analysis is drawn from a unique panel data of
monthly crimes (incendiary and explosive attacks) reported by police forces in 105
Italian provinces from 1983 to 2003 (Minister of Interior - SDI data set). Through a
diff-in-diffs design, the paper finds statistical evidence that there is a positive
correlation between mafia violence and elections, which means that as elections
approach intimidation attacks increase in Southern Italy. These findings are consistent
with a large case study literature documenting the interventions of criminal
organizations into the electoral process in southern Italy. All the evidence indicates
that criminal groups used a wide variety of strategies to make sure that their preferred
candidates got elected.
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1. INTRODUCTION
Elections are crucial in democracy and when they are perceived as unfair, unresponsive, or
corrupt, democratic legitimacy is compromised (Fisher, 2002). Therefore, it represents a serious threat
if criminal resources are absorbed in electoral process than if they were exclusively devoted to illegal
activities.
Numerous studies on political violence and terrorism show that terrorist groups (Eubank and
Weinberg, 2001; Pape, 2003; Kydd and Walter; 2002, 2006; Chenoweth, 2010; Aksoy, 2010) or ethnic
groups (Cohen, 1997; Collier, 2009) use strategically violence around elections times, or that political
violence can be manipulated by incumbents according to the competitiveness of elections (Wilkinson,
2004; Collier and Vicente, 2009; Acemoglu & al., 2009). However, no empirical works exist on criminalelectoral violence, i.e. that violence employed strategically by criminal organizations as elections
approach. This paper shows that electoral timing explains variation both in politics and in crime
(Sanchez and Chacon, 2005). This is true not for all types of crime, but especially for those criminal
phenomena which are organized and institutionalized over time in specific areas1. In the case of Italy,
many qualitative studies and media report about criminal violence during electoral campaigns but there
is no cross-regional empirical exploration of the relationship between the timing of elections and such
violence (Gambetta, 1993; Della Porta and Vannucci, 1999). What is the relationship between election
times and violence in those countries where strong institutionalized criminal groups operate? Why is
violence preferred to non-coercive means to influence electoral competition?
Few empirical studies have dealt with this urgent issue due the lack of data and secrecy and the
reliability of the materials collected by law enforcement agencies. This paper seeks to overcome these
serious methodological problems by focusing on the relationship between elections and criminal
violence, arguing that some single points in time (i.e. elections) have an impact on criminal violence.
The analysis evaluates this effect in Italy where several criminal groups operate and are commonly
clustered in four regional organizations: Camorra in Campania, Sacra Corona Unita in Apulia,
‘Ndrangheta in Calabria and Cosa Nostra in Sicily. Data for the empirical analysis are drawn from a
Lack of property rights enforcement or weak monopoly of violence exercised by central government versus its
peripheries, together explain the informal institutionalization of criminal enterprises, specialized in providing
“protection”, according to the insightful analysis of Diego Gambetta (1993). This is the case of protection
market in Russia lead by the Mafiya (Varese, 2001), or the trouble transitions in some eastern European
countries. In Japan, on the contrary, Yakuza criminal groups (Hill, 2003) are more similar to Italian organized
crime, both, in fact, operate in established democracies, compared to the environment of some democratic
transitions in Latin America, such as in Brazil, or the penetration of drug cartels in Mexico and Colombia.
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unique panel data of monthly crimes (arson and bomb attacks) reported by police forces in Italian
provinces from 1983 to 2003 (Minister of Interior - SDI data set). The evidence shows that Italian
mafias are most likely to engage in violence in electoral periods, thus as elections approach these
organizations strategically use violence – and other means – in order to influence the electoral process.
Approaching elections, I argue, lead to an increase in the volume of attacks in those areas where
the presence of criminal organizations is high, while in those areas with lower criminal presence this is
not the case. Thus, periods close to elections are periods of heightened criminal activity when areas are
controlled by mafias. The logic behind the argument is as follows. In all democracies election times are
periods of heightened political competition not only among party candidates and interests groups, but
similarly among criminal groups when they are interested in influencing the political process (Aksoy,
2010). Therefore, at first glance, criminal organizations are similar to terrorist groups, but they critically
diverge. They share a single tactic – the use of violence – but criminal organizations have a much wider
repertoire of action, including illegal activities, money, and especially collusive ties with political elites
(Makarenko, 2004; Sciarrone, 2006; Lupo, 2010). Thus a different strategy moves such action. Unlike
ordinary criminal organizations, which are avowedly nonpartisan and have virtually no contact with
parties, mafias are structurally integrated within the political systems in which they operate. In fact,
although they are industries in illegal markets and driven by profit (Gambetta, 1993), they naturally
gravitate toward government, because they seek to influence the direction and content of governmental
action to reach organizational goals – immunity against law-enforcement, rent-seeking (Harasymiw,
2003). Mafias are, after all, organizations which pay attention to whatever is necessary to the
maintenance of the integrity and continuity of the organization itself (Selznick, 1948: 29). Therefore,
studying mafia-politics relation means looking at the conditions under which political parties are
captured by criminal organized interests (Barro, 1993; Grossman&Helpman, 2001; Golden&Tiwari,
2009; Acemoglu et al., 2009). In exchange of immunity, they can affect elections in many ways by
contributing to finance campaigns, or mobilizing voters to provide electoral support to politicians they
prefer to favor, or, in extreme cases, being themselves running for elections (Della Porta and Vannucci,
1999). Based on this literature I show that the volume and the timing of organized crime’s violence can
be explained by the occurrence of elections.
The paper is organized as follows. The theoretical setting of the relation between criminal
organizations and politics is presented in Section 2. In Section 3 I formulate the hypotheses. Data
source and construction are explained in Section 4. Descriptive analysis of data about organized and
criminal violence is presented in Section 5. Then the empirical strategy is designed in Section 6,
followed by the presentations of main results.
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2. ORGANIZED CRIME, ELECTIONS AND PARTIES IN ITALY
The literature on organized crime provides compelling evidence that criminal organizations are directly
involved in electoral campaigns both in consolidated democracies (Allum & Siebert, 2003) and many
democracies in transition that experience a dramatic rise in reported criminality and citizen insecurity,
such as in Latin America (Bailey & Godson, 2000; Bergman & Whitehead, 2009). A large case study
literature has emerged, documenting such interventions. Interaction and exchanged resources between
politicians and criminals can vary significantly from electoral finance to voter mobilization, or finally
violence in order to intimidate opposition candidates, voters, or criminal rivals. Intimidation is used
also to keep opposition parties representatives away from the polls or simply threatening them (Sberna
2010)2, or as a mean of electoral propaganda in public markets.
