Organised Crime and Technology

This paper investigates the relation between the presence of organized crime and the technology level in north Italy. Our analysis proposes two provincial indexes. The first portrays technology at a fine-grained industrial sector level. The second describes mafia-type organizations in line with the investigation approach currently used by Italian National Antimafia Directorate (DNA) and Antimafia District Directorates (DDAs). With these indexes, we provide empirical evidence that in north Italy, the larger the presence of organized crime, the less innovation and the technological level of the industrial fabric. Our reading of this finding is that without organized crime, Nature selects agents according to their capacity to innovate. Instead, with organized crime, agents can choose an alternative strategy: relate with organized crime, which hinders innovation. Modelling the interaction innovation - relation with mafias by evolutionary game theory, we show that the presence of organized crime, through natural selection, leads to low levels of technology. Our model also shows how to use sanctions and indemnities to address the problem.

[1]  R. Blundell,et al.  Market share, market value and innovation in a panel of British manufacturing firms , 1999 .

[2]  M. Partridge,et al.  Geography and High-Tech Employment Growth in US Counties , 2014 .

[3]  T. Besley Property Rights and Investment Incentives: Theory and Evidence from Ghana , 1995, Journal of Political Economy.

[4]  Giuseppe Albanese,et al.  Organized Crime and Productivity: Evidence from Firm-Level Data , 2013 .

[5]  Marco Di Cataldo,et al.  Organised Crime, Captured Politicians and the Allocation of Public Resources , 2018 .

[6]  Jeffrey M. Woodbridge Econometric Analysis of Cross Section and Panel Data , 2002 .

[7]  Oshua,et al.  USING MAIMONIDES’ RULE TO ESTIMATE THE EFFECT OF CLASS SIZE ON SCHOLASTIC ACHIEVEMENT* , 2003 .

[8]  Josh Lerner,et al.  The Financing of R&D and Innovation , 2009 .

[9]  Franco Pelella I. Sales, Storia dell'Italia mafiosa. Perché le mafie hanno avuto successo , 2016 .

[10]  Magne Mogstad,et al.  The Skill Complementarity of Broadband Internet , 2015, SSRN Electronic Journal.

[11]  Georg Graetz,et al.  The Review of Economics and Statistics , 2018 .

[12]  Robert E. Carpenter,et al.  Capital Market Imperfections, High-Tech Investment, and New Equity Financing , 2002 .

[13]  Sauro Mocetti,et al.  Natural Disasters, Growth and Institutions: A Tale of Two Earthquakes , 2014 .

[14]  G. Spagnolo,et al.  Competition Policy and Productivity Growth: An Empirical Assessment , 2009, Review of Economics and Statistics.

[15]  Michael P. Murray,et al.  The Bad, the Weak, and the Ugly: Avoiding the Pitfalls of Instrumental Variables Estimation , 2006 .

[16]  Paolo Pinotti,et al.  The Economic Costs of Organised Crime: Evidence from Southern Italy , 2015 .

[17]  R. Axelrod,et al.  Evolutionary Dynamics , 2004 .

[18]  E. Papaioannou,et al.  Human Capital, the Structure of Production, and Growth , 2005, The Review of Economics and Statistics.

[19]  Diego Gambetta,et al.  The Sicilian mafia: the business of private protection , 1994 .

[20]  Francesco Calderoni,et al.  Where is the mafia in Italy? Measuring the presence of the mafia across Italian provinces , 2011 .

[21]  Allan Kearns,et al.  The tangible contribution of R&D-spending foreign-owned plants to a host region: a plant level study of the Irish manufacturing sector (1980-1996) , 2001 .

[22]  P. Bustos Trade Liberalization, Exports, and Technology Upgrading: Evidence on the Impact of MERCOSUR on Argentinian Firms , 2011 .

[23]  G. Mastrobuoni The Value of Connections: Evidence Based on the Italian-American Mafia , 2013 .

[24]  D. Masciandaro,et al.  Is It Worth Having the Sopranos on Board? Corporate Governance Pollution and Organized Crime: The Case of Italy , 2017 .

