The effect of institutional ownership on firm performance: the case of U.S.-listed shipping companies

ABSTRACT

This paper examines the relationship between institutional ownership and firm performance for U.S.-listed shipping companies using quarterly 13F reports of institutional holdings over the period 2002 to 2016. Traditionally, public shipping companies exhibit a large concentration of ownership as specific individuals and families hold large percentages of the total shares outstanding. However, institutional investors also hold a substantial percentage of ownership of U.S.-listed shipping firms, whose effects on firm performance have not been examined previously in the literature. Results reveal a negative relationship between the percentage of institutional ownership and firm performance, which is primarily attributed to non-strategic rather than strategic institutional investors. This result survives a set of panel data estimators which take into account the presence of dynamic endogeneity in the relationship examined.

KEYWORDS:

• Institutional ownership
• firm performance
• dynamic panel data
• dynamic endogeneity
• U.S. listed shipping companies

Acknowledgments

The author wishes to thank the Editor-in-Chief (Professor Li), the Associate Editor and two anonymous reviewers for their insightful comments on earlier versions of this paper. Any remaining errors or omissions are the author’s responsibility.

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

1. The main types of institutional investors holding assets across the OECD countries are investment funds, insurance companies and pension funds (OECD 2014).

2. For a full review of the institutional ownership literature see Luo et al. (2014) and for the shipping finance literature see (Alexandridis et al. 2018).

3. Transportation by sea forms the leading mode of transportation worldwide, carrying over 80% of the global trade in volume terms (UNCTAD 2017) and contributing around $380 billion a year to the global economy (Catalyst Corporate Finance 2016). The large bulk of sea transportation globally is facilitated by the U.S.-listed shipping companies which are the largest in terms of capitalization globally (Drobetz et al. 2013).

4. The global shipping industry exhibits unique characteristics and forms an excessively risky business environment for shipping firms to operate within, which is also reflected in their increased cost of capital (Drobetz et al. 2013).

5. (Luo et al. 2014) report an average percentage of around 17% of institutional ownership from institutional investors across all U.S.-listed firms, whereas the same figure for the shipping firms examined in this study is 25.16%. Shipping companies also exhibit a large concentration of ownership as specific individuals, families or holding companies hold large percentages of the total shares out held (Tsionas, Merikas, and Merika 2012). Specifically, the average total ownership percentage held by all blockholders (i.e. shareholders having more than 5% of the total ownership of the firm) is equal to 39% across all U.S.-listed firms (Holderness 2009), whereas for the U.S.-listed shipping firms examined in this study it is equal to 43%.

6. The use of a quarterly frequency of data captures changes in the percentage of institutional ownership that may happen during a given calendar year. This is important as some institutional investors may trade large blocks of ownership within a relatively small period of time.

7. Specifically, transient institutional investors exhibit a short investment horizon to maximize short-term profits. Dedicated institutions commit themselves with long-term investment horizons and support to a specific company. Finally, the quasi-indexers exhibit high diversified portfolios of investments and low turnover (i.e. they typically follow a buy-and-hold strategy of a portfolio mimicking broader stock indices like the S&P 500) (Bushee 1998).

8. European exchanges were: London Stock Exchange (LSE), Oslo, Frankfurt, and Asian exchanges were: Singapore, Hong Kong, Malaysia, Taiwan.

9. In that case, one of the α_i or α_t is dropped to enable estimation.

10. This is typical when firms sampled are drawn from a large population of data. In this paper, the existence of such effects is determined empirically, as explained later in the paper.

11. By collecting information from shipping firms’ websites and news sources it is verified that individual investors holding large percentages (over 1%) of ownership for U.S.-listed shipping companies are in their great majority founders or members of the extended founding family.

12. Classifying an investor as a strategic one is not a straightforward task. Thus, apart from relying on the strategic vs. non-strategic investor classification as provided by Thomson Reuters database, we also experiment with alternative ways to classify investors. Specifically, we classify an investor as a strategic one if she holds a total of more than 1% of total ownership and maintains her percentage of shares for more than two calendar years. This ad-hoc classification almost coincides completely with the one performed by Thomson Reuters database. Overall, results obtained late in the paper remain qualitatively the same when using this classification of strategic investors and are available from the author upon request.

13. The founding date of each firm examined is collected through its official website and cross-checked through its publically disclosed financial statements in NYSE or NASDAQ stock exchanges.

14. Manufacturing and shipping sectors are capital intensive, operate assets with long economic lives and use assets as the main collateral. The manufacturing firms out of which the ‘matched’ sample is chosen include all firms with the first-digit SIC code equal to two or three apart for the ones with a two-digit SIC code of 39 (Miscellaneous Manufacturers).

15. Thomson Reuters 13F institutional holdings database provides limited data for the sample of U.S.-listed shipping companies examined in this paper prior to 2002Q1.

16. As a robustness test and to enable comparisons with the extant literature, Tobin’s Q is used as an alternative firm performance measure instead of ROA, while dropping market-to-book ratio from the control variables. The results remain qualitatively the same.

17. A measure of voting rights along with the percentage of ownership held by institutional investors could be used in the analysis performed in this paper. However, such data were not available for the sample of shipping firms examined in this paper.

18. The same ad-hoc threshold of 0.6 is adopted in the general finance literature (see, e.g. (Dick-Nielsen, Feldhütter, and Lando 2012).

19. VIF coefficients for each explanatory variable are computed through the following formula: $VI{F}_i=\frac{1}{1-R_i^2}$, where R_i² is the coefficient of determination of an auxiliary regression in which the dependent variable is the independent variable under scrutiny for multicollinearity in the original equation, while the independent variables in this auxiliary regression are the rest of the independent variables of the original model (for details see Gujarati and Porter 2008). As a rule of thumb, variables with VIF values greater than 10 indicate high collinearity (i.e. that the variable could be considered as a linear combination of other independent variables).

20. Results are untabulated to preserve space but are available from the author upon request.

21. Squared terms of the variables Own_inst, Own_inst_s and Own_inst_ns have been included in models M1 to M5 in order to explore the possibility of a U-shaped relationship between institutional ownership and firm performance. In all cases, the squared terms included are not statistically significant. The results are available from the author upon request.