The Effect of Information Asymmetry on the Method of Payment and Post-M&A Involuntary Delisting
| Autor: | Changki Kim, Ephraim Kwashie Thompson |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
History
Polymers and Plastics Accrual media_common.quotation_subject Sample (statistics) Payment Industrial and Manufacturing Engineering Incentive Information asymmetry Mergers and acquisitions Econometrics Quality (business) Business Business and International Management Stock (geology) media_common |
| Zdroj: | SSRN Electronic Journal. |
| ISSN: | 1556-5068 |
| DOI: | 10.2139/ssrn.3701055 |
| Popis: | Purpose - This paper shows an unexplored area related to involuntary delisting. Specifically, this research investigates the effect of target firm information asymmetry on the likelihood that the acquirer or newly merged firm will be forcibly delisted post-merger. Design/methodology/approach - The research uses a sample gathered on local US mergers and acquisitions from the Thomson Reuters Securities Data Company (SDC) Platinum Mergers and Acquisitions database. It applies the logistic regression with industry and year effects and corrects the error term using clustering at the industry level. The research also matches the forced delisted firms to control firms based on industry, acquisition completion year, and firm size and then employs a matched sample analysis. Findings - Findings show that M&As between firms where the target firm is opaque and burdened with high information asymmetry issues are likely to be paid for using majority stock and that M&As involving such opaque targets also have a higher likelihood of getting delisted post-merger. Research implications or Originality - Our results are relevant given the very nature of M&As which involve two players: the acquirer and target who both may have different incentives. Acquirers especially have the tendency to suffer losses and even get delisted if they over-pay for or get merged to a poor target which conceals its poor performance evidenced by higher accruals quality. |
| Databáze: | OpenAIRE |
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