- Email: [email protected]
Firm performance, reporting goals, and language choices in narrative disclosures
Accepted Manuscript
Firm Performance, Reporting Goals, and Language Choices in Narrative Disclosures H. Scott Asay , Robert Libby , Kristina Rennekamp PII: DOI: Reference:
S0165-4101(18)30018-1 10.1016/j.jacceco.2018.02.002 JAE 1184
To appear in:
Journal of Accounting and Economics
Received date: Revised date: Accepted date:
7 November 2016 15 February 2018 26 February 2018
Please cite this article as: H. Scott Asay , Robert Libby , Kristina Rennekamp , Firm Performance, Reporting Goals, and Language Choices in Narrative Disclosures , Journal of Accounting and Economics (2018), doi: 10.1016/j.jacceco.2018.02.002
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Firm Performance, Reporting Goals, and Language Choices in Narrative Disclosures
H. Scott Asay
[email protected]
Robert Libby
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Cornell University
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The University of Iowa
[email protected]
Kristina Rennekamp†
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Cornell University
February 2018
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[email protected]
We thank Randy Beatty, Rob Bloomfield, Sarah Bonner, Doug DeJong, Ken Merkley, Tracie Majors, Bill Mayew, Greg Miller, Terence Ng, Mark Nelson, Hun-Tong Tan, participants at the 2016 Cornell Summer Accounting Camp, and workshop participants at the University of Bern, University of Southern California and Nanyang Technological University for comments on earlier versions of this paper. We also thank Mike Durney and Patrick Witz for expert research assistance. †Corresponding author. 401P Sage Hall, Cornell University, 14853. Email: [email protected]
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1. Introduction Prior work suggests that the linguistic characteristics of narrative disclosures vary with firm performance. For example, when performance is poor, earnings announcements, 10-Ks, and other narrative disclosures tend to be less readable (see, e.g., Jones and Shoemaker (1994) and Li (2010) for
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discussions), include additional explanations for performance (Merkley, 2014; Guay, Samuels, and
Taylor, 2016; Bushee, Gow, and Taylor, 2018), and use more future-oriented words (Li, 2008;
Matsumoto, Pronk, and Roelofsen, 2011). Further, it has been suggested that managers may choose to use language that highlights their contribution to good performance (e.g., active voice, first-person
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pronouns, etc.) and downplays their contribution to poor performance (e.g., passive voice, third-person pronouns, etc.).1 Implicit in these studies is the idea that managers’ reporting goals shape these linguistic choices.
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We provide more-direct evidence on how reporting goals influence managers’ language choices by using an experiment that independently varies both the sign of firm performance and the strength of
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self-enhancement motives, while holding constant the environmental complexity that prior literature has suggested may also influence linguistic characteristics of disclosures (Merkley, 2014; Guay et al.,
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2016; Bushee et al., 2018). Stronger self-enhancement motives induce a reporting goal to make the firm
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appear more favorable. By manipulating whether self-enhancement motives are relatively weak or strong as well as the sign of the news, we can directly test whether stronger self-enhancement motives
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lead to greater or smaller differences in the linguistic characteristics of good and bad news disclosures. Further, we can determine whether these changes result from how managers report good news, bad news, or both. For example, managers with a stronger self-enhancement motive might decrease the
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For example, see Chafe and Danielewicz (1987); Hyland (2005); Reilly, Zamora, and McGivern (2005); Asay, Libby, and Rennekamp (2018).
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readability of bad news in an attempt to obfuscate poor performance (Bloomfield, 2002; Li, 2008) and increase the readability of good news in an attempt to present good news more clearly. Similarly, managers with a stronger self-enhancement motive might make other language choices in order to communicate additional information when reporting poor performance (e.g., providing a more detailed
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explanation for past performance and discussion of future plans). Thus, our study allows us to gain additional insight into how firm performance and reporting goals affect disclosure readability and other linguistic features. We also provide some evidence on the intentionality of, and motives for, these
linguistic choices, which is of interest given the mixed evidence in prior work.2 We rely on evidence from
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our primary experiment, a supplemental experiment, and an additional survey.
In our primary experiment, experienced managers assume they are in charge of investor relations for a hypothetical firm and that they have been asked to draft a report explaining its
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performance to investors. In a 2 x 2 between-subjects design, we manipulate (1) firm performance in the most recent quarter (good or bad) and (2) participants’ reporting goal (unbiased or favorable).3 We
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then examine the effects of these manipulations on disclosure readability and other linguistic features of the disclosure (use of first person pronouns and passive voice, causal explanations, and focus on the
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future). We also directly ask participants about the reports they have written to provide evidence on the
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intentionality of their linguistic choices. First, consistent with prior archival evidence, we find that bad news reports are less readable than good news reports. This effect is driven by an increase in the
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readability of good news reports when participants have a favorable reporting goal, rather than a
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We discuss some of this mixed evidence further in Section 2.1.
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In both reporting goal conditions, all participants are instructed to report the division’s performance accurately. However, in the favorable reporting goal condition, we introduce a stronger self-enhancement motive by layering on the additional explicit goal of portraying the performance in a manner that is as favorable as possible.
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decrease in the readability of bad news reports. We also find that neither the valence of performance nor the reporting goal affects participants’ perceptions of the readability of their own reports, or their ratings of the extent to which they were motivated to make the report easier or more difficult to read. Second, we find that participants use more passive voice and fewer first person singular pronouns (e.g.,
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“I”, “me”) when news is bad – techniques that distance a manager from the information being
conveyed. Further, the increased use of passive voice is particularly true when participants have a
favorable reporting goal. Third, we find that participants use more words that reflect causal thinking (e.g., “because”, “effect”, “therefore”) and use more future tense relative to past tense when news is
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bad than when news is good. When directly asked, participants accurately report that they increase the use of causal and future words when news is bad, although they also believe that the use of these words is even greater when a favorable reporting goal is present.
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In our supplemental experiment, we examine the robustness of our results by testing how the linguistic features of bad news disclosures are influenced by an alternative operationalization of the self-
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enhancement motive – portraying the performance in the least unfavorable manner as possible. This alternative reporting goal reduces the readability of disclosures when performance is poor, as a result of
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increased use of negations (e.g., saying a firm is “not doing well” rather than “doing poorly”). However,
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we find that this alternative reporting goal does not affect participants’ perceptions of the readability of their own reports. In combination, the results of our supplemental experiment suggest that although
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managers appear to be unaware that they are doing so, they provide disclosures that are less readable (via increased use of negations) when performance is poor and they have a goal to present the firm in
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the “least unfavorable” light possible.4 Results also provide additional support for the idea that, in order to frame poor performance in a positive light, managers tend to focus more on the future, provide causal explanations for poor performance, and use more passive voice and fewer personal pronouns. Finally, in an additional survey of managers, we summarize the characteristics of the
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performance reports prepared in our primary experiment and ask participants to provide their opinions on factors that drove the characteristics of the performance reports. Survey participants primarily
believe that (1) managers intentionally write more readable reports when performance is good with the
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objective of highlighting positive performance, and (2) managers intentionally provide more causal explanations for past performance and more information about future plans when performance is bad in order to satisfy investors’ demand. In contrast, the survey provides much more limited evidence that participants believe managers intentionally write less readable reports when performance is bad with
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the objective of hiding poor performance. Moreover, when participants were asked to assume they were a manager that had to describe some poor performance in their firm, a majority of participants
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indicated that they would choose to issue a more readable disclosure rather than a less readable disclosure.5 Accordingly, our survey provides additional evidence suggesting that managers attempt to
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write more readable reports when disclosing good performance, provide additional useful information
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when disclosing poor performance, and that differences in readability between good news and bad
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news disclosures are unlikely driven by intentional obfuscation of poor performance.
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It is also possible that participants did not want to admit to having done so, but this possibility is unlikely given that our manipulations were done between participants. The combination of results discussed in Section 4.2 of the paper and the additional survey results further suggest this is an unlikely alternative explanation for our findings. 5
The disclosure options presented to participants in the survey were not labeled as more or less readable. Instead, participants were just shown two possible disclosures (which varied in readability), and indicated which they would choose to provide.
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Our study capitalizes on the comparative advantage of experiments (Libby, Bloomfield, and Nelson, 2002) and complements prior work by testing hypotheses that would be difficult to test using archival data. For example, examining how self-enhancement motives affect the linguistic characteristics of disclosures would be difficult in real-world disclosure settings because managers generally have
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strong motives to present the firm favorably (i.e., it would be hard to find situations where firms have weak self-enhancement motives for comparison). Also, by holding information content constant in our experiments, we control for underlying differences in firm circumstances or environmental complexity which are likely to be confounded with firm performance and reporting goals in a natural setting. This
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allows us to complement prior archival work and disentangle the effects of firm performance and
reporting goals from the effects of environmental complexity, all of which are likely to be confounded in a natural setting. Our experiments also eliminate potential effects of other parties (e.g., legal counsel, etc.) on the attributes of the narratives, which may again explain some of the differences documented in
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archival studies. This allows us to focus on the manager’s contributions to the narratives independent of
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these filters. In the experiments, we ask participants to prepare open-ended reports rather than to just respond to scaled questions. This is more analogous to how disclosures would be prepared in the real
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world, and allows us to use textual analysis measures similar to those used in archival studies.
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The remainder of the paper is organized as follows. We provide background and develop hypotheses in Section 2. We discuss the experimental method we employ for our primary experiment in
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Section 3 and discuss its results in Section 4. Section 5 describes our supplemental experiment and its results. Section 6 describes results of our independent survey of experienced managers. We summarize and conclude in Section 7.
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2. Background and Development of Hypotheses At its core, language is a social construct. The vast sociolinguistics literature describes how individuals’ linguistic choices reveal their social-psychological processes and vary with personal and environmental circumstances (Gee, 1999; Pennebaker, Mehl, and Niederhoffer, 2003). In a financial
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reporting context, prior research suggests that the linguistic characteristics of narrative disclosures are likely to vary with firm performance (for reviews, see Jones and Shoemaker, 1994; Li, 2010). In this section, we consider how managers’ reporting goals combine with firm performance to influence
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disclosure readability and other linguistic characteristics of narrative disclosures. 2.1 Disclosure Readability
Prior literature has shown that disclosures are less readable when firm performance is poor. Using a sample of 60 U.S. firms, Subramanian, Insley, and Blackwell (1993) examine how readability of
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the Chairman’s Letter varies with firm performance. They find that readability is significantly higher for
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the firms where performance improves over the prior period rather than deteriorates. However, other pre-2003 studies do not find evidence that readability varies with performance (e.g., Courtis, 1986;
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Jones, 1988; and Clatworthy and Jones, 2001). Rutherford (2003) argues that early (pre-2003) readability studies should be interpreted cautiously because they rely on “small samples of tests, testing of limited
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amounts of text, and the application of weak tests of association.” Li (2008) provides the first large-
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sample evidence on the issue and finds that firms with higher earnings have more readable annual reports. Further, when performance is positive, firms with more readable annual reports have more persistent positive earnings. Much of the accounting literature assumes that less-readable bad news disclosures result from a conscious attempt by management to obfuscate bad news (for reviews, see Jones and Shoemaker, 1994; 6
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and Li, 2008). Recent research in accounting supports the idea that intentional obfuscation of bad news may be a useful strategy for managers and finds evidence consistent with the prediction that investors react less strongly to less readable disclosures.6 However, archival studies generally cannot differentiate between strategies that involve obfuscating bad news or clarifying good news, which would produce a
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similar pattern of results.
In addition, it is possible that bad news leads managers to make other linguistic choices that affect disclosure readability even in the absence of intentional obfuscation (Bloomfield, 2008). For
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example, Bushee et al. (2018) find that, while there is some evidence of intentional obfuscation in
conference calls, there is also evidence that managers’ linguistic complexity is driven by providing more discussion of firm information, and that this portion of linguistic complexity reduces information asymmetry. Guay et al. (2016) find that financial statement complexity is strongly associated with
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additional voluntary disclosure. They also find that firms that are affected by new accounting standards also respond with increases in voluntary disclosures. This again supports the idea that firms respond to
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difficult circumstances with additional disclosures which reduce information asymmetry.7 Combined, the literature provides evidence that bad news disclosures are likely to have different linguistic
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performance.
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characteristics than good news disclosures even when managers do not try to obfuscate poor
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Recent examples include You and Zhang (2009); Miller (2010); Rennekamp (2012); Lawrence (2013); Tan, Wang and Zhou (2015); and Koonce, Leitter, and White (2016). 7
This literature also suggests that bad news disclosures can be less readable than good news disclosures because the business environment related to poor performance is inherently more complex (see, e.g., Bloomfield 2008; Guay et al. 2016; Bushee et al. 2018). As we discuss in Section 3.3 and Section 7, we design our experiment to hold constant the complexity of the underlying causes of good vs. poor performance. As a consequence, we cannot assess the influence of this factor.
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Whether managers are intentionally issuing less readable disclosures when performance is poor, attempting to provide more information to explain poor performance and reduce information asymmetry, and/or attempting to clarify the meaning of good news, disclosures of bad performance will be less readable than disclosures of good performance. Also, if this behavior is driven by self-
enhancement motive. Our first hypothesis is therefore:
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enhancement motives, the difference in readability will be larger when managers have a stronger self-
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H1a: Managers will prepare less readable disclosures of bad performance than of good performance.
H1b: The difference between the readability of disclosures of good and bad performance will be greater when managers have a stronger self-enhancement motive. Our first hypothesis predicts that differences in readability between good and bad news
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disclosures will be larger as self-enhancement motives get stronger, but we do not make ex ante predictions about the specific pattern of responses to a shift in the strength of self-enhancement
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motives. However, our tests allow us to examine whether managers respond to a stronger selfenhancement motive by decreasing the readability of bad news disclosures and/or increasing the
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readability of good news disclosures. We also do not make ex ante predictions as to the intentionality of
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managers’ disclosure readability decisions, but we do ask participants debriefing questions to better understand intentionality. Our survey of experienced managers provides further evidence of both the
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intentionality of, and motives for, certain linguistic choices. 2.2 Linguistic Characteristics and Managers’ Association with the Message We next consider two specific language choices that are related to disclosure readability and may also be influenced by firm performance and managers’ reporting goals – the use of first person 8
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pronouns and the use of active versus passive voice. Both of these characteristics capture the extent to which management associates themselves or distances themselves from the information in the disclosure.8 Prior work in psychology finds that individuals use fewer first person singular pronouns (e.g., “I”, “me”) when they feel more psychologically distant from the target being described (Cohn, Mehl, and
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Pennebaker, 2004).9 Similarly, work on pragmatics and discourse argues that the avoidance of personal pronouns (Reilly et al., 2005), and first person pronouns in particular (Hyland, 2005), conveys less
involvement with a message. This suggests that managers may use fewer first person pronouns in their disclosures when news is bad than when news is good, given that it may be an effective method to
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distance themselves from the poor performance being described (Asay, Libby, and Rennekamp, 2018). Likewise, the use of passive voice rather than active voice can also distance an individual from the information being conveyed (Chafe and Danielewicz, 1987; Reilly et al., 2005). For example, consider
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the sentence, “the Company increased sales this quarter.” The use of active voice in the sentence highlights the company’s role in increasing sales. Alternatively, the sentence could be constructed using
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the passive voice as, “the Company’s sales increased this quarter.” In the sentence using passive voice, the agent (i.e., the Company) is de-emphasized. Thus, the use of passive voice in disclosures can
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distance the firm from the actions or outcomes being described. In addition, we expect the use of first
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person pronouns and passive voice to interact with self-enhancement motives, given that managers
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In Section 3.4.5 we discuss how our measures of first person pronouns and passive voice relate to our broader measure of disclosure readability. 9
Although Cohn et al. (2004) specifically focus on the reduction in first person singular words (e.g., “I”, “me”, “mine”) as a distancing device, we also include first person plural words (e.g., “we”, “us”, “our”) in our analyses, given that managers are speaking on behalf of a group of individuals when discussing firm performance. In Section 4 where we discuss our results, our primary analyses are based on all first person pronouns, but we also separately consider the effects of firm performance and reporting goals on the use of first person singular and first person plural pronouns.
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with stronger self-enhancement motives should be even more interested in distancing themselves from poor performance and associating themselves with good performance. Our second and third hypotheses are therefore:
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H2a: Managers will prepare disclosures that include fewer first person pronouns when performance is bad than when performance is good.
H2b: The difference in the use of first person pronouns between disclosures of good and bad performance will be greater when managers have a stronger self-enhancement motive.
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H3a: Managers will prepare disclosures that include more passive voice when performance is bad than when performance is good.
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H3b: The difference in the use of passive voice between disclosures of good and bad performance will be greater when managers have a stronger self-enhancement motive. 2.3 Causal Explanations for Performance and Focus on the Future
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Finally, we consider two additional disclosure characteristics – the provision of causal explanations for performance and a focus on the future – that may result in linguistic differences
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depending on firm performance and managers’ reporting goals.
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2.3.1 Causal Explanations
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Prior literature argues that investors demand more explanation when performance is poor (Bloomfield, 2008; Bushee et al., 2018). Further, managers appear to understand this demand and respond with more informative disclosures when performance is poor (Merkley, 2014). Stronger selfenhancement motives should further increase the provision of causal explanations when performance is poor. Precise causal explanations describe the contributors to poor performance and isolate them to a 10
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specific set of circumstances. By highlighting causal explanations for poor performance, managers are better able to reassure investors that poor performance is not ongoing and that future performance has the potential to improve.10 Our fourth hypothesis is therefore:
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H4a: Managers will prepare disclosures that include more causal language when performance is bad than when performance is good.
H4b: The difference in the use of causal language between disclosures of good and bad performance will be greater when managers have a stronger self-enhancement motive.
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2.3.2 Focus on the Future
Prior archival work shows that firms use more future-oriented words in both their 10-K’s (Li, 2008) and in conference calls (Matsumoto, Pronk, and Roelofsen, 2011) when firm performance is poor. Our study complements this prior work by holding constant everything except the firm’s economic
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performance, in order to rule out that results may be driven by other firm characteristics. In addition,
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we expect the association between poor performance and increased use of future-oriented words to be stronger as self-enhancement motives increase, as discussion of the future gives management the
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opportunity to highlight opportunities for improvement. Note that our prediction could be driven by two effects that are not mutually exclusive. Managers may opportunistically shift discussion to the
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future to downplay negative past performance or to provide useful information on how performance
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will be improved.11 Our final hypothesis is that:
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Causal language not only has the potential to reassure investors, but has also been shown to change employee behavior and performance. In a controlled experimental setting, Loftus and Tanlu (2017) show that the inclusion of causal language in performance feedback leads to improved performance in a subsequent task, particularly when the initial feedback related to relatively poor performance. 11
As with H1, we do not make ex ante predictions about the intentionality of managers’ choices for our remaining hypotheses, but we do ask participants directly about their disclosure decisions in order to shed light on
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H5a: Managers will prepare disclosures that focus more on the future relative to the past when performance is bad than when performance is good.
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H5b: The difference in relative focus on the future versus the past between disclosures of good and bad performance will be greater when managers have a stronger self-enhancement motive.
3. Primary Experiment: Method 3.1 Participants
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Participants in our primary experiment are 205 experienced managers.12 On average,
participants are 40.1 years old and have 16.9 years of work experience. 165 participants (80.5%) report being directly (114 participants) or indirectly (51 participants) involved with preparing performance
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reports. 133 participants (65%) report being directly (73 participants) or indirectly (60 participants) involved with making projections and/or providing explanations to analysts and investors. 130
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participants (63.4%) report being directly (62 participants) or indirectly (68 participants) involved in making choices that relate to the preparation of financial statements. 173 participants (84.4%) are
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male.13
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intentionality. Responses to these questions are discussed in our results section alongside the evidence on what participants actually do in their reports. 12
We recruited participants in three ways. First, we directly emailed alumni of a top-rated MBA program (22 participants). Second, we posted announcements on the LinkedIn alumni association pages (69 participants). Third, we asked current EMBA students to participate in our study (114 participants). Inferences are unchanged if we control for the source of our participants. 13
While we do not directly ask participants whether they are native English speakers, we have two independent coders (who are blind to our conditions) read the responses of our participants and rate whether they have concerns about any of the participants’ effectiveness at communicating in written English. Coders independently
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3.2 Design and Manipulations Participants are asked to assume that they are in charge of investor relations for the Dexico Corporation, a hypothetical firm. In addition, they are asked to assume that, as part of their job duties, they often prepare press releases for investors on behalf of Dexico and its different divisions.
