
This study tests the hypothesis that non-domestic cross-listing is associated with increased firm visibility. We examine visibility changes on the two exchanges with the largest number of non-domestic listings: the London Stock Exchange (LSE) and the New York Stock Exchange (NYSE). Noting that the costs associated with NYSE listing are greater than those for LSE listing, we also test the hypothesis that non-domestic cross-listing on the NYSE is associated with larger visibility increases than LSE listing. Our proxies for visibility are analyst coverage and media attention. Our tests using analyst coverage generally support our hypothesis that non-domestic cross-listing increases visibility, while tests using media attention provide partial support of the hypothesis. Further empirical tests support the hypothesis that non-domestic cross-listing on the NYSE is associated with a larger visibility increase than on the LSE, which partially compensates firms for the higher costs associated with NYSE listing. All of our results are robust to conditioning on the firm's home country capital market type (developed or emerging); the country's geographical region; analysts' tendencies to initiate coverage on firms with good prospects; and the popularity of a firm's industry or country.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 364 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
