Abstract
We investigate for a positive relation between growth and the aggressiveness of accounting choices. The motivation is that this relation is an unexamined and very general implication from most existing theories and types of accounting choice. Note that the firms’ decision to use aggressive choices is determined by the joint presence of two factors: specific incentives to increase earnings such as maximizing compensation and also the ability to increase earnings. Growth captures the ability to increase income because an “aggressive” accounting choice will only increase earnings for growing firms and will have no effect or even decrease earnings for no-growth or negative growth firms. Thus, a ranking on growth can be potentially used as a powerful large-sample lens that summarizes the economic importance of many disparate accounting theories and settings of aggressive choice. The empirical tests use a sample of 260,000 observations over the last 50 years and a wide set of nine accounting choices to provide a comprehensive investigation of the hypothesized relation. Our main finding is that there is essentially no reliable relation between growth and aggressive accounting choice. A number of specifications and sensitivity analyses confirm this main finding. In additional tests unrelated to the growth argument, we find no reliable positive correlation between the aggressiveness of individual accounting choices, which implies that companies make no concerted efforts to increase income over the available set of accounting choices. Finally, changes in accounting choice are rare, which implies that accounting choice is a blunt and unwieldy instrument for most aggressive earnings objectives. The conclusion is that visible and long-term accounting choices are seldom used for achieving income-increasing objectives.
1. Introduction
Research on accounting choice is a prominent theme in modern accounting research; for example, Fields et al. (2001) find that 10% of the papers in the top three accounting journals address accounting choice questions. Accounting choice here means mostly visible and long-term choices such as depreciation and inventory methods rather than unobservable choices such as discretionary accruals. The most prominent strand of this literature investigates various theories of aggressive accounting choice in response to contractual and stock market motivations. Much of this research finds that opportunistic motivations are an important driver of accounting choice (see reviews in Fields et al., 2001, hereafter FLV; Watts and Zimmerman, 1990, and Beyer et al., 2010). However, a number of other studies find little support for aggressive accounting choice, for example, DeAngelo et al. (1994), Healy and Palepu (1990). In addition, existing evidence reveals that some accounting choices are highly sticky (Keating and Zimmerman, 2000), which suggests that they are rather blunt tools for achieving evolving earnings targets.
More generally, it has been difficult to assess the broad economic prevalence and importance of aggressive accounting choice because of various research design limitations. Specifically, FLV highlight two major shortcomings of the existing literature. Firstly, most existing studies examine the choice of a particular accounting method, while managers have access to multiple accounting choices to achieve their goals. Secondly, firms face multiple motivations with respect to accounting choice, while existing studies typically examine a single motivation; for example, compensation studies focus on examining the hypothesis that managers use accounting discretion to maximize compensation.
We use a novel setting to provide comprehensive evidence about the broad economic importance of aggressive accounting choice. Our investigation relies on the intuition that while most existing research concentrates on specific motivations for income-increasing accounting choice, a crucial and very general consideration in the ultimate decision about accounting choice is whether the choice will be actually “income-increasing”. The point is that most accounting choices are not intrinsically income-increasing or decreasing; they merely produce income-increasing or decreasing effects depending on rate of growth. For example, straight-line depreciation is income-increasing as compared to accelerated depreciation when the firm is growing but the income difference disappears in a steady-state firm, and actually reverses for firms in decline. This effect of growth rates on the income patterns of accounting choice is a well-known intuition in accounting, and examples of it are commonly found in most accounting textbooks (e.g., Revsine et al., 2005: 656). We assume that most of our readers are familiar with this intuition; for the interested reader, Appendix 1 provides a longer and more systematic exposition, including examples.