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Participants are informed that they will prepare a report on behalf of the Beverages and Snacks division to explain its performance to investors. The experiment uses a 2x2 between-subjects design,
manipulating (1) performance (good versus bad) and (2) reporting goal (unbiased versus favorable
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reporting). Varying the reporting goal allows us to provide participants with either a relatively weak or strong self-enhancement motive (unbiased versus favorable reporting goal condition, respectively). 3.3 Task and Procedure
After reading a brief introduction to the task, participants are told they will be given some basic
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facts. Participants are asked to rely on their past experiences to make assumptions about the
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circumstances surrounding the facts and how they may have contributed to the division’s performance to provide a more coherent explanation to investors. To help participants understand how they might
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use the facts to write their report, they are given an example before moving to the main task. Participants consider the hypothetical fact that “The division moved its administrative offices into a new
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building this quarter.” They are told that if the division performed well, they might describe the fact as
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“The move to a new office revitalized employees. They were more excited about coming to work, the transition to the new facilities went smoothly, and most employees expressed that the new location made their commute easier." In contrast, participants are told that if the division performed poorly, they
agree that they have concerns about two of the participants. Inferences are unchanged if we exclude these two participants, so we include them in all analyses.
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might describe the fact as “The move to a new office demoralized employees. They were less excited about coming to work, the transition to the new facilities did not go smoothly, and most employees expressed that the new location made their commute harder.” The readability of these sample reports is held as constant as possible for the good and bad performance examples.14 Importantly, these
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instructions are held constant across conditions, so they are unlikely to explain any differences in between-condition results.
Next, participants are presented with a paragraph containing our experimental manipulations.
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In the good (bad) news condition, participants are told that the Beverages and Snacks division of Dexico delivered a 10% increase (decrease) in sales this quarter compared to the same quarter last year. They are also told that this performance is better (worse) than all other divisions within the company, and better (worse) than most other firms in the same industry. In the unbiased reporting goal condition,
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participants are told that they should report the division’s performance accurately, and “in a manner that is as unbiased as possible”. In the favorable reporting goal condition, participants are told that they
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should report the division’s performance accurately, but “in a manner that presents the performance in
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as favorable a light as possible”.
Next, participants proceed to a page containing four facts available for use in their report.15
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Participants are instructed that the facts are presented in no particular order and that they can use one
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Using our measure of readability, which is discussed in more detail later in this section, the Good News example had a score of 15.01, and the Bad News example had a score of 15.00, indicating that they were nearly identical in terms of readability. 15
To choose the four facts to be included, we started by presenting a larger list of facts to 60 individuals recruited from Amazon Mechanical Turk. For each fact presented, these individuals were asked to rate on a 101-point scale whether the fact was “unambiguously negative” (0) or “unambiguously positive” (100). For the current study, we retained the four facts that did not significantly differ from the midpoint of 50 on the scale (Kida, 1984; Libby and
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or more facts in their report to support their description of why the division performed as it did. Below the four facts is a box in which participants can type their report (see Figure 1). They are told that they must remain on the page for at least three minutes in order to give them time to draft the report. After three minutes have passed, a button pops up allowing them to move forward in the study whenever
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they are ready. This technique allows participants to provide responses that are (1) long enough for our analyses and (2) varied enough to detect real differences in language choices. Finally, participants answer follow-up questions about their report, manipulation check questions, and demographic
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questions.
Our goal in designing this task was to provide a rich enough performance setting to allow the experienced managers to craft relatively detailed performance reports while also drawing on their prior
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experience as managers. For example, this setting allows participants to draw upon the tradeoffs and motives they face when reporting on firm performance. If we had instead used a real performance task
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with constructed incentives, we would have limited our ability to gain insight from participants’
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knowledge of the reporting environment in practice while also potentially confounding performance with individual characteristics of participants (e.g., participants who performed well might be more
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hardworking or intelligent, making it difficult to determine whether differences in participants’ reports
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are due to performance or participant characteristics).16 This task allows us to achieve these objectives
Trotman, 1993). This design ensures that participants could plausibly use any of the four facts (held constant across all conditions) to explain either good or bad performance in the division. 16
For example, prior accounting studies have asked participants to create rebus puzzles (Kachelmeier, Reichert, and Williamson, 2008; Kachelmeier and Williamson, 2010), complete a sandwich-making task (Farrell, Kadous, and Towry, 2008), or complete a trivia task (Libby and Rennekamp, 2012; Asay, 2018).
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and directly capture the language choices of experienced managers without being modified by the various parties that craft and create press releases in the real world (e.g., legal departments). One potential limitation of our task is that participants do not actually observe the true cause of performance and instead construct a story for performance based on the facts we provide. While we
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acknowledge this as a potential limitation, there are at least three important reasons to believe it does not affect the validity of our results. First, in constructing causal narratives, individuals generally draw on the most accessible potential factors available in memory – not necessarily the true causal drivers of an
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outcome (Tversky and Kahneman, 1973). Similarly, in our setting, the four facts provide accessible
factors that are plausible contributors to realized performance and individuals are asked to draw upon these accessible potential factors and upon their prior experiences to construct a causal narrative. Second, even if our task relies on a slightly different cognitive mechanism than creating a causal
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narrative by drawing on memory, this could change the levels of the linguistic characteristics we measure, but is less likely to change the directional effects of our performance and reporting goal
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manipulations. Finally, many of our findings align with empirical patterns documented in the literature,
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providing at least some level of validation for this measurement technique. 3.4 Dependent Measures
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Our dependent variables are selected to match those used in prior archival empirical and
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experimental studies to increase the comparability of our results. 3.4.1 Readability Measure There is considerable disagreement in the literature over how best to measure “readability.”
Many of the standard readability measures were developed for leveling grade-school textbooks and consist of simple formulas based on sentence length and the average number of syllables in words 16
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(Dubay, 2004). Two such measures that have been widely used in the prior accounting literature are the Fog Index and the Flesch Reading Ease Score (Flesch Score)17. While the Fog Index and Flesch Score measures are easy to calculate and their use is widespread, some have argued that they are too simple to provide a meaningful measure of readability (Dubay, 2004), particularly in business communications
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(Jones and Shoemaker, 1994; Miller, 2010; Loughran and McDonald, 2014a,b).18 Specifically, the Fog and Flesch measures do not do a good job of capturing the complexity of sentence structure. For instance, “the cat sat on the mat” would be judged to have the same readability as a phrase including the exact same words but rearranged (e.g., “mat sat the on the cat”), even though the latter is clearly less
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readable. More recently, some studies have used either file size (Loughran and McDonald, 2014a) or the Bog Index (Bonsall, Leone, Miller, and Rennekamp, 2017) to capture readability of disclosures in archival samples. While a file size proxy allows for calculation of readability in large-sample archival studies, it is likely to be much noisier than a measure based on the actual language used in a disclosure (Bonsall et
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al., 2017). The Bog Index also allows for calculation of readability in large-sample archival studies, but
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the proprietary Stylewriter software that is used to collect the measure provides less transparency with respect to the actual components that contribute to readability.
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In our study, we use a measure of readability that is more complex to calculate than some
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alternative measures used in prior studies, but is more transparent and more precisely captures actual levels of readability. We develop a measure of readability that includes most of the features of
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readability that are manipulated in Rennekamp (2012) and measured in Miller (2010). Thus, our
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See e.g., Li (2008); Biddle, Hilary, and Verdi (2009); Miller (2010); Lehavy, Li, and Merkley (2011); Lawrence (2013); Bushee et al. (2018). 18
For example, multi-syllabic words such as “telecommunication” or “depreciation” would indicate lower levels of readability according to the Fog Index and Flesch Score, although these words are unlikely to be difficult to read for most investors.
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Readability measure is largely based on the features the SEC suggests will improve the readability of firm disclosures (SEC, 1998). Our measure of readability is similar to Miller’s (2010) measure and is calculated as instances of [(Passive Voice + Hidden Verbs + Superfluous words + Negations + Complex Synonyms – Personal Pronouns)*10]/[number of words/average words per sentence].19 Finally, we rescale the
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Readability measure such that higher scores indicate higher readability.20 3.4.2 Association with the Message Measures
Our first measure of association with the message is the use of first person pronouns. Our
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measure of participants’ use of first person pronouns is calculated by capturing the I and we variables from the LIWC2015 software. The I variable captures first person singular words (e.g., “I”, “me”) and the we variable captures first person plural words (e.g., “we”, “our”). We sum these variables to get a total measure of the use of first person pronouns. Our second measure of association with the message
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relates to the use of passive voice. Our measure of participants’ use of passive voice is calculated by analyzing each report using Stylewriter software. Stylewriter summarizes various linguistic
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characteristics from written texts. For our analyses, we use the output measure counting the number of
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instances of passive voice in a text.
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3.4.3 Causal Explanation Measure
19
The number of Negations and Personal Pronouns are calculated using LIWC2015 software rather than Stylewriter, because Stylewriter does not separately report these two linguistic style features. 20
To rescale the Readability measure we subtract the raw score (where higher measures indicate lower readability) from 20. The rescaling procedure and values were chosen so that most participants’ reports had positive readability scores and so that higher scores indicated greater readability to make results more interpretable.
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Our measure of participants’ use of causal explanation words is calculated by capturing the cause variable from the LIWC2015 software, which includes component words related to providing causal explanations (e.g., “because”, “effect”).
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3.4.4 Focus on the Future Measure Our measure of participants’ relative focus on the future is calculated by using the focusfuture and focuspast variables from the LIWC2015 software to capture the number of words that focus on the future (e.g., “will”, “soon”) and past (e.g., “did”, “talked”). We then construct the measure used in our
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analyses by dividing the number of future words by the sum of future and past words. 3.4.5 Relation between Readability and other Measures
First person pronouns and passive voice are both components of readability, but they also relate
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to the distinct construct of association with the message. For example, our measure of readability includes personal pronouns (first and third person), whereas our measure of association with the
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message relates only to first person pronouns. While the third person pronouns captured in our readability measure can improve the understandability of text by more clearly indicating the target
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objects in a conversation (e.g., “You will receive a $1.00 dividend” vs. “Shareholders will receive a $1.00
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dividend”), they do not capture differences in the speaker’s association with a message. Similarly, passive voice is only one component of our readability measure, such that there is uncertainty, ex ante,
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whether passive voice will exhibit a similar pattern of results as readability overall. Most notably, managers’ reporting goal and performance may influence their propensity to associate themselves with the message, even in the absence of intentional obfuscation of poor performance. The extent to which the reports focus on the future and provide causal explanations for performance are not directly related
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to readability. Rather, these two linguistic characteristics reflect alternative approaches managers might use to communicate poor performance.21 4. Primary Experiment: Results
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4.1 Manipulation Checks For our manipulation check questions, 90.7% of participants correctly report whether the
division’s performance was good or bad in the recent quarter, while 85.4% of participants correctly report whether their primary reporting goal in writing the report was to be as unbiased as possible or to
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present the division in as favorable a light as possible.22 We also ask participants to rate the extent to which another person reading their report would judge the division favorably or unfavorably (1 = “very unfavorably”, 10 = “very favorably”). Consistent with a successful performance manipulation, participants believe that the division would be viewed more favorably when news is good (mean = 6.81)
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than when news is bad (mean = 6.26), and the difference is significant (p = 0.018, one-tailed). Consistent
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with a successful reporting goal manipulation, participants believe that the division would be viewed
21
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By construction, readability is highly correlated with the use of passive voice (ρ = -0.345; p < 0.001, two-tailed, untabulated) and the use of first person pronouns (ρ = 0.697; p < 0.001, two-tailed, untabulated). Readability is also correlated with the use of future tense words (ρ = 0.221; p = 0.002, two-tailed, untabulated) but not with the use of causal words (ρ = .107; p = 0.128, two-tailed, untabulated). In addition, untabulated results indicate that personal pronoun usage is associated with both causal words (ρ = 0.697, p < 0.001, two-tailed) and with future tense words (ρ = 0.252, p <0.001, two-tailed). The use of passive voice is negatively correlated with future tense words (ρ = -0.143; p = 0.042), but is only marginally significantly correlated with causal words (ρ = 0.120, p = 0.088, two-tailed) and not significantly correlated with personal pronoun usage (ρ = -0.077, p = 0.273, two-tailed). A regression analysis including each of these four linguistic characteristics (as well as our manipulated variables) indicates that readability is increasing in pronoun usage (t = 12.97; p < 0.001, two-tailed) and decreasing in the use of passive voice (t = -2.66; p < 0.001, two-tailed), but is unrelated to the use of causal words (t = -0.175; p = 0.490, two-tailed) or future tense words (t = 0.947; p = 0.690, two-tailed). 22
Inferences are unchanged if we exclude participants who answered manipulation check questions incorrectly.
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more favorably when there is a favorable reporting goal in place (mean = 6.92) than when the reporting goal is to be unbiased (mean = 6.15) and the difference is significant (p = 0.002, one-tailed). 4.2 Tests of Readability Hypotheses
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H1a predicts that participants will prepare reports that are less readable when performance is bad than when performance is good, and H1b predicts that this will be particularly true when managers have a stronger self-enhancement motive. Panel B of Table 1 shows that, consistent with H1a,
participants prepare reports that are less readable when news is bad than when news is good (p = 0.058,
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one-tailed) and, consistent with H1b, this is particularly true when they have a stronger self-
enhancement motive (p = 0.015, one-tailed). Panel A of Figure 2 presents these results graphically.
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While our results support that bad news disclosures are less readable, particularly when selfenhancement motives are stronger, this does not appear to be driven by participants intentionally
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making bad news disclosures less readable. Instead, in this primary experiment, the interaction appears to be driven by participants making good news disclosures more readable when they have a stronger
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self-enhancement motive. The simple main effect of reporting goal is not significant when news is bad (p = 0.596, two-tailed, untabulated). When news is good, however, participants prepare significantly more
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readable reports when they have a favorable reporting goal than a goal to be as unbiased as possible (p = 0.010, two-tailed, untabulated). Participants’ responses to debriefing questions provide additional insight into the intentionality of disclosure readability decisions. Panel A of Table 2 shows mean responses, by condition, to two 21
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questions participants answered about the readability of their reports. The first question asks participants “How easy or difficult would you say it is to read your report?” (1 = “very easy”, 10 = “very difficult”). The second question asks participants about the extent to which they were motivated to make their report easier or more difficult to understand (1 = “I was motivated to make my report easier
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to understand”, 10 = “I was motivated to make my report more difficult to understand”). Panel B of Table 2 shows that we find no significant main effects or an interaction on either of these two measures. These results should be interpreted with caution for at least two reasons. First, the lack of a significant effect is not affirmative evidence that the effect is not there. Second, participants may be reluctant to
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admit to intentionally making disclosures less readable. Nevertheless, in combination with the results shown in Table 1, our results generally support the idea that participants at least do not appear to be intentionally making bad news disclosures less readable to obfuscate poor performance, contrary to
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arguments made in prior literature.
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4.3 Tests of Hypotheses Related to Managers’ Association with the Message
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H2 and H3 make predictions about linguistic characteristics that can be used to associate or distance oneself from the information in a disclosure. H2a predicts that participants will use fewer first
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person pronouns (e.g., “I”, “We”, etc.) when performance is bad than when performance is good, and H2b predicts that this difference will be greater when participants have a stronger self-enhancement
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motive.23 Panel B of Table 3 shows that neither H2a nor H2b is supported (both p-values > 0.220, onetailed). Panel B of Figure 2 presents these results graphically. However, participants do use more first
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The first person pronouns counted in the two categories include the following: I, I’d, I’ll, I’m, I’ve, id, ive, me, mine, my, myself, let’s, lets, our, ours, ourselves, us, we, we’d, we’ll, we’re, we’ve, and weve.
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person pronouns when they have a stronger self-enhancement motive (p = 0.054, two-tailed). This finding suggests that managers are more willing to associate themselves with the information in the report when they have written the report to present the firm more favorably.24 Panel A of Table 4 shows mean responses, by condition, to our open-ended debriefing question asking participants to estimate
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the number of first person pronouns used in their reports. Panel B of Table 4 shows that participants do not believe that they used fewer first person pronouns when news was bad than when news was good (p = 0.448, two-tailed). They also do not indicate any difference in first person pronouns when there is a
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stronger self-enhancement motive (p = 0.732, two-tailed).
Because prior work distinguishes between first person singular (e.g., “I”, “me”) and first person
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plural (e.g., “we”, “our”) pronouns, we also separately look at the effects of performance and reporting
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goals on these two categories of pronouns. When analyzed separately, we find that participants use fewer first person singular pronouns when news is bad (p = 0.039, one-tailed, untabulated), but do not
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use fewer first person plural pronouns (p = 0.369, one-tailed- untabulated). This provides some support for H2a. Participants appear to use fewer first person singular pronouns like “I”, or “me” when
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performance is poor, consistent with distancing themselves from the information. When analyzed
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separately, we still do not observe an interaction between performance and reporting goal on the use of either first person singular pronouns (p = 0.255, one-tailed, untabulated) or first person plural pronouns (p = 0.288, one-tailed, untabulated).
24
Consistent with this idea, untabulated results indicate that pronoun usage is positively associated with disclosure tone (ρ = 0.152; p = 0.030, two-tailed) and with positive emotion words (ρ = 0.189; p = 0.007, two-tailed).
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H3a predicts that participants will use more passive voice in their reports when performance is bad than when performance is good, and H3b predicts that the difference will be greater when they have a stronger self-enhancement motive. Consistent with H3a, Panel B of Table 3 shows that participants use more passive voice when performance is bad than when performance is good (p =
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0.057, one-tailed). Consistent with H3b, the difference in use of passive voice between good and bad news is greater when participants have a stronger self-enhancement motive (p < 0.001, one-tailed). Panel C of Figure 2 presents these results graphically. Panel A of Table 4 shows mean responses, by condition, to our debriefing question asking participants the extent to which their report used active or
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passive voice in their report (1 = “My report primarily used active voice”, 10 = “My report primarily used passive voice”). Panel B of Table 4 shows that, despite our finding support for H3a and H3b, participants do not report that they use more passive voice when news is bad (p = 0.882, two-tailed), or that there is a stronger difference in the use of passive voice between good and bad news when they have a stronger
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self-enhancement motive (p = 0.361). Pennebaker (2011) suggests that linguistic style choices (such as
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the use of active versus passive voice) are particularly likely to occur beneath awareness as compared to content choices (such as discussions of the future or causal explanations), which may help to explain
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why participants appear unable to accurately report differences in their use of passive voice across our
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performance and reporting goal conditions. 4.4 Tests of Hypotheses Related to Causal Explanations for Performance and Focus on the Future
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H4a predicts that participants will prepare reports that include more causal explanation words
when performance is bad than when performance is good and H4b predicts that this will be particularly true when they have a stronger self-enhancement motive. Consistent with H4a, Panel B of Table 3 shows that participants use more causal words when performance is bad than when performance is good (p = 0.003, one-tailed). However, H4b is not supported, as we do not find that this effect is 24
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stronger when participants have a stronger self-enhancement motive (p = 0.416, one-tailed). Panel D of Figure 2 presents these results graphically. Panel A of Table 4 shows mean responses, by condition, to our debriefing question asking participants the extent to which their report focused on explaining underlying causes for the firm’s
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performance (1 = “I was primarily focused on reporting ‘just the facts’”, 10 = “I was primarily focused on explaining the underlying causes for performance”). Panel B of Table 4 shows that, consistent with H4a, participants believe that their report focuses on providing more causal explanation for underlying
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performance when news is bad than when news is good (p = 0.010, two-tailed). They also report that they provide more causal explanation when they have a stronger self-enhancement motive (i.e., a favorable reporting goal), (p = 0.006, two-tailed).25
H5a predicts that participants will prepare reports that focus more on the future relative to the
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past when performance is bad than when performance is good, and H5b predicts that this will be particularly true when they have a stronger self-enhancement motive. Consistent with H5a, Panel B of
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Table 3 shows that, when performance is bad, participants use more words that focus on the future in
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their reports, relative to words that focus on the past (p < 0.001, one-tailed). However, H5b is not supported, as we do not find that this effect is stronger when participants have a stronger self-
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enhancement motive (p = 0.894, one-tailed). Panel E of Figure 2 presents these results graphically.
