Contrôle des activités illégales en présence d'un biais d'optimisme
Although expensive, monitoring is the most efficient mean to repress a criminal activity. This is typically included in economic models of crime thanks to a probability of detection, and only based on risk aversion. According to recent results in psychology literature, the perception of this probability can however be specific to each individual. This paper experimentally investigates the existence of such errors in probabilities forecasts, often labelled “optimism bias”. The experiment relies on choices between a no risky (legal) activity and an illegal activity – randomly penalized by a fine. The experimental treatments assess whether the way the monitoring policy is announced can affect the optimism bias. The results provide a guide into costless devices to undermine illegal activities, grounded on an idiosyncratic perception of risk. Classification JEL : C91, C92, D82, H21, H26
References listed on IDEAS
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- Fang, Hanming & Moscarini, Giuseppe, 2005.
Journal of Monetary Economics,
Elsevier, vol. 52(4), pages 749-777, May.
- Hanming Fang & Giuseppe Moscarini, 2003. "Morale Hazard," Cowles Foundation Discussion Papers 1422, Cowles Foundation for Research in Economics, Yale University.
- Hanming Fang & Giuseppe Moscarini, 2004. "Morale Hazard," Yale School of Management Working Papers ysm386, Yale School of Management.
- Gervais, Simon & Odean, Terrance, 2001. "Learning to be Overconfident," Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 1-27.
- Simon Gervais & Terrance Odean, "undated". "Learning To Be Overconfident," Rodney L. White Center for Financial Research Working Papers 5-97, Wharton School Rodney L. White Center for Financial Research.
- Simon Gervais & Terrance Odean, "undated". "Learning To Be Overconfident," Rodney L. White Center for Financial Research Working Papers 05-97, Wharton School Rodney L. White Center for Financial Research.
- Charles A. Holt & Susan K. Laury, 2005. "Risk Aversion and Incentive Effects: New Data without Order Effects," American Economic Review, American Economic Association, vol. 95(3), pages 902-912, June. Full references (including those not matched with items on IDEAS)
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