The main implication of this intuition is that – assuming income-increasing incentives are present – only growth firms have both the ability and the incentive to use “income-increasing” accounting choices, and therefore growth firms will have higher propensity to make income-increasing accounting choices. This observation implies that, holding income-increasing motivations constant, a ranking on growth should map into a strong ranking on aggressiveness in accounting choice. The growth argument is further bolstered by the fact that the growth construct likely captures not only the ability but also some of the incentives for aggressive choices, because growth firms typically need external capital and are generally more sensitive to earnings-based information (Skinner and Sloan, 2002). Finally, the strength of the observable relation between growth and aggressive accounting choice allows one to make inferences about the combined economic importance of the various and often unobservable income-increasing motivations.
The main advantage of the growth approach is its sweeping generality. Specifically, it allows much generalizability on three dimensions. Firstly, it applies to nearly all available accounting choices, which allows us to provide a comprehensive investigation over a wide set of nine accounting choices. In contrast, much of the prior research investigates just one or, at most, a few choices (e.g., pension and postretirement accounting assumptions by Fried et al., 2010; stock option expensing choice by Reppenhagen, 2010). Secondly, the growth argument applies to virtually all known and even conceivable income-increasing motivations. Regardless of whether the income-increasing incentives are based on contractual incentives (e.g., the bonus and debt covenant hypotheses) or capital market considerations such as maximizing stock price, growth firms always have greater ability to make income-increasing choices. Thus, holding income-increasing incentives constant, growth firms will be more likely to make income-increasing choices. The implication is that a ranking on growth can be thought of as a powerful lens that summarizes the economic importance of many disparate income-increasing motivations. Thirdly, the growth approach allows much generalizability in terms of data availability. Reasonable growth variables can be constructed for wide cross-sections and long time series, which ensures that the results are not driven by various sample and data selection biases. In contrast, much other research on accounting choice is limited by small samples and poor proxies for the underlying incentive variables; for example, studies on the bonus and debt covenant hypotheses typically employ samples of several dozen to several hundred observations and struggle with the usually unobservable bonus and debt covenant thresholds.
Our empirical analysis aims to exploit and embody the generality of the growth argument. Specifically, we identify a battery of nine accounting choices that span a wide spectrum of firm activities and test for a positive relation between growth and the aggressiveness of these choices over a large cross-section of firms comprising 260,000 observations over the last 50 years. Our main result is that there is essentially no reliable relation between growth and income-increasing accounting choices. Some individual choices show a modest positive relation with growth but the results go in the predicted direction about as often as they go in the opposite to the predicted direction. In addition, the identified relations display little economic importance or are non-monotonic. A number of sensitivity analyses and various alternative specifications leave the main results largely unchanged.
Two additional investigations, which are independent of the growth argument and construct, corroborate our main results. Firstly, we expect that firms that have income-increasing goals will be motivated to take an income-increasing stance over several of the available accounting choices and therefore we examine for a positive association between the aggressiveness of individual accounting choices. However, we find no reliable relation between the aggressiveness of individual accounting choices. Most correlations are economically small and positive correlations occur about as often as negative correlations. Secondly, using our broad sample we investigate the frequency of changes in accounting choice because, for accounting choice to be useful for achieving strategic earnings objectives, changes in accounting choice have to be relatively frequent. However, we find that changes in accounting choice are rare; for example, the frequency of annual changes is on the magnitude of 1–2%, which implies that for the average firm a change happens only once in 50–100 years. Such frequencies imply that accounting method choice is rarely used for achieving short- and medium-term earnings objectives such as maximizing proceeds from stock issues, hitting bonus targets or avoiding debt covenant violations.
Our conclusion is that opportunistic motivations are simply not that important for the type of accounting choices we consider. We study accounting choices that are primarily visible and long-term, so opportunistic choices are more likely to be detected and unraveled by the various stakeholders of the firm. Thus, these results imply that opportunistic choices are more likely for less visible and shorter-horizon settings, such as management of accruals to beat earnings benchmarks. The combined impression from these results also suggests that the existing literature paints a picture of aggressive accounting choice, which is too strong given the underlying broad prevalence of such behavior. A possible explanation for the inordinately strong existing impressions is the prevalence of well-known biases against the null. As explained and illustrated by Burgstahler (1987) and Bamber et al. (2000), authors are less likely to write up papers that do not reject the null, and editors and referees are less likely to encourage the publication of such findings. The outcome from this process is that often our impression of existing results is too strong given the true nature of the underlying evidence.
