講座主題：Minimum Performance Targets, Multitasking, and Incentives: Theory and Evidence from China's Air Quality Controls

主講嘉賓：翁翕，北京大學光華管理學院應用經濟學系長聘教授

講座時間：2021年5月13日（周四），下午15:00-16:30

講座地點：學院11号樓308會議室

嘉賓簡介：翁翕，現為北京大學光華管理學院應用經濟學系長聘教授。北京大學經濟學學士、碩士，美國賓夕法尼亞大學經濟學博士。研究興趣主要研究領域為信息經濟學、組織經濟學和行為經濟學。研究成果發表或即将發表于國外頂級學術期刊，如Journal of Finance, Management Science, Economic Journal, American Economic Journal: Microeconomics, Journal of Economic Theory (兩篇), International Economic Review (兩篇), Economic Theory, Journal of Economic Behavior & Organization, 和Journal of Economics & Management Strategy等國際知名期刊。

主持國家自然科學基金面上項目“組織經濟學理論與應用”。曾獲獎項有：2020第八屆高等學校科學研究優秀成果獎（人文社會科學）青年成果獎，2020中國信息經濟學優秀成果獎，2019光華管理學院第十三屆厲以甯科研獎，2019北京大學教學優秀獎，2017中國信息經濟學青年創新獎，2017北京大學教學優秀獎，2017第十三屆北京大學人文社會科學研究優秀成果一等獎，2016北京大學北京銀行獎教金，2016中國信息經濟學烏家培獎等。

内容摘要：This paper examines how local Chinese officials respond strategically to minimum air quality control targets when they care more about pursuing regional economic development, which is closely linked to their career prospects. Using a novel prefecture-day level dataset on air quality and applying a regression discontinuity design, we find strong evidence that air quality tends to improve when the air quality target is doomed to fail, but deteriorates significantly after the early fulfillment of the target is guaranteed. These "asymmetric'' strategic responses are mainly driven by "outsiders'' – local officials with no previous exposure to the regions to which they are assigned. Greater pressure to promote local economic development reinforces outsiders’ asymmetric responses. For "non-outsiders'' who have been promoted from the local area and who are more likely to intrinsically value the local environment, air quality performance is stable in both cases of target fulfillment. We build a simple theoretical model to rationalize these key findings. Our study sheds light on how minimum air quality targets have functioned in China's context and highlights the role of intrinsic motivations in mitigating strategic responses to minimum performance targets in a multitasking environment.