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Cross-listing in the U.S. and domestic investor protection

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  • Thomas C O'Connor

    (Economics, National University of Ireland, Maynooth)

Abstract

Using the change in ordinary dividend payout as a proxy for improved governance, I show that cross-listing in the U.S. is associated with enhanced protection for the minority ordinary shareholders of exchange listed non-U.S. firms. These firms substitute dividends for enhanced governance. I find no such effect for Rule 144a firms. Interestingly, I document evidence inconsistent with the legal bonding hypothesis for Level 1 firms. I believe that their ability to pay lower dividends post-listing is primarily due to their ability to credibly commit to fair treatment of thek minority investors, given their record for equitable treatment of their ordinary shareholders. They achieve this reputation by consistently paying out a sizable proportion of their earnings as dividends. I find that the firm-level governance of Level 1 firms, as measured by the number of closely held shares improves in the post-listing period. I find no such effect for Rule 144a traded firms. My results also have important implications for the agency models of dividends.

Suggested Citation

  • Thomas C O'Connor, 2007. "Cross-listing in the U.S. and domestic investor protection," Economics Department Working Paper Series n1861107.pdf, Department of Economics, National University of Ireland - Maynooth.
    • Handle: RePEc:may:mayecw:n1861107.pdf
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    More about this item

    Keywords

    Cross-listing; legal bonding; dividend policy;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G34 - Financial Economics - - Corporate Finance and Governance - - - Mergers; Acquisitions; Restructuring; Corporate Governance
    • G35 - Financial Economics - - Corporate Finance and Governance - - - Payout Policy
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models

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