Learning about compliance under asymmetric information

被引:8
作者
Arguedas, Carmen [1 ]
Rousseau, Sandra [2 ,3 ]
机构
[1] Univ Autonoma Madrid, Dept Anal Econ Teoria Econ & Hist Econ, E-28049 Madrid, Spain
[2] Katholieke Univ Leuven, HUBrussel, Fac Econ & Management, Louvain, Belgium
[3] Katholieke Univ Leuven, Ctr Econ Studies, Louvain, Belgium
关键词
Monitoring and enforcement; Pollution; Learning; Signaling; ENFORCEMENT LEVERAGE; POLITICAL-ECONOMY; SELF-REGULATION; OPTIMAL FINES; POLLUTION; EQUILIBRIUM; PENALTIES; MODEL; RECONSIDERATION; OVERCOMPLIANCE;
D O I
10.1016/j.reseneeco.2011.09.001
中图分类号
F [经济];
学科分类号
02 ;
摘要
Over time, inspection agencies gather information about firms' pollution levels and this information may allow agencies to differentiate their monitoring strategies in the future. If a firm is less successful than its peers in reducing emissions, it faces the risk of being targeted for increased inspections in the next period. This risk of stricter monitoring might induce high-abatement cost firms to mimic low-abatement cost firms by choosing lower emission levels, while the latter might try to avoid being mimicked. We explain firms' compliance decisions and the inspection agency's monitoring strategy by means of a signaling game which incorporates dynamic enforcement and learning. Interestingly, we show that the ongoing signaling game between firm types might lead to firms over-complying with the emission standard. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码:55 / 73
页数:19
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