The remainder of the paper is organized as follows. Section 2 describes the theory and relation to existing research. Section 3 discusses the empirical specifications and presents the results. Section 4 provides a discussion of the results. Section 5 concludes.
2. Theory and relation to existing research
The preceding section offers a broad outline for using the growth construct to investigate for aggressive accounting choices. In this section, we use a simple example to illustrate and expand the logic of this argument. We start with a basic scenario where a population of 1000 firms all have the same uniform motivation to increase income (e.g., boost stock price) using depreciation method choice. Half of these firms are no-growth firms and since both methods produce the same result, they split randomly into straight-line and accelerated depreciation users. The other half are growth firms and since for them the straight-line method produces higher income, they all choose straight line. A research design coding the accelerated choice observations as 0 and straight-line as 1, and ranking the firms on growth will produce the following results (in expectation):
Thus, a ranking on growth produces a clear positive relation with the aggressiveness of accounting choice. In addition, note that the “boost stock price” motivation is in reality often unobservable or is measured with error. However, based on the positive correlation between growth and accounting choice, one can infer that some sort of motivation for aggressive choice exists.
This baseline example easily generalizes to more complicated situations, with more than one motivation for increasing income and where strength of the motivation varies across firms, so that not all firms behave opportunistically. For example, let us assume that there is an unknown number and type of motivations for income-increasing behavior but we know that as a net result 60% of the firms will try to increase income if they can. We also know that the firms are half growth and half no-growth, and that the rate of growth is independent of the motivations for increasing income. The result is that all no-growth firms are again indifferent between the choices and for growth firms 40% choose randomly and 60% choose straight-line, which produces the following observable results (in expectation):
Again, based on the positive correlation between growth and aggressive accounting choices, one can infer that some sort of income-increasing motivations exist in the sample. In addition, a comparison of the two sets of results reveals that from the strength of the relation between growth and aggressive choice one can draw inferences about the combined economic importance of the underlying motivations. A weak statistical and economic relation between growth and aggressive accounting choice reveals that the underlying economic motivations for aggressive reporting must have been weak as well.
It is also probably clear that this set-up can be further generalized on many dimensions and the basic result still obtained. The only thing that can make this result disappear is a strong negative correlation between growth and the opportunistic motivations to increase income. However, this scenario is highly unlikely. In fact, existing empirical evidence suggests that growth firms have stronger incentives to increase earnings (e.g., Jensen and Fuller, 2002). The intuition for this result is straightforward. Growth firms are expanding their asset base and their operations, so they are typically net users of cash and are thus continually raising debt and equity capital. Since capital markets consider earnings to be the most important accounting variable, growth firms are likely to be more sensitive to earnings management considerations. Specific evidence along these lines is provided by Dechow et al. (1996), who find that firms with Securities and Exchange Commission (SEC) accounting enforcement actions have much higher market-to-book ratio (their proxy for growth) as compared to a control sample. In a similar vein, Skinner and Sloan (2002) find that growth stocks are much more sensitive to earnings surprises than value (or low-growth) stocks and Madhogarhia et al. (2009) show that that growth firms tend to manage their earnings upward and downward more aggressively than value firms. Growth firms are also “high-risk, high-reward” firms, which suggests that they are more likely to be subject to contractual-based incentives for earnings management, for example, under the bonus and debt covenant hypotheses. Thus, a ranking on the growth variable seems attractive because it lines firms up on both the broad ability and many of the specific incentives for aggressive earnings management.
The investigation for a positive relation between growth and aggressive accounting choice also seems promising because it offers several unique advantages. Firstly, the predicted relation between growth and accounting choice is quite general in the sense that it applies to most accounting choices that affect earnings. Thus, in comparison to research that examines more specialized and limited accounting choices (e.g., studies on the choice of last-in, first-out (LIFO) versus first-in, first-out (FIFO) accounting), our setting offers broad evidence and much generalizability. As can be seen later in the paper, this setting allows us to use a wide set of nine accounting choices, which surpasses anything in comparable research (e.g., see Watts and Zimmerman, 1990 and FLV).
