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A holistic approach to merger models with an emphasis on heterogeneity

机译:兼并模型的整体方法,强调异质性

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Though mergers and acquisitions comprise a significant share of aggregate economic activity in the US, researchers disagree on the effect and importance of M&A determinants. Such disagreement stems from adherence to disparate theoretical models that preclude the use of significant explanatory variables. Our paper contributes to this scattered literature by demonstrating the presence of significant bias in the most common approaches to this question. We do so by comparing the Neoclassical, behavioral, and macro approaches to explaining M&A activity. Finding that the assumptions of these respective paradigms have inhibited individual researchers from including important determinants of M&A, we show that these constraints have generated misleading point estimates. By constructing a more holistic model of M&A activity, we produce more accurate estimates of merger determinants and reveal the bias of previous estimation techniques. Additionally, we relax the common, yet unrealistic, assumption that firms are homogeneous, showing that the determinants of M&A vary by firm size, region, and sector. These results demonstrate that an aggregated approach to merger determinants conceals important variation.
机译:尽管并购在美国总体经济活动中占很大比重,但研究人员对并购决定因素的影响和重要性持不同意见。这样的分歧源于坚持使用完全不同的理论模型,从而无法使用重要的解释变量。我们的论文通过证明在最常见的问题解决方法中存在明显的偏见,为这一分散的文献做出了贡献。通过比较新古典,行为和宏观方法来解释并购活动,我们可以做到这一点。发现这些各自范式的假设阻碍了单个研究人员纳入并购的重要决定因素,我们发现这些约束条件产生了误导点估计。通过构建更全面的并购活动模型,我们可以得出对合并决定因素的更准确的估计,并揭示先前估计技术的偏见。此外,我们放宽了公司均质的普遍但不切实际的假设,这表明并购的决定因素随公司规模,区域和行业的不同而不同。这些结果表明,合并决定因素的综合方法掩盖了重要的变化。

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