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Antitrust policy and hospital mergers: recommendations for a new approach

机译：反托拉斯政策与医院合并：新方法的建议

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We began this article with several related questions of practical significance for antitrust analysis of hospital mergers. Do data indicating substantial patient flows support the absence of market power? Do mergers that easily pass muster using flow analysis fail or pass using the SSNIP criterion? Do patient flow data provide an accurate view of the appropriate market boundaries? We conclude that patient flow data have little relationship to the SSNIP criteria over a wide range of situations in which patient flow data indicate a competitive market is present. In other words, merger analysis using patient flow data incorrectly indicates that there is no problem when more structured approaches indicate that there may indeed be a risk of competitive harm. We advocate replacing the use of flow data in courtroom proceedings with formal demand analysis. We derive three related methods based on logit demand to identify the ability of sellers to raise prices in differentiated goods markets. Two models apply when consumers make direct purchases, and one applies in option demand markets. The option demand model is preferred because it specifically accounts for the important role of managed care; also, it is not subject to the potential bias present in the other two approaches. Nevertheless, the models yield consistent results―mergers that are anticompetitive using one approach tend to be anticompetitive using the others. This is not surprising, given the common underlying logit demand structure. In logit demand, sellers who are attractive to a large number of consumers yet have no obvious competitors are able to raise prices. This is a powerful and satisfying intuition that is borne out in our empirical analyses.
机译：我们从本文的几个相关问题开始，这些问题对医院合并的反托拉斯分析具有实际意义。指示大量患者流量的数据是否支持缺乏市场支配力？使用流程分析轻松通过要求的合并会失败还是使用SSNIP标准通过？患者流量数据是否可以提供适当市场边界的准确视图？我们得出的结论是，在患者流量数据表明存在竞争市场的广泛情况下，患者流量数据与SSNIP标准关系不大。换句话说，使用患者流量数据进行合并分析会错误地表明，当更结构化的方法表明确实存在竞争损​​害的风险时，这没有问题。我们主张在法庭诉讼程序中使用正式的需求分析来代替流量数据的使用。我们基于对数需求推导了三种相关方法，以确定卖方在差异商品市场上提高价格的能力。当消费者直接购买时，有两种模型适用，而在期权需求市场中，有一种适用。优先选择期权模型，因为它特别说明了管理式护理的重要作用；同样，它不受其他两种方法中存在的潜在偏差的影响。尽管如此，这些模型仍能产生一致的结果-使用一种方法具有反竞争性的合并往往会使用其他方法具有反竞争性。考虑到常见的基本logit需求结构，这不足为奇。在原木需求中，对大量消费者具有吸引力但没有明显竞争对手的卖方能够提高价格。这是一种强有力而令人满意的直觉，在我们的经验分析中得到了证实。

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