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Advocatus, et non latro? Testing the Supplier-Induced-Demand Hypothesis for Italian Courts of Justice

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  • Paolo Buonanno

    (University of Bergamo)

  • Matteo M. Galizzi

    (University of Brescia)

Abstract

We explore the relationship between litigation rates and the number of lawyers, in a typical supplier-induced demand (SID) frame. Drawing on an original panel dataset for the 169 Italian courts of justice between 2000 and 2007, we first document that the number of lawyers is positively correlated with different measures of litigation rate. Then, using an instrumental variables strategy we find that a 10 percent increase of lawyers over population is associated with an increase between 1.6 to 6 percent in civil litigation rates. Thus, our empirical analysis supports the SID hypothesis for the Italian lawyers: following an increase in their relative number, lawyers may exploit their informational advantage to induce clients to access to courts even when litigation is unnecessary or ineffective.

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Paper provided by Fondazione Eni Enrico Mattei in its series Working Papers with number 2010.52.

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Date of creation: May 2010
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Handle: RePEc:fem:femwpa:2010.52

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Keywords: Lawyers; Litigiosity; Causality;

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Cited by:
  1. Martin Meier & Enrico Minelli & Herakles Polemarchakis, 2014. "Competitive markets with private information on both sides," Economic Theory, Springer, vol. 55(2), pages 257-280, February.
  2. Alberto Bisin & John Geanakoplos & Piero Gottardi & Enrico Minelli & Herakles Polemarchakis, 2010. "Markets and contracts," Economics Working Papers ECO2010/29, European University Institute.
    • Alberto Bisin & John Geanakoplos & Piero Gottardi & Enrico Minelli & Heracles Polemarchakis, 2009. "Markets and Contracts," Working Papers 0915, University of Brescia, Department of Economics.
  3. Massenot, Baptiste, 2010. "Contract enforcement, litigation, and economic development," MPRA Paper 27501, University Library of Munich, Germany.
  4. Monica Billio & Roberto Casarin, 2010. "Bayesian Estimation of Stochastic-Transition Markov-Switching Models for Business Cycle Analysis," Working Papers 1002, University of Brescia, Department of Economics.

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