یادگیری در مورد انطباق تحت اطلاعات نامتقارن
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|50385||2012||19 صفحه PDF||سفارش دهید||12923 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Resource and Energy Economics, Volume 34, Issue 1, January 2012, Pages 55–73
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.