Secondly, the predicted relation is also quite general in the sense that it applies to almost any conceivable theory of aggressive accounting choice. For example, our setting readily accommodates well-known theories such as the bonus and the debt covenant hypotheses on accounting choice. But it fits just as well a broad class of theories that invoke some form of “functional fixation”, meaning that capital markets rely uncritically on earnings and managers use income-increasing choice to produce higher earnings and achieve favorable capital markets outcomes (such as high initial public offering (IPO) price or prolonged periods of favorable prices at which to exercise employee stock options). Similar arguments and implications apply to still other settings, where managers make income-increasing choices to achieve favorable outcomes with suppliers, customers, employees and various other stakeholders of the firm.
Thirdly, note that the relation between growth and accounting choice is predicted to be monotonic not only across growth categories (growth, steady-state, decline) but within categories as well; for example, high-growth firms are expected to make more aggressive accounting choices than low-growth firms. Thus, assuming income-increasing incentives exist, a simple unconditional ranking on the algebraic level of growth provides a clean ranking on incentives to use income-increasing choices, and allows for simple and powerful empirical tests later in the paper.
Fourthly, the growth approach allows one to marshal very large samples in which to study the broad economic importance of accounting choice, for example, our sample is on the magnitude of 260,000 observations over the last 50 years. This generality is in contrast to the typical approach in research on accounting choice, which utilizes samples on the magnitude of a few dozen to several hundred observations, often concentrated in certain industries or time periods.
Finally, it seems that the relation between growth and accounting choice has not been studied before. In fact, we could not identify a single existing study that specifically investigates this relation, and more generally the theme of growth is almost completely absent from the literature on accounting choice. For example, Watts and Zimmerman’s (1990) review of accounting choice includes no reference to growth at all. FLV includes references to 140 studies but mentions growth only twice, once as a pure control variable and once as an interactive variable in explaining banks’ capital-raising responses (Collins et al., 1995). Perhaps the only study that provides some but indirect and limited evidence on the importance of growth is Skinner (1993), where two of his proxies for firms’ investment opportunity set, level of research and development (R&D) and Tobin’s Q, can be also viewed as proxies for growth. Skinner finds mixed results for the relation between these variables and three measures of accounting choice; however, this evidence has to be viewed with caution because it is subject to several important limitations, especially the indirect nature of the measures of growth and small sample size (300–500 observations over one year of data).
3. Empirical specification and results
As discussed above, our goal is to provide a comprehensive examination of the relation between growth and accounting choice. Thus, we aim for a comprehensive measure of growth, a wide set of accounting choice variables and a large sample. Our principal measure of growth is based on sales growth. The reason is that sales growth is the driver behind virtually all measures of firm growth, and is likely to be strongly related to other possible measures of growth (e.g., growth in specific types of assets or total assets), especially in the long run. Later in the paper, we provide additional results for alternative measures of growth. Specifically, our measure is defined as the firm’s organic sales growth rate, which is the firm’s nominal growth adjusted for the effect of mergers and acquisitions (M&As). The adjustment for M&As is necessary because the idea behind using sales growth is that the firm is expanding its asset base by bringing in new assets in increasing amounts and thus keeping the average asset age below the tipping point beyond which the effects of income-increasing choices are beginning to revert. However, while M&As clearly increase sales, their effect on average asset age can go either way, and therefore an adjustment for this type of growth is needed. In any case, results are similar using nominal growth in sales (unadjusted for M&As).
