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Mergers and sequential innovation: evidence from patent citations


  • Jessica C. Stahl


An extensive literature has investigated the effect of market structure on innovation. A persistent concern is that market structure may be endogenous to innovation. Firms may choose to merge so as to capture information spillovers or they may choose to merge so as to dampen competition in innovation. These two scenarios have very different welfare implications. This paper attempts to distinguish between the two scenarios empirically, looking at recent mergers among public companies in the United States. Using patent citation data, I find evidence that firms increase their rate of sequential innovation in the years preceding a merger, and reduce their rate of sequential innovation in the years following a merger. This suggests that mergers are motivated more by the desire to dampen competition than by the desire to capture information spillovers. I use citation-based measures of patent value to shed light on the welfare implications. The question is relevant for policy, as the FTC and DOJ frequently cite innovation as a reason for concern about a merger.

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  • Jessica C. Stahl, 2010. "Mergers and sequential innovation: evidence from patent citations," Finance and Economics Discussion Series 2010-12, Board of Governors of the Federal Reserve System (U.S.).
  • Handle: RePEc:fip:fedgfe:2010-12

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    References listed on IDEAS

    1. Bronwyn H. Hall & Adam B. Jaffe & Manuel Trajtenberg, 2001. "The NBER Patent Citation Data File: Lessons, Insights and Methodological Tools," NBER Working Papers 8498, National Bureau of Economic Research, Inc.
    2. Sharon Belenzon, 2006. "Knowledge Flow and Sequential Innovation: Implications for Technology Diffusion, R&D and Market Value," Economics Series Working Papers 259, University of Oxford, Department of Economics.
    3. Lunn, John E, 1986. "An Empirical Analysis of Process and Product Patenting: A Simultaneous Equation Framework," Journal of Industrial Economics, Wiley Blackwell, vol. 34(3), pages 319-330, March.
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    Cited by:

    1. Ma, Tingting & Zhang, Yi & Huang, Lu & Shang, Lining & Wang, Kangrui & Yu, Huizhu & Zhu, Donghua, 2017. "Text mining to gain technical intelligence for acquired target selection: A case study for China's computer numerical control machine tools industry," Technological Forecasting and Social Change, Elsevier, vol. 116(C), pages 162-180.

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    Technological innovations ; Consolidation and merger of corporations;

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