Cost Stickiness and Stock Price Delay

ABSTRACT

This study examines the effect of cost stickiness on stock price delay. Using a sample of U.S. firms in the period of 1984–2019, I find that the stickiness of Selling, General, and Administrative (SG&A) costs is positively associated with stock price delay. This finding is consistent with the notion that cost stickiness reduces the quality of information available to investors and causes stock price delay (the direct channel). Using a mediation test, I document that cost stickiness reduces the analyst following of the firm, thus increasing stock price delay (the indirect channel). Cross-sectional analyses reveal that the effect of cost stickiness on stock price delay is prominent in firms characterized ex-ante by a relatively poor information environment. Meanwhile, the effect is weak for firms with managers who use less uncertain and more positive words in Management Discussion and Analysis (MD&A) disclosures within 10-K filings. This study contributes to the growing literature on cost behavior by documenting the adverse consequences of managers’ cost decisions on the capital market and the role of the information environment in mitigating these negative implications.

Keywords:

• SG&A
• Cost stickiness
• Asymmetric cost management
• Stock price delay

Acknowledgments

I thank the editor (Beatriz Garcia Osma) and two anonymous referees for their valuable inputs in revising this paper. I also thank Mani Sethuraman, Sanjay Kallapur, Hariom Manchiraju, Abdul Khizer, and workshop participants at the University of Western Australia and the Indian School of Business for helpful comments and suggestions. Any remaining errors are my own.

Disclosure statement

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

Supplemental Data and Research Materials

Supplemental data for this article can be accessed online at https://doi.org/10.1080/09638180.2022.2121739.

Appendix A1: Variable Measurements.

Appendix A2: Tables (A2-1, A2-2, A2-3, and A2-4).

Notes

1 Following prior literature, I focus on SG&A costs, which form a significant proportion of a firm’s cost structure (Chen et al., 2012) and create future value for a firm (Banker et al., 2011).

2 The measurement of cost stickiness and stock price delay is described in detail in the online Appendix A1.

3 It is not perfectly accurate to label this finding as the one from the direct channel because there could be alternative channels other than the two discussed in this paper. The pertinent point is that this finding filters out the effect of analyst following (the indirect channel) and thus indicates that cost stickiness affects stock price delay in ways other than a reduced analyst following.

4 The mediation test uses contemporaneous analyst following, whereas the cross-sectional tests uses analyst following at the beginning of the year.

5 For this line of argument, the quality of newly arriving information needs to be held constant in the cross section of firms, and only the quality of the pre-existing information set is allowed to vary across firms. If this were not true, then the stock price delay could simply be attributed to the variation in the quality of the newly arriving information, as proposed by Verrecchia (1980).

6 Following Callen et al. (2013), I use contemporaneous values for the control variables.

7 As the institutional ownership data begin in 1981, the earliest start date could have been 1981. However, the lagged measure of cost stickiness ensures that the sample period can only begin from 1982. Further, the variable lossfreq requires data from the last three years (including the current year), hence the sample period beginning from 1984.

8 Advertising expenses are replaced by zero in the case of missing values.

9 Industry is defined at the Fama–French 12 level.

10 In other words, it is the information conveyed by the observed cost behavior that results in a poor-quality preexisting information set and not the information contained in the underlying drivers of stickiness that reduce the quality of the preexisting information set.

11 To construct the instrument, I define industry at the 4-digit SIC level.

12 I only discuss the results from Panel A of Table A2-1. The results reported in Panel B of Table A2-1 are similar to the ones in Panel A and do not require additional discussion.

13 Recent research (Sajons, 2020) and textbook publication (Wooldridge, 2015) indicate that R-squared is meaningless for a 2SLS model. Following this recommendation, I do not report the R-squared values in the panels of Table A2-1.

14 The construct of investor disagreement differs from stock price delay, as defined in this paper. Investor disagreement revolves around a specific event (earnings announcement in this case), whereas stock price delay is not measured around an event. Rather, stock price delay captures the inherent ability of stock prices to impound new information regardless of an event.