External governance and capital structure: evidence from media coverage

ABSTRACT

This paper examines how external governance pressure from the media affects capital structure. Using a comprehensive set of corporate news, we find a negative relation between media coverage and financial leverage. The tests we use to address endogeneity suggest that the effect is causal. Cross-sectional tests indicate that the results are more pronounced when board or shareholder monitoring is weaker. We further find that the effect of media coverage is more pronounced for news related to executives (i.e., the news that are more likely to impose reputational costs on managers). Our findings are consistent with a substitution effect between the external governance imposed by the media and the discipline provided by debt financing.

KEYWORDS:

• Media coverage
• corporate news
• capital structure
• leverage
• corporate governance

JEL classification:

• G14
• G30
• G32
• G41

Acknowledgments

We thank the Editor (Victor Gonzalez), the Associate Editor (Susana Menendez Requejo) and two anonymous referees for their insightful comments. We also thank Ivan Blanco, Alberta Di Giuli, Ana-Isabel Fernandez, Alexandre Garel, Sergio Garcia, Marc Goergen, Francisco Gonzalez, Bartolome Pascual-Fuster, David Stolin, David Wehrheim and seminar participants at ESCP, CUNEF and SKEMA for their helpful comments.

Disclosure statement

No potential conflict of interest shall be reported by the authors.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Notes

1. We measure media coverage as the number of news articles on the company in a given year using data from RavenPack, a leading global media database. RavenPack news dataset covers all news stories and press releases reported by the Dow Jones Newswires, regional editions of the Wall Street Journal, Barron’s and MarketWatch, and has been increasingly used in recent finance and accounting studies (e.g., Bushman et al., 2017; Dang et al., 2015; Yang et al., 2020).

2. The rationale for this instrument is as follows. First, the proximity between a firm and news outlets is likely to influence the firm’s media coverage because journalists incur lower costs by collecting and analysing information on nearby firms (Chhaochharia et al., 2012; Giroud, 2013; Gurun & Butler, 2012). The number of media firms in the same two-digit ZIP code is therefore likely to be positively associated with media coverage. Importantly, there is no theoretical argument or empirical evidence that our instrument is directly linked to leverage. We provide suggestive empirical evidence supporting the exclusion restriction in Section 3.

3. The negative association between media coverage and the cost of debt documented by Gao et al. (2020) is unlikely to explain our main findings. If anything, a lower cost of debt would, all else equal, push companies with high media coverage to have more debt financing.

4. This ratio is used in the literature as a proxy for agency costs (Bae et al., 2011).

5. Lemmon et al. (2008) show that the majority of variation in leverage ratios is driven by an unobserved time-invariant effect.

6. For comparison, the magnitude of the effect of media coverage represents nearly half of the effect of the ROA or market-to-book ratio, which are two of the most important and well-established determinants of capital structure.

7. One limitation of this instrument is that it does not have sufficient variation across time at the firm level to allow the use of firm fixed effects. This limitation is common to all studies using similar instruments for media coverage (e.g., You et al., 2018). In line with common approach, we therefore estimate the instrumental variable regressions with industry fixed effects. Furthermore, we augment the model and control for the number of bank branches at the two-digit ZIP code level and for a dummy variable capturing the effect of urban areas in order to mitigate the concern that our instrument may capture economic development.

8. In unreported tests, we find that the results of the instrumental variable analysis are unchanged if we do not include these two variables.

9. Unobserved regional heterogeneity may cause high media firms and media outlets to be located in the same states. To address this issue, in unreported tests, we augment the reported model with state fixed effects clustering standard errors at the state level and find that the results are qualitatively similar to the ones reported in Table 4, Panel B.

10. As for long-term investor ownership and blockholder ownership, we define firms with board independence in the top 30^th percentile as firms with high board independence and those with board independence in the bottom 30^th percentile as firms with low board independence.

11. Other topics include: Earnings, Revenues, Products, Stock, Mergers, Rating Previsions, Being Acquired, Acquisitions, Investments, Equity Financing, and Debt Financing. On average, roughly 20% of news are related to the firm’s executives.

12. A one standard deviation increase in Media Coverage without Executive is associated with a decrease in the leverage ratio of 0.6 percentage points (=−0.007*0.86).

13. To purge the data from erroneous values, we exclude all observations for which the sum of bank loans and bond financing is greater than 100% of the total debt reported in Compustat.

14. The results from Table 2 already show that media coverage is negatively associated with market leverage.

15. Not accounting for operating leases may result in the underestimation of a firm’s true magnitude of leverage (Rampini & Viswanathan, 2013; Rauh & Sufi, 2011).

16. Strebulaev and Yang (2013) show that a significant portion of US listed firms have zero debt. Saona et al. (2020) provide similar evidence for an international sample of firms. We run this test to rule out the possibility that the existence of zero-leverage firms influence our results. In unreported tests, we find that all results reported throughout the paper are similar if we exclude zero-leverage firms from the sample.

Additional information

Funding

This paper was prepared while José M. Martin-Flores was a Ph.D. Candidate at ESCP Business School (Paris Campus). José M. Martin-Flores gratefully acknowledges support from French Laboratory of Excellence on Financial Regulation (LabEx ReFi) supported by PRES heSam and ESCP Business School (reference ANR-10-LABX-0095). Likewise, José M. Martin-Flores gratefully acknowledges support from the Spanish Ministry of Science, Innovation and Universities (Project PID2019-111066GA-I00).