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Despite the fact that we do not find support for H5b when looking at the reports that participants actually prepare, our debriefing question related to the focus on future versus past 25
While we do not find a significant interaction between performance and reporting goal (p = 0.124, two-tailed), the simple main effect of performance is not significant when the reporting goal is to be unbiased (p = 0.442, twotailed), but is significant when participants have a favorable reporting goal (p = 0.004, two-tailed), providing at least some support for the idea that participants’ beliefs about the provision of causal explanations in their reports is consistent with what we predict in H3b about their actual behavior.
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performance suggests that participants believe they behave in the predicted way. Panel A of Table 4 shows responses, by condition, to our debriefing question asking participants to rate the extent to which their report focused on past performance versus future expectations (1 = “My report focused primarily on past performance”, 10 = “My report focused primarily on future performance expectations.” Panel B
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shows that, consistent with what we predict in H5a, participants believe that their report focuses more on future expectations than past performance when news is bad than when news is good (p < 0.001, two-tailed).26 Further, and consistent with what we predict in H5b, this difference is even greater when
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participants have a stronger self-enhancement motive (p = 0.048, two-tailed).
The difference between what participants do (as tested in H5b and shown in Table 3) and what they say they do (as shown in Table 4’s supplemental analyses) could be driven by participants’ inability to accurately infer their linguistic choices (Pennebaker, 2011) and/or by noise in our measure for testing
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participants’ relative focus on the future in their reports. The predetermined words in the LIWC2015 categories were not developed specifically for the purpose of analyzing business texts. As a result, our
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measures may be (1) including words that should not be counted or (2) omitting words that should be
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counted in a business context (Matsumoto et al., 2011; Dikolli, Keusch, Mayew, and Steffen, 2015). 5. Supplemental Experiment
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In our primary experiment, we operationalized our reporting goal manipulation by instructing
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participants to report performance either “in a manner that is as unbiased as possible” or “in a manner that presents the performance in as favorable a light as possible.” Given that poor performance is
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All supplemental analyses of participants’ beliefs about their linguistic choices are reported as two-tailed rather than one-tailed tests. Given that prior work in linguistics provides mixed evidence as to whether individuals are aware of their linguistic choices (Pennebaker, 2011), we do not make directional predictions ex ante as to whether participants will be able to accurately infer the linguistic characteristics of their reports.
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unfavorable by definition, it is possible that participants in the bad news condition were unclear as to how to present unfavorable news in a favorable light. Instead, the instructions may have prompted participants to think of ways to provide a justifiable explanation (as predicted by H4) and describe a more favorable future (as predicted by H5), but not to think of ways to make bad news less readable.
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The instructions may have also led participants to consider ways to maximize the favorable tone of the disclosure rather than to minimize the unfavorable tone. If so, using a less positive tone in the high selfenhancement motives instructions might affect the extent to which the participants use causal language in describing their performance and focus on the future. Further, a less positive tone in these
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instructions might lead participants to more naturally resort to intentionally issuing a less readable report to obfuscate poor performance.
To test these possibilities, we conduct a supplemental experiment using a 1 x 2 between-
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subjects design in which all participants receive the bad news information and we manipulate the instructions used to induce a stronger self-enhancement motive. 74 experienced managers enrolled in a
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highly-rated EMBA program participated. The participants are instructed to present their performance “in a manner that presents the performance in as favorable a light as possible” (the “most favorable
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condition”, which uses the same wording as in our primary experiment) or “in a manner that presents
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the performance in the least unfavorable light as possible” (the “least unfavorable condition”). All other procedures are identical to our primary experiment.
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As shown in Table 5 Panel A, we find no difference across conditions in participants’ use of
personal pronouns (p = 0.461, two-tailed), passive voice (p = 0.400, two-tailed), causal words (p = 194, two-tailed), or words that focus on the future relative to words that focus on the past (p = 0.812, twotailed). These findings suggest that the tests of H2, H3, H4, and H5 are robust to using a less positive tone in the self-enhancement instructions. Interestingly, we do find that participants in the least 27
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unfavorable condition write marginally less readable reports than participants in the favorable condition (p = 0.091, two-tailed).27 This result does not, however, appear to be driven by an attempt to obfuscate poor performance. Specifically, participants in the least unfavorable condition report being less motivated to make their reports difficult to understand (p = 0.060, two-tailed) and believe another
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person would judge the division less favorably after reading their report (p = 0.091, two-tailed).
Additional analyses (see Panel B) indicate that the difference in readability arises because participants in the least unfavorable condition use more negations (p = 0.002, two-tailed). Further, our manipulation is no longer a significant predictor of readability after controlling for participants’ use of negations (p =
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0.237, two-tailed, untabulated). Combined, these results provide additional support for the inferences drawn from our primary experiment related to managers’ linguistic choices, with one exception. The exception is that, although unaware that they are doing so, managers appear to provide less readable disclosures under “least unfavorable” reporting goals when performance is poor, primarily through the
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increased use of negations.
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6. Survey of Experienced Managers
Our primary experiment provides evidence on how firm performance and reporting goals affect
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linguistic choices in disclosures, and responses to post-experimental questions provide evidence on the
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intentionality of these choices. The purpose of our survey is to provide complementary evidence on the
27
These results are subject to at least one caveat, in that we identify an influential outlier observation in the “least unfavorable” condition (with a mean readability score of 15, which is greater than 3 standard deviations below the overall mean readability score of 16.74). When this participant is excluded, the mean Readability for the “least unfavorable” condition goes from 14.64 to 15.49, and the significance of the difference between the mean readability score in the “most favorable” and “least unfavorable” conditions goes from 0.091 to 0.158. However, the difference in the use of negations still remains significant.
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possible motives behind these choices. Participants in our survey are 144 experienced managers enrolled in a highly-rated EMBA program.28 In the survey, the participants rate possible explanations for three of the differences noted in our main experiment and choose between two reports to issue to describe some poor performance in their firm.
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6.1 Method
To begin, participants are provided with background information about our experiment. This background information explains (1) that the experienced managers in our experiment were asked to
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read information about a hypothetical firm, (2) that half of the experienced managers were told that recent performance was relatively good while the other half were told that recent performance was relatively poor, (3) that the experienced managers were each provided with the same four facts that may have contributed to performance, and (4) that the experienced managers were asked to prepare a
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performance report by making assumptions about those facts and drawing on their prior business experiences in order to create a more coherent story for investors. In addition, survey participants are
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informed that the experienced managers were provided with a reporting goal to portray the firm in “as
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favorable a light as possible.” We focus on the favorable reporting goal condition because managers
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generally have strong motives to present the firm favorably.
28
On average, participants are 37.6 years old and have 15.1 years of work experience. 113 participants (78.5%) report being directly (64 participants) or indirectly (49 participants) involved with preparing performance reports. 89 participants (61.8%) report being directly (37 participants) or indirectly (52 participants) involved with making projections and/or providing explanations to analysts and investors. 73 participants (51.0%) report being directly (22 participants) or indirectly (51 participants) involved in making choices that relate to the preparation of financial statements (one participant did not indicate his/her involvement). 115 participants (81.0%) are male (two participants did not indicate their gender).
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Survey participants are then presented with a summary of three of the differences observed (readability, causal words, and focus on the future) between the reports of participants in the good performance/favorable reporting goal condition and participants in the bad performance/favorable reporting goal condition. We focus on these three characteristics because responses in our primary
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experiment suggest that they are more likely to be driven by intentional choices than either passive voice or the use of personal pronouns. For each difference presented, survey participants are then asked to rate on 101-point scales (endpoints: 0 = “very unlikely” to 100 = “very likely”), based on their own past experience, the extent to which several factors may have contributed to the characteristics of the
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performance reports. Finally, participants are asked to assume that they are a manager who has to describe some poor performance in their firm, are presented with a more and less readable disclosure that otherwise contains the same performance information, and indicate which of the two disclosures
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they would choose to provide. 6.2 Results
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6.2.1 Readability
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Survey participants are informed that the reports were less readable when describing poor performance than when describing good performance.29 They then rate five potential explanations for
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this finding. The order in which the five potential explanations were presented was randomized for each
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survey participant. The five explanations and results are summarized in Table 6 Panel A.30 Directionally,
29
A less readable disclosure was defined as one that uses language that goes against some of the suggestions made by the Securities and Exchange Commission (SEC) to use Plain English in firm disclosures. In addition, less readable disclosures were described as using longer sentences, more complex synonyms, more passive voice, etc. 30
A repeated measures ANOVA (with participant as a random variable) reveals that at least one of the explanations is different (F(4, 535.6) = 14.06; p < 0.001, not tabulated).
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survey participants agreed most strongly with the explanation that managers intentionally write more readable reports when performance is good, with the specific intention of highlighting positive performance. This is the only explanation where the 95% confidence interval for the mean did not overlap with the 95% confidence interval of the other explanations (not tabulated). Further, pairwise
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comparisons reveal that participants rated this explanation significantly higher than any other
explanation (all p < 0.001, two-tailed), and none of the other explanations differed from one another (all p > 0.100, two-tailed).
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6.2.2 Causal Words
Survey participants are informed that the reports included more causal language when firm performance was bad than when firm performance was good. They then rate four potential
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explanations for this finding. As with our other questions, the order in which the potential explanations
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were presented was randomized. The four explanations and results are summarized in Table 6 Panel B. Directionally, survey participants agreed most strongly with the explanation that managers
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intentionally try to provide more information about the reasons for performance when performance is bad in order to satisfy investors’ demand. This is the only explanation where the 95% confidence interval
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for the mean did not overlap with the 95% confidence interval of the other explanations (not tabulated).
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Further, pairwise comparisons reveal that participants rated this explanation significantly higher than any other explanation (all p < 0.005, two-tailed). The explanation suggesting managers intentionally provide more causal explanation when performance is bad with the specific intention of hiding poor
31
A repeated measures ANOVA (with participant as a random variable) reveals that at least one of the explanations is different (F(3, 400.4) = 12.04; p < 0.001, not tabulated).
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performance is also marginally lower than the explanation suggesting managers provide less causal explanation when performance is good with the specific intention of avoiding scrutiny about the reasons for positive performance (p = 0.086, two-tailed).
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6.2.3 Focus on the Future Survey participants are informed that the reports were more focused on the future when they were describing bad performance rather than good performance. Survey participants rate four potential explanations for this finding. Again, the order in which the potential explanations were presented was
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randomized. The four explanations and results are summarized in Table 6 Panel C. 32 Directionally,
survey participants agreed most strongly with the explanation that managers intentionally try to provide more information about how performance is likely to improve in the future when performance is bad in order to satisfy investors’ demand for information. This is the only explanation where the 95%
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confidence interval for the mean did not overlap with the 95% confidence interval of the other explanations (not tabulated). Further, pairwise comparisons reveal that participants rated this
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explanation significantly higher than any other explanation (all p < 0.012, two-tailed), and participants
two-tailed).
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agreed least with the explanation that the increased focus on the future is unintentional (all p < 0.001,
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6.3.4 Disclosure Choice
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Finally, survey participants choose between two disclosure options (one more readable and one less readable) for describing poor performance in their firm. Of the 135 participants who responded to
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A repeated measures ANOVA (with participant as a random variable) reveals that at least one of the explanations is different (F(3, 412.8) = 35.70; p < 0.001, not tabulated).
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this question, 84 (62.22%) chose the more readable disclosure while 51 (37.78%) chose the less readable disclosure. This difference is significantly greater than chance (χ2 = 8.15; p = 0.005, not tabulated). 7. Conclusion
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Using two experiments and a survey of experienced managers, we investigate the determinants of disclosure readability and other linguistic characteristics in a controlled setting. In our primary experiment, we find that participants provide reports that are significantly less readable when
performance is bad than when performance is good, particularly when participants have a stronger self-
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enhancement motive in the form of a reporting goal to portray the firm as favorably as possible. In our supplemental experiment, we find some evidence that participants provide less readable bad news reports when they have a reporting goal to portray the firm in the least unfavorable light possible, rather than in as favorable a light as possible. In both experiments, our results do not appear to be
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driven by intentional obfuscation of poor performance. When directly asked about the reports they have prepared, there is no indication of intentional obfuscation in participants’ perceptions of the
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readability of their reports or their ratings of the extent to which they were motivated to make the
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report easier or more difficult to read. Further, our survey participants believe the most likely explanation for our pattern of results is that managers increase the readability of good news disclosures
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to highlight the positive performance. Combined, the results do not appear to support arguments made in prior literature that managers intentionally obfuscate poor performance by making disclosures less
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readable.
In addition to the results discussed above on readability, we also provide evidence on how other
linguistic choices are affected by variation in firm performance and reporting goals. Specifically, we find that participants use more passive voice and fewer first person singular pronouns when news is bad – a
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technique that distances the manager from the information conveyed. Further, the effect of bad news on the use of passive voice is larger when participants have a favorable reporting goal. We also find that participants include more causal words and use words that focus more on the future when performance is bad than when performance is good. Debriefing questions that directly ask participants about their
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reporting choices suggest that they are aware of these differences and survey participants believe the most likely explanation for these results is that managers try to provide more information about the future in order to satisfy investors’ demand. Results from a supplemental experiment provide additional support for the idea that, to frame poor performance in a positive light, managers provide causal
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explanations for poor performance, focus more on the future, use more passive voice and fewer personal pronouns, and increase the readability of positive information in their disclosures. The supplemental experiment also suggests that, to the extent that managers view their goals when
reporting bad news to be presenting the results in the “least unfavorable” manner possible, use of more
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negations which decreases readability might be expected. Overall, our results support the idea that
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when reporting bad news, individuals distance themselves from poor performance by using passive voice and fewer first person singular pronouns, provide additional explanation, and focus more on
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future expectations.
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Our study adds to the growing literature investigating the language used in disclosures. Controlling for actual firm performance and other characteristics, recent archival studies use methods
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from computational linguistics to analyze large bodies of text, as suggested by Core (2001). Our study, on the other hand, uses a controlled experiment to provide complementary evidence on managers’ disclosure choices, holding constant other factors that are not of primary interest, while using dependent measures that are comparable to recent archival studies.
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Our use of an experiment allows us to complement prior archival work, while isolating the effects of individual drivers of linguistic characteristics of disclosures. For example, prior literature has argued that bad news disclosures may be less readable, at least in part, due to the inherent difficulty of describing poor performance (Bloomfield, 2008) or the complexity of the operating environment in
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times of poor performance (Guay et al., 2016; Bushee et al., 2018). We hold environmental complexity constant by using identical underlying facts across all conditions in our setting in order to isolate the effects of firm performance and reporting goals on linguistic characteristics. Future work could further
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examine how the complexity of the operating environment affects the language used in disclosures.
This study has some important limitations. First, we use a setting where participants describe hypothetical performance, rather than performance on a real task (e.g., intelligence tasks,
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manufacturing tasks, etc.). This mitigates potential confounds between linguistic choices and participant characteristics, while also presenting participants with a setting that is rich enough to allow them to
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draw on their experiences when describing firm performance. A consequent downside of asking
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participants to describe hypothetical performance is that it potentially reduces their personal involvement in the task and may influence their linguistic choices as well. However, we would expect
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that lower personal involvement is likely to only weaken our results rather than change the directional
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pattern of responses or the resulting inferences. Second, disclosures provided in the real world are influenced by consultation with legal
departments, public-relations professionals, etc. Consequently, our study does not strictly capture the final disclosures that might actually be provided to investors. Different types of disclosures likely vary with respect to the level of third-party input (see, e.g., Dikolli et al., 2015). Future research could also
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layer in additional features that might affect linguistic choices of reporting complexity. Some interesting possibilities for factors that might affect reporting complexity include managers’ experience, managers’ reporting reputations, different incentive structures, legal considerations, or different types of target
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investors.
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REFERENCES ASAY, S. ‘Horizon-Induced Optimism as a Gateway to Earnings Management.’ Forthcoming in Contemporary Accounting Research, 2018.
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ASAY, S., R. LIBBY, and K. RENNEKAMP. ‘Do Features that Associate Management with a Message Magnify Investors’ Reactions to Narrative Disclosures?’ Forthcoming in Accounting, Organizations and Society, 2018.
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BIDDLE, G.C., G. HILARY, and R.S. VERDI. ‘How does Financial Reporting Quality Relate to Investment Efficiency?’ Journal of Accounting and Economics 48 (2009): 112-131.
BLOOMFIELD, R. ‘The ‘Incomplete Revelation Hypothesis’ and Financial Reporting.’ Accounting Horizons 16 (2002): 233-243.
ED
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BLOOMFIELD, R. ‘Discussion of ‘Annual Report Readability, Current Earnings and Earnings Persistence’.’ Journal of Accounting and Economics 45 (2008): 248-252.
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BONSALL, S., A. LEONE, B. MILLER and K. RENNEKAMP. ‘A Plain English Measure of Financial Reporting Readability.’ Journal of Accounting and Economics 63 (2017): 329-357.
AC
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BUSHEE, B., I. GOW, and D. TAYLOR. ‘Linguistic Complexity in Firm Disclosures: Obfuscation or Information?” Journal of Accounting Research 56 (2018): 85-121.
CHAFE, W.L. and J. DANIELEWICZ. 1987. Properties of Written and Spoken Language. In: Horowitz, R., Samuels, S.J. (Eds.) Comprehending Oral and Written Language. Academic Press, San Diego, CA, pp. 83-113.
CLATWORTHY, M., and M. JONES. ‘The Effect of Thematic Structure on the Variability of Annual Report Readability.’ Accounting, Auditing and Accountability Journal 14 (2001): 311-326. 37
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COHN, M.A., M.R. MEHL, and J.W. PENNEBAKER. ‘Linguistic Markers of Psychological Change Surrounding September 11, 2001. Psychological Science 15 (2004): 687-693.
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CORE, J. ‘A Review of the Empirical Disclosure Literature: A Discussion.’ Journal of Accounting and Economics 31 (2001): 441-456.
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COURTIS, J.K. ‘An Investigation into Annual Report Readability and Corporate Risk Return Relationships.’ Accounting and Business Research 16 (1986): 285-294.
DIKOLLI, S., T. KEUSCH, W. MAYEW, and T. STEFFEN. ‘Using Shareholder Letters to Measure CEO Integrity.’ Working paper, 2015.
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DUBAY, W. The Principles of Readability. Costa Mesa, California: Impact Information, 2004.
PT
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FARRELL, A., K. KADOUS, and K. TOWRY. ‘Contracting on Contemporaneous vs. Forward-Looking Measures: An Experimental Investigation.’ Contemporary Accounting Research 25 (2008): 773802.
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GEE, J.P. An Introduction to Discourse Analysis: Theory and Method. London, England: Routledge, 1999.
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GUAY, W., SAMUELS, D., and D. TAYLOR. ‘Guiding Through the Fog: Financial Statement Complexity and Voluntary Disclosure.’ Journal of Accounting and Economics 62 (2016): 234-269.
HYLAND, K. Metadiscourse: Exploring Interaction in Writing. Oxford, England: Continuum, 2005.
JONES, M.J. ‘A Longitudinal Study of the Readability of the Chairman's Narratives in the Corporate Reports of a UK Company.’ Accounting and Business Research 18 (1988): 297-305. 38
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JONES, M.J., and P.A. SHOEMAKER. ‘Accounting Narratives: A Review of Empirical Studies of Content and Readability.’ Journal of Accounting Literature 13 (1994): 142-184.
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KACHELMEIER, S., B. REICHERT, and M. WILLIAMSON. ‘Measuring and Motivating Quantity, Creativity, or Both.’ Journal of Accounting Research 46 (2008): 341-373.
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KACHELMEIER, S., and M. WILLIAMSON. ‘Attracting Creativity: The Initial and Aggregate Effects of Contract Selection on Creativity-Weighted Productivity.’ The Accounting Review 85 (2010): 1669-1691.
KIDA, T. ‘The Impact of Hypothesis-Testing Strategies on Auditors’ Use of Judgment Data.’ Journal of Accounting Research 22 (1984): 332-340.
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KOONCE, L., Z. LEITTER, and B. WHITE. ‘The Effect of a Cautionary Notice on Investors’ Reactions to More and Less Readable Disclosures.’ Working paper, 2016.
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LAWRENCE, A. ‘Individual Investors and Financial Disclosure.’ Journal of Accounting and Economics 56 (2013): 130-147.
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LEHAVY, R., F. LI, and K. MERKLEY. ‘The Effect of Annual Report Readability on Analyst Following and the Properties of Their Earnings Forecasts.’ The Accounting Review 86 (2011): 1087-1115.
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LI, F. ‘Annual Report Readability, Current Earnings, and Earnings Persistence.’ Journal of Accounting and Economics 45 (2008): 221-247.
