Extortion, firm s size and the sectoral allocation of capital

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1 Extortion, firm s size and the sectoral allocation of capital Luigi Balletta Mario Lavezzi June 29, 2013 Abstract In this paper we provide a theoretical and empirical analysis of extortion, which represents a typical activity of organized crime. In particular, we study extortion in the framework of a principal-agent model, where the criminal organization cannot perfectly observe firms productivity. The theoretical predictions of the model are tested against a unique database on extorted firms in Sicily, which contains informations about amounts of extortion and individual firms characteristics. Keywords: Organised Crime, Economic Structure, Sicilian Mafia, Asymmetric Information, Principal-Agent Theory. JEL Classification Numbers: C72, D86, K42. 1 Extended abstract In this paper we provide a theoretical and empirical analysis of extortion, which represents a typical activity of organized crime (see, e.g., Gambetta (1993)) and has a direct consequence on the economy, as it is targeted to firms. Previous economic analyses of extortion focused on the emergence of conflict between firms and criminal organizations ( Konrad Università di Palermo, Italy. Università di Palermo, Italy. 1

2 and Skaperdas (1998)), or on the equilibria characterizing the interaction of a Mafia, firms and the Government ( Bueno de Mesquita and Hafer (2007)). In this paper, we focus instead on the effect that extortion may have on the size of the firms. In particular, our aims in this paper are: i) to study the optimal investment of a firm in presence of extortion. Lavezzi (2008) provides empirical evidence for the intuition of Schelling (1971) that a small size of firms can make extortion easier, 1 therefore providing advantages to criminal organizations. Here we wish to study the opposite casual link going from the presence of criminal organization to the size of the firms, namely the hypothesis that, because of the presence of criminal organizations, firms remain small, in particular they underinvest in physical capital. At present, this hypothesis is supported by casual evidence only. For example, Scaglione (2008b), p. 150, mentions instances in which entrepreneurs claim that they refrain from expanding their business for fear of paying higher tributes to the Mafia. ii) To study the shape of the extortion function, that is the optimal choice by the criminal organization of how much demand to firms as pizzo (the Sicilian word for extortion money). iii) To provide an empirical assessment of the theoretical prediction by studying a unique dataset containing information on pizzo in Sicily for a sample of firms and on their characteristics. In the following we briefly describe the model and the database. 1 [I]n large organisations too many people have to sign the checks, initial the vouchers, audit the books, scrutinize budgets, take inventory... The small independent entrepreneur... would be more able to meet the demands than a complex organization would be Schelling (1971), p

3 2 The model We study extortion in the framework of a principal-agent model, where the criminal organization cannot perfectly observe firms productivity. In our model a monopolistic Mafia chooses optimal extortion as a function of observable characteristics firms. There is a continuum of firms indexed by a productivity parameter θ, distributed according to G( ) with strict positive density g ( ) on the interval [θ L, θ H ]. Moreover G satisfies monotone hazard rate property. As in standard hidden information models, θ is private information of the firm but its distribution is common knowledge. Firm s profits, gross of any amount she is forced to pay to Mafia, are written as θf (K) rk, where K is a choice variable, which can be understood to be capital, as a measure of size of the firm, and r is a parameter, which can be understood as cost of capital. The function f is assumed to be increasing and strictly concave. This assumption guarantees single-crossing. The timing we have in mind is the following. Mafia is a Stackelberg leader and its existence is commonly acknowledged by firms. Its offer for protection is summarized by a function x (K) representing the amount of money asked to a firm which has chosen K. Mafia also makes clear the punishment in the case of non-compliance. We assume its monetary equivalent is a positive real number z, which is exogenous. The idea is that z represents firepower. Higher values indicate a strong organization which is able to inflict much damage to a non-compliant firm. Firms know both x (K) and z when choosing whether to open for business. Once in the market, they choose the amount of observable K optimally. Moreover, they have the choice to refuse to pay the extortion amount, in which case they don t pay x but they suffer the cost z. For the purpose of this basic model, we assume that Mafia has enough reputation concerns that it finds always optimal not to renegotiate the extortion in case of compliance and to inflict the punishment to a non-compliant firm. The sequence of moves 3

4 is therefore the following: 1. Nature extracts type θ that is observed only by the firm. 2. Mafia proposes an extortion function x (K), given the level of firepower z. 3. Firm decides whether to open for business having observed both x (K) and z. Outside option is normalized to 0, independent of firm s type. 4. If the firm is in business, she chooses K to maximize profits. 5. Firm decides whether to be compliant, in which case she pays x (K), or to refuse to pay, in which case she suffers the cost z. The optimization problem of the Mafia can be written in the following compact form: θh max x (θ) dg K(θ),x(θ) θ L s.t. π (θ) = f (K (θ)) π (θ) 0 x (θ) z K (θ) 0. We derive analytically firms optimal investment in K as a function of θ, and the optimal extortion function in two different scenarios: i) a powerful Mafia (PM); ii) a weak Mafia (WM). Scenario i) refers to the case in which the Mafia is able to impose a punishment z large enough so the constraint on x is never binding. Applying standard techniques in contract theory the following proposition follows: 4