[25]  Steven D. Levitt,et al.  The Effect of Prison Population Size on Crime Rates: Evidence from Prison Overcrowding Litigation , 1995 .

[26]  Leslie E. Papke,et al.  Panel data methods for fractional response variables with an application to test pass rates , 2008 .

[27]  F. Chiesa Passaggio a Nord : la colonizzazione mafiosa , 2016 .

[28]  D. Hecker,et al.  High-Technology Employment: A NAICS-Based Update: Among High-Technology Industries-Those with a High Proportion of Scientists, Engineers, and Technicians-Some Are Projected to Grow Rapidly; Overall, However, This Group of Industries Is Expected to Continue to Grow Slowly , 2005 .

[29]  J. Stock,et al.  Instrumental Variables Regression with Weak Instruments , 1994 .

[30]  J. Hausman Specification tests in econometrics , 1978 .

[31]  Emilia Bonaccorsi di Patti Weak Institutions and Credit Availability: The Impact of Crime on Bank Loans , 2009 .

[32]  Ufuk Akcigit,et al.  The Rise of American Ingenuity: Innovation and Inventors of the Golden Age , 2017 .

[33]  F. Schivardi,et al.  Italy’s Productivity Conundrum. A Study on Resource Misallocation in Italy , 2016 .

[34]  D. Rivers,et al.  Limited Information Estimators and Exogeneity Tests for Simultaneous Probit Models , 1988 .

[35]  Fernando De la Torre,et al.  Robust Regression , 2016, IEEE Trans. Pattern Anal. Mach. Intell..

[36]  R. Paap,et al.  Generalized Reduced Rank Tests Using the Singular Value Decomposition , 2003 .

[37]  Thomas C. Schelling,et al.  What Is the Business of Organized Crime , 2016 .

[38]  Ufuk Akcigit,et al.  Innovation, Reallocation and Growth , 2013, American Economic Review.

[39]  James A. Robinson,et al.  The Colonial Origins of Comparative Development: An Empirical Investigation , 2000 .

[40]  J. Angrist,et al.  Journal of Economic Perspectives—Volume 15, Number 4—Fall 2001—Pages 69–85 Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments , 2022 .

[41]  P. Aghion,et al.  NBER WORKING PAPER SERIES THE CAUSAL EFFECTS OF COMPETITION ON INNOVATION: EXPERIMENTAL EVIDENCE , 2014 .

[42]  F. Palm,et al.  Persistence of Innovation in Dutch Manufacturing: Is It Spurious? , 2006, The Review of Economics and Statistics.

[43]  P. Aghion,et al.  Distance to Frontier, Selection, and Economic Growth , 2002 .

[44]  Giuseppe De Feo Mafia in the Ballot Box , 2014 .

[45]  Philippe Aghion,et al.  ENTRY AND PRODUCTIVITY GROWTH: EVIDENCE FROM MICROLEVEL PANEL DATA , 2004 .

[46]  Philippe Aghion,et al.  The Effects of Entry on Incumbent Innovation and Productivity , 2005, The Review of Economics and Statistics.

[47]  A. Alesina,et al.  Organized Crime, Violence, and Politics , 2016, The Review of Economic Studies.

[48]  P. Buonanno,et al.  Organized Crime and Electoral Outcomes in Sicily , 2014 .

[49]  Federico Varese,et al.  How Mafias Migrate: The Case of the 'Ndrangheta' in Northern Italy , 2006 .

[50]  Daniel Lederman,et al.  What causes violent crime , 2002 .

[51]  S. Nickell Competition and Corporate Performance , 1996, Journal of Political Economy.

[52]  A. Rodríguez‐Pose,et al.  Papers in Evolutionary Economic Geography # 17 . 19 Industrial Clusters , Organized Crime and Productivity Growth in Italian SMEs , 2017 .

[53]  A. Scognamiglio When the mafia comes to town , 2015, European Journal of Political Economy.