LI, F. ‘Textual Analysis of Corporate Disclosures: A Survey of the Literature.’ Journal of Accounting Literature 29 (2010): 143-165.
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LIBBY, R., R. BLOOMFIELD, and M. NELSON. ‘Experimental Research in Financial Accounting.’ Accounting, Organizations and Society 27 (2002): 775-810.
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LIBBY, R., and K. RENNEKAMP. ‘Self-Serving Attribution Bias, Overconfidence, and the Issuance of Voluntary Disclosures.’ Journal of Accounting Research 50 (2012): 197-231.
LIBBY, R., and K. TROTMAN. ‘Audit Review as a Control for Biased Recall of Evidence in Decision Making.’ Accounting, Organizations and Society 18 (1993): 559-574.
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LOFTUS, S., and L. TANLU. ‘Because of “Because”: Examining the Use of Causal Language in Relative Performance Feedback.’ Forthcoming in The Accounting Review.
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LOUGHRAN, T., and B. MCDONALD. ‘Measuring Readability in Financial Disclosures.’ Journal of Finance 69 (2014a): 1643-1671.
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LOUGHRAN, T., and B. MCDONALD. ‘Regulation and Financial Disclosure: The Impact of Plain English.’ Journal of Regulatory Economics 45 (2014b): 94-113.
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MATSUMOTO, D., M. PRONK, and E. ROELOFSEN. ‘What Makes Conference Calls Useful? The Information Content of Managers’ Presentations and Analysts’ Discussion Sessions.’ The Accounting Review 86 (2011): 1383-1414.
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MERKLEY, K. "Narrative Disclosure and Earnings Performance: Evidence from R&D Disclosures." The Accounting Review 89 (2014): 725-757.
MILLER, B. ‘The Effects of Reporting Complexity on Small and Large Investor Trading.’ The Accounting Review 85 (2010): 2107-2143.
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PENNEBAKER, J.W. The Secret Life of Pronouns: What our words say about us. New York, New York: Bloomsbury, 2011.
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PENNEBAKER, J.W., M.R. MEHL, and K.G. NIEDERHOFFER. ‘Psychological Aspects of Natural Language Use: Our Words, Our Selves.’ Annual Review of Psychology 54 (2003): 547-577.
REILLY, J., A. ZAMORA, and R. MCGIVERN. ‘Acquiring perspective in English: the development of stance.’ Journal of Pragmatics 37 (2005): 185-208.
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RENNEKAMP, K. ‘Processing Fluency and Investors’ Reactions to Disclosure Readability.’ Journal of Accounting Research, 50 (2012): 1319-1354.
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RUTHERFORD, B.A. ‘Obfuscation, Textual Complexity, and the Role of Regulated Narrative Accounting Disclosure in Corporate Governance.’ Journal of Management and Governance 7 (2003): 187210.
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Securities and Exchange Commission. (1998). ‘A Plain English Handbook: How to Create Clear SEC Disclosure.’ SEC Office of Investor Education and Assistance. Available at: http://www.sec.gov/pdf/handbook.pdf.
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SUBRAMANIAN, R., R. INSLEY and R. BLACKWELL. ‘Performance and Readability: A Comparison of Annual Reports of Profitable and Unprofitable Corporations.’ The Journal of Business Communication 30 (1993): 49-61.
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TAN, H-T., E. WANG, and B. ZHOU. ‘How does Readability Influence Investors’ Judgments? Consistency of Benchmark Performance Matters.’ The Accounting Review 90 (2015): 371-393.
TVERSKY, A., and D. KAHNEMAN. ‘Availability: A Heuristic for Judging Frequency and Probability.’ Cognitive Psychology 5 (1973): 207-232.
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YOU, H., and X. ZHANG. ‘Financial Reporting Complexity and Investor Underreaction to 10-K Information.’ Review of Accounting Studies 14 (2009): 559-586.
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Figure 1. Screen Shot Showing the Four Ambiguous Facts Provided to Participants for the Preparation of their Report
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This figure depicts a screen shot from our experiment, in which 205 experienced managers assume the role of director of investor relations and explain the performance of a division in a hypothetical firm. Participants are randomly assigned to one of four cells in a 2x2 manipulation of whether (1) the division had good or bad performance for the quarter and (2) the reporting goal is either to be unbiased or to elicit as favorable a reaction as possible. In all conditions, participants receive the same four facts to use in drafting their report (as shown above). These four facts were pretested with a different group of participants and were selected because they were not considered to be unambiguously positive or negative. This design choice was meant to ensure that participants in the study could plausibly use any of the four facts to explain either good or bad performance in the division.
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Figure 2. Primary Experiment Results by Condition for Linguistic Measures Used to Test our Hypotheses
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Panel A. Readability
Panel B. Personal Pronouns
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Panel C. Passive Voice
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Figure 2. Results by Condition for Linguistic Measures Used to Test our Hypotheses, continued.
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Panel D. Causal Explanation Words
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Panel E. Focus on the Future
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This figure presents results graphically for our five dependent variables of interest. In our experiment, 205 experienced managers assume the role of director of investor relations and explain the performance of a division in a hypothetical firm. Participants are randomly assigned to one of four cells in a 2x2 manipulation of whether (1) the division had good or bad performance for the quarter and (2) the reporting goal is either to be unbiased or to elicit as favorable a reaction as possible. In all conditions, participants draft an open-ended report, drawing on their prior experience. We then use textual analysis to analyze these reports for the linguistic characteristics of interest. Panel A presents readability scores from these reports, by condition. Panel B presents the extent to which the language in the reports focuses on the future vs. the past, by condition. Panel C presents the extent to which the reports include causal language, by condition. Panel D presents the extent to which the reports use more personal pronouns, by condition. Panel E presents the extent to which the reports use passive rather than active voice, by condition.
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Table 1. Primary Experiment Descriptive Statistics and Analysis of Variance – Readability Measure
Panel A. Descriptive Statistics - Mean and (Standard Deviation), by condition
Unbiased
Favorable
Overall
Good
10.74
16.52
13.47
(10.09)
(11.92)
(11.31)
n = 56
n = 50
n = 106
11.71
10.48
11.10
(11.64)
(12.26)
(11.91)
n = 50
n = 49
n = 99
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Bad
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Performance
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Reporting Goal
11.20
13.53
12.32
(10.81)
(12.40)
(11.64)
n = 106
n = 99
n = 205
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Overall
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Panel B. Results of Analysis of Variance (ANOVA) – Test of H1
Source
S.S.
d.f.
M.S.
F-statistic
p-value
Performance
328.45
1
328.45
2.50
0.058†
Reporting Goal
264.55
1
264.55
2.01
0.158
Performance x Goal
625.40
1
625.40
4.76
0.015†
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Table 1, Panel A presents descriptive statistics on the Readability measure in our experiment, in which 205 experienced managers draft a report explaining the performance of a division in a hypothetical firm. Panel B presents ANOVA results investigating whether firm performance (good vs. bad) and reporting goal (unbiased vs. favorable) affect the readability of the report. One-tailed equivalent, given directional predictions.
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†
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Table 2. Primary Experiment Descriptive Statistics and Analysis of Variance – Participant Responses to Questions about the Readability of their Reports
Panel A. Descriptive Statistics – Mean and (Standard Deviation), by condition
How easy or difficult would you say it is to read your report?
Bad Performance & Unbiased Reporting Goal
Bad Performance & Favorable Reporting Goal
3.22
3.04
3.39
(1.92)
(1.92)
(1.78)
(1.62)
n = 56
n = 50
n = 50
n = 49
3.41
3.50
3.50
3.73
(1.94)
(2.01)
(2.05)
(2.14)
n = 56
n = 50
n = 50
n = 49
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1: “Very Easy” 10: “Very Difficult”
3.43
Good Performance & Favorable Reporting Goal
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Measure (and scale endpoints)
Good Performance & Unbiased Reporting Goal
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Condition
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To what extent were you motivated to make your report easier or more difficult for investors to understand?
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1: “I was motivated to make my report easier to understand” 10: “I was motivated to make my report more difficult to understand”
Panel B. Results of Analysis of Variance (ANOVA)
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Measure: Easy vs. difficult to read your report S.S.
d.f.
M.S.
F-statistic
p-value
Performance
0.62
1
0.62
0.19
0.665
Goal
0.24
1
0.24
0.07
0.785
Performance x Goal
3.95
1
3.95
1.19
0.276
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Source
Measure: Motivated to make your report easier or more difficult to understand S.S.
d.f.
M.S.
Performance
1.34
1
1.34
Goal
1.34
Performance x Goal
0.27
F-statistic
p-value
0.32
0.570
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Source
1
1.34
0.32
0.570
1
0.27
0.07
0.799
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Table 2, Panel A presents descriptive statistics for follow-up questions in our experiment related to disclosure readability, in which 205 experienced managers draft a report explaining the performance of a division in a hypothetical firm. Panel B presents ANOVA results investigating whether firm performance (good vs. bad) and reporting goal (unbiased vs. favorable) affect participants’ responses to these follow-up questions about their report.
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Table 3. Primary Experiment Descriptive Statistics and Analysis of Variance – Other Linguistic Characteristics
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Panel A. Descriptive Statistics – Mean and (Standard Deviation), by condition*
Measure
Condition Good Performance & Unbiased Reporting 51
Good Performance & Favorable Reporting
Bad Performance & Unbiased Reporting
Bad Performance & Favorable Reporting
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Causal Explanation Words
Goal
Goal
2.48
3.62
2.46
2.98
(2.59)
(3.50)
(3.02)
(3.12)
n = 56
n = 50
n = 50
n = 49
1.48
1.06
(1.10)
(0.93)
n = 56
n = 50
1.18
1.88
(1.06)
(1.49)
n = 50
n = 49
4.38
4.90
5.33
(2.52)
(3.62)
(3.60)
n = 50
n = 50
n = 49
0.22
0.38
0.32
(0.28)
(0.23)
(0.224)
(0.23)
n = 55*
n = 50
n = 49*
n = 49
4.09 (2.63)
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n = 56
0.20
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Focus on the Future
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Passive Voice
Goal
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Personal Pronouns
Goal
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Panel B. Results of Analysis of Variance (ANOVA)
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Measure: Personal Pronouns (Test of H2) Source
S.S.
d.f.
M.S.
F-statistic
p-value
Performance
5.62
1
5.62
0.60
0.220†
Goal
35.08
1
35.08
3.75
0.054
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1
4.89
0.52
0.235†
S.S.
d.f.
M.S.
F-statistic
p-value
Performance
3.39
1
3.39
2.51
<0.057†
Goal
0.97
1
0.97
Performance x Goal
16.02
1
16.02
Performance x Goal
4.89
0.72
0.398
11.86
<0.001†
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Source
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Measure: Passive Voice (Test of H3)
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Table 3, Panel B (continued)
Measure: Causal Explanation Words (Test of H4) S.S.
d.f.
M.S.
F-statistic
p-value
Performance
39.48
1
39.48
7.60
0.003†
Goal
6.58
1
6.58
Performance x Goal
0.24
1
0.24
0.262
0.27
0.416†
S.S.
d.f.
M.S.
F-statistic
p-value
Performance
1.02
1
1.02
16.90
<0.001†
Goal
0.01
1
0.01
0.23
0.629
Performance x Goal
0.09
1
0.09
1.56
0.894†
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Source
1.27
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Measure: Focus on the Future (Test of H5)
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Source
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Table 3, Panel A presents descriptive statistics for other linguistic characteristics used by participants preparing reports in our experiment, in which 205 experienced managers draft a report explaining the performance of a division in a hypothetical firm. Panel B presents ANOVA results investigating whether firm performance (good vs. bad) and reporting goal (unbiased vs. favorable) affect the use of personal pronouns, passive voice, causal words, and future-tense words. Two observations were removed from these analyses because they had zero values in the denominator for the calculation of the measure (future words count/(past words count + future words count)). One-tailed equivalent, given directional predictions.
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Table 4. Primary Experiment Descriptive Statistics and Analysis of Variance – Participant Responses to Questions about Other Linguistic Characteristics of their Reports
Panel A. Descriptive Statistics – Mean and (Standard Deviation), by condition
Measure (and scale endpoints)
Good Performance & Unbiased Reporting Goal
Good Performance & Favorable Reporting Goal
Bad Performance & Unbiased Reporting Goal
Bad Performance & Favorable Reporting Goal
3.71
4.90
3.42
4.12
(4.65)
(6.52)
(4.05)
(4.64)
n = 56
n = 50
n = 50
n = 49
5.34
5.00
5.06
5.39
(2.65)
(2.52)
(2.60)
(2.64)
n = 56
n = 50
n = 50
n = 49
5.55
5.96
5.90
7.31
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Please provide your best estimate (in whole numbers) of the number of first person pronouns (e.g., “I”, “We”, “Our”) contained in your report.
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Condition
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To what extent did you use active or passive voice in your report?
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1: “My report primarily used active voice” 10: “My report primarily used passive voice”
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To what extent did your report focus on reporting “just the facts” of the division’s performance vs. explaining the underlying causes for the division’s performance?
(2.62)
(2.33)
(2.43)
(1.72)
n = 56
n = 50
n = 50
n = 49
4.34
3.72
5.44
6.18
(2.71)
(2.32)
(2.62)
(2.05)
n = 56
n = 50
n = 50
n = 49
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To what extent did your report focus on past performance of the division vs. expectations for future performance?
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Panel B. Results of Analysis of Variance (ANOVA)
Measure: Use of Personal Pronouns in the Report S.S.
d.f.
M.S.
F-statistic
p-value
Performance
14.68
1
14.68
0.58
0.448
Goal
45.55
1
45.55
Performance x Goal
2.98
1
2.98
0.182
0.12
0.732
S.S.
d.f.
M.S.
F-statistic
p-value
Performance
0.15
1
0.15
0.02
0.882
Goal
0.00
1
0.00
0.00
0.987
Performance x Goal
5.69
1
5.69
0.84
0.361
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Source
1.79
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Measure: Active vs. Passive Voice
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Measure: Just the Facts vs. Explaining Underlying Causes
Performance
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Goal
Performance x Goal
AC
S.S.
d.f.
M.S.
F-statistic
p-value
36.60
1
36.60
6.85
0.010
41.98
1
41.98
7.85
0.006
12.77
1
12.77
2.39
0.124
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Source
Measure: Focus on Past Performance vs. Expectations for Future Performance Source
Performance Goal
S.S.
d.f.
M.S.
F-statistic
p-value
162.33
1
162.33
27.05
<0.001
0.20
1
0.20
0.03
0.856
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Performance x Goal
23.74
1
23.74
3.95
0.048
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Table 4, Panel A presents descriptive statistics for several follow-up questions in our experiment related to participants’ perceptions of the linguistic choices they made in their reports. In our experiment, 205 experienced managers draft a report explaining the performance of a division in a hypothetical firm. Panel B presents ANOVA results investigating whether firm performance (good vs. bad) and reporting goal (unbiased vs. favorable) affect participants’ responses to these follow-up questions about their report.
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Table 5. Supplemental Experiment Comparisons in Linguistic Characteristics of Disclosures Prepared by Managers between the Most Favorable and Least Unfavorable Instructions Conditions
Panel A. Supplemental Experiment Results Using Measures from our Main Experiment
Measure
"Least Unfavorable" Condition
p-value
14.64
0.091
3.48
0.461
1.29
1.06
0.400
4.24
5.05
0.194
0.37
0.36
0.812
18.72
First Person Personal Pronouns (H2)
4.07
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Readability (H1)
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Passive Voice (H3) Causal Explanations (H4)
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Future Focus (H5)
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Panel B. Supplemental Experiment Results for Individual Component Measures of Readability
"Least Unfavorable" Condition
p-value
0.32
0.47
0.325
Passive Voice
1.29
1.06
0.400
Superfluous Words
0.87
0.94
0.761
Negations
0.16
0.72
0.002
Complex Synonyms
2.45
2.81
0.278
First and Third Person Personal Pronouns
4.89
4.31
0.493
Number of Words
86.05
85.03
0.878
Measure
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Hidden Verbs
PT
"Most Favorable" Condition
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Average Words/Sentence
21.55
22.02
0.709
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Table 5 presents results of our supplemental 1x2 experiment, in which 74 experienced participants are provided with four facts and are asked to draft a report explain the poor performance of a hypothetical firm. Participants are randomly assigned to either receive instructions to present the firm in as favorable a light as possible (“most favorable” condition) or the least unfavorable light as possible (“least unfavorable” condition). Panel A summarizes results, by condition, for the five measures used in our main experiment to test our hypotheses. Panel B summarizes results, by condition, for the components that make up our readability measure. All p-values are twotailed given our lack of directional predictions. Higher numbers indicate a disclosure is more readable, or includes more words related to the future relative to the past, more causal explanation words, more personal pronouns, and more passive voice.
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Table 6. Survey Descriptive Statistics and Pairwise Comparisons –Participant Ratings of Potential Explanations for Readability, Future Focus, and Causal Words Results
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Panel A. Readability
Rating Mean
Explanation
(Median)
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Managers intentionally write less readable reports when performance is bad with the specific intention of hiding poor performance.
59.94
B
(67)
76.41
Bad news is inherently more difficult to discuss than good news, which results in less readable language in reports when news is bad and more readable language in reports when news is good.
63.08
Managers intentionally try to provide more information when performance is bad, in order to satisfy investors’ demand, which results in less readable language in reports.
57.39
Managers unintentionally change their language when describing performance, and this change in language results in less readable language in reports when performance is bad than when performance is good.
55.95
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Managers intentionally write more readable reports when performance is good with the specific intention of highlighting positive performance.
A (80)
B (70)
B (64)
B (62)
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Pairwise Comparisons*
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Panel B. Causal Words
Rating Mean Explanation
(Median)
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Pairwise Comparisons*
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Managers intentionally provide more causal explanation when performance is bad with the specific intention of hiding poor performance.
54.37
Managers intentionally provide less causal explanation when performance is good with the specific intention of avoiding scrutiny about the reasons for positive performance.
47.15
Managers intentionally try to provide more information about the reasons for performance when performance is bad, in order to satisfy investors’ demand, which results in reports that include more causal language.
63.56
B (56)
B
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(50)
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CE
PT
ED
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Managers unintentionally change their language when describing performance, and this change in language corresponds with the use of fewer causal words when news is good and more causal words when news is bad.
62
A
(70)
51.02
B
(50)
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Panel C. Future Focus
Rating Mean (Median)
Pairwise Comparisons*
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Explanation
65.15
Managers intentionally shift their discussion to the past when performance is good with the specific intention of highlighting positive performance.
70.86
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Managers intentionally shift their discussion to the future when performance is bad with the specific intention of hiding poor performance.
Managers intentionally try to provide more information about how performance is likely to improve in the future when performance is bad, in order to satisfy investors’ demand, which results in reports that use language that focuses more on the future.
ED
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Managers unintentionally change their language when describing performance, and this change in language results in more focus on the future when performance is bad than when performance is good.
B
(71)
B
(76)
79.45 A (81) 51.65 C (50)
AC
CE
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Table 6 presents descriptive statistics and pairwise comparisons for survey participants’ responses to questions related to the pattern of results observed in our experiment. In the survey, 144 experienced managers are presented with a summary of three of the differences observed in our experiment (readability, focus on the future, and causal words) and asked to rate, based on their own past experience, the extent to which several factors may have contributed to the characteristics of the performance reports. For readability, survey participants are informed that the reports were less readable when they were describing poor performance than when they were describing good performance. Survey participants rate five potential explanations for this finding on a 101-point scale (endpoints: 0 = “very unlikely” to 100 = “very likely” to explain differences in readability). For causal words, survey participants are informed that the reports included more causal language when firm performance was bad than when firm performance was good. Survey participants rate four potential explanations for this finding on a 101-point scale (endpoints: 0 = “very likely” to 100 = “very unlikely” to explain differences in causal language). For focus on the future, survey participants are informed that the reports were more focused on the future when they were describing bad performance rather than good performance. Survey participants rate four potential explanations for this finding on a 101-point scale (endpoints: 0 = “very unlikely” to 100 = “very likely” to explain differences in future focus).
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*
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ED
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All pairwise comparisons are made using Tukey’s Honest Significant Difference test, with the Tukey-Kramer adjustment for multiple comparisons. Explanations not connected by the same letter are significantly different (p ≤ 0.050, two-tailed).
