A Large-Scale Analysis of Mergers and Merger Simulations

大规模合并分析和合并模拟

• 批准号: 2116934
• 负责人: Vivek Bhattacharya
• 金额: $ 36万
• 依托单位: Northwestern University
• 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: 2021-07-15 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2116934&HistoricalAwards=false
• 关键词: Large; Scale; Analysis; Mergers; Merger

AbstractAntitrust agencies in the United States reviewed over two thousand prospective mergers and acquisitions per year in recent years. Their task is to trade off harms from market power with potential synergies that may be passed on to consumers—and to convince a court to either block mergers that they predict will cause significant consumer harm or to order that the merging parties adopt remedies. These projects will study two aspects of antitrust enforcement in the US. First, the project will document the realized price and quantity effects of mergers that have been approved, studying a near-universe of sufficiently large deals in a number of industries. This quantification will help inform the effects of current policy and may point to avenues for future adjustments. Second, the project will study the efficacy of one of the standard tools for predicted price effects of prospective mergers: the merger simulation. There will be systematic assessment of the predictive power of mergers simulations and characterize the reasons why predictions differ from realized observations. The results of the project will have important implications for antitrust policy, and will provide tools for conducting merger evaluations in the US for a variety of industries.The project will first estimate the price and quantity effect of mergers—on both merging parties and non-merging parties—using data before and after the completion date of the merger and a variety of controls. The project will correlate these effects, both across mergers and within-mergers across markets, with measures of concentration, such as the Herfindahl-Hirschman Index (HHI) and the naïve change of the HHI. There will be a documentation of the time path of the change in prices. Second, the project will estimate a structural model of demand for each of the mergers in the dataset using only data before the merger was consummated, choosing among a variety of demand specifications. The project will then predict post-merger prices using these estimates, the implied costs, and the assumption of static Bayesian-Nash equilibrium. Finally, there will be a decomposition of the prediction error into that due to demand-side changes and supply-side changes (such as synergies and conduct) by estimating parameters of the structural model using post-merger data. This decomposition may provide guidance for how to adjust merger simulations in practice.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.

摘要近年来，美国反垄断机构每年审查的潜在并购案超过2000起。他们的任务是权衡市场支配力的危害和可能传递给消费者的潜在协同效应，并说服法院要么阻止他们预测会造成重大消费者损害的合并，要么命令合并方采取补救措施。这些项目将研究美国反垄断执法的两个方面。首先，该项目将记录已获批准的合并的实际价格和数量效应，研究若干行业中几乎所有的足够大的交易。这种量化将有助于了解当前政策的影响，并可能为未来的调整指明方向。第二，本项目将研究预测预期合并的价格影响的标准工具之一：合并模拟的效力。将对合并模拟的预测能力进行系统评估，并说明预测与实际观察不同的原因。该项目的研究结果将对反垄断政策产生重要影响，并将为在美国对各种行业进行合并评估提供工具。该项目将首先使用合并完成日期前后的数据和各种控制来估计合并对合并方和非合并方的价格和数量影响。该项目将把这些影响，包括跨市场的兼并和兼并内的影响，与集中度的衡量标准，如赫芬达尔-赫希曼指数（HHI）和HHI的幼稚变化联系起来。将有一个文件的时间路径的价格变化。其次，该项目将估计数据集中每个合并的需求结构模型，仅使用合并完成之前的数据，在各种需求规格中进行选择。然后，该项目将使用这些估计、隐含成本和静态贝叶斯纳什均衡假设来预测合并后的价格。最后，通过使用合并后的数据估计结构模型的参数，将预测误差分解为需求方变化和供给方变化（协同效应和行为）引起的误差。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。