We examine the effect of managerial expectations on asymmetric cost behavior in the context of resource adjustment costs and unused resource constraints. Our results show that the incremental impact of managerial expectations on cost asymmetry is the strongest when adjustment costs and unused resources are high. Conversely, when both are low, expectations have no impact on the degree of cost asymmetry. Furthermore, when the degree of unused resources is high, managerial pessimism is associated with anti-sticky cost behavior but managerial optimism reverses this relation and results in cost stickiness. Finally, we find the strongest cost stickiness under the following: a low degree of unused resources, a high magnitude of adjustment costs, and optimistic managerial expectations; by contrast, the strongest cost anti-stickiness occurs when all three drivers operate in the opposite direction. Our study suggests that additional economic determinants should be considered when assessing the impact of managerial expectations on cost behavior.
These studies document an association between asymmetric cost behavior and a number of financial variables, including prior period revenue decrease and the change in gross national product (Anderson et al. 2003), CEO’s option exercising behavior (a measure of managerial overconfidence) (Chen et al. 2013), the 2008–2009 economic downturn (Banker, Fang, and Mehta 2013), and changes in prior period sales, gross domestic product and order backlog (Banker et al. 2014).
These properties also differentiate our measure of managerial expectations from those of studies that rely on historical realizations of variables (e.g., change in GDP, order backlog, and change in prior sales). Furthermore, GDP as a proxy for managerial expectations does not capture the variation in these expectations across firms. Order backlog captures only one dimension of managerial expectations and results in a significant loss of data. Finally, as discussed by Banker and Byzalov (2014) and Banker et al. (2014), change in prior period sales likely captures both the amount of unused resources and managerial expectations. In our study, we show the incremental explanatory power of forward-looking statement tone over and above that of other measures used in prior studies.
Anti-sticky costs are those that show less of an increase when sales rise than a decrease when sales fall by an equivalent amount (e.g., Kama and Weiss 2013; Banker et al. 2014).
The current and future costs of adjusting resources (e.g., severance payments, training costs and other employee-related expenses, rent, utilities, and insurance) in response to changes in demand as well as the availability of unused resources carried over the current period have both been shown to impact the sign and magnitude of the cost asymmetry and to exacerbate or moderate asymmetric cost behavior (e.g., Noreen and Soderstrom 1997; Balakrishnan et al. 2004; Banker, Byzalov, and Chen 2013; Cannon 2014).
When the degree of unused resources available at the beginning of the period is high, managers may use these resources in responding to an increase in sales, thereby reducing the need to acquire additional resources. Conversely, managers who begin the current period with a low degree of unused resources will need to increase resources proportionally in the current period in response to an increase in demand.
Note that using a single measure of the combined effect of both the degree of initial unused resources and managerial expectations captures only a subset of cases when a high degree of unused resources (prior period sales decrease) is accompanied by managerial pessimism or when a low degree of unused resources (prior period sales increase) is accompanied by managerial optimism.
While prior period sales change may capture some aspects of managerial expectations, even after controlling for forward-looking statement tone, our finding that both measures are incrementally significant supports the ability of prior period changes in sales to proxy for the amount of unused resources and the ability of forward-looking statement tone to capture managerial expectations. This reasoning is further supported by the relatively low correlation between prior period sales decrease and forward-looking statement tone of −0.09.
The traditional view that variable and fixed costs mechanistically determine the relation between costs and activity level assumes that adjustment costs are either zero or infinite (Balakrishnan et al. 2014). By contrast, the revised view in the academic literature is based on the notion that the drivers of cost behavior are resource adjustment costs and deliberate management resource allocation decisions. Under this view, significant, yet finite, adjustment costs would result in asymmetric cost behavior (Banker and Byzalov 2014).
Note that the relative impact of managerial expectations on costs is likely to be stronger when demand rises than when demand falls. When demand falls and managers cut unused resources, the cost savings resulting from the reduction in resources is partly offset by the adjustment costs. However, when demand rises, the decision to increase resources results in adjustment costs, such as installation costs of new equipment, which in turn intensify the increase in total costs.
As noted previously, we extend the findings of Banker et al. (2014), who use a single measure to capture the combined effect of both the degree of initial unused resources and managerial expectations, by empirically examining the individual and incremental impact of each determinant.
As mentioned, if adjustment costs were fully negligible, then management would exhibit a symmetric response to rises and falls in demand. Furthermore, negligible costs would imply that management expectations should have little to no impact on cost behavior as managers would not need to consider current or future adjustment costs when making resource allocation decisions.
At the extreme, when the degree of unused resources is insignificant and current demand rises, a manager who needs to meet current demand will acquire additional resources, regardless of her expectations.