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Firm Performance, Reporting Goals, and Language Choices in Narrative Disclosures H. Scott Asay , Robert Libby , Kristina Rennekamp PII: DOI: Reference:
S0165-4101(18)30018-1 10.1016/j.jacceco.2018.02.002 JAE 1184
To appear in:
Journal of Accounting and Economics
Received date: Revised date: Accepted date:
7 November 2016 15 February 2018 26 February 2018
Please cite this article as: H. Scott Asay , Robert Libby , Kristina Rennekamp , Firm Performance, Reporting Goals, and Language Choices in Narrative Disclosures , Journal of Accounting and Economics (2018), doi: 10.1016/j.jacceco.2018.02.002
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Firm Performance, Reporting Goals, and Language Choices in Narrative Disclosures
H. Scott Asay
[email protected]
Robert Libby
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Cornell University
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The University of Iowa
[email protected]
Kristina Rennekamp†
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Cornell University
February 2018
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[email protected]
We thank Randy Beatty, Rob Bloomfield, Sarah Bonner, Doug DeJong, Ken Merkley, Tracie Majors, Bill Mayew, Greg Miller, Terence Ng, Mark Nelson, Hun-Tong Tan, participants at the 2016 Cornell Summer Accounting Camp, and workshop participants at the University of Bern, University of Southern California and Nanyang Technological University for comments on earlier versions of this paper. We also thank Mike Durney and Patrick Witz for expert research assistance. †Corresponding author. 401P Sage Hall, Cornell University, 14853. Email: [email protected]
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1. Introduction Prior work suggests that the linguistic characteristics of narrative disclosures vary with firm performance. For example, when performance is poor, earnings announcements, 10-Ks, and other narrative disclosures tend to be less readable (see, e.g., Jones and Shoemaker (1994) and Li (2010) for
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discussions), include additional explanations for performance (Merkley, 2014; Guay, Samuels, and
Taylor, 2016; Bushee, Gow, and Taylor, 2018), and use more future-oriented words (Li, 2008;
Matsumoto, Pronk, and Roelofsen, 2011). Further, it has been suggested that managers may choose to use language that highlights their contribution to good performance (e.g., active voice, first-person
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pronouns, etc.) and downplays their contribution to poor performance (e.g., passive voice, third-person pronouns, etc.).1 Implicit in these studies is the idea that managers’ reporting goals shape these linguistic choices.
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We provide more-direct evidence on how reporting goals influence managers’ language choices by using an experiment that independently varies both the sign of firm performance and the strength of
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self-enhancement motives, while holding constant the environmental complexity that prior literature has suggested may also influence linguistic characteristics of disclosures (Merkley, 2014; Guay et al.,
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2016; Bushee et al., 2018). Stronger self-enhancement motives induce a reporting goal to make the firm
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appear more favorable. By manipulating whether self-enhancement motives are relatively weak or strong as well as the sign of the news, we can directly test whether stronger self-enhancement motives
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lead to greater or smaller differences in the linguistic characteristics of good and bad news disclosures. Further, we can determine whether these changes result from how managers report good news, bad news, or both. For example, managers with a stronger self-enhancement motive might decrease the
1
For example, see Chafe and Danielewicz (1987); Hyland (2005); Reilly, Zamora, and McGivern (2005); Asay, Libby, and Rennekamp (2018).
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readability of bad news in an attempt to obfuscate poor performance (Bloomfield, 2002; Li, 2008) and increase the readability of good news in an attempt to present good news more clearly. Similarly, managers with a stronger self-enhancement motive might make other language choices in order to communicate additional information when reporting poor performance (e.g., providing a more detailed
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explanation for past performance and discussion of future plans). Thus, our study allows us to gain additional insight into how firm performance and reporting goals affect disclosure readability and other linguistic features. We also provide some evidence on the intentionality of, and motives for, these
linguistic choices, which is of interest given the mixed evidence in prior work.2 We rely on evidence from
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our primary experiment, a supplemental experiment, and an additional survey.
In our primary experiment, experienced managers assume they are in charge of investor relations for a hypothetical firm and that they have been asked to draft a report explaining its
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performance to investors. In a 2 x 2 between-subjects design, we manipulate (1) firm performance in the most recent quarter (good or bad) and (2) participants’ reporting goal (unbiased or favorable).3 We
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then examine the effects of these manipulations on disclosure readability and other linguistic features of the disclosure (use of first person pronouns and passive voice, causal explanations, and focus on the
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future). We also directly ask participants about the reports they have written to provide evidence on the
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intentionality of their linguistic choices. First, consistent with prior archival evidence, we find that bad news reports are less readable than good news reports. This effect is driven by an increase in the
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readability of good news reports when participants have a favorable reporting goal, rather than a
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We discuss some of this mixed evidence further in Section 2.1.
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In both reporting goal conditions, all participants are instructed to report the division’s performance accurately. However, in the favorable reporting goal condition, we introduce a stronger self-enhancement motive by layering on the additional explicit goal of portraying the performance in a manner that is as favorable as possible.
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decrease in the readability of bad news reports. We also find that neither the valence of performance nor the reporting goal affects participants’ perceptions of the readability of their own reports, or their ratings of the extent to which they were motivated to make the report easier or more difficult to read. Second, we find that participants use more passive voice and fewer first person singular pronouns (e.g.,
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“I”, “me”) when news is bad – techniques that distance a manager from the information being
conveyed. Further, the increased use of passive voice is particularly true when participants have a
favorable reporting goal. Third, we find that participants use more words that reflect causal thinking (e.g., “because”, “effect”, “therefore”) and use more future tense relative to past tense when news is
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bad than when news is good. When directly asked, participants accurately report that they increase the use of causal and future words when news is bad, although they also believe that the use of these words is even greater when a favorable reporting goal is present.
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In our supplemental experiment, we examine the robustness of our results by testing how the linguistic features of bad news disclosures are influenced by an alternative operationalization of the self-
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enhancement motive – portraying the performance in the least unfavorable manner as possible. This alternative reporting goal reduces the readability of disclosures when performance is poor, as a result of
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increased use of negations (e.g., saying a firm is “not doing well” rather than “doing poorly”). However,
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we find that this alternative reporting goal does not affect participants’ perceptions of the readability of their own reports. In combination, the results of our supplemental experiment suggest that although
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managers appear to be unaware that they are doing so, they provide disclosures that are less readable (via increased use of negations) when performance is poor and they have a goal to present the firm in
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the “least unfavorable” light possible.4 Results also provide additional support for the idea that, in order to frame poor performance in a positive light, managers tend to focus more on the future, provide causal explanations for poor performance, and use more passive voice and fewer personal pronouns. Finally, in an additional survey of managers, we summarize the characteristics of the
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performance reports prepared in our primary experiment and ask participants to provide their opinions on factors that drove the characteristics of the performance reports. Survey participants primarily
believe that (1) managers intentionally write more readable reports when performance is good with the
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objective of highlighting positive performance, and (2) managers intentionally provide more causal explanations for past performance and more information about future plans when performance is bad in order to satisfy investors’ demand. In contrast, the survey provides much more limited evidence that participants believe managers intentionally write less readable reports when performance is bad with
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the objective of hiding poor performance. Moreover, when participants were asked to assume they were a manager that had to describe some poor performance in their firm, a majority of participants
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indicated that they would choose to issue a more readable disclosure rather than a less readable disclosure.5 Accordingly, our survey provides additional evidence suggesting that managers attempt to
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write more readable reports when disclosing good performance, provide additional useful information
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when disclosing poor performance, and that differences in readability between good news and bad
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news disclosures are unlikely driven by intentional obfuscation of poor performance.
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It is also possible that participants did not want to admit to having done so, but this possibility is unlikely given that our manipulations were done between participants. The combination of results discussed in Section 4.2 of the paper and the additional survey results further suggest this is an unlikely alternative explanation for our findings. 5
The disclosure options presented to participants in the survey were not labeled as more or less readable. Instead, participants were just shown two possible disclosures (which varied in readability), and indicated which they would choose to provide.
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Our study capitalizes on the comparative advantage of experiments (Libby, Bloomfield, and Nelson, 2002) and complements prior work by testing hypotheses that would be difficult to test using archival data. For example, examining how self-enhancement motives affect the linguistic characteristics of disclosures would be difficult in real-world disclosure settings because managers generally have
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strong motives to present the firm favorably (i.e., it would be hard to find situations where firms have weak self-enhancement motives for comparison). Also, by holding information content constant in our experiments, we control for underlying differences in firm circumstances or environmental complexity which are likely to be confounded with firm performance and reporting goals in a natural setting. This
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allows us to complement prior archival work and disentangle the effects of firm performance and
reporting goals from the effects of environmental complexity, all of which are likely to be confounded in a natural setting. Our experiments also eliminate potential effects of other parties (e.g., legal counsel, etc.) on the attributes of the narratives, which may again explain some of the differences documented in
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archival studies. This allows us to focus on the manager’s contributions to the narratives independent of
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these filters. In the experiments, we ask participants to prepare open-ended reports rather than to just respond to scaled questions. This is more analogous to how disclosures would be prepared in the real
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world, and allows us to use textual analysis measures similar to those used in archival studies.
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The remainder of the paper is organized as follows. We provide background and develop hypotheses in Section 2. We discuss the experimental method we employ for our primary experiment in
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Section 3 and discuss its results in Section 4. Section 5 describes our supplemental experiment and its results. Section 6 describes results of our independent survey of experienced managers. We summarize and conclude in Section 7.
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2. Background and Development of Hypotheses At its core, language is a social construct. The vast sociolinguistics literature describes how individuals’ linguistic choices reveal their social-psychological processes and vary with personal and environmental circumstances (Gee, 1999; Pennebaker, Mehl, and Niederhoffer, 2003). In a financial
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reporting context, prior research suggests that the linguistic characteristics of narrative disclosures are likely to vary with firm performance (for reviews, see Jones and Shoemaker, 1994; Li, 2010). In this section, we consider how managers’ reporting goals combine with firm performance to influence
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disclosure readability and other linguistic characteristics of narrative disclosures. 2.1 Disclosure Readability
Prior literature has shown that disclosures are less readable when firm performance is poor. Using a sample of 60 U.S. firms, Subramanian, Insley, and Blackwell (1993) examine how readability of
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the Chairman’s Letter varies with firm performance. They find that readability is significantly higher for
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the firms where performance improves over the prior period rather than deteriorates. However, other pre-2003 studies do not find evidence that readability varies with performance (e.g., Courtis, 1986;
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Jones, 1988; and Clatworthy and Jones, 2001). Rutherford (2003) argues that early (pre-2003) readability studies should be interpreted cautiously because they rely on “small samples of tests, testing of limited
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amounts of text, and the application of weak tests of association.” Li (2008) provides the first large-
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sample evidence on the issue and finds that firms with higher earnings have more readable annual reports. Further, when performance is positive, firms with more readable annual reports have more persistent positive earnings. Much of the accounting literature assumes that less-readable bad news disclosures result from a conscious attempt by management to obfuscate bad news (for reviews, see Jones and Shoemaker, 1994; 6
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and Li, 2008). Recent research in accounting supports the idea that intentional obfuscation of bad news may be a useful strategy for managers and finds evidence consistent with the prediction that investors react less strongly to less readable disclosures.6 However, archival studies generally cannot differentiate between strategies that involve obfuscating bad news or clarifying good news, which would produce a
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similar pattern of results.
In addition, it is possible that bad news leads managers to make other linguistic choices that affect disclosure readability even in the absence of intentional obfuscation (Bloomfield, 2008). For
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example, Bushee et al. (2018) find that, while there is some evidence of intentional obfuscation in
conference calls, there is also evidence that managers’ linguistic complexity is driven by providing more discussion of firm information, and that this portion of linguistic complexity reduces information asymmetry. Guay et al. (2016) find that financial statement complexity is strongly associated with
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additional voluntary disclosure. They also find that firms that are affected by new accounting standards also respond with increases in voluntary disclosures. This again supports the idea that firms respond to
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difficult circumstances with additional disclosures which reduce information asymmetry.7 Combined, the literature provides evidence that bad news disclosures are likely to have different linguistic
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performance.
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characteristics than good news disclosures even when managers do not try to obfuscate poor
6
Recent examples include You and Zhang (2009); Miller (2010); Rennekamp (2012); Lawrence (2013); Tan, Wang and Zhou (2015); and Koonce, Leitter, and White (2016). 7
This literature also suggests that bad news disclosures can be less readable than good news disclosures because the business environment related to poor performance is inherently more complex (see, e.g., Bloomfield 2008; Guay et al. 2016; Bushee et al. 2018). As we discuss in Section 3.3 and Section 7, we design our experiment to hold constant the complexity of the underlying causes of good vs. poor performance. As a consequence, we cannot assess the influence of this factor.
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Whether managers are intentionally issuing less readable disclosures when performance is poor, attempting to provide more information to explain poor performance and reduce information asymmetry, and/or attempting to clarify the meaning of good news, disclosures of bad performance will be less readable than disclosures of good performance. Also, if this behavior is driven by self-
enhancement motive. Our first hypothesis is therefore:
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enhancement motives, the difference in readability will be larger when managers have a stronger self-
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H1a: Managers will prepare less readable disclosures of bad performance than of good performance.
H1b: The difference between the readability of disclosures of good and bad performance will be greater when managers have a stronger self-enhancement motive. Our first hypothesis predicts that differences in readability between good and bad news
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disclosures will be larger as self-enhancement motives get stronger, but we do not make ex ante predictions about the specific pattern of responses to a shift in the strength of self-enhancement
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motives. However, our tests allow us to examine whether managers respond to a stronger selfenhancement motive by decreasing the readability of bad news disclosures and/or increasing the
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readability of good news disclosures. We also do not make ex ante predictions as to the intentionality of
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managers’ disclosure readability decisions, but we do ask participants debriefing questions to better understand intentionality. Our survey of experienced managers provides further evidence of both the
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intentionality of, and motives for, certain linguistic choices. 2.2 Linguistic Characteristics and Managers’ Association with the Message We next consider two specific language choices that are related to disclosure readability and may also be influenced by firm performance and managers’ reporting goals – the use of first person 8
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pronouns and the use of active versus passive voice. Both of these characteristics capture the extent to which management associates themselves or distances themselves from the information in the disclosure.8 Prior work in psychology finds that individuals use fewer first person singular pronouns (e.g., “I”, “me”) when they feel more psychologically distant from the target being described (Cohn, Mehl, and
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Pennebaker, 2004).9 Similarly, work on pragmatics and discourse argues that the avoidance of personal pronouns (Reilly et al., 2005), and first person pronouns in particular (Hyland, 2005), conveys less
involvement with a message. This suggests that managers may use fewer first person pronouns in their disclosures when news is bad than when news is good, given that it may be an effective method to
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distance themselves from the poor performance being described (Asay, Libby, and Rennekamp, 2018). Likewise, the use of passive voice rather than active voice can also distance an individual from the information being conveyed (Chafe and Danielewicz, 1987; Reilly et al., 2005). For example, consider
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the sentence, “the Company increased sales this quarter.” The use of active voice in the sentence highlights the company’s role in increasing sales. Alternatively, the sentence could be constructed using
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the passive voice as, “the Company’s sales increased this quarter.” In the sentence using passive voice, the agent (i.e., the Company) is de-emphasized. Thus, the use of passive voice in disclosures can
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distance the firm from the actions or outcomes being described. In addition, we expect the use of first
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person pronouns and passive voice to interact with self-enhancement motives, given that managers
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In Section 3.4.5 we discuss how our measures of first person pronouns and passive voice relate to our broader measure of disclosure readability. 9
Although Cohn et al. (2004) specifically focus on the reduction in first person singular words (e.g., “I”, “me”, “mine”) as a distancing device, we also include first person plural words (e.g., “we”, “us”, “our”) in our analyses, given that managers are speaking on behalf of a group of individuals when discussing firm performance. In Section 4 where we discuss our results, our primary analyses are based on all first person pronouns, but we also separately consider the effects of firm performance and reporting goals on the use of first person singular and first person plural pronouns.
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with stronger self-enhancement motives should be even more interested in distancing themselves from poor performance and associating themselves with good performance. Our second and third hypotheses are therefore:
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H2a: Managers will prepare disclosures that include fewer first person pronouns when performance is bad than when performance is good.
H2b: The difference in the use of first person pronouns between disclosures of good and bad performance will be greater when managers have a stronger self-enhancement motive.
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H3a: Managers will prepare disclosures that include more passive voice when performance is bad than when performance is good.
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H3b: The difference in the use of passive voice between disclosures of good and bad performance will be greater when managers have a stronger self-enhancement motive. 2.3 Causal Explanations for Performance and Focus on the Future
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Finally, we consider two additional disclosure characteristics – the provision of causal explanations for performance and a focus on the future – that may result in linguistic differences
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depending on firm performance and managers’ reporting goals.
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2.3.1 Causal Explanations
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Prior literature argues that investors demand more explanation when performance is poor (Bloomfield, 2008; Bushee et al., 2018). Further, managers appear to understand this demand and respond with more informative disclosures when performance is poor (Merkley, 2014). Stronger selfenhancement motives should further increase the provision of causal explanations when performance is poor. Precise causal explanations describe the contributors to poor performance and isolate them to a 10
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specific set of circumstances. By highlighting causal explanations for poor performance, managers are better able to reassure investors that poor performance is not ongoing and that future performance has the potential to improve.10 Our fourth hypothesis is therefore:
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H4a: Managers will prepare disclosures that include more causal language when performance is bad than when performance is good.
H4b: The difference in the use of causal language between disclosures of good and bad performance will be greater when managers have a stronger self-enhancement motive.
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2.3.2 Focus on the Future
Prior archival work shows that firms use more future-oriented words in both their 10-K’s (Li, 2008) and in conference calls (Matsumoto, Pronk, and Roelofsen, 2011) when firm performance is poor. Our study complements this prior work by holding constant everything except the firm’s economic
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performance, in order to rule out that results may be driven by other firm characteristics. In addition,
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we expect the association between poor performance and increased use of future-oriented words to be stronger as self-enhancement motives increase, as discussion of the future gives management the
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opportunity to highlight opportunities for improvement. Note that our prediction could be driven by two effects that are not mutually exclusive. Managers may opportunistically shift discussion to the
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future to downplay negative past performance or to provide useful information on how performance
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will be improved.11 Our final hypothesis is that:
10
Causal language not only has the potential to reassure investors, but has also been shown to change employee behavior and performance. In a controlled experimental setting, Loftus and Tanlu (2017) show that the inclusion of causal language in performance feedback leads to improved performance in a subsequent task, particularly when the initial feedback related to relatively poor performance. 11
As with H1, we do not make ex ante predictions about the intentionality of managers’ choices for our remaining hypotheses, but we do ask participants directly about their disclosure decisions in order to shed light on
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H5a: Managers will prepare disclosures that focus more on the future relative to the past when performance is bad than when performance is good.
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H5b: The difference in relative focus on the future versus the past between disclosures of good and bad performance will be greater when managers have a stronger self-enhancement motive.
3. Primary Experiment: Method 3.1 Participants
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Participants in our primary experiment are 205 experienced managers.12 On average,
participants are 40.1 years old and have 16.9 years of work experience. 165 participants (80.5%) report being directly (114 participants) or indirectly (51 participants) involved with preparing performance
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reports. 133 participants (65%) report being directly (73 participants) or indirectly (60 participants) involved with making projections and/or providing explanations to analysts and investors. 130
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participants (63.4%) report being directly (62 participants) or indirectly (68 participants) involved in making choices that relate to the preparation of financial statements. 173 participants (84.4%) are
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male.13
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intentionality. Responses to these questions are discussed in our results section alongside the evidence on what participants actually do in their reports. 12
We recruited participants in three ways. First, we directly emailed alumni of a top-rated MBA program (22 participants). Second, we posted announcements on the LinkedIn alumni association pages (69 participants). Third, we asked current EMBA students to participate in our study (114 participants). Inferences are unchanged if we control for the source of our participants. 13
While we do not directly ask participants whether they are native English speakers, we have two independent coders (who are blind to our conditions) read the responses of our participants and rate whether they have concerns about any of the participants’ effectiveness at communicating in written English. Coders independently
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3.2 Design and Manipulations Participants are asked to assume that they are in charge of investor relations for the Dexico Corporation, a hypothetical firm. In addition, they are asked to assume that, as part of their job duties, they often prepare press releases for investors on behalf of Dexico and its different divisions.
