TY - JOUR
T1 - Making corruption harder
T2 - Asymmetric information, collusion, and crime
AU - Ortner, Juan
AU - Chassang, Sylvain
N1 - Publisher Copyright:
© 2018 by The University of Chicago. All rights reserved.
PY - 2018/10/1
Y1 - 2018/10/1
N2 - We model criminal investigation as a principal-agent-monitor problem in which the agent can bribe the monitor to destroy evidence. Building on insights from Laffont and Martimort’s 1997 paper, we study whether the principal can profitably introduce asymmetric information between agent and monitor by randomizing the monitor’s incentives. We show that it can be the case, but the optimality of random incentives depends on unobserved preexisting patterns of private information. We provide a data-driven framework for policy evaluation requiring only unverified reports. A potential local policy change is an improvement if, everything else equal, it is associated with greater reports of crime.
AB - We model criminal investigation as a principal-agent-monitor problem in which the agent can bribe the monitor to destroy evidence. Building on insights from Laffont and Martimort’s 1997 paper, we study whether the principal can profitably introduce asymmetric information between agent and monitor by randomizing the monitor’s incentives. We show that it can be the case, but the optimality of random incentives depends on unobserved preexisting patterns of private information. We provide a data-driven framework for policy evaluation requiring only unverified reports. A potential local policy change is an improvement if, everything else equal, it is associated with greater reports of crime.
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U2 - 10.1086/699188
DO - 10.1086/699188
M3 - Article
AN - SCOPUS:85054126927
SN - 0022-3808
VL - 126
SP - 2108
EP - 2133
JO - Journal of Political Economy
JF - Journal of Political Economy
IS - 5
ER -