In operational terms, adjusted sales (AdjSales) are defined as Compustat item 6 (Sales) minus item 249 (Acquisition – sales contribution). 1 Since it is not clear what the appropriate horizon for the growth measure should be, initially we employed two alternative measures of growth in year t: Growth1 is defined as AdjSalest/AdjSalest−1 and Growth3 is defined as (AdjSalest+1/AdjSalest + AdjSalest/AdjSalest−1 + AdjSalest−1/AdjSalest−2)/3). The short-horizon measure has the advantage of being a more sensitive indicator of changes in the firm’s current growth rate, while the longer-horizon measure is less sensitive but is more representative of the firm’s longer-term growth rate, which is the more relevant construct with respect to the type of accounting choices we consider. Growth1 and Growth3 are both winsorized at 0.1 and 10 to exclude the influence of extreme observations. In untabulated results we find that the results for Growth1 are very similar to the results for Growth3, and therefore for parsimony we only include and discuss the results for the more relevant Growth3 variable in the paper.
In the selection of accounting choice variables, we search Compustat’s US annual data to include all possible information. The result is nine variables that cover a wide set of accounting choices, where all variables are coded so that higher values mean more income-increasing effect.
Depreciation method. Depreciation method is commonly regarded as an important accounting choice that has a large effect on earnings. We use Compustat footnote 15 (AFTNT15), which is related to item 196 (Depreciation, Depletion, and Amortization). We set our variable DeprMeth to 2 if AFTNT15 = “TS” or “TX” (straight-line method), 1 if AFTNT15 = “TB” or “TU” (a mix of straight-line and accelerated method) and 0 if AFTNT15 = “TC” or “TV” (accelerated method).
Depreciable lives of property, plant and equipment. The depreciable life of assets is another important parameter in determining the amount of depreciation, where firms with longer depreciable lives report higher income as long as they are growing. We first estimate the average depreciable life of property, plant and equipment (PPE) for a firm-year as item 7/(item 14 – item 65), where item 7 is “Property, Plant and Equipment -Total (Gross)”, item 14 is “Depreciation and Amortization” and item 65 is “Amortization of Intangibles”. Our variable to measure the aggressiveness of the depreciable lives choice (DeprLife) equals 1 if our estimate of the depreciable life is above the two-digit Standard Industrial Classification (SIC) industry median in the same year and 0 otherwise. Industry adjustment is necessary because there is substantial variation in depreciable lives across industries and we want to capture discretionary aggressive choices controlling for business fundamentals.
Full-cost versus successful efforts (oil exploration). The full-cost method of accounting allows firms to capitalize and amortize most exploration costs, while the successful efforts method prescribes immediate expensing of the costs of dry holes. Thus, the full-cost method represents a deferral of costs and results in higher reported income as long as the firm is growing. Correspondingly, the variable FullCost equals 1 if AFTNT31 = “TH” (full-cost method) and 0 if AFTNT31 = “TG” (successful efforts).
Purchase versus pooling accounting in acquisitions. SFAS 141 mandates purchase accounting for all acquisitions after 2001, so this variable is only available until 2001. For years before 2001, Pooling equals 2 if AFTNT37 = “AI” (pooling method for M&A), 1 if AFTNT = “AE” (a combination of purchase and pooling) and 0 if AFTNT = “AP” (purchase method). Note that the pooling versus purchase choice is different from the other accounting choices considered here in the sense that it creates permanent rather than temporary and reversible differences, and therefore we view the Pooling variable as more of a calibration variable rather than one of our main choice variables. The reason is that the pooling choice creates a permanent reduction in expenses, so that all firms have an incentive to use pooling regardless of their growth rate. Thus, one would expect a relation between pooling and growth only if growth firms have higher incentives (but not necessarily differential ability) to report high income. This relation is also muddled by the fact that usually the most important income-increasing aspect of the pooling choice has to do with avoiding the amortization of goodwill. To the extent that many stakeholders ignored the amortization of goodwill effect on income (e.g., goodwill amortization was rarely included in pro-forma definitions of earnings), the incentive to choose pooling is also decreased. Thus, we include the Pooling variable as more of a baseline variable for what the relation between growth and accounting choice is in the absence of the differential ability to report higher income.