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Participants are informed that they will prepare a report on behalf of the Beverages and Snacks division to explain its performance to investors. The experiment uses a 2x2 between-subjects design,
manipulating (1) performance (good versus bad) and (2) reporting goal (unbiased versus favorable
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reporting). Varying the reporting goal allows us to provide participants with either a relatively weak or strong self-enhancement motive (unbiased versus favorable reporting goal condition, respectively). 3.3 Task and Procedure
After reading a brief introduction to the task, participants are told they will be given some basic
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facts. Participants are asked to rely on their past experiences to make assumptions about the
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circumstances surrounding the facts and how they may have contributed to the division’s performance to provide a more coherent explanation to investors. To help participants understand how they might
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use the facts to write their report, they are given an example before moving to the main task. Participants consider the hypothetical fact that “The division moved its administrative offices into a new
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building this quarter.” They are told that if the division performed well, they might describe the fact as
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“The move to a new office revitalized employees. They were more excited about coming to work, the transition to the new facilities went smoothly, and most employees expressed that the new location made their commute easier." In contrast, participants are told that if the division performed poorly, they
agree that they have concerns about two of the participants. Inferences are unchanged if we exclude these two participants, so we include them in all analyses.
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might describe the fact as “The move to a new office demoralized employees. They were less excited about coming to work, the transition to the new facilities did not go smoothly, and most employees expressed that the new location made their commute harder.” The readability of these sample reports is held as constant as possible for the good and bad performance examples.14 Importantly, these
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instructions are held constant across conditions, so they are unlikely to explain any differences in between-condition results.
Next, participants are presented with a paragraph containing our experimental manipulations.
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In the good (bad) news condition, participants are told that the Beverages and Snacks division of Dexico delivered a 10% increase (decrease) in sales this quarter compared to the same quarter last year. They are also told that this performance is better (worse) than all other divisions within the company, and better (worse) than most other firms in the same industry. In the unbiased reporting goal condition,
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participants are told that they should report the division’s performance accurately, and “in a manner that is as unbiased as possible”. In the favorable reporting goal condition, participants are told that they
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should report the division’s performance accurately, but “in a manner that presents the performance in
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as favorable a light as possible”.
Next, participants proceed to a page containing four facts available for use in their report.15
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Participants are instructed that the facts are presented in no particular order and that they can use one
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Using our measure of readability, which is discussed in more detail later in this section, the Good News example had a score of 15.01, and the Bad News example had a score of 15.00, indicating that they were nearly identical in terms of readability. 15
To choose the four facts to be included, we started by presenting a larger list of facts to 60 individuals recruited from Amazon Mechanical Turk. For each fact presented, these individuals were asked to rate on a 101-point scale whether the fact was “unambiguously negative” (0) or “unambiguously positive” (100). For the current study, we retained the four facts that did not significantly differ from the midpoint of 50 on the scale (Kida, 1984; Libby and
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or more facts in their report to support their description of why the division performed as it did. Below the four facts is a box in which participants can type their report (see Figure 1). They are told that they must remain on the page for at least three minutes in order to give them time to draft the report. After three minutes have passed, a button pops up allowing them to move forward in the study whenever
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they are ready. This technique allows participants to provide responses that are (1) long enough for our analyses and (2) varied enough to detect real differences in language choices. Finally, participants answer follow-up questions about their report, manipulation check questions, and demographic
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questions.
Our goal in designing this task was to provide a rich enough performance setting to allow the experienced managers to craft relatively detailed performance reports while also drawing on their prior
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experience as managers. For example, this setting allows participants to draw upon the tradeoffs and motives they face when reporting on firm performance. If we had instead used a real performance task
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with constructed incentives, we would have limited our ability to gain insight from participants’
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knowledge of the reporting environment in practice while also potentially confounding performance with individual characteristics of participants (e.g., participants who performed well might be more
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hardworking or intelligent, making it difficult to determine whether differences in participants’ reports
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are due to performance or participant characteristics).16 This task allows us to achieve these objectives
Trotman, 1993). This design ensures that participants could plausibly use any of the four facts (held constant across all conditions) to explain either good or bad performance in the division. 16
For example, prior accounting studies have asked participants to create rebus puzzles (Kachelmeier, Reichert, and Williamson, 2008; Kachelmeier and Williamson, 2010), complete a sandwich-making task (Farrell, Kadous, and Towry, 2008), or complete a trivia task (Libby and Rennekamp, 2012; Asay, 2018).
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and directly capture the language choices of experienced managers without being modified by the various parties that craft and create press releases in the real world (e.g., legal departments). One potential limitation of our task is that participants do not actually observe the true cause of performance and instead construct a story for performance based on the facts we provide. While we
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acknowledge this as a potential limitation, there are at least three important reasons to believe it does not affect the validity of our results. First, in constructing causal narratives, individuals generally draw on the most accessible potential factors available in memory – not necessarily the true causal drivers of an
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outcome (Tversky and Kahneman, 1973). Similarly, in our setting, the four facts provide accessible
factors that are plausible contributors to realized performance and individuals are asked to draw upon these accessible potential factors and upon their prior experiences to construct a causal narrative. Second, even if our task relies on a slightly different cognitive mechanism than creating a causal
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narrative by drawing on memory, this could change the levels of the linguistic characteristics we measure, but is less likely to change the directional effects of our performance and reporting goal
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manipulations. Finally, many of our findings align with empirical patterns documented in the literature,
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providing at least some level of validation for this measurement technique. 3.4 Dependent Measures
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Our dependent variables are selected to match those used in prior archival empirical and
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experimental studies to increase the comparability of our results. 3.4.1 Readability Measure There is considerable disagreement in the literature over how best to measure “readability.”
Many of the standard readability measures were developed for leveling grade-school textbooks and consist of simple formulas based on sentence length and the average number of syllables in words 16
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(Dubay, 2004). Two such measures that have been widely used in the prior accounting literature are the Fog Index and the Flesch Reading Ease Score (Flesch Score)17. While the Fog Index and Flesch Score measures are easy to calculate and their use is widespread, some have argued that they are too simple to provide a meaningful measure of readability (Dubay, 2004), particularly in business communications
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(Jones and Shoemaker, 1994; Miller, 2010; Loughran and McDonald, 2014a,b).18 Specifically, the Fog and Flesch measures do not do a good job of capturing the complexity of sentence structure. For instance, “the cat sat on the mat” would be judged to have the same readability as a phrase including the exact same words but rearranged (e.g., “mat sat the on the cat”), even though the latter is clearly less
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readable. More recently, some studies have used either file size (Loughran and McDonald, 2014a) or the Bog Index (Bonsall, Leone, Miller, and Rennekamp, 2017) to capture readability of disclosures in archival samples. While a file size proxy allows for calculation of readability in large-sample archival studies, it is likely to be much noisier than a measure based on the actual language used in a disclosure (Bonsall et
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al., 2017). The Bog Index also allows for calculation of readability in large-sample archival studies, but
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the proprietary Stylewriter software that is used to collect the measure provides less transparency with respect to the actual components that contribute to readability.
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In our study, we use a measure of readability that is more complex to calculate than some
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alternative measures used in prior studies, but is more transparent and more precisely captures actual levels of readability. We develop a measure of readability that includes most of the features of
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readability that are manipulated in Rennekamp (2012) and measured in Miller (2010). Thus, our
17
See e.g., Li (2008); Biddle, Hilary, and Verdi (2009); Miller (2010); Lehavy, Li, and Merkley (2011); Lawrence (2013); Bushee et al. (2018). 18
For example, multi-syllabic words such as “telecommunication” or “depreciation” would indicate lower levels of readability according to the Fog Index and Flesch Score, although these words are unlikely to be difficult to read for most investors.
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Readability measure is largely based on the features the SEC suggests will improve the readability of firm disclosures (SEC, 1998). Our measure of readability is similar to Miller’s (2010) measure and is calculated as instances of [(Passive Voice + Hidden Verbs + Superfluous words + Negations + Complex Synonyms – Personal Pronouns)*10]/[number of words/average words per sentence].19 Finally, we rescale the
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Readability measure such that higher scores indicate higher readability.20 3.4.2 Association with the Message Measures
Our first measure of association with the message is the use of first person pronouns. Our
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measure of participants’ use of first person pronouns is calculated by capturing the I and we variables from the LIWC2015 software. The I variable captures first person singular words (e.g., “I”, “me”) and the we variable captures first person plural words (e.g., “we”, “our”). We sum these variables to get a total measure of the use of first person pronouns. Our second measure of association with the message
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relates to the use of passive voice. Our measure of participants’ use of passive voice is calculated by analyzing each report using Stylewriter software. Stylewriter summarizes various linguistic
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characteristics from written texts. For our analyses, we use the output measure counting the number of
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instances of passive voice in a text.
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3.4.3 Causal Explanation Measure
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The number of Negations and Personal Pronouns are calculated using LIWC2015 software rather than Stylewriter, because Stylewriter does not separately report these two linguistic style features. 20
To rescale the Readability measure we subtract the raw score (where higher measures indicate lower readability) from 20. The rescaling procedure and values were chosen so that most participants’ reports had positive readability scores and so that higher scores indicated greater readability to make results more interpretable.
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Our measure of participants’ use of causal explanation words is calculated by capturing the cause variable from the LIWC2015 software, which includes component words related to providing causal explanations (e.g., “because”, “effect”).
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3.4.4 Focus on the Future Measure Our measure of participants’ relative focus on the future is calculated by using the focusfuture and focuspast variables from the LIWC2015 software to capture the number of words that focus on the future (e.g., “will”, “soon”) and past (e.g., “did”, “talked”). We then construct the measure used in our
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analyses by dividing the number of future words by the sum of future and past words. 3.4.5 Relation between Readability and other Measures
First person pronouns and passive voice are both components of readability, but they also relate
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to the distinct construct of association with the message. For example, our measure of readability includes personal pronouns (first and third person), whereas our measure of association with the
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message relates only to first person pronouns. While the third person pronouns captured in our readability measure can improve the understandability of text by more clearly indicating the target
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objects in a conversation (e.g., “You will receive a $1.00 dividend” vs. “Shareholders will receive a $1.00
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dividend”), they do not capture differences in the speaker’s association with a message. Similarly, passive voice is only one component of our readability measure, such that there is uncertainty, ex ante,
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whether passive voice will exhibit a similar pattern of results as readability overall. Most notably, managers’ reporting goal and performance may influence their propensity to associate themselves with the message, even in the absence of intentional obfuscation of poor performance. The extent to which the reports focus on the future and provide causal explanations for performance are not directly related
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to readability. Rather, these two linguistic characteristics reflect alternative approaches managers might use to communicate poor performance.21 4. Primary Experiment: Results
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4.1 Manipulation Checks For our manipulation check questions, 90.7% of participants correctly report whether the
division’s performance was good or bad in the recent quarter, while 85.4% of participants correctly report whether their primary reporting goal in writing the report was to be as unbiased as possible or to
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present the division in as favorable a light as possible.22 We also ask participants to rate the extent to which another person reading their report would judge the division favorably or unfavorably (1 = “very unfavorably”, 10 = “very favorably”). Consistent with a successful performance manipulation, participants believe that the division would be viewed more favorably when news is good (mean = 6.81)
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than when news is bad (mean = 6.26), and the difference is significant (p = 0.018, one-tailed). Consistent
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with a successful reporting goal manipulation, participants believe that the division would be viewed
21
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By construction, readability is highly correlated with the use of passive voice (ρ = -0.345; p < 0.001, two-tailed, untabulated) and the use of first person pronouns (ρ = 0.697; p < 0.001, two-tailed, untabulated). Readability is also correlated with the use of future tense words (ρ = 0.221; p = 0.002, two-tailed, untabulated) but not with the use of causal words (ρ = .107; p = 0.128, two-tailed, untabulated). In addition, untabulated results indicate that personal pronoun usage is associated with both causal words (ρ = 0.697, p < 0.001, two-tailed) and with future tense words (ρ = 0.252, p <0.001, two-tailed). The use of passive voice is negatively correlated with future tense words (ρ = -0.143; p = 0.042), but is only marginally significantly correlated with causal words (ρ = 0.120, p = 0.088, two-tailed) and not significantly correlated with personal pronoun usage (ρ = -0.077, p = 0.273, two-tailed). A regression analysis including each of these four linguistic characteristics (as well as our manipulated variables) indicates that readability is increasing in pronoun usage (t = 12.97; p < 0.001, two-tailed) and decreasing in the use of passive voice (t = -2.66; p < 0.001, two-tailed), but is unrelated to the use of causal words (t = -0.175; p = 0.490, two-tailed) or future tense words (t = 0.947; p = 0.690, two-tailed). 22
Inferences are unchanged if we exclude participants who answered manipulation check questions incorrectly.
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more favorably when there is a favorable reporting goal in place (mean = 6.92) than when the reporting goal is to be unbiased (mean = 6.15) and the difference is significant (p = 0.002, one-tailed). 4.2 Tests of Readability Hypotheses
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H1a predicts that participants will prepare reports that are less readable when performance is bad than when performance is good, and H1b predicts that this will be particularly true when managers have a stronger self-enhancement motive. Panel B of Table 1 shows that, consistent with H1a,
participants prepare reports that are less readable when news is bad than when news is good (p = 0.058,
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one-tailed) and, consistent with H1b, this is particularly true when they have a stronger self-
enhancement motive (p = 0.015, one-tailed). Panel A of Figure 2 presents these results graphically.
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While our results support that bad news disclosures are less readable, particularly when selfenhancement motives are stronger, this does not appear to be driven by participants intentionally
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making bad news disclosures less readable. Instead, in this primary experiment, the interaction appears to be driven by participants making good news disclosures more readable when they have a stronger
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self-enhancement motive. The simple main effect of reporting goal is not significant when news is bad (p = 0.596, two-tailed, untabulated). When news is good, however, participants prepare significantly more
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readable reports when they have a favorable reporting goal than a goal to be as unbiased as possible (p = 0.010, two-tailed, untabulated). Participants’ responses to debriefing questions provide additional insight into the intentionality of disclosure readability decisions. Panel A of Table 2 shows mean responses, by condition, to two 21
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questions participants answered about the readability of their reports. The first question asks participants “How easy or difficult would you say it is to read your report?” (1 = “very easy”, 10 = “very difficult”). The second question asks participants about the extent to which they were motivated to make their report easier or more difficult to understand (1 = “I was motivated to make my report easier
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to understand”, 10 = “I was motivated to make my report more difficult to understand”). Panel B of Table 2 shows that we find no significant main effects or an interaction on either of these two measures. These results should be interpreted with caution for at least two reasons. First, the lack of a significant effect is not affirmative evidence that the effect is not there. Second, participants may be reluctant to
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admit to intentionally making disclosures less readable. Nevertheless, in combination with the results shown in Table 1, our results generally support the idea that participants at least do not appear to be intentionally making bad news disclosures less readable to obfuscate poor performance, contrary to
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arguments made in prior literature.
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4.3 Tests of Hypotheses Related to Managers’ Association with the Message
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H2 and H3 make predictions about linguistic characteristics that can be used to associate or distance oneself from the information in a disclosure. H2a predicts that participants will use fewer first
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person pronouns (e.g., “I”, “We”, etc.) when performance is bad than when performance is good, and H2b predicts that this difference will be greater when participants have a stronger self-enhancement
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motive.23 Panel B of Table 3 shows that neither H2a nor H2b is supported (both p-values > 0.220, onetailed). Panel B of Figure 2 presents these results graphically. However, participants do use more first
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The first person pronouns counted in the two categories include the following: I, I’d, I’ll, I’m, I’ve, id, ive, me, mine, my, myself, let’s, lets, our, ours, ourselves, us, we, we’d, we’ll, we’re, we’ve, and weve.
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person pronouns when they have a stronger self-enhancement motive (p = 0.054, two-tailed). This finding suggests that managers are more willing to associate themselves with the information in the report when they have written the report to present the firm more favorably.24 Panel A of Table 4 shows mean responses, by condition, to our open-ended debriefing question asking participants to estimate
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the number of first person pronouns used in their reports. Panel B of Table 4 shows that participants do not believe that they used fewer first person pronouns when news was bad than when news was good (p = 0.448, two-tailed). They also do not indicate any difference in first person pronouns when there is a
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stronger self-enhancement motive (p = 0.732, two-tailed).
Because prior work distinguishes between first person singular (e.g., “I”, “me”) and first person
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plural (e.g., “we”, “our”) pronouns, we also separately look at the effects of performance and reporting
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goals on these two categories of pronouns. When analyzed separately, we find that participants use fewer first person singular pronouns when news is bad (p = 0.039, one-tailed, untabulated), but do not
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use fewer first person plural pronouns (p = 0.369, one-tailed- untabulated). This provides some support for H2a. Participants appear to use fewer first person singular pronouns like “I”, or “me” when
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performance is poor, consistent with distancing themselves from the information. When analyzed
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separately, we still do not observe an interaction between performance and reporting goal on the use of either first person singular pronouns (p = 0.255, one-tailed, untabulated) or first person plural pronouns (p = 0.288, one-tailed, untabulated).
24
Consistent with this idea, untabulated results indicate that pronoun usage is positively associated with disclosure tone (ρ = 0.152; p = 0.030, two-tailed) and with positive emotion words (ρ = 0.189; p = 0.007, two-tailed).
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H3a predicts that participants will use more passive voice in their reports when performance is bad than when performance is good, and H3b predicts that the difference will be greater when they have a stronger self-enhancement motive. Consistent with H3a, Panel B of Table 3 shows that participants use more passive voice when performance is bad than when performance is good (p =
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0.057, one-tailed). Consistent with H3b, the difference in use of passive voice between good and bad news is greater when participants have a stronger self-enhancement motive (p < 0.001, one-tailed). Panel C of Figure 2 presents these results graphically. Panel A of Table 4 shows mean responses, by condition, to our debriefing question asking participants the extent to which their report used active or
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passive voice in their report (1 = “My report primarily used active voice”, 10 = “My report primarily used passive voice”). Panel B of Table 4 shows that, despite our finding support for H3a and H3b, participants do not report that they use more passive voice when news is bad (p = 0.882, two-tailed), or that there is a stronger difference in the use of passive voice between good and bad news when they have a stronger
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self-enhancement motive (p = 0.361). Pennebaker (2011) suggests that linguistic style choices (such as
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the use of active versus passive voice) are particularly likely to occur beneath awareness as compared to content choices (such as discussions of the future or causal explanations), which may help to explain
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why participants appear unable to accurately report differences in their use of passive voice across our
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performance and reporting goal conditions. 4.4 Tests of Hypotheses Related to Causal Explanations for Performance and Focus on the Future
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H4a predicts that participants will prepare reports that include more causal explanation words
when performance is bad than when performance is good and H4b predicts that this will be particularly true when they have a stronger self-enhancement motive. Consistent with H4a, Panel B of Table 3 shows that participants use more causal words when performance is bad than when performance is good (p = 0.003, one-tailed). However, H4b is not supported, as we do not find that this effect is 24
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stronger when participants have a stronger self-enhancement motive (p = 0.416, one-tailed). Panel D of Figure 2 presents these results graphically. Panel A of Table 4 shows mean responses, by condition, to our debriefing question asking participants the extent to which their report focused on explaining underlying causes for the firm’s
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performance (1 = “I was primarily focused on reporting ‘just the facts’”, 10 = “I was primarily focused on explaining the underlying causes for performance”). Panel B of Table 4 shows that, consistent with H4a, participants believe that their report focuses on providing more causal explanation for underlying
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performance when news is bad than when news is good (p = 0.010, two-tailed). They also report that they provide more causal explanation when they have a stronger self-enhancement motive (i.e., a favorable reporting goal), (p = 0.006, two-tailed).25
H5a predicts that participants will prepare reports that focus more on the future relative to the
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past when performance is bad than when performance is good, and H5b predicts that this will be particularly true when they have a stronger self-enhancement motive. Consistent with H5a, Panel B of
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Table 3 shows that, when performance is bad, participants use more words that focus on the future in
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their reports, relative to words that focus on the past (p < 0.001, one-tailed). However, H5b is not supported, as we do not find that this effect is stronger when participants have a stronger self-
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enhancement motive (p = 0.894, one-tailed). Panel E of Figure 2 presents these results graphically.
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Despite the fact that we do not find support for H5b when looking at the reports that participants actually prepare, our debriefing question related to the focus on future versus past 25
While we do not find a significant interaction between performance and reporting goal (p = 0.124, two-tailed), the simple main effect of performance is not significant when the reporting goal is to be unbiased (p = 0.442, twotailed), but is significant when participants have a favorable reporting goal (p = 0.004, two-tailed), providing at least some support for the idea that participants’ beliefs about the provision of causal explanations in their reports is consistent with what we predict in H3b about their actual behavior.