Management earnings guidance can also be used as a measure of management expectations. However, there are several limitations associated with this measure: (1) issuing earnings guidance is not a pervasive practice. For example, Hamm et al. (2018) document that during 1997–2012 23.6% of their sample issue guidance (see also Ball and Shivakumar 2008; Beyer et al. 2010; Rogers and Van Buskirk 2013). (2) Prior literature (e.g., Houston et al. 2010; Chen et al. 2011) has documented that firms that stop providing guidance have poorer prior performance, more uncertain operating environments, and fewer informed investors; accordingly, using earnings guidance might lead to a biased sample. (3) Managers may strategically use their guidance to manage analysts’ earnings expectations (e.g., Cotter et al. 2006; Koh et al. 2008; Kim and Park 2012; Ciconte et al. 2014). (4) Earnings guidance is a quantitative, short-term aggregate measure that does not indicate earnings components.
In a robustness test, we re-run our main tests using a measure of forward-looking statement tone based on the identification of words that more explicitly relate to demand (e.g., “sales,” “revenues,” “pricing”). Our results from this analysis are similar to those reported using the tone of the entire set of forward-looking statements.
Further validation of the ability of forward-looking statements to capture future events is provided by Muslu et al. (2015), who find that firms with poor information environments provide more forward-looking statements in their MD&As that investors find useful in predicting future earnings, and by Bozanic et al. (2018), who find evidence that suggests that the forward-looking statements in MD&A are positively associated with both market reactions and changes in analyst forecast accuracy.
For the lists of optimistic and pessimistic words, see http://www3.nd.edu/~mcdonald/Word_Lists.html. The use of the Loughran and Mcdonald (2011) word lists is pervasive in the literature. These lists are based on the word usage in a large sample of 10-K reports, which makes them particularly appropriate in the context of our study. As noted by Loughran and Mcdonald (2016), applying other dictionaries (such as those of Henry 2008, Harvard’s GI, or Diction) that are based on other types of financial disclosures (e.g., earnings press releases, conference calls) to 10-K reports can produce spurious results.
We repeat our analysis using the tone at either the beginning or the end of the year (instead of an average) as well as the lagged values of average tone and obtain similar results. Additionally, results using the abnormal tone measure developed by Huang et al. (2014) in the context of earnings press releases are qualitatively the same. As discussed by Davis and Tama-Sweet (2012), earnings press releases are subject to fewer regulations, compared to MD&A, and are thus more likely to be used strategically.
This finding suggests that managerial expectations, as reflected in forward-looking statement tone, are on average, unbiased. However, even if these expectations are partially impacted by psychological biases (in addition to available information), all of our hypotheses and inferences remain the same. A similar argument is made in Banker et al. (2014) (footnote 17): “Managerial optimism and pessimism may reflect either rational inferences about future sales based on available (favorable or unfavorable) information, or managers’ psychological biases, such as dispositional optimism (Weinstein 1980). Both interpretations lead to the same predictions.”
As discussed in the comprehensive review of this nascent literature by Li (2010b) and Lougharn and McDonald (2016), additional studies have used word lists to gauge tone in a variety of other contexts.
By including prior-period change in sales and the forward-looking statement tone as proxies for the degree of unused resources and management expectations, respectively, we can assess the incremental and distinct effect of each driver on cost asymmetry while controlling for the effect of the other driver.
Some studies use employee intensity as an additional measure of adjustment costs. However, Kama and Weiss (2013) indicate that the coefficient estimate of employee intensity is insignificant for large firms. Furthermore, Chen et al. (2012) show that the sign and significance level of employee intensity are not stable over time, presumably due to the increase in temporary labor in recent years. Our results are statistically indistinguishable when we add employee intensity as an additional control variable.
In estimating all our regression models, we cluster observations by firm and year to provide standard errors that are robust to autocorrelation and heteroscedasticity, as suggested by Petersen (2009).
In an untabulated analysis, we find no evidence of a systematic industry clustering within forward-looking statement tone quintiles. For example, the most pessimistic tone quintile has a slightly higher representation of energy, business equipment, and telecommunications, while the most optimistic quintile has a slightly higher representation of consumer nondurables, consumer durables, manufacturing, chemicals, and retail. Importantly, no industry has less than 15% representation in any given quintile. (The only exception is chemicals, with 11% of its observations in the lowest quintile.)
For brevity, we report only our findings using our primary measure of unused resources (prior-period change in sales). We obtain similar results using the two alternative measures of unused resources.
The value of γ2 associated with a high magnitude of adjustment costs (−0.312) is significantly more negative than (1) the value of γ2 associated with a low magnitude of adjustment costs (−0.100; the difference between −0.330 and − 0.100 is significant at the 0.01 level) and (2) the value of γ2 + ν2 associated with a high magnitude of adjustment costs; (−0.312 + 0.178 = −0.134; the difference between −0.312 and − 0.134 is significant at the 0.04 level).
We find that, incremental to EXP, the degree of cost stickiness increases with the real change in GDP but is unrelated to the change in order backlog. Similar to prior studies, order backlog is available for only 25% of our sample. Anecdotally, Apple Inc. notes in its 2016 10-K filing that “In the Company’s experience, the actual amount of product backlog at any particular time is not a meaningful indication of its future business prospects.” It further indicates that “backlog should not be considered a reliable indicator of the Company’s ability to achieve any particular level of revenue or financial performance.”