5 Proposition 1 Suppose z > x P M (θ H ). The optimal solution to.. satisfies: ( ) (i) θ 1 G(θ) g(θ) f ( K P M (θ) ) = r, (ii) x P M (θ) = θf ( K P M (θ) ) rk P M (θ) θ θ L f ( K P M (s) ) ds. (iii) Denoting with θ P M (K) the inverse of K M (θ) the optimal solution can be implemented via an extortion function x P M (K) = x P M ( θ P M (K) ). Figures 1 and 2 describe the functions K M (θ) and x P M (K) when f (K) = 2 K, G is uniform on [1, 2] and r = 1. In black we report the undistorted (first best) level of K. Figure 1: Optimal K Figure 2: Optimal extortion function It can be observed that there is underinvest in K for all firms type except for the highest θ firm, and that the optimal extortion function is concave. In Scenario ii) a weak Mafia is not able to implement the unconstrained solution of Proposition 1. In this case we derive the following: Proposition 2 Suppose z < x P M (θ H ), where x P M is the solution described in Proposition 1. The optimal solution to the Mafia problem is such that there exists a threshold θ with ( ) (i) θ G( θ) G(θ) g(θ) f ( K W M (θ) ) = r for θ θ. (ii) K W M (θ) = K for θ > θ, where K satisfies θf ( ) K = r. (iii) z θf ( ) K + r K + π (θ l ) + θ θ l f(k (θ))dθ = 0 5

6 We display in Figures 3 and 4 optimal K W M and x W M in green, for the same parameters as in Figures 1 and 2 and for z = 3/2. We compare the solution to the solution for a powerful Mafia in red. Figure 3: Optimal K Figure 4: Optimal extortion function In this case there is still understment, but the optimal K becomes constant at a threshold level of θ, while the optimal extortion function is concave until the critical value of z is reached by the optimal level of x. 3 The Database Data on extortion analyzed in this paper were gathered by the Fondazione Chinnici of Palermo in The database contains information on extortionary activities by Cosa Nostra in the nine provinces of Sicily in the period For a recorded extortion, the database contains information on: 1) the identity of extorted firm; 2) its sector; 3) its 2 The construction of the database was part of a project on The Costs of Illegality (I costi dell illegalità), whose results are published in La Spina (2008) (see also Asmundo and Lisciandra (2008) and Lavezzi (2008)). 3 Approximately, 200 documents were examined and 45 interviews were conducted. 6

7 administrative location (Town, Province, Address); 4) its Mandamento 4 ; 5) the amount of extorted money; 6) the period of the payments; 7) the type of payment: monthly, annual, one-off; 7) the presence of additional impositions (e.g. forced supply, forced hiring of workers, etc.) 8) some reference on the source of data (excerpts from documents, the name of police operation/investigation that originated the documentation). Overall, the database contains 2239 entries 5 of different quality. In particular, the amounts paid are reported precisely only for a subset of cases, that is: 480 observations for monthly payments, 314 and 137 for, respectively one-off and annual payments. The quality of the data, however, varies: the firm is not always perfectly identifiable, 6 and other firms characteristics (sector, location, etc.) are not always present. We matched the database on extortion with information on the firms. In particular, for the 480 monthly payment observations, we identified 327 firms, of which 134 belong to the category of limited companies (Società di capitali) and 193 are instead partnerships (Società di Persone). For the former group it was possible to collect balance sheet data, as they required by law to file a copy at the local Chamber of Commerce, while the latter do not have such obligation. For this group we were able only to collect qualitative data such as the year of creation, the number of employees and whether the firm is still in business. References Asmundo, A., and M. Lisciandra (2008), The Cost of Protection Racket in Sicily, Global Crime 9, A Mandamento is: a district incorporating an average of three mafia families. 5 This number is obtained by considering only one observation per firm, since some firms appear in the database more than once. The original number of recorded extortion cases is approximately For example, an entry of the database may be of this type: commercial activity of Mr Torres, not identified. The choice in this paper was to preserve as much as possible entries for which the amount paid is available, with the obvious limitations implied. 7

8 Bueno de Mesquita, E. and C. Hafer (2007), Public Protection or Private Extortion?, Economics & Politics 20, Gambetta, D. (1993), The Sicilian Mafia: the Business of Private Protection, Harvard University Pres. La Spina, A. (ed.) (2008), I costi dell illegalità. Mafia ed estorsioni in Sicilia, Il Mulino. Lavezzi, A. M. (2008), Economic Structure and Vulnerability to Organized Crime: Evidence from Sicily, Global Crime 9, Konrad, K. A., and S. Skaperdas (1998), Extortion, Economica 65, Scaglione, A. (2008b), Le interviste agli imprenditori, in La Spina, A. (ed.), I costi dell illegalità. Mafia ed estorsioni in Sicilia, Il Mulino. Schelling, T. C. (1971), What is the Business of Organized Crime?, Journal of Public Law 20, Reprinted in T. C. Schelling (1984), Choice and Consequences, Harvard University Press. 8