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performance suggests that participants believe they behave in the predicted way. Panel A of Table 4 shows responses, by condition, to our debriefing question asking participants to rate the extent to which their report focused on past performance versus future expectations (1 = “My report focused primarily on past performance”, 10 = “My report focused primarily on future performance expectations.” Panel B
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shows that, consistent with what we predict in H5a, participants believe that their report focuses more on future expectations than past performance when news is bad than when news is good (p < 0.001, two-tailed).26 Further, and consistent with what we predict in H5b, this difference is even greater when
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participants have a stronger self-enhancement motive (p = 0.048, two-tailed).
The difference between what participants do (as tested in H5b and shown in Table 3) and what they say they do (as shown in Table 4’s supplemental analyses) could be driven by participants’ inability to accurately infer their linguistic choices (Pennebaker, 2011) and/or by noise in our measure for testing
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participants’ relative focus on the future in their reports. The predetermined words in the LIWC2015 categories were not developed specifically for the purpose of analyzing business texts. As a result, our
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measures may be (1) including words that should not be counted or (2) omitting words that should be
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counted in a business context (Matsumoto et al., 2011; Dikolli, Keusch, Mayew, and Steffen, 2015). 5. Supplemental Experiment
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In our primary experiment, we operationalized our reporting goal manipulation by instructing
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participants to report performance either “in a manner that is as unbiased as possible” or “in a manner that presents the performance in as favorable a light as possible.” Given that poor performance is
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All supplemental analyses of participants’ beliefs about their linguistic choices are reported as two-tailed rather than one-tailed tests. Given that prior work in linguistics provides mixed evidence as to whether individuals are aware of their linguistic choices (Pennebaker, 2011), we do not make directional predictions ex ante as to whether participants will be able to accurately infer the linguistic characteristics of their reports.
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unfavorable by definition, it is possible that participants in the bad news condition were unclear as to how to present unfavorable news in a favorable light. Instead, the instructions may have prompted participants to think of ways to provide a justifiable explanation (as predicted by H4) and describe a more favorable future (as predicted by H5), but not to think of ways to make bad news less readable.
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The instructions may have also led participants to consider ways to maximize the favorable tone of the disclosure rather than to minimize the unfavorable tone. If so, using a less positive tone in the high selfenhancement motives instructions might affect the extent to which the participants use causal language in describing their performance and focus on the future. Further, a less positive tone in these
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instructions might lead participants to more naturally resort to intentionally issuing a less readable report to obfuscate poor performance.
To test these possibilities, we conduct a supplemental experiment using a 1 x 2 between-
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subjects design in which all participants receive the bad news information and we manipulate the instructions used to induce a stronger self-enhancement motive. 74 experienced managers enrolled in a
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highly-rated EMBA program participated. The participants are instructed to present their performance “in a manner that presents the performance in as favorable a light as possible” (the “most favorable
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condition”, which uses the same wording as in our primary experiment) or “in a manner that presents
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the performance in the least unfavorable light as possible” (the “least unfavorable condition”). All other procedures are identical to our primary experiment.
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As shown in Table 5 Panel A, we find no difference across conditions in participants’ use of
personal pronouns (p = 0.461, two-tailed), passive voice (p = 0.400, two-tailed), causal words (p = 194, two-tailed), or words that focus on the future relative to words that focus on the past (p = 0.812, twotailed). These findings suggest that the tests of H2, H3, H4, and H5 are robust to using a less positive tone in the self-enhancement instructions. Interestingly, we do find that participants in the least 27
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unfavorable condition write marginally less readable reports than participants in the favorable condition (p = 0.091, two-tailed).27 This result does not, however, appear to be driven by an attempt to obfuscate poor performance. Specifically, participants in the least unfavorable condition report being less motivated to make their reports difficult to understand (p = 0.060, two-tailed) and believe another
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person would judge the division less favorably after reading their report (p = 0.091, two-tailed).
Additional analyses (see Panel B) indicate that the difference in readability arises because participants in the least unfavorable condition use more negations (p = 0.002, two-tailed). Further, our manipulation is no longer a significant predictor of readability after controlling for participants’ use of negations (p =
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0.237, two-tailed, untabulated). Combined, these results provide additional support for the inferences drawn from our primary experiment related to managers’ linguistic choices, with one exception. The exception is that, although unaware that they are doing so, managers appear to provide less readable disclosures under “least unfavorable” reporting goals when performance is poor, primarily through the
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increased use of negations.
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6. Survey of Experienced Managers
Our primary experiment provides evidence on how firm performance and reporting goals affect
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linguistic choices in disclosures, and responses to post-experimental questions provide evidence on the
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intentionality of these choices. The purpose of our survey is to provide complementary evidence on the
27
These results are subject to at least one caveat, in that we identify an influential outlier observation in the “least unfavorable” condition (with a mean readability score of 15, which is greater than 3 standard deviations below the overall mean readability score of 16.74). When this participant is excluded, the mean Readability for the “least unfavorable” condition goes from 14.64 to 15.49, and the significance of the difference between the mean readability score in the “most favorable” and “least unfavorable” conditions goes from 0.091 to 0.158. However, the difference in the use of negations still remains significant.
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possible motives behind these choices. Participants in our survey are 144 experienced managers enrolled in a highly-rated EMBA program.28 In the survey, the participants rate possible explanations for three of the differences noted in our main experiment and choose between two reports to issue to describe some poor performance in their firm.
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6.1 Method
To begin, participants are provided with background information about our experiment. This background information explains (1) that the experienced managers in our experiment were asked to
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read information about a hypothetical firm, (2) that half of the experienced managers were told that recent performance was relatively good while the other half were told that recent performance was relatively poor, (3) that the experienced managers were each provided with the same four facts that may have contributed to performance, and (4) that the experienced managers were asked to prepare a
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performance report by making assumptions about those facts and drawing on their prior business experiences in order to create a more coherent story for investors. In addition, survey participants are
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informed that the experienced managers were provided with a reporting goal to portray the firm in “as
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favorable a light as possible.” We focus on the favorable reporting goal condition because managers
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generally have strong motives to present the firm favorably.
28
On average, participants are 37.6 years old and have 15.1 years of work experience. 113 participants (78.5%) report being directly (64 participants) or indirectly (49 participants) involved with preparing performance reports. 89 participants (61.8%) report being directly (37 participants) or indirectly (52 participants) involved with making projections and/or providing explanations to analysts and investors. 73 participants (51.0%) report being directly (22 participants) or indirectly (51 participants) involved in making choices that relate to the preparation of financial statements (one participant did not indicate his/her involvement). 115 participants (81.0%) are male (two participants did not indicate their gender).
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Survey participants are then presented with a summary of three of the differences observed (readability, causal words, and focus on the future) between the reports of participants in the good performance/favorable reporting goal condition and participants in the bad performance/favorable reporting goal condition. We focus on these three characteristics because responses in our primary
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experiment suggest that they are more likely to be driven by intentional choices than either passive voice or the use of personal pronouns. For each difference presented, survey participants are then asked to rate on 101-point scales (endpoints: 0 = “very unlikely” to 100 = “very likely”), based on their own past experience, the extent to which several factors may have contributed to the characteristics of the
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performance reports. Finally, participants are asked to assume that they are a manager who has to describe some poor performance in their firm, are presented with a more and less readable disclosure that otherwise contains the same performance information, and indicate which of the two disclosures
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they would choose to provide. 6.2 Results
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6.2.1 Readability
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Survey participants are informed that the reports were less readable when describing poor performance than when describing good performance.29 They then rate five potential explanations for
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this finding. The order in which the five potential explanations were presented was randomized for each
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survey participant. The five explanations and results are summarized in Table 6 Panel A.30 Directionally,
29
A less readable disclosure was defined as one that uses language that goes against some of the suggestions made by the Securities and Exchange Commission (SEC) to use Plain English in firm disclosures. In addition, less readable disclosures were described as using longer sentences, more complex synonyms, more passive voice, etc. 30
A repeated measures ANOVA (with participant as a random variable) reveals that at least one of the explanations is different (F(4, 535.6) = 14.06; p < 0.001, not tabulated).
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survey participants agreed most strongly with the explanation that managers intentionally write more readable reports when performance is good, with the specific intention of highlighting positive performance. This is the only explanation where the 95% confidence interval for the mean did not overlap with the 95% confidence interval of the other explanations (not tabulated). Further, pairwise
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comparisons reveal that participants rated this explanation significantly higher than any other
explanation (all p < 0.001, two-tailed), and none of the other explanations differed from one another (all p > 0.100, two-tailed).
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Survey participants are informed that the reports included more causal language when firm performance was bad than when firm performance was good. They then rate four potential
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explanations for this finding. As with our other questions, the order in which the potential explanations
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were presented was randomized. The four explanations and results are summarized in Table 6 Panel B. Directionally, survey participants agreed most strongly with the explanation that managers
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intentionally try to provide more information about the reasons for performance when performance is bad in order to satisfy investors’ demand. This is the only explanation where the 95% confidence interval
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for the mean did not overlap with the 95% confidence interval of the other explanations (not tabulated).
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Further, pairwise comparisons reveal that participants rated this explanation significantly higher than any other explanation (all p < 0.005, two-tailed). The explanation suggesting managers intentionally provide more causal explanation when performance is bad with the specific intention of hiding poor
31
A repeated measures ANOVA (with participant as a random variable) reveals that at least one of the explanations is different (F(3, 400.4) = 12.04; p < 0.001, not tabulated).
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performance is also marginally lower than the explanation suggesting managers provide less causal explanation when performance is good with the specific intention of avoiding scrutiny about the reasons for positive performance (p = 0.086, two-tailed).
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6.2.3 Focus on the Future Survey participants are informed that the reports were more focused on the future when they were describing bad performance rather than good performance. Survey participants rate four potential explanations for this finding. Again, the order in which the potential explanations were presented was
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randomized. The four explanations and results are summarized in Table 6 Panel C. 32 Directionally,
survey participants agreed most strongly with the explanation that managers intentionally try to provide more information about how performance is likely to improve in the future when performance is bad in order to satisfy investors’ demand for information. This is the only explanation where the 95%
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confidence interval for the mean did not overlap with the 95% confidence interval of the other explanations (not tabulated). Further, pairwise comparisons reveal that participants rated this
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explanation significantly higher than any other explanation (all p < 0.012, two-tailed), and participants
two-tailed).
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agreed least with the explanation that the increased focus on the future is unintentional (all p < 0.001,
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6.3.4 Disclosure Choice
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Finally, survey participants choose between two disclosure options (one more readable and one less readable) for describing poor performance in their firm. Of the 135 participants who responded to
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A repeated measures ANOVA (with participant as a random variable) reveals that at least one of the explanations is different (F(3, 412.8) = 35.70; p < 0.001, not tabulated).
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this question, 84 (62.22%) chose the more readable disclosure while 51 (37.78%) chose the less readable disclosure. This difference is significantly greater than chance (χ2 = 8.15; p = 0.005, not tabulated). 7. Conclusion
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Using two experiments and a survey of experienced managers, we investigate the determinants of disclosure readability and other linguistic characteristics in a controlled setting. In our primary experiment, we find that participants provide reports that are significantly less readable when
performance is bad than when performance is good, particularly when participants have a stronger self-
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enhancement motive in the form of a reporting goal to portray the firm as favorably as possible. In our supplemental experiment, we find some evidence that participants provide less readable bad news reports when they have a reporting goal to portray the firm in the least unfavorable light possible, rather than in as favorable a light as possible. In both experiments, our results do not appear to be
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driven by intentional obfuscation of poor performance. When directly asked about the reports they have prepared, there is no indication of intentional obfuscation in participants’ perceptions of the
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readability of their reports or their ratings of the extent to which they were motivated to make the
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report easier or more difficult to read. Further, our survey participants believe the most likely explanation for our pattern of results is that managers increase the readability of good news disclosures
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to highlight the positive performance. Combined, the results do not appear to support arguments made in prior literature that managers intentionally obfuscate poor performance by making disclosures less
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readable.
In addition to the results discussed above on readability, we also provide evidence on how other
linguistic choices are affected by variation in firm performance and reporting goals. Specifically, we find that participants use more passive voice and fewer first person singular pronouns when news is bad – a
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technique that distances the manager from the information conveyed. Further, the effect of bad news on the use of passive voice is larger when participants have a favorable reporting goal. We also find that participants include more causal words and use words that focus more on the future when performance is bad than when performance is good. Debriefing questions that directly ask participants about their
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reporting choices suggest that they are aware of these differences and survey participants believe the most likely explanation for these results is that managers try to provide more information about the future in order to satisfy investors’ demand. Results from a supplemental experiment provide additional support for the idea that, to frame poor performance in a positive light, managers provide causal
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explanations for poor performance, focus more on the future, use more passive voice and fewer personal pronouns, and increase the readability of positive information in their disclosures. The supplemental experiment also suggests that, to the extent that managers view their goals when
reporting bad news to be presenting the results in the “least unfavorable” manner possible, use of more
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negations which decreases readability might be expected. Overall, our results support the idea that
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when reporting bad news, individuals distance themselves from poor performance by using passive voice and fewer first person singular pronouns, provide additional explanation, and focus more on
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future expectations.
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Our study adds to the growing literature investigating the language used in disclosures. Controlling for actual firm performance and other characteristics, recent archival studies use methods
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from computational linguistics to analyze large bodies of text, as suggested by Core (2001). Our study, on the other hand, uses a controlled experiment to provide complementary evidence on managers’ disclosure choices, holding constant other factors that are not of primary interest, while using dependent measures that are comparable to recent archival studies.
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Our use of an experiment allows us to complement prior archival work, while isolating the effects of individual drivers of linguistic characteristics of disclosures. For example, prior literature has argued that bad news disclosures may be less readable, at least in part, due to the inherent difficulty of describing poor performance (Bloomfield, 2008) or the complexity of the operating environment in
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times of poor performance (Guay et al., 2016; Bushee et al., 2018). We hold environmental complexity constant by using identical underlying facts across all conditions in our setting in order to isolate the effects of firm performance and reporting goals on linguistic characteristics. Future work could further
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examine how the complexity of the operating environment affects the language used in disclosures.
This study has some important limitations. First, we use a setting where participants describe hypothetical performance, rather than performance on a real task (e.g., intelligence tasks,
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manufacturing tasks, etc.). This mitigates potential confounds between linguistic choices and participant characteristics, while also presenting participants with a setting that is rich enough to allow them to
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draw on their experiences when describing firm performance. A consequent downside of asking
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participants to describe hypothetical performance is that it potentially reduces their personal involvement in the task and may influence their linguistic choices as well. However, we would expect
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that lower personal involvement is likely to only weaken our results rather than change the directional
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pattern of responses or the resulting inferences. Second, disclosures provided in the real world are influenced by consultation with legal
departments, public-relations professionals, etc. Consequently, our study does not strictly capture the final disclosures that might actually be provided to investors. Different types of disclosures likely vary with respect to the level of third-party input (see, e.g., Dikolli et al., 2015). Future research could also
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layer in additional features that might affect linguistic choices of reporting complexity. Some interesting possibilities for factors that might affect reporting complexity include managers’ experience, managers’ reporting reputations, different incentive structures, legal considerations, or different types of target
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investors.
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REFERENCES ASAY, S. ‘Horizon-Induced Optimism as a Gateway to Earnings Management.’ Forthcoming in Contemporary Accounting Research, 2018.
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ASAY, S., R. LIBBY, and K. RENNEKAMP. ‘Do Features that Associate Management with a Message Magnify Investors’ Reactions to Narrative Disclosures?’ Forthcoming in Accounting, Organizations and Society, 2018.
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BIDDLE, G.C., G. HILARY, and R.S. VERDI. ‘How does Financial Reporting Quality Relate to Investment Efficiency?’ Journal of Accounting and Economics 48 (2009): 112-131.
BLOOMFIELD, R. ‘The ‘Incomplete Revelation Hypothesis’ and Financial Reporting.’ Accounting Horizons 16 (2002): 233-243.
ED
M
BLOOMFIELD, R. ‘Discussion of ‘Annual Report Readability, Current Earnings and Earnings Persistence’.’ Journal of Accounting and Economics 45 (2008): 248-252.
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BONSALL, S., A. LEONE, B. MILLER and K. RENNEKAMP. ‘A Plain English Measure of Financial Reporting Readability.’ Journal of Accounting and Economics 63 (2017): 329-357.
AC
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BUSHEE, B., I. GOW, and D. TAYLOR. ‘Linguistic Complexity in Firm Disclosures: Obfuscation or Information?” Journal of Accounting Research 56 (2018): 85-121.
CHAFE, W.L. and J. DANIELEWICZ. 1987. Properties of Written and Spoken Language. In: Horowitz, R., Samuels, S.J. (Eds.) Comprehending Oral and Written Language. Academic Press, San Diego, CA, pp. 83-113.
CLATWORTHY, M., and M. JONES. ‘The Effect of Thematic Structure on the Variability of Annual Report Readability.’ Accounting, Auditing and Accountability Journal 14 (2001): 311-326. 37
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COHN, M.A., M.R. MEHL, and J.W. PENNEBAKER. ‘Linguistic Markers of Psychological Change Surrounding September 11, 2001. Psychological Science 15 (2004): 687-693.
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CORE, J. ‘A Review of the Empirical Disclosure Literature: A Discussion.’ Journal of Accounting and Economics 31 (2001): 441-456.
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COURTIS, J.K. ‘An Investigation into Annual Report Readability and Corporate Risk Return Relationships.’ Accounting and Business Research 16 (1986): 285-294.
DIKOLLI, S., T. KEUSCH, W. MAYEW, and T. STEFFEN. ‘Using Shareholder Letters to Measure CEO Integrity.’ Working paper, 2015.
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DUBAY, W. The Principles of Readability. Costa Mesa, California: Impact Information, 2004.
PT
ED
FARRELL, A., K. KADOUS, and K. TOWRY. ‘Contracting on Contemporaneous vs. Forward-Looking Measures: An Experimental Investigation.’ Contemporary Accounting Research 25 (2008): 773802.
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GEE, J.P. An Introduction to Discourse Analysis: Theory and Method. London, England: Routledge, 1999.
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GUAY, W., SAMUELS, D., and D. TAYLOR. ‘Guiding Through the Fog: Financial Statement Complexity and Voluntary Disclosure.’ Journal of Accounting and Economics 62 (2016): 234-269.
HYLAND, K. Metadiscourse: Exploring Interaction in Writing. Oxford, England: Continuum, 2005.
JONES, M.J. ‘A Longitudinal Study of the Readability of the Chairman's Narratives in the Corporate Reports of a UK Company.’ Accounting and Business Research 18 (1988): 297-305. 38
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JONES, M.J., and P.A. SHOEMAKER. ‘Accounting Narratives: A Review of Empirical Studies of Content and Readability.’ Journal of Accounting Literature 13 (1994): 142-184.
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KACHELMEIER, S., B. REICHERT, and M. WILLIAMSON. ‘Measuring and Motivating Quantity, Creativity, or Both.’ Journal of Accounting Research 46 (2008): 341-373.
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KACHELMEIER, S., and M. WILLIAMSON. ‘Attracting Creativity: The Initial and Aggregate Effects of Contract Selection on Creativity-Weighted Productivity.’ The Accounting Review 85 (2010): 1669-1691.
KIDA, T. ‘The Impact of Hypothesis-Testing Strategies on Auditors’ Use of Judgment Data.’ Journal of Accounting Research 22 (1984): 332-340.
ED
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KOONCE, L., Z. LEITTER, and B. WHITE. ‘The Effect of a Cautionary Notice on Investors’ Reactions to More and Less Readable Disclosures.’ Working paper, 2016.
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LAWRENCE, A. ‘Individual Investors and Financial Disclosure.’ Journal of Accounting and Economics 56 (2013): 130-147.
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LEHAVY, R., F. LI, and K. MERKLEY. ‘The Effect of Annual Report Readability on Analyst Following and the Properties of Their Earnings Forecasts.’ The Accounting Review 86 (2011): 1087-1115.
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LI, F. ‘Annual Report Readability, Current Earnings, and Earnings Persistence.’ Journal of Accounting and Economics 45 (2008): 221-247.
LI, F. ‘Textual Analysis of Corporate Disclosures: A Survey of the Literature.’ Journal of Accounting Literature 29 (2010): 143-165.
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LIBBY, R., R. BLOOMFIELD, and M. NELSON. ‘Experimental Research in Financial Accounting.’ Accounting, Organizations and Society 27 (2002): 775-810.
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LIBBY, R., and K. RENNEKAMP. ‘Self-Serving Attribution Bias, Overconfidence, and the Issuance of Voluntary Disclosures.’ Journal of Accounting Research 50 (2012): 197-231.
LIBBY, R., and K. TROTMAN. ‘Audit Review as a Control for Biased Recall of Evidence in Decision Making.’ Accounting, Organizations and Society 18 (1993): 559-574.
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LOFTUS, S., and L. TANLU. ‘Because of “Because”: Examining the Use of Causal Language in Relative Performance Feedback.’ Forthcoming in The Accounting Review.
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LOUGHRAN, T., and B. MCDONALD. ‘Measuring Readability in Financial Disclosures.’ Journal of Finance 69 (2014a): 1643-1671.
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LOUGHRAN, T., and B. MCDONALD. ‘Regulation and Financial Disclosure: The Impact of Plain English.’ Journal of Regulatory Economics 45 (2014b): 94-113.
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MATSUMOTO, D., M. PRONK, and E. ROELOFSEN. ‘What Makes Conference Calls Useful? The Information Content of Managers’ Presentations and Analysts’ Discussion Sessions.’ The Accounting Review 86 (2011): 1383-1414.
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MERKLEY, K. "Narrative Disclosure and Earnings Performance: Evidence from R&D Disclosures." The Accounting Review 89 (2014): 725-757.
MILLER, B. ‘The Effects of Reporting Complexity on Small and Large Investor Trading.’ The Accounting Review 85 (2010): 2107-2143.
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PENNEBAKER, J.W. The Secret Life of Pronouns: What our words say about us. New York, New York: Bloomsbury, 2011.
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PENNEBAKER, J.W., M.R. MEHL, and K.G. NIEDERHOFFER. ‘Psychological Aspects of Natural Language Use: Our Words, Our Selves.’ Annual Review of Psychology 54 (2003): 547-577.
REILLY, J., A. ZAMORA, and R. MCGIVERN. ‘Acquiring perspective in English: the development of stance.’ Journal of Pragmatics 37 (2005): 185-208.
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RENNEKAMP, K. ‘Processing Fluency and Investors’ Reactions to Disclosure Readability.’ Journal of Accounting Research, 50 (2012): 1319-1354.
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RUTHERFORD, B.A. ‘Obfuscation, Textual Complexity, and the Role of Regulated Narrative Accounting Disclosure in Corporate Governance.’ Journal of Management and Governance 7 (2003): 187210.
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Securities and Exchange Commission. (1998). ‘A Plain English Handbook: How to Create Clear SEC Disclosure.’ SEC Office of Investor Education and Assistance. Available at: http://www.sec.gov/pdf/handbook.pdf.
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SUBRAMANIAN, R., R. INSLEY and R. BLACKWELL. ‘Performance and Readability: A Comparison of Annual Reports of Profitable and Unprofitable Corporations.’ The Journal of Business Communication 30 (1993): 49-61.
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TAN, H-T., E. WANG, and B. ZHOU. ‘How does Readability Influence Investors’ Judgments? Consistency of Benchmark Performance Matters.’ The Accounting Review 90 (2015): 371-393.
TVERSKY, A., and D. KAHNEMAN. ‘Availability: A Heuristic for Judging Frequency and Probability.’ Cognitive Psychology 5 (1973): 207-232.
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YOU, H., and X. ZHANG. ‘Financial Reporting Complexity and Investor Underreaction to 10-K Information.’ Review of Accounting Studies 14 (2009): 559-586.
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Figure 1. Screen Shot Showing the Four Ambiguous Facts Provided to Participants for the Preparation of their Report
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This figure depicts a screen shot from our experiment, in which 205 experienced managers assume the role of director of investor relations and explain the performance of a division in a hypothetical firm. Participants are randomly assigned to one of four cells in a 2x2 manipulation of whether (1) the division had good or bad performance for the quarter and (2) the reporting goal is either to be unbiased or to elicit as favorable a reaction as possible. In all conditions, participants receive the same four facts to use in drafting their report (as shown above). These four facts were pretested with a different group of participants and were selected because they were not considered to be unambiguously positive or negative. This design choice was meant to ensure that participants in the study could plausibly use any of the four facts to explain either good or bad performance in the division.
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Figure 2. Primary Experiment Results by Condition for Linguistic Measures Used to Test our Hypotheses
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Panel A. Readability
Panel B. Personal Pronouns
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Panel C. Passive Voice
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Figure 2. Results by Condition for Linguistic Measures Used to Test our Hypotheses, continued.
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Panel D. Causal Explanation Words
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Panel E. Focus on the Future
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This figure presents results graphically for our five dependent variables of interest. In our experiment, 205 experienced managers assume the role of director of investor relations and explain the performance of a division in a hypothetical firm. Participants are randomly assigned to one of four cells in a 2x2 manipulation of whether (1) the division had good or bad performance for the quarter and (2) the reporting goal is either to be unbiased or to elicit as favorable a reaction as possible. In all conditions, participants draft an open-ended report, drawing on their prior experience. We then use textual analysis to analyze these reports for the linguistic characteristics of interest. Panel A presents readability scores from these reports, by condition. Panel B presents the extent to which the language in the reports focuses on the future vs. the past, by condition. Panel C presents the extent to which the reports include causal language, by condition. Panel D presents the extent to which the reports use more personal pronouns, by condition. Panel E presents the extent to which the reports use passive rather than active voice, by condition.
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Table 1. Primary Experiment Descriptive Statistics and Analysis of Variance – Readability Measure
Panel A. Descriptive Statistics - Mean and (Standard Deviation), by condition
Unbiased
Favorable
Overall
Good
10.74
16.52
13.47
(10.09)
(11.92)
(11.31)
n = 56
n = 50
n = 106
11.71
10.48
11.10
(11.64)
(12.26)
(11.91)
n = 50
n = 49
n = 99
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Bad
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Performance
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Reporting Goal
11.20
13.53
12.32
(10.81)
(12.40)
(11.64)
n = 106
n = 99
n = 205
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Overall
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Panel B. Results of Analysis of Variance (ANOVA) – Test of H1
Source
S.S.
d.f.
M.S.
F-statistic
p-value
Performance
328.45
1
328.45
2.50
0.058†
Reporting Goal
264.55
1
264.55
2.01
0.158
Performance x Goal
625.40
1
625.40
4.76
0.015†
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Table 1, Panel A presents descriptive statistics on the Readability measure in our experiment, in which 205 experienced managers draft a report explaining the performance of a division in a hypothetical firm. Panel B presents ANOVA results investigating whether firm performance (good vs. bad) and reporting goal (unbiased vs. favorable) affect the readability of the report. One-tailed equivalent, given directional predictions.
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†
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Table 2. Primary Experiment Descriptive Statistics and Analysis of Variance – Participant Responses to Questions about the Readability of their Reports
Panel A. Descriptive Statistics – Mean and (Standard Deviation), by condition
How easy or difficult would you say it is to read your report?
Bad Performance & Unbiased Reporting Goal
Bad Performance & Favorable Reporting Goal
3.22
3.04
3.39
(1.92)
(1.92)
(1.78)
(1.62)
n = 56
n = 50
n = 50
n = 49
3.41
3.50
3.50
3.73
(1.94)
(2.01)
(2.05)
(2.14)
n = 56
n = 50
n = 50
n = 49
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1: “Very Easy” 10: “Very Difficult”
3.43
Good Performance & Favorable Reporting Goal
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Measure (and scale endpoints)
Good Performance & Unbiased Reporting Goal
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Condition
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To what extent were you motivated to make your report easier or more difficult for investors to understand?
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1: “I was motivated to make my report easier to understand” 10: “I was motivated to make my report more difficult to understand”
Panel B. Results of Analysis of Variance (ANOVA)
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Measure: Easy vs. difficult to read your report S.S.
d.f.
M.S.
F-statistic
p-value
Performance
0.62
1
0.62
0.19
0.665
Goal
0.24
1
0.24
0.07
0.785
Performance x Goal
3.95
1
3.95
1.19
0.276
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Source
Measure: Motivated to make your report easier or more difficult to understand S.S.
d.f.
M.S.
Performance
1.34
1
1.34
Goal
1.34
Performance x Goal
0.27
F-statistic
p-value
0.32
0.570
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Source
1
1.34
0.32
0.570
1
0.27
0.07
0.799
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Table 2, Panel A presents descriptive statistics for follow-up questions in our experiment related to disclosure readability, in which 205 experienced managers draft a report explaining the performance of a division in a hypothetical firm. Panel B presents ANOVA results investigating whether firm performance (good vs. bad) and reporting goal (unbiased vs. favorable) affect participants’ responses to these follow-up questions about their report.
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Table 3. Primary Experiment Descriptive Statistics and Analysis of Variance – Other Linguistic Characteristics
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Panel A. Descriptive Statistics – Mean and (Standard Deviation), by condition*
Measure
Condition Good Performance & Unbiased Reporting 51
Good Performance & Favorable Reporting
Bad Performance & Unbiased Reporting
Bad Performance & Favorable Reporting
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Causal Explanation Words
Goal
Goal
2.48
3.62
2.46
2.98
(2.59)
(3.50)
(3.02)
(3.12)
n = 56
n = 50
n = 50
n = 49
1.48
1.06
(1.10)
(0.93)
n = 56
n = 50
1.18
1.88
(1.06)
(1.49)
n = 50
n = 49
4.38
4.90
5.33
(2.52)
(3.62)
(3.60)
n = 50
n = 50
n = 49
0.22
0.38
0.32
(0.28)
(0.23)
(0.224)
(0.23)
n = 55*
n = 50
n = 49*
n = 49
4.09 (2.63)
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n = 56
0.20
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Focus on the Future
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Passive Voice
Goal
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Personal Pronouns
Goal
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Panel B. Results of Analysis of Variance (ANOVA)
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Measure: Personal Pronouns (Test of H2) Source
S.S.
d.f.
M.S.
F-statistic
p-value
Performance
5.62
1
5.62
0.60
0.220†
Goal
35.08
1
35.08
3.75
0.054
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1
4.89
0.52
0.235†
S.S.
d.f.
M.S.
F-statistic
p-value
Performance
3.39
1
3.39
2.51
<0.057†
Goal
0.97
1
0.97
Performance x Goal
16.02
1
16.02
Performance x Goal
4.89
0.72
0.398
11.86
<0.001†
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Measure: Passive Voice (Test of H3)
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Table 3, Panel B (continued)
Measure: Causal Explanation Words (Test of H4) S.S.
d.f.
M.S.
F-statistic
p-value
Performance
39.48
1
39.48
7.60
0.003†
Goal
6.58
1
6.58
Performance x Goal
0.24
1
0.24
0.262
0.27
0.416†
S.S.
d.f.
M.S.
F-statistic
p-value
Performance
1.02
1
1.02
16.90
<0.001†
Goal
0.01
1
0.01
0.23
0.629
Performance x Goal
0.09
1
0.09
1.56
0.894†
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Source
1.27
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Measure: Focus on the Future (Test of H5)
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Source
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Table 3, Panel A presents descriptive statistics for other linguistic characteristics used by participants preparing reports in our experiment, in which 205 experienced managers draft a report explaining the performance of a division in a hypothetical firm. Panel B presents ANOVA results investigating whether firm performance (good vs. bad) and reporting goal (unbiased vs. favorable) affect the use of personal pronouns, passive voice, causal words, and future-tense words. Two observations were removed from these analyses because they had zero values in the denominator for the calculation of the measure (future words count/(past words count + future words count)). One-tailed equivalent, given directional predictions.
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Table 4. Primary Experiment Descriptive Statistics and Analysis of Variance – Participant Responses to Questions about Other Linguistic Characteristics of their Reports
Panel A. Descriptive Statistics – Mean and (Standard Deviation), by condition
Measure (and scale endpoints)
Good Performance & Unbiased Reporting Goal
Good Performance & Favorable Reporting Goal
Bad Performance & Unbiased Reporting Goal
Bad Performance & Favorable Reporting Goal
3.71
4.90
3.42
4.12
(4.65)
(6.52)
(4.05)
(4.64)
n = 56
n = 50
n = 50
n = 49
5.34
5.00
5.06
5.39
(2.65)
(2.52)
(2.60)
(2.64)
n = 56
n = 50
n = 50
n = 49
5.55
5.96
5.90
7.31
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Please provide your best estimate (in whole numbers) of the number of first person pronouns (e.g., “I”, “We”, “Our”) contained in your report.
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Condition
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To what extent did you use active or passive voice in your report?
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1: “My report primarily used active voice” 10: “My report primarily used passive voice”
55
To what extent did your report focus on reporting “just the facts” of the division’s performance vs. explaining the underlying causes for the division’s performance?
(2.62)
(2.33)
(2.43)
(1.72)
n = 56
n = 50
n = 50
n = 49
4.34
3.72
5.44
6.18
(2.71)
(2.32)
(2.62)
(2.05)
n = 56
n = 50
n = 50
n = 49
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1: “My report focused primarily on past performance” 10: “My report focused primarily on future performance expectations”
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To what extent did your report focus on past performance of the division vs. expectations for future performance?
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Panel B. Results of Analysis of Variance (ANOVA)
Measure: Use of Personal Pronouns in the Report S.S.
d.f.
M.S.
F-statistic
p-value
Performance
14.68
1
14.68
0.58
0.448
Goal
45.55
1
45.55
Performance x Goal
2.98
1
2.98
0.182
0.12
0.732
S.S.
d.f.
M.S.
F-statistic
p-value
Performance
0.15
1
0.15
0.02
0.882
Goal
0.00
1
0.00
0.00
0.987
Performance x Goal
5.69
1
5.69
0.84
0.361
M
Source
1.79
AN US
Measure: Active vs. Passive Voice
CR IP T
Source
ED
Measure: Just the Facts vs. Explaining Underlying Causes
Performance
CE
Goal
Performance x Goal
AC
S.S.
d.f.
M.S.
F-statistic
p-value
36.60
1
36.60
6.85
0.010
41.98
1
41.98
7.85
0.006
12.77
1
12.77
2.39
0.124
PT
Source
Measure: Focus on Past Performance vs. Expectations for Future Performance Source
Performance Goal
S.S.
d.f.
M.S.
F-statistic
p-value
162.33
1
162.33
27.05
<0.001
0.20
1
0.20
0.03
0.856
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Performance x Goal
23.74
1
23.74
3.95
0.048
AC
CE
PT
ED
M
AN US
CR IP T
Table 4, Panel A presents descriptive statistics for several follow-up questions in our experiment related to participants’ perceptions of the linguistic choices they made in their reports. In our experiment, 205 experienced managers draft a report explaining the performance of a division in a hypothetical firm. Panel B presents ANOVA results investigating whether firm performance (good vs. bad) and reporting goal (unbiased vs. favorable) affect participants’ responses to these follow-up questions about their report.
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Table 5. Supplemental Experiment Comparisons in Linguistic Characteristics of Disclosures Prepared by Managers between the Most Favorable and Least Unfavorable Instructions Conditions
Panel A. Supplemental Experiment Results Using Measures from our Main Experiment
Measure
"Least Unfavorable" Condition
p-value
14.64
0.091
3.48
0.461
1.29
1.06
0.400
4.24
5.05
0.194
0.37
0.36
0.812
18.72
First Person Personal Pronouns (H2)
4.07
AN US
Readability (H1)
CR IP T
"Most Favorable" Condition
Passive Voice (H3) Causal Explanations (H4)
M
Future Focus (H5)
ED
Panel B. Supplemental Experiment Results for Individual Component Measures of Readability
"Least Unfavorable" Condition
p-value
0.32
0.47
0.325
Passive Voice
1.29
1.06
0.400
Superfluous Words
0.87
0.94
0.761
Negations
0.16
0.72
0.002
Complex Synonyms
2.45
2.81
0.278
First and Third Person Personal Pronouns
4.89
4.31
0.493
Number of Words
86.05
85.03
0.878
Measure
AC
CE
Hidden Verbs
PT
"Most Favorable" Condition
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Average Words/Sentence
21.55
22.02
0.709
AC
CE
PT
ED
M
AN US
CR IP T
Table 5 presents results of our supplemental 1x2 experiment, in which 74 experienced participants are provided with four facts and are asked to draft a report explain the poor performance of a hypothetical firm. Participants are randomly assigned to either receive instructions to present the firm in as favorable a light as possible (“most favorable” condition) or the least unfavorable light as possible (“least unfavorable” condition). Panel A summarizes results, by condition, for the five measures used in our main experiment to test our hypotheses. Panel B summarizes results, by condition, for the components that make up our readability measure. All p-values are twotailed given our lack of directional predictions. Higher numbers indicate a disclosure is more readable, or includes more words related to the future relative to the past, more causal explanation words, more personal pronouns, and more passive voice.
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Table 6. Survey Descriptive Statistics and Pairwise Comparisons –Participant Ratings of Potential Explanations for Readability, Future Focus, and Causal Words Results
CR IP T
Panel A. Readability
Rating Mean
Explanation
(Median)
AN US
Managers intentionally write less readable reports when performance is bad with the specific intention of hiding poor performance.
59.94
B
(67)
76.41
Bad news is inherently more difficult to discuss than good news, which results in less readable language in reports when news is bad and more readable language in reports when news is good.
63.08
Managers intentionally try to provide more information when performance is bad, in order to satisfy investors’ demand, which results in less readable language in reports.
57.39
Managers unintentionally change their language when describing performance, and this change in language results in less readable language in reports when performance is bad than when performance is good.
55.95
ED
M
Managers intentionally write more readable reports when performance is good with the specific intention of highlighting positive performance.
A (80)
B (70)
B (64)
B (62)
CE
PT
Pairwise Comparisons*
AC
Panel B. Causal Words
Rating Mean Explanation
(Median)
61
Pairwise Comparisons*
ACCEPTED MANUSCRIPT
Managers intentionally provide more causal explanation when performance is bad with the specific intention of hiding poor performance.
54.37
Managers intentionally provide less causal explanation when performance is good with the specific intention of avoiding scrutiny about the reasons for positive performance.
47.15
Managers intentionally try to provide more information about the reasons for performance when performance is bad, in order to satisfy investors’ demand, which results in reports that include more causal language.
63.56
B (56)
B
CR IP T
(50)
AC
CE
PT
ED
M
AN US
Managers unintentionally change their language when describing performance, and this change in language corresponds with the use of fewer causal words when news is good and more causal words when news is bad.
62
A
(70)
51.02
B
(50)
ACCEPTED MANUSCRIPT
Panel C. Future Focus
Rating Mean (Median)
Pairwise Comparisons*
CR IP T
Explanation
65.15
Managers intentionally shift their discussion to the past when performance is good with the specific intention of highlighting positive performance.
70.86
AN US
Managers intentionally shift their discussion to the future when performance is bad with the specific intention of hiding poor performance.
Managers intentionally try to provide more information about how performance is likely to improve in the future when performance is bad, in order to satisfy investors’ demand, which results in reports that use language that focuses more on the future.
ED
M
Managers unintentionally change their language when describing performance, and this change in language results in more focus on the future when performance is bad than when performance is good.
B
(71)
B
(76)
79.45 A (81) 51.65 C (50)
AC
CE
PT
Table 6 presents descriptive statistics and pairwise comparisons for survey participants’ responses to questions related to the pattern of results observed in our experiment. In the survey, 144 experienced managers are presented with a summary of three of the differences observed in our experiment (readability, focus on the future, and causal words) and asked to rate, based on their own past experience, the extent to which several factors may have contributed to the characteristics of the performance reports. For readability, survey participants are informed that the reports were less readable when they were describing poor performance than when they were describing good performance. Survey participants rate five potential explanations for this finding on a 101-point scale (endpoints: 0 = “very unlikely” to 100 = “very likely” to explain differences in readability). For causal words, survey participants are informed that the reports included more causal language when firm performance was bad than when firm performance was good. Survey participants rate four potential explanations for this finding on a 101-point scale (endpoints: 0 = “very likely” to 100 = “very unlikely” to explain differences in causal language). For focus on the future, survey participants are informed that the reports were more focused on the future when they were describing bad performance rather than good performance. Survey participants rate four potential explanations for this finding on a 101-point scale (endpoints: 0 = “very unlikely” to 100 = “very likely” to explain differences in future focus).
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*
AC
CE
PT
ED
M
AN US
CR IP T
All pairwise comparisons are made using Tukey’s Honest Significant Difference test, with the Tukey-Kramer adjustment for multiple comparisons. Explanations not connected by the same letter are significantly different (p ≤ 0.050, two-tailed).
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