Does product market competition influence annual report readability?

Abstract

We study product market competition’s influence on annual report readability. As competition increases in an industry, our findings show that firms reduce the readability of their annual reports. We further document that the impact of competition on annual report readability is stronger for research and development (R&D)-intensive firms, for firms that have a higher level of trade secrecy (i.e. proprietary information), and for firms with higher levels of CEO performance-based incentives. Overall, our findings highlight the importance of the proprietary cost effect of competition on annual report readability.

Keywords:

• product market competition
• annual report readability
• 10-K annual reports
• tariff rates

JEL:

• D4
• G14
• G34
• M41

Acknowledgments

We thank the editor, associate editor, and two anonymous reviewers for their constructive comments. We also acknowledge helpful comments while presenting this paper in 2019 Australasian Finance & Banking Conference and 2019 New Zealand Finance Meeting.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Prior literature also documents the association between readability and firm performance (Baxamusa et al. 2018); investment efficiency (Biddle et al. 2009), information efficiency of stock prices (Lee 2012, Yekini et al. 2016); cost of capital and stock price crash risk (Ertugrul et al. 2017, Kim et al. 2019); corporate liquidity and payout policies (Hasan and Habib 2020); cash holding and derivative use (Friberg and Seiler 2017); analyst forecasts (Lehavy et al. 2011); and individual investment decisions (Lawrence 2013).

2 The constituents and suitability of this index are described in the variable description.

3 We also consider tariff shocks that are two times and four times greater than the industry average in our difference-in-differences (DiD) design. Our results remain qualitatively similar. The results are un-tabulated and available upon request.

4 Following Huang et al. (2017), we argue that these shocks increase competition from existing competitors rather than from new entrants. Contingent on the existing market structure, new competition (i.e. new exporters) needs more lead time than the existing rivals to enter the industry. As a result, when tariffs decrease, their effect on the U.S. import should be reflected in subsequent years. Huang et al. (2017), who use the same tariff shocks we do, show that the import volume principally increases in the year of tariff cut while increases in subsequent years is minimal. This indicates that the competition is mainly among the existing rivals who quickly take advantage of the tariffs cut. We also empirically validate that tariff shocks increase the degree of competition from existing competitors. For details, see Section 4.1 and Table 6, Panel A.

5 We also use firm fixed effects and a lagged Bog Index value as an additional control variable to address omitted variable concern and find consistent results.

6 The Bog Index data are retrieved from Brian P. Miller’s webpage at Kelley School of Business, Indiana University <https://kelley.iu.edu/bpm/activities/bogindex.html>.

7 The definitions of variables appear in the Appendix. All the continuous variables are winsorized at the 1% level in both tails to control for outliers.

8 The data for these measures are retrieved from <http://webuser.bus.umich.edu/feng/>.

9 This index is available at <http://hobergphillips.tuck.dartmouth.edu/industryconcen.htm>.

10 Our baseline results are also robust at industry-level clustering. These results are available upon request.

11 As suggested by one anonymous reviewer of our paper, we empirically check whether tariff shocks affect industry competition using multiple measures. For details, see Table 6, Panel A.

12 We note that only ROA is significantly different at the 5% level. However, this difference is not expected to be of such high relevance to warrant further investigation, particularly given that treated firms have higher profitability compared to control firms.

13 We also conduct a cross-sectional test using pre-shock competition (high vs. low competition based on sample median of COMPETITION_textual) as a sorting variable. We find that firms with low competition group experience a more significant decrease in readability after the shock than pre-shock period. The results are un-tabulated and available upon request.

14 This process is repeated 1000 times and the results (distribution) provide evidence consistent with our results in Table 6. The distribution is un-tabulated and available upon request.

15 Table 7’s bottom panel reports the diagnostic statistics. Our instrument is neither weak nor under-identified; Wu–Hausman’s F statistic (84.277) is significant at the 1% level; no over-identifying restrictions are found.

16 All our regression results in this paper remain qualitatively unchanged with the inclusion of 10K_SIZE as an additional control variable. The results are available upon request.

17 We obtain CEO_VEGA data from Coles et al. (2006).