Mergers and Wages in Digital Networks: a Public Interest Perspective View Full Text


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Article Info

DATE

2019-04-01

AUTHORS

Sumit K. Majumdar, Rabih Moussawi, Ulku Yaylacicegi

ABSTRACT

This article has examined the relationship between mergers and their impact on average per-person wages for incumbents, over long periods of institutional changes within the United States telecommunications industry, from a public interest perspective. We evaluate the relationship of mergers and wages across two differing periods; one, when the sector was completely regulated, and, the other, when competition was introduced after the Telecommunications Act of 1996. We treat mergers as endogenous and use treatment effects analysis to examine the relationship of mergers and wages. Having split the data set into data for regulated and deregulated periods, we find no impact of mergers on wages in the regulated period. In the deregulated period, however, between 1996 and 2001, we find a significant negative impact on mergers and wages. For firms experiencing mergers, real average wages per employee are a third lower than in non-merging firms. This suggests a post-merger cost-cutting approach by firms. Our before-and-after findings of wages declining after mergers, in the 1996 to 2001 period, lead us to conclude that the merger approvals given after the passage of TA 1996 will not have met public interest guidelines as per which merger outcomes ought to be fair to affected firms’ employees and stakeholders. Additionally, we suggest a resolution to the empirical puzzle, of half-negative and half-positive merger and wage outcome findings existing in the literature, by incorporating institutional context into our analysis to explain why during some periods of time the relationship of merger and wage outcomes may be positive and at other times may be negative. More... »

PAGES

1-33

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s10842-019-00297-1

    DOI

    http://dx.doi.org/10.1007/s10842-019-00297-1

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1113177734


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