NSF-BSF: Collaborative Research: Market Conduct in Technology Adoption in the Automobile Industry
NSF-BSF:合作研究:汽车行业技术采用的市场行为
基本信息
- 批准号:2049263
- 负责人:
- 金额:$ 18.99万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-03-01 至 2025-02-28
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
AbstractAntitrust enforcement research has mostly focused on price and quantity collusion, even though antitrust law encompasses more ways to collude. This project will explore the causes and welfare consequences of automakers colluding on the adoption of emission control technologies. The project focuses on automakers that have been alleged to have colluded on adopting Diesel Exhaust Fluid (DEF) tanks that were too small to effectively clean up nitrogen oxide (NOx), a major contributor to air pollution. The project will investigate how the alleged collusion by automakers concealed violation of NOx emissions regulation. The project will quantify the effects of the alleged collusion on NOx pollution damages, car buyer surplus, and firm profits. These effects inform the proper amount of antitrust penalties to remedy welfare damages of such collisions. Finally, the project will examine whether and how environmental and antitrust regulation can mitigate inefficiencies from technology collusion. The project will build and estimate a structural model of consumer vehicle demand and automaker technology choice, and simulate counterfactual policies. The project utilizes a comprehensive new data set on vehicle prices, sales, and characteristics. A novel feature of the employed structural model is that the probability of non-compliance detection for one firm depends on other firms' behavior as well as its own. A more dispersed distribution in choices may cause a regulator to question why some firms need to use large DEF tanks while others apparently manage with small tanks. By coordinating on small tanks, the automakers simultaneously reduce the probability of being detected by the regulator and make their vehicles more attractive to car buyers (as the tank reduces cargo space, a valuable vehicle feature). With the model and estimates of consumer tastes and automaker costs, the project will conduct counterfactual simulation to explore the following issues: (i) quantify the benefit of strengthening the enforcement of emission standards; (ii) calculate the anti-competitive damage of technology collusion compared to the competitive counterfactual; and (iii) identify the demand and supply conditions most conducive to technology collusion. The project advances the economics research and has regulatory and policy implications on firm collusion, antitrust enforcement, and industry standards.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
摘要 反垄断执法研究主要集中在价格和数量共谋上,尽管反垄断法涵盖了更多的共谋方式。该项目将探讨汽车制造商串通采用排放控制技术的原因和福利后果。 该项目的重点是据称合谋采用柴油机尾气处理液(DEF)罐的汽车制造商,这些罐体太小,无法有效净化氮氧化物(NOx),而氮氧化物是造成空气污染的主要因素。 该项目将调查汽车制造商涉嫌串通是如何隐瞒违反氮氧化物排放法规的行为。该项目将量化所谓的共谋对氮氧化物污染损害、汽车购买者盈余和公司利润的影响。 这些影响决定了适当数额的反垄断处罚,以弥补此类冲突造成的福利损失。 最后,该项目将研究环境和反垄断监管是否以及如何能够减轻技术共谋造成的低效率。该项目将建立和估计消费者汽车需求和汽车制造商技术选择的结构模型,并模拟反事实政策。该项目利用了有关车辆价格、销售和特性的全面新数据集。 所采用的结构模型的一个新颖特征是,一个公司发现不合规的概率取决于其他公司以及其自身的行为。 选择的更加分散的分布可能会导致监管机构质疑为什么一些公司需要使用大型 DEF 储罐,而其他公司显然使用小型储罐。 通过在小型油箱上进行协调,汽车制造商同时降低了被监管机构检测到的可能性,并使他们的车辆对汽车购买者更具吸引力(因为油箱减少了载货空间,这是一项有价值的车辆功能)。 通过对消费者品味和汽车制造商成本的模型和估计,该项目将进行反事实模拟,以探讨以下问题:(i)量化加强排放标准执行的效益; (ii) 与竞争反事实相比,计算技术共谋的反竞争损害; (iii) 确定最有利于技术共谋的供求条件。该项目推进了经济学研究,并对公司串通、反垄断执法和行业标准产生了监管和政策影响。该奖项反映了 NSF 的法定使命,并通过使用基金会的智力优点和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Jing Li其他文献
[Epidemiological analysis on a family cluster of COVID-19].
COVID-19家庭聚集性流行病学分析[J].
- DOI:
10.3760/cma.j.cn112338-20200221-00147 - 发表时间:
2020-03-05 - 期刊:
- 影响因子:0
- 作者:
Y. Qiu;S. Q. Wang;X. Wang;W. Lu;D. Qiao;Jing Li;Y. Gu;Y. Zeng;Y. Chen;W. Bai;B. Xu;T. Han - 通讯作者:
T. Han
Amine-Ligated Approach for the Synthesis of Extra-Large-Pore Zinc Phosphites with qtz-h and bnn Topologies.
用于合成具有 qtz-h 和 bnn 拓扑的超大孔磷酸锌的胺连接方法。
- DOI:
10.1021/acs.inorgchem.6b00589 - 发表时间:
2016-04-01 - 期刊:
- 影响因子:4.6
- 作者:
Kangcai Wang;Yixuan Bian;Jing Li;Dingguo Xu;Zhien Lin - 通讯作者:
Zhien Lin
A novel magnetic-field-driving method for fabricating Ni/epoxy resin functionally graded materials
一种新型磁场驱动方法制备镍/环氧树脂功能梯度材料
- DOI:
10.1016/j.matlet.2018.03.180 - 发表时间:
2018-07-01 - 期刊:
- 影响因子:3
- 作者:
Jing Li;X. Peng;Yanting Yang;Jiangcai Xu;Panfeng Wang;B. Hong;Dingfeng Jin;Hongxiao Jin;Xinqing Wang;H. Ge - 通讯作者:
H. Ge
Solubilities and Thermodynamic Study of Carbon Tetrachloride in Imidazolium Ionic Liquids at Different Temperatures
不同温度下四氯化碳在咪唑鎓离子液体中的溶解度及热力学研究
- DOI:
10.1021/je4006008 - 发表时间:
2014-02-27 - 期刊:
- 影响因子:0
- 作者:
Jun Zhang;H. Yao;Chengxuan Li;Xigang Du;X. Bai;Jing Li;Junna Liu - 通讯作者:
Junna Liu
Analyzing the gain and noise characteristics of the Bi/Er co-doped fiber amplifier
Bi/Er共掺光纤放大器的增益和噪声特性分析
- DOI:
10.1016/j.infrared.2024.105388 - 发表时间:
2024-06-01 - 期刊:
- 影响因子:0
- 作者:
Lihong Wang;T. Ning;L. Pei;Jingjing Zheng;Dingchen Wang;Wen;Wenqiang Hou;Jing Li;Jianshuai Wang - 通讯作者:
Jianshuai Wang
Jing Li的其他文献
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{{ truncateString('Jing Li', 18)}}的其他基金
CAREER: Towards Safety-Critical Real-Time Systems with Learning Components
职业:迈向具有学习组件的安全关键实时系统
- 批准号:
2340171 - 财政年份:2024
- 资助金额:
$ 18.99万 - 项目类别:
Continuing Grant
Collaborative Research: RUI: Structured Population Dynamics Subject to Stoichiometric Constraints
合作研究:RUI:受化学计量约束的结构化人口动态
- 批准号:
2322104 - 财政年份:2023
- 资助金额:
$ 18.99万 - 项目类别:
Standard Grant
PIPP Phase I: Comprehensive, Integrated, Intelligent System for Early and Accurate Pandemic Prediction, Prevention, and Preparation at Personal and Population Levels
PIPP第一阶段:全面、集成、智能的系统,用于个人和人群层面的早期、准确的流行病预测、预防和准备
- 批准号:
2200255 - 财政年份:2022
- 资助金额:
$ 18.99万 - 项目类别:
Standard Grant
FET: CCF: Small: Computational Drug Prediction through Joint Learning
FET:CCF:小型:通过联合学习进行计算药物预测
- 批准号:
2006780 - 财政年份:2020
- 资助金额:
$ 18.99万 - 项目类别:
Standard Grant
Inverse Mapping of Spatial-Temporal Molecular Heterogeneity from Imaging Phenotype
从成像表型逆映射时空分子异质性
- 批准号:
2053170 - 财政年份:2020
- 资助金额:
$ 18.99万 - 项目类别:
Continuing Grant
RAPID:Genomic Variation Analysis of Coronavirus to Better Understand the Spread of COVID-19
RAPID:冠状病毒的基因组变异分析,以更好地了解 COVID-19 的传播
- 批准号:
2027667 - 财政年份:2020
- 资助金额:
$ 18.99万 - 项目类别:
Standard Grant
CAREER: Associative In-Memory Graph Processing Paradigm: Towards Tera-TEPS Graph Traversal In a Box
职业:关联内存图处理范式:在盒子中实现 Tera-TEPS 图遍历
- 批准号:
2040463 - 财政年份:2020
- 资助金额:
$ 18.99万 - 项目类别:
Continuing Grant
CRII: CSR: Enabling Efficient Real-Time Systems upon Multiple Parallel Resources
CRII:CSR:在多个并行资源上实现高效的实时系统
- 批准号:
1948457 - 财政年份:2020
- 资助金额:
$ 18.99万 - 项目类别:
Standard Grant
Inverse Mapping of Spatial-Temporal Molecular Heterogeneity from Imaging Phenotype
从成像表型逆映射时空分子异质性
- 批准号:
1903135 - 财政年份:2019
- 资助金额:
$ 18.99万 - 项目类别:
Continuing Grant
CAREER: Associative In-Memory Graph Processing Paradigm: Towards Tera-TEPS Graph Traversal In a Box
职业:关联内存图处理范式:在盒子中实现 Tera-TEPS 图遍历
- 批准号:
1748988 - 财政年份:2018
- 资助金额:
$ 18.99万 - 项目类别:
Continuing Grant
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