Inventory valuation method. Using FIFO as opposed to LIFO accounting results in lower cost of goods sold and higher income as long as the firm is growing and increasing its inventory levels (and prices are increasing). Thus, Inventory equals 2 if item #59 = 1 (FIFO method), 1 if item 59 = 4 (a combination of FIFO and LIFO) and 0 if item 59 = 2 (LIFO method). We have somewhat mixed expectations with respect to the Inventory variable. On one hand, inventory choice produces large effects on income for many firms, so we expect it to be a powerful variable in our investigation. On the other hand, we expect that the relation between growth and inventory choice is relatively weaker because the book-tax conformity rules impose substantial real costs on aggressive inventory choice.
Capital versus operating leases. Operating leases recognize as expense the lease payment, while capital leases recognize imputed interest on the lease obligation and depreciation for the leased asset. While the total expense over the life of the lease is the same under the two methods, operating leases show lower expenses and higher income in the beginning of the lease. Assuming that the firm is growing and expanding its lease base, the average lease will be young and structuring leases as operating is the income-increasing accounting choice. For our measure of this choice, we first calculate the ratio of the capital lease’s obligation to the imputed value of the operating lease’s obligation as item 84/PV(item 96, item164, item 165, item 166, item 167), 2 where all the items are from Compustat and PV is the present-value operator (see Ge (2006) for more detail). For simplicity, we use a 10% discount rate for all firms. Lease is set to 1 if the capital to operating lease ratio is below the two-digit SIC industry median in the same year and 0 otherwise. Here and for all measures that follow, we use industry adjustment for the same reasons as for depreciable lives above.
Rate of compensation increases (pensions). Firms with defined benefit compensation plans need to project their future rate of compensation increases to calculate their pension expense. Using a lower-than-appropriate rate of compensation increases acts as a deferral of pension costs because it reduces current Service Costs but will result in higher future expenses through the amortization of actuarial losses due to future compensation and pension obligation rising faster than provided for. Thus, a lower rate of assumed increases in compensation reduces the pension expense and increases earnings in the current period, as long as the firm is growing. Therefore, Pensions1 equals 1 if item 335 (the rate of compensation increases) is below the two-digit SIC industry median in the same year and 0 otherwise.
Expected rate of return for pension assets. Using an expected rate of return on pension assets is an approximation for the actual long-run rate of return on these assets, with a built-in catch-up effect in terms of the amortization of actuarial gains or losses. So, if a firm uses a higher than warranted expected rate of return, this will reduce present expense at the cost of increased future amortization of actuarial losses. Thus, choosing a high discount rate is a deferral of expenses and increases earnings (for growth firms). Hence, Pensions2 is set to 1 if item 336 (expected rate of return on pension assets) is above the yearly median and 0 otherwise. Note that the investment made by firms in the same industry in pension assets does not have to be similar. For this reason we benchmark the expected rate of return relative to all other firms in the same year, rather than to firms in the same industry only.
Discount rate for pension expense computation. The level of the discount rate slices the estimated future pension benefit cash payments into present-value Service Costs and future Interest Costs. Note that the ultimate sum of Service Costs and related Interest Costs is by definition the same for different discount rates (because they are derived from the same expected future cash outlays). Thus, using a higher-than-appropriate discount rate minimizes present expense at the cost of higher future expenses or, in other words, acts as a deferral of costs that increases current earnings (but only for growth firms). Therefore, we set Pensions3 to 1 if item 246 (pension expense discount rate) is above the economy-wide median in the same year and 0 otherwise.
Our final sample consists of 264,003 firm-years covering fiscal years 1951–2004. Because not all of the nine accounting choices are available or relevant for every firm or over all periods, sample size varies greatly in the tests. Our empirical specifications rely mostly on portfolio analysis and regressions. We start with portfolio analysis to provide a direct feel for the economic magnitude of the results and to identify possible non-linearities in the hypothesized relations. We follow up with regression analysis for better power and flexibility with statistical testing, especially the ability to do multivariