赢/输数据与消费者转换成本：衡量分流比率和合并的影响*

IF 1.7 4区经济学 Q3 BUSINESS, FINANCE

Journal of Industrial Economics Pub Date : 2023-11-10 DOI:10.1111/joie.12371

Y. Jeff Qiu, Masayuki Sawada, Gloria Sheu

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引用次数: 0

摘要

我们提出了一种基于输赢数据的分流识别策略。首先，我们证明合并企业的赢/亏数据和所有企业在两个时期的市场份额足以识别合并伙伴之间的分流比率。其次，我们证明，仅合并企业的赢亏数据就足以进行部分识别，我们还构建了一个下限，当转换成本较高时，该下限能很好地近似分流比率。我们通过数值模拟和对 Anthem/Cigna 合并案的应用证明了我们方法的性能。

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Win/Loss Data and Consumer Switching Costs: Measuring Diversion Ratios and the Impact of Mergers*

We propose an identification strategy for diversion based on win/loss data. First, we show that win/loss data from the merging firms and market shares in two periods for all firms are sufficient to identify the diversion ratios between the merging partners. Second, we show that win/loss data from the merging firms alone are sufficient for partial identification, and we construct a lower bound that provides a good approximation to the diversion ratio when switching costs are high. We demonstrate the performance of our method with numerical simulations and with an application to the Anthem/Cigna merger.

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来源期刊

Journal of Industrial Economics Multiple-

CiteScore

1.60

自引率

0.00%

发文量

期刊介绍： First published in 1952, the Journal of Industrial Economics has a wide international circulation and is recognised as a leading journal in the field. It was founded to promote the analysis of modern industry, particularly the behaviour of firms and the functioning of markets. Contributions are welcomed in all areas of industrial economics including: - organization of industry - applied oligopoly theory - product differentiation and technical change - theory of the firm and internal organization - regulation - monopoly - merger and technology policy Necessarily, these subjects will often draw on adjacent areas such as international economics, labour economics and law.