More recently a growing literature illustrates theoretically the link between crime and politics
(Pimental, 2000; Vannucci & Della Porta, 2010), and some empirical studies evaluate the likelihood that
criminals can be selected by national parties to run for elections and then to get elected (Golden &
Tiwari, 2009). Therefore, what emerges is that organized crime does not attempt to displace the state,
even though it is at war with it. It exists side-by-side with the state, in a relationship variously referred
to as complementary or symbiotic (Armao, 2003). This relation is based on mutual interests, both of
criminal organizations and politicians. Politicians are not venal but captured, and they are captured
because they want to win the next election. In fact, even in democratic regimes, elected politicians
devise strategies to gain unanticipated control over votes (Kitschelt, 2000). They need an intimate
knowledge of the voter, and for this reason they often hold “political machines” which allow them an
electoral advantage (Golden and Tiwari, 2009). The presence of organized crime opens alternative
strategies normally not available to candidates in democratic elections, including intimidation and
violence, criminal vote buying, fraud. Menu of electoral manipulation (Schedler, 2002) consists of
several alternatives for controlling voters, more than the mere use of intimidation and force. Through
these means criminal organizations help favored politicians in retaining political support by voters.
Therefore, parties’ relation with organized crime is based on the premise that the latter can control
citizens’ voting behavior. Looking at organized crime, interests are clear: criminal organizations
naturally seek immunity from law-enforcement agencies in order to protect their illegal business.
However, greed of immunity tells us only a very limited part of the story. More often these
organizations control both illegal markets (protection-extortion, drug) and some specific sectors in legal
In the municipality of Seminara in Calabria, for example, the local boss decided to confiscate some voters’
electoral cards, giving them back few hours before poll closed, and providing to illiterate voters of the so called
‘stampino’, which is a mould with the name of favored candidate stamped on it (Sberna 2010).
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markets thanks to money laundering (Lavezzi, 2008). In construction, concrete and waste sectors, the
control is often overwhelming and quantitatively hegemonic, but also highly dependent on public
investments and regulations. Therefore, mafias naturally gravitate around government because they
have preferences over public policies, and this element reduces the incentives of the politicians they
favor to disrupt criminal networks3. This explains why mafia-politics equilibriums likely persist along
the time (Acemoglu et al., 2009).
Italian mafias have been structurally integrated within the Italian political system despite the
regime changes that occurred in the country since the last century. Such relations were by no means
contingent but regular and systemic. Police and historical records present exhaustive evidence
convincingly demonstrating the persistence of a close link between organized crime and politics from
the Eighteen century (Franchetti, 1900; Lupo, 2010). During the First Republic (1948-1992) the
systemic network of collusion and the special relationship with the Christian Democracy party (DC)
was explained by several factors: among all the lasting one-party dominance of DC in almost all
legislative districts and in the majority of municipalities in Southern Italy4 (LaPalombara, 1964; Leonardi
and Wertman, 1989; D.Scheiner, 2006; Magaloni, 2006). Even though there was remarkable evidence
about collusion, accusations were serious enough to lead to prosecutions and charges. The analysis of
voting behavior in some areas exhibited some un-explainable results, such as massive changes in voting
patterns from a candidate to another and very high concentrations of votes for some candidates in
particular municipalities.
The turning point in mafia-parties relation is widely acknowledged to occur in early 1990s.
Italy’s 1994 national elections were the most volatile elections in the history of the Republic (41,9%
Gunther, 2005:255) and marked the end of political dominance by Christian Democracy, broken down
by “Clean Hands” campaign. However, opportunities and constraints of this interaction had already
changed in the 1980s, when judiciary investigations uncovered and permitted the arrest of many top
bosses (Jamienson, 1999). The heightened intra-bloc volatility favored DC’s coalition allies (Partito
Socialista Italiano and Partito Repubblicano) to the detriment of DC’s electoral support (Gunther,
2005). At local level, party system fragmentation eroded DC’s dominance in criminal-political ties with
criminal groups that in many cases preferred to colonize DC’s coalition parties at local level (Mete,
2009; Sberna, 2010)5.
Evidence of a criminal-political capture can be found in those areas where due the penetration of criminal
organizations citizens obtain fewer public goods (and other policies they value), because policies cater to the
preferences of criminal families.
4 The DC was the largest party in every coalition government between 1948 and 1992 and, except for 1981-82
and 1983-87, controlled the prime ministership every year until 1993 (Leonardi, 1993). At regional and municipal
level, the DC was also the largest party in local cabinets.
5 In southern Italy many municipalities have been ruled for a long time by criminal families’ members, and
sometimes through a tough transition from father to son, such as the city of Quindici in Campania, where
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However, Italy is not the only case where crime-politics connections have been so tight that
criminal groups have colonized parties or been directly involved in electoral campaigns since they are
themselves running elections. Pablo Escobar in Colombia is probably the most popular case of drug
carteler in politics and it was not an exception. Therefore, the evaluation of elections’ impact on
criminal violence is the first step in the empirical study of politics-crime nexus. In fact, I argue that the
analysis of politics of crime can tell us something more about the criminalization of politics even in
established democracies.
3. ELECTIONS AND VIOLENCE. HYPOTHESES
Criminal organizations use violence in a myriad of ways and for several motives both in legal
and illegal markets. Violence clearly arises from producing illegality6, and it is exploited instrumentally
to pursue diverse goals, such as to resolve disputes among mafioso families, or to enforce the
monopoly in illegal markets (Schelling, 1967). However this paper is not interested in explaining all
several motives, goals and strategies of mafias’ violence. I look at a specific type of criminal violence,
that I define criminal-electoral violence, i.e. any organized act or threat by criminal organizations that occur
during an electoral process, from the date of nomination for political offices to the date of elections, to
intimidate, physically harm, blackmail, or abuse a political stakeholder in seeking to influence directly or
indirectly an electoral process (Fisher, 2002). Therefore, the strategic timing differentiates this violence
from other examples. Election times are crucial for at least two reasons. (1) In democracy, elections
increase uncertainty in political equilibriums. Around election times many political groups try to
influence the political process and they increase the volume of their activities. Political parties seek
contributions and resources for campaigns while interest groups increase their lobbying activities
providing such resources. Criminal organizations’ action is also driven by this logic. If this is true, we
should observe an increase in the number of intimidation attacks as elections are close since even
criminal groups fiercely compete. Homicides or intimidation among criminals in election times are
demonstration of the willingness to use violence and of power both to legal and illegal actors. By those
acts they can indirectly enforce other illegal deals and their control upon voters and candidates.
several bosses of Graziano clan, part of the New Organized Camorra, inherited the office of mayor for more
than 30 years. It was not by chance that in the 80s in Quindici the PSI gained 100% of the seats of the city
council.
6 First, the criminal victims of violence are disadvantaged in seeking police protection. And this is obvious since
the process of providing an informative complaint will yield information to the police about the illegal activities
of the complainant. Second, it is endogenous of illegal markets the problem that participants in illegal markets
lack recourse to state provided facilities for settlement of disputes. Violence or its threat (intimidation) may
constitute the only method of resolving disputes in some situations (Reuter, 1983).
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(2) An additional reason makes elections crucial for criminal lobbying. During elections the
saliency of organized crime as policy issue raises inevitably, because electoral campaigns can draw
public attention to mafia-politics collusion. Lack of debate about crime is the first goal criminal groups
seek to reach, and this is why they would intimidate political candidates. These informative asymmetries
between political-criminal networks and voters can be put at risk if opposition parties’ candidate
denounce the existence of such links, or simply move suspicions about people involved. Therefore
public attention can lead to criminal violence. Drawing on these propositions, I formulate synthetically
the main hypotheses of this study: the first group proposes an explanation about the variation in
criminal violence between electoral and non-electoral periods; the last one is about the variation
depending on the nature of elections.
Hypothesis 1a. In those areas controlled by organized crime intimidation attacks increase when elections are close.
According to this formulation, I argue that elections have an exogenous effect on criminal-electoral
violence. I would expect an overall increase of intimidation attacks before elections in those areas
controlled by organized crime. The null hypothesis is that criminal violence does not vary significantly
as elections approach if the area is not controlled by criminal organizations. Many empirical studies
about political violence in electoral times have already tested a similar hypothesis (Wilkinson, 2004;
Collier and Vicente, Aksoy, 2010). In literature some theoretical studies show that the timing of
terrorist attacks is not random, but strategically decided (Kydd and Walter, 2002, 2006). This paper goes
further these contributions, in which electoral violence remains confined to developing democracies, or
to countries highly fragmented along ethnic lines. I do not refer to spontaneous or terrorist violence,
but to that violence employed by criminal organizations. Doing it, this paper is similar to some recent
empirical analyses about the impact of criminal/guerilla violence in Colombia. These studies investigate
the electoral effect of guerrilla in a sample of municipalities, and also the willingness of federal
government in disrupting guerilla networks (Sánchez & Chacón, 2005), and thus lower the intensity of
non-state violence (Acemoglu et al., 2009). However, the existing related literature shows that
approaching elections do not unconditionally increase violent attacks from terrorist or ethnic groups,
other institutional variables can intervene: the permissiveness of electoral system (Aksoy, 2010); the
competitiveness of elections (Wilkinson, 2004); cost-benefit calculations depending on being
incumbent or challenger (Collier and Vicente, 2009)7. The nature of elections (national or local) can also
7 In a recent study about elections in Nigeria, Collier and Vicente (2009) come to this result through a field
experiment. They found that voter intimidation is effective in reducing voter turnout, and that violence was
systematically dissociated from incumbents, contradicting Wilkinson (2004)’s results. Interestingly, they
established that incumbents have a comparative advantage in alternative strategies as vote buying and ballot
fraud, because they control both the electoral process and state resources.
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have an impact as some recent studies suggest. According to the econometric results in Sánchez &
Chacón (2005), decentralization process in Colombia has been negatively correlated with the increase of
guerilla violence, since they found “a strong connection between the intensification of armed activities
and local governments’ greater political independence and fiscal strength”. This finding is consistent
with qualitative evidence in Italy, and the current paper aims at testing empirically whether criminal
organizations are more likely to employ violence during local elections. Therefore I formulate a
following hypothesis:
Hypothesis 2. Intimidation attacks are most likely to increase when local elections are close.
This hypothesis helps me testing the argument that criminal organizations deepen their ties with local
society (Sciarrone, 1996), because they are basically single and autonomous criminal groups without a
centralized governance. Therefore, the influence of local politics is the first goal to be reached by these
groups.
4. DATA SOURCE AND CONSTRUCTION
The most important data for this study are on criminal-electoral violence. They are provided by
the Servizio di Indagine (SDI), under the Italian Minister of Interior. The SDI collects data about crimes
reported by the three main Italian police forces (Arma dei Carabinieri, Polizia di Stato, Guardia di
Finanza) to the courts. The system aggregates criminal acts in several categories by type of action and
crime. The measure of criminal-electoral violence is constructed by simply aggregating two of these
variables: “arson attacks” and “incendiary attacks” (“incendi dolosi” and “attacchi dinamitardi e
incendiari”). I employ the number of incendiary and explosive attacks as indicator of criminal violence
among other types of mafia offences reported by the police. By doing so, I explicitly restrict my analysis
to real cases of mafias’ violence. Other reported offences – such as extortion, criminal association,
drugs dealing – encounter at least two limits: they capture only the effectiveness of anti-mafia
programs, and they are not related to electoral process. This is the reason why I decide also to use the
offences reported by the police instead of the crimes prosecuted by district tribunals and gathered by
the Minister of Justice.
I have variable criminal violence for each month in the period 1983 to 2003. The uniqueness of
this dataset derives from the temporal disaggregation, which permits to exploit temporal variation in
violence to better understand its causes and effects. I selected the period 1983 to 2003 for two reasons:
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since 1983 police forces reported separately crimes committed by criminal organizations from ordinary
crimes; second, the information system of data collection changed after 20038. The sample consists of
103 provinces for the full sample which includes 24 provinces located in 4 southern regions where
mafias are deeply rooted in: Campania, Puglia, Calabria and Sicily. In order to increase the number of
observations I consider separately the variation in crime both in province principal towns (capoluoghi)
and in the rest of the province (which includes all towns in the province except for principal towns). I
check the robustness of the results with a more precise measure of criminal organizations’ presence in
the areas computing the number of people arrested for mafia-association in each province and principal
towns. In this panel are included those units that have a value of mafia-type association arrests above
the 75th percentile.
Concerning the reliability of these data, although indicators on crime and delinquency are
notoriously fraught with problems, the indicators used in this paper are expected to be well measured.
Under-reporting is negligible for arson attacks because we can suppose that they are well reported for
insurance purposes, but also because police and fire department necessarily intervene in these
circumstances. However, offences reported as ‘arson attacks’ do not include in their sample those cases
of intimidation which are mainly under-reported by victims because they may be unwilling or afraid to
report to authorities for a variety of reasons9. Tactics used by criminals to influence voters, politicians,
bureaucrats is much more complex than simple arson attacks. As the qualitative evidences show, mafias
intimidate politicians, voters and enemies in a myriad of ways. To summarize, the present source only
takes into account what is reported, not what goes unreported. However, information collected by
police are a reliable source of criminal violence, thus I can assume that the dependent variable is
accurately measured.
While temporal disaggregation makes practically feasible the explanation of variation in violence
across months, data do not provide information about both victims and offenders of such events10.
First, I do not use victimization data, which means that we don’t know the victims of these intimidation
attacks. Therefore, the panel includes all violent acts, not only those targeting voters, politicians,
bureaucrats. I deal with this inconvenience by coding as electoral only the month in which electoral
Under the “165 scheme report”, Servizio di indagine e analisi criminale collected data about those
crimes reported by three Italian police forces (Polizia di Stato, Arma dei Carabinieri and Guardia di Finanza) in
all Italian provinces from 1983 to 2003. The system of reporting was not based on a hierarchical rule according
to severity of criminal events, but, on the contrary, gather data about specific and single criminal acts and
offenses. It included up to 20 separate offenses per incident, without providing elements on victims and
offenders.
9 Many examples of intimidation can be not reported to the police, such as when victims receive letters
containing bullets, or attacks which do not need the intervention by the police or the firefighters.
10 A further inconvenient is represented by the aggregation over provinces, instead of municipalities. If most
violence occurs in a particular town, aggregation to the provincial unit of analysis has the effect of biasing the
results in favor of finding a stronger relationship between the explanatory and independent variables.
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process effectively take place and the month prior to elections. Election-related violence is centered
around a moment. By isolating it to one month I make more tractable and reliable the measurement of
criminal and electoral violence. Second, except for mafioso homicides and mafia-type association crime,
I do not get information about offenders, i.e. who actually commit those crimes.
Concerning elections, Table 1 shows when regional elections have taken place in Italy from
1983 to 2003 (5 times). Elections are held in different years across regions and it will be used as a
source of identifying variation among groups.
5. ORGANIZED CRIME AND VIOLENCE: DESCRIPTIVE ANALYSIS
Before proceeding to analyze criminal violence, I do a brief assessment of the criminal presence over
time and across regions in Italy. Starting with mafia-association crimes, data show that their distribution
varies across provinces even in Southern Italy. Although it is heuristically valid to speak of ‘mafia-type
association’ for the four regionally-based organized crime networks11, Italian mafia cannot be
considered as though it was a uniform and nation-wide entity, or even regionally organized. Several
features concerning origins and development deserve attention from a comparative perspective. No
single organizational formula is applicable to all Italian mafia groups. Every group has its own criminal
formula, degree of institutionalization, strategic objectives, expressed by the different temporal and
geographical expansion dynamics. According to the Direzione Nazionale Antimafia, 40 criminal groups
are counted in those regions, with ramifications in several provinces of northern Italy and other
countries in Europe (Paoli, 1997).
Therefore, if we look at the distribution across regions, Southern Italy is the area where criminal
organizations mostly operate. Figure 1 illustrates the geographic distribution and evolution of mafiatype association crime and other mafia-related crimes (i.e. extortion and mafia-type homicides) from
1983 to 2003. A huge divide exists between the rest of country and four regions in particular:
Campania, Apulia, Calabria and Sicily (see Figure 3). Since the inclusion of the mafia-type association
crime into the criminal code in 1982, more than 4350 people have been arrested for being a member of
a mafioso organization. Data on mafia-type homicides depict again a highly polarized phenomenon. In
Among various definitions, I use in this paper the legal one provided by the Italian Criminal Code, relying on
the empirical definition adopted by the law-enforcement agencies in reporting mafia related crimes. The criminal
code provides a specific definition of mafia-type organized crime as having additional characteristics. According
to article 416 bis: “the organization is of the mafia type when its components use intimidation, subjection and,
consequentially, silence (omertà), to commit crimes, directly or indirectly acquire the management or the control
of businesses, concessions, authorizations, public contracts and public services to obtain either unjust profits or
advantages for themselves or others”.
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twenty years, more than 5570 mafia-related homicides have been committed until 2003, mainly in the
same regions. Calabria is the one with the highest per-capita rate (see Figure 2). Figure 5 shows the
evolution of mafias’ homicides and intimidation attacks in twenty years (1983-2003). It reveals that a
huge peak in mafias’ homicides was at the beginning of nineties due mafia wars and the instability
created by anti-mafia legislation. In contrast, despite the recent decrease in homicides, intimidation
attacks are progressively increasing and counter-intuitively it might prove that these organizations can
relay anymore on non-coactive resources in lobbying and illegal activities, but they need to engage in
violence in order achieve their criminal goals.
Moreover, although the concentration in few regions, the distribution of these crimes varies
across provinces even within regions under organized crime’s control. Figure 2 and 3 show that some
southern provinces have a lower crimes rate, such as in Sicily (Ragusa, Enna) or in Campania (Avellino,
Benevento). As we will see in the empirical section, the variation within regions will be useful to
identify more homogenized control groups.
Among the provinces Figure 6 shows the raw correlation between the number of mafia
members per 100,000 inhabitants and provincial levels of violent and non-violent crimes. It appears
that while the estimated correlations between mafia indicators and crimes are only mild for non-violent
crimes, they are clearly strong and positive for violent crimes. Organized crime’s penetration is
therefore correlated with the outcome this study seeks to explain. Criminal violence, measured as
intimidation attacks, is positively associated with the penetration of organized crime in the same area.
This is important because in this study I argue that criminal-electoral violence is mostly organized and
strategically employed by these organizations.
A further proof of this relation is well illustrated in Figure 7. The plot shows that in Southern
Italy intimidation attacks evolve differently in electoral and non-electoral provinces. In contrast, trends
in the rest of country show an increase during the months after the elections, and this can be easily
explained by the fact that the right part of the plot displays summer months. Therefore, in line with
Figure 7, pre- and post-elections average comparison suggest that elections increase criminal violence.
In contrast, no marked pre-post difference arises for other type of crimes, robbery or homicides. I
argue below that one should not expect these categories to be affected by elections. In fact I will use
them as falsification tests. Moreover, an overview of the summary statistics on electoral and nonelectoral provinces in Table 2, suggests that only in organized crime territories the difference between
electoral and non-electoral is relevant. In the pre-electoral period, the average two-months rate was 11,6
in electoral provinces. This is 10% higher than in the post-electoral one. In all cases expect for southern
electoral areas, intimidation attacks are lower value in pre-electoral periods. Finally, while intimidation
attacks are slightly higher in electoral areas during elections, in non-electoral areas these attacks are
markedly higher in the post-elections periods. Concerning other crimes (rubbery, extortion, homicides),
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they show similar trends simultaneously in electoral and non-electoral areas, suggesting that the
variation is explained by other cross-areas time invariant effects. This is the case of rubbery which is
slightly higher in pre-electoral periods but in both groups.
6. EMPIRICAL STRATEGY
This empirical section aims at identifying the effect of elections on criminal violence. This impact can
be estimated by computing for every province the change in criminal violence in electoral and nonelectoral time periods, i.e. in the months immediately prior and after elections. Given the high
frequency of data (monthly data at a sub-provincial level), I argue that a significant variation in violence
during election times can reliably be explained mostly by the approaching of elections. However, many
other factors unfolding over times, besides elections, might have caused the change in violence over
time. In order to exclude the presence of confounding factors, I adopt a difference-in-differences
identification strategy, which is usually used in economics to study the impact of some ‘treatments’ (i.e.
policy reforms) on economic issues such as unemployment, income convergence, etc. etc. This
estimation model compares changes over time for treated units with the change experienced by a
control group in the same time period. Applied to this study, elections can be considered as a suitable
form of treatment. In fact: (a) elections are clearly exogenous since organized crime cannot affect their
timing; (b) they also occur at a single point in time because they have clear starting and stopping dates
thus it permits to observe the variation in criminal violence both before and after elections are held; (c)
and finally we have more elections over time (i.e. more pre-/post- time periods) and they do not occur
necessarily across provinces at the same moment (as regional elections do).
In this setting the control group is composed by areas which do not experience elections in the
same time period. Thus, the impact of elections on criminal violence can be estimated by computing a
double difference, one over time (before-after elections) and one across units (between electoral and nonelectoral areas). The crucial assumption is that in the absence of elections the trend among the two
groups would have been the same.
In order to be more precise, the outcome variable is some measure of criminal violence. For
each province I measure monthly arson and bomb attacks (“attacchi dinamitardi e incendiari” and
“incendi dolosi”). The selection of electoral periods is constrained by data disaggregation, since the
dataset provides monthly crimes per province. Therefore, in this study electoral periods are defined as
the month prior and the month when elections take place; otherwise non-electoral periods are defined
12
as the two months after elections12. By this selection I cover the entire time period of electoral
campaign, and for symmetry, I define the non-electoral period to be as long as the former and it
effectively covers the time in which the new elected representatives take up office. The strategy to
shortening the span of the electoral period is justified by the need to capture those reported crimes that
– I assume – are connected to the electoral process rather than to other illegal goals (Angrist and
Pischke, 2008).
Concerning the selection of control groups I use a simple method. Table 1 lists two groups of
areas in which regional elections are held in different years13. Control areas have to be ‘very similar to
the treatment group’ but for the treatment (Bertrand et al., 2004). For this reason, I select those areas
that do not receive the treatment, i.e. elections, during the same period. In this control group, for
defining electoral and non-electoral months I follow the same strategy used for the treatment group as
described above. To summarize, I estimate several versions of the following model:
Violencepi,t = α + β ELECT_PROVpi + γPRE_ELECTt
(1)
+ δElections pi,t + Dp + Di + Dt+ εpi,t
In this specification,
VIOLENCEpi,t are intimidation attacks in period t and area i of province p. The variable is constructed by
summing reported crimes about arson and bomb attacks ("Incendi dolosi" and "Attentati dinamitardi e
incendiari"), by area of the province and time period;
ELECT_PROVpi is defined as a dummy variable assuming value 1 if in areas p and i elections take place;
otherwise it will be 0;
PRE_ELECTt is defined as a dummy variable assuming value 1 if month t is the one prior or the same of
elections; otherwise it will be 0;
Electionspi,t is the interaction term – i.e. the product of the two binary variables (ELECT_PROVpi*
PRE_ELECTt) and it is equal to 1 only in those months and provinces when and where elections are held.
Dp province fixed effects;
Di area fixed effects;
Dt time fixed effects
εpi,t is the error term of the regression with variance σ2
p indicates province; i indicates the area of the province (every province is composed by two areas: one coincide
with the municipality of the main city, the other include the rest of the province); t indicates the month of a
certain year;
α, β, γ , δ are the regression parameters to be estimated
In this equation δ is the key coefficient which identifies the causal effect of elections. It is
obtained by calculating the ‘difference in differences’ equal to the change in mean outcomes of violence
12 I also tested a model in which I define as electoral month only the month prior to elections and results are still
significant.
13 Information on both dates and provinces are taken from the Anagrafe degli amministratori locali, Minister of
Interior (1983-2003).
13
for the electoral provinces minus the change in mean outcomes for the control group, i.e. not electoral
provinces. Assuming that the only treatment pre- and post-elections between the two groups are
elections, δ identifies its effect. If elections tend to increase (decrease) violence among the electoral
provinces then δ is positive (negative). Any cross-regime time effects on criminal-electoral violence
over periods are captured by γ, and any time-invariant differences in criminal-electoral violence between
groups is captured by β. Observations are clustered at the city level, hence all estimated standard errors
are robust to within province correlation.
I run the baseline regression for full sample (all Italian provinces). Then the analysis is restricted
to explore the casual mechanisms among areas of the country. I examine Center-North Italy, Southern
Italy and finally, in a further specification of the model, as robustness check, I restrict the sample to
those provinces that have a value of mafia-association arrests above the 75th percentile. I expect that
the relation would be not significant for Northern Italy (2.a) due the lack of organized crime
penetration. In the last two models (2.b and 3) I expect a significant and positive correlation even
though I restrict the sample. The diff-in-diffs estimation for organized crime provinces (3) is crucial
because groups within this panel are very similar, and therefore it is more valid the assumption that in
the absence of elections the trend among the groups would have been the same.
7. MAIN ESTIMATES
Table 3 shows the main estimates of several versions of model (1). All models include a full set
of time, province and principal town dummies. Column (1) in panel (I) shows the estimates of the
linear regression for full sample. The estimated coefficient on the variable Electionspi,t (δ) is +1,1 and it is
statistically significant as we expected. Results show that as elections approach there is an increase of
1.1 intimidation attacks compared to the case in which elections had not occurred. More interestingly,
even though the coefficient of PRE_ELECT does not answer directly to our research question, it
shows clearly that in general, without considering the effective occurrence of elections, there is a
significant and positive increase in criminal violence in post-electoral months (+2,5). This result is
plausible if we consider that in our panel post-electoral months usually correspond with summer when
temperatures are naturally higher. Figure 8 clearly shows the evolution of intimidation attacks to and
from elections in Northern and Southern regions. The figure graphically confirms these first results. In
contrast, Figure 9 proves that other crimes (robbery) do not evolve differently in electoral and nonelectoral periods both in electoral and non-electoral areas.
14
Therefore, this first estimation confirms the hypothesis that criminal organizations are most
likely to engage in violence during elections. However, the magnitude and the significance of the
relation is slightly weak. One can argue that organized crime is not equally distributed across regions in
Italy. If this is true we should not expect an increase in criminal violence as elections approach in those
provinces not controlled by criminal organizations. In order to test it, in the following columns (2.a and
2.b) I break down the full sample in two panels Center/North Italy and Southern Italy (Campania,
Puglia, Calabria, Sicily). Results clearly change. In panel 2.a, the relation is not significant anymore and
weaker in magnitude. On the contrary, results in column (2.b) for Southern Italy show that as we move
to some areas controlled by organized crime the relation between elections time and criminal violence is
stronger. By restricting the panel I identify a more homogenous sample for those unobserved
characteristics (political culture, social capital) across provinces that can affect the estimation. For
Southern provinces, the estimated coefficient on the variable Elections (β3) is 2.1, and it is well estimated
(t-value +2,57). Given that on average in every electoral province there are 9,3 attacks per electoral
period, according to our estimates elections produce an increase in intimidation attacks by 22%.
Moreover in the last column, I test the robustness of the previous finding, by looking at those areas
that have a value of mafia-association arrests above the 75th percentile. Restricting the attention to
organized crime areas involves a variance-bias trade-off. On the one hand, excluding non-organized
crime discards relevant variation and increases variance. On the other hand, restricting the sample to
organized crime areas I reach two goals reducing potential bias: concentrating on them helps to
“homogenize” the control and treatment groups; second, it reduces the risk of capturing potential
unobserved characteristics across provinces. The results of column (3) clearly show that elections
timing explains variation in criminal violence. In this model the estimated coefficient is a much bigger
in magnitude (+3.4), moreover, the relation is still significant at 5% although a sharp reduction in the
number of observations (640 obs.).
Moreover, I test the same models but weighted by population (per 100,000 inhabitants), which
serves to emulate a regression at the individual level. The weight is in population in 1991 (National
2001 Census, Istat). Estimates should be compared within a column. Results in columns WLS show
that the estimated impact of elections is robust to weighting procedure.
An alternative way to test the models is the estimation of the effect of elections on common
crimes. I suppose, in fact, that common crimes are not significantly related with the electoral months
since they are not related to criminal intimidation. Columns (Rubbery Extortion Homicides) show that no
significant correlation exists between common crimes and electoral timing. Similar fixed-effects to
model (1) are used here to test the robustness of this specification, and the panel is restricted to
organized crime provinces. Moreover, even thought the sign of this relation is not relevant for this
study, the negative coefficient indicates a decrease in the volume of those crimes before elections.
15
Therefore we can argue that only mafia crimes can be considered politics-oriented in the sense that they
are correlated with institutional variables, such as elections. Finally, I test separately the impact of
national elections (column National Elections). The results show that legislative elections are not
significantly correlated with mafia violence. The estimated coefficient on the national elections is also
smaller in magnitude -0.2 and more interestingly it is negative. Evidence shows that criminal
organizations do not use violence during legislative elections as they do for local elections due the
different nature of the electoral race.
To summarize the robustness checks, difference-in-differences estimations using different
panels and types of crime, provide the basis for validation and falsification tests and support the
estimation strategy. A further step of this analysis would be to test whether this violence can decisively
affect electoral outcomes in Italy, but due the availability of data no statistical evidence about that can
be offered at this moment.
8. CONCLUSIONS
According to the estimation, elections cause monthly intimidation attacks to increase by almost
2,1 in Southern provinces, and by 3,4 in organized crime areas, which means a 22% increase in the first
case and a 31% in the second one. To the best of our knowledge, this is the first estimate of the impact
of elections on criminal violence accounting for cross-areas and secular trends. These findings are
consistent with a large case study literature documenting the interventions of criminal organizations
into the electoral process in Southern Italy.
Moreover, even though the goal of the study was not to evaluate empirically the effects of
criminal-electoral violence upon the electoral process, we can reasonably argue that in some parts of the
country an impact on electoral turnout or on voters’ preferences might be discovered. The effect of
criminal-electoral violence still needs to be estimated carefully. In fact, by moving beyond the existing
work, I argue that the increase in criminal violence during electoral campaigns is not linked with
stronger criminal control upon electorate, but, in contrast, it is associated positively to higher degree of
opposition and electoral accountability. If criminal organizations had a direct control both of voters and
agenda-setting, violence would be unnecessary. In contrast, the growing incidence of violence may be
an indicator of greater levels of opposition, and a lessening of voter mobilization control. Violence is
costly, especially when it is employed too liberally. In that case, criminal organizations may attract
unwanted attention from law enforcers or produce a counter-mobilization by civil society. There is less
16
violence in organized crime than international cinema and journalism suggest. It is often the threat of
violence, rather than its exercise, the source of mafias’ power to compel others to do what they
otherwise would not. Diego Gambetta makes the point in his study of the Sicilian mafia: «violent
action, while crucial, is only occasionally demanded of a mafioso (although it must always be perceived
as a potential threat)» (Gambetta, 1993:273). The likelihood to use intimidation depends on an
evaluation of likely payoff from relying on alternative non-violent resources (money, reputation,
membership) and the capacity to effectively influence candidates and voters (Collier and Vicente, 2009).
Violence is only one, and probably the most costly resource to be exploited in order to provide mafioso
“protection”, compared to non-coercive means which are equally strategic, such like reputation and
information (Gambetta, 1993). When non-violent means become useless, violence is the only available
tactic to influence elections. Motivated by this evidence, I argue that an increase of criminal violence
could be interpreted as an unexpected effect of political accountability and of the end of one-party
dominance in many provinces in Southern Italy since the ‘80s.
The availability of victimization data would help us scrutinizing this mechanism. These data can
reveal which side of the political market is particularly favored and targeted by criminal organizations.
In fact, criminal groups may choose between two different channels to affect representation: the
demand side or the offer side. In the first case, the attempt to change preferences of restive voters
through intimidation is not only the most costly strategy, but also the less effective because it might
lead to unforeseeable outcomes, such as the increase of antimafia opposition. Only in small
municipalities where criminal groups can control directly voters, we can suppose that it would be
rational to use violence to convince them.
In other conditions, the alternative way is more attractive and cheap. Criminal organizations can
target the offer side of political market, by contributing to candidate nominees or creating a climate of
fear and terror that would raise the cost of political campaigns and, especially at local level, it would
avoid people from standing as candidate cause the risk of being victim of such violence. This becomes
the first-best option if criminal groups are capable to capture the nominee of that candidate with
preferences very close to theirs, and most likely to win such elections. When criminal groups are not
able to capture candidates, therefore they tend to more often resort to violent means to exert influence
at a time when the degree of electoral uncertainty is higher. Increased level of competition around
election times motivates criminal groups to use violence to influence electoral results.
The findings of the paper confirm the abundant judiciary evidence about criminal-electoral
violence. More importantly the paper illustrates a previously unexplored dynamic between electoral
institutions and the strategic timing of organized crime’s intimidation attacks. However, a full analysis
on electoral behavior and turnout should be conducted in order to assert confidently that criminal17
electoral violence has an effect on them. A similar study would help researchers evaluating whether
organized crime can only mobilize voters or also change their preferences.
18
Table 1
Regional Elections in Southern Italy (1983-2003)
Source: Archivio Elettorale, Ministero dell’Interno
Region
Sicilia
Calabria
Campania
Puglia
Province
Agrigento
Caltanissetta
Catania
Enna
Messina
Palermo
Ragusa
Siracusa
Trapani
Catanzaro
Cosenza
Crotone*
Reggio Calabria
Vibo Valentia*
Avellino
Benevento
Caserta
Napoli
Salerno
Bari
Brindisi
Foggia
Lecce
Taranto
Regional Elections
National Elections
June 24, 2001
June 16, 1996
June 16, 1991
June 22, 1986
April 16, 2000
April 23, 1995
May 6, 1990
May 12, 1985
May 13, 2001
April 21, 1996
March 27, 1994
April 5, 1992
June 14, 1987
June 26, 1983
19
Kkkkkk
Figure 1
Fig. 1.1
Fig. 1.2
Evolution of mafia-type association rate (c.p 416 bis) in Southern Italy and in the rest of country from 1983 to 2003
(Left: total number/Right: Crime Rates per 100.000 inhabitants) Source: SDI Min. Interno
Evolution of extortion rate reported in Southern Italy and in the rest of country from 1983 to 2003 (Left: total number/Right:
Crime Rates per 100.000 inhabitants) Source: SDI Min. Interno
Fig. 1.3 Evolution of mafia-type homicides in Southern Italy and in the rest of country from 1983 to 2003 (Left: total number/Right:
Crime Rates per 100.000 inhabitants) Source: SDI Min. Interno
20
Fig. 2 Mafia-type homicides in 50.000 inhabitants (1983-2003)
Source: SDI Min. Interno
Fig. 3 People arrested for mafia-type association (c.p 416 bis) 19832003 per 50.000 inhabitants Source: SDI Min. Interno
Fig. 4 City Councils dissolved by central government due mafias’
penetration (1991-2009) Source: Criminal-Political Capture Dataset,
Sberna 2010
21
Figure 5
Evolution of mafia-type homicides and intimidation attacks from 1983 to 2003
Source: SDI Min. Interno
22
Figure 6
Violent and Non-Violent Crime Correlation by Mafia Density (1983-2003)
Source: SDI, Ministero dell’Interno
INTIMIDATION
ATTACKS
TENTATI
OMICIDI
0,5
ESTORSIONI
ROBBERY
0,4
INGIURIE
OMICIDI COLPOSI
STRAGE
0,3
HOMICIDES
0,2
RICETTAZIONE
0,1
PERCOSSE
INCENDI
0
DELITTI INFORMATICI
VIOLAZI. PROPRIETÀ INTELLETT.
-0,1
SFRUTTAMENTO PROSTITUZIONE
RICICLAGGIO
-0,2
VIOLENZE SESSUALI
ASSOCIAZ. DELINQUERE
ALTRIDELITTI
LESIONI DOLOSE
FURTI
ATTENTATI
OMICIDIO PRETERINT.
STUPEFACENTI
MINACC
CORRUZIONE MINORENNE
INFANTICIDI
SEQUESTRI PERSONA
CONTRABBANDO
TRUFFE
DANNEGGIAMENTI
USUR
ATTI SESSUALI CON MINORENNE
CONTRAFFAZIONE
Lllllllllllllllllllllllllllll
Figure 7
Intimidation attacks for months to and from elections
Note Source: SDI, Ministero dell’Interno
23
Table 2
Summary Statistics, Electoral and Non-Electoral Areas
North
Electoral areas
Pre-Elect Post_Elect
Intimidation Attacks
Extortion
Robbery
Homicides
2,84
(9,03)
0,75
(1,88)
8,22
(27,09)
0,15
(0,51)
3,04
(7,55)
0,88
(3,73)
8,18
(26,40)
0,16
(0,53)
Non-electoral areas
Pre-Elect Post_Elect
2,43
(4,98)
0,83
(1,71)
8,59
(28,34)
0,16
(0,56)
3,05
(6,49)
0,75
(1,72)
8,47
(27,04)
0,16
(0,51)
South
Electoral areas
Non-electoral areas
Pre-Elect Post_Elect Pre-Elect Post_Elect
Intimidation Attacks
Extortion
Robbery
Homicides
9,43
(10,9)
2,59
(4,25)
29,51
(67,62)
0,63
(1,31)
9,16
(9,66)
2,61
(3,60)
28,85
(65,45)
0,625
(1,16)
8,52
(9,21)
2,84
(3,94)
31,61
(77,46)
0,71
(1,28)
9,98
(11,11)
2,49
(3,87)
28,22
(66,98)
0,77
(1,38)
Organized Crime Areas
Electoral areas
Non-electoral areas
Pre-Elect Post_Elect Pre-Elect Post_Elect
Intimidation Attacks
Extortion
Robbery
Homicides
11,66
(12,81)
3,21
(5,49)
53,99
(95,36)
0,89
(1,72)
10,93
(10,30)
3,38
(4,31)
52,79
(92,12)
0,97
(1,49)
9,625
(10,19)
3,275
(4,36)
59,28
(110,91)
1,04
(1,56)
12,70
(13,34)
3,10
(4,97)
52,44
(95,55)
1,01
(1,65)
Note: Northern Italy, 158 areas and 10850 obs.; Southern Italy, 48 areas and 1456 obs; OC Areas, 20 areas
and 640 obs. Source: SDI, Ministero dell’Interno.
24
Table 3
Main Estimates
(I) Dependent variable: Monthly intimidation attacks
(1)
Italy
(2.a)
Center/North
(2.b)
South
(3)
Organized Crime Prov.
PRE-ELECT
-2.454
(0.610)***
0.165
(0.321)
-8.989
(1.627)***
-12.151
(2.957)***
ELECT_PROV
0.164
(0.431)
0.500
(0.751)
-0.813
(0.571)
-1.896
(0.981)*
Elections
1.130
(0.655)*
0.392
(1.088)
2.096
(0.817)**
3.430
(1.388)**
CONSTANT
8.717
(0.715)***
2.012
(0.193)***
13.986
(1.486)***
21.657
(2.692)***
OBSERVATIONS
17420
10940
1456
640
PROV. FIXED EFF.
YES
YES
YES
YES
TIME FIXED EFF.
YES
YES
YES
YES
PRINC. TOWN
YES
YES
YES
YES
FIXED EFFECTS
Note: Robust standard errors in parentheses *** significant at 1% ** significant at 5%; * significant at 10% ; Elections are all regional
elections from 1983 to 2003; Source: SDI, Ministero dell’Interno
(II) Dependent variable: Monthly intimidation attacks per 100000 inhabitants
(WLS.1)
Italy
(WLS.2.a)
Center/North
(WLS.2.b)
South
( WLS.2.b )
Organized Crime Prov.
-0.229
(0.052)***
-0.317
(0.053)***
-0.746
(0.244)***
-0.911
(0.289)***
ELECT_PROV
0.443
(0.183)**
0.424
(0.241)*
-0.039
(0.322)
-0.227
(0.354)
Elections
0.007
(0.131)
0.027
(0.136)
0.752
(0.393)*
1.007
(0.472)**
CONSTANT
2.500
(0.257)*
0.353
(0.127)***
1.164
(0.490)**
1.164
(0.490)**
PRE-ELECT
OBSERVATIONS
17420
10940
1456
1136
PROV. FIXED EFF.
YES
YES
YES
YES
TIME FIXED EFF.
YES
YES
YES
YES
PRINC. TOWN
YES
YES
YES
YES
FIXED EFFECTS
Note: Robust standard errors in parentheses *** significant at 1% ** significant at 5%; * significant at 10% ; Elections are all regional
elections from 1983 to 2003; Source: SDI, Ministero dell’Interno
(III) Dependent variable: Other crimes per 100000 inhabitants
Intimidation Attacks†
Extortion
Rubbery
Homicides
PRE-ELECT
0.219
(0.233)
-0.819
(0.619)
0.052
(0.059)
ELECT_PROV
0.103
(0.231)
0.000
(0.556)
0.066
(0.063))
Elections
-0.230
(0.333)
-0.736
(0.810)
-0.133
(0.083)
-0.184
(0.610)
CONSTANT
1.441
(0.542)***
2.147
(0.939)**
0.226
(0.161)
10.548
(0.605)***
OBSERVATIONS
620
620
PROV. FIXED EFF.
YES
YES
TIME FIXED EFF.
YES
YES
PRINC. TOWN
YES
YES
FIXED EFFECTS
Note: Robust standard errors in parentheses *** significant at 1% ** significant at 5%; *
elections in 1983-2003 sequence; Estimations for Organized Crime Provinces Panel (75th
legislative elections; Source: SDI, Ministero dell’Interno
620
YES
YES
5040
YES
YES
YES
YES
significant at 10% ; Elections are all regional
percentile); †Single-difference estimation for
25
Figure 8
Intimidation attacks for months to and from elections
Note Source: SDI, Ministero dell’Interno
26
Figure 9
Robbery crimes for months to and from elections
Note Source: SDI, Ministero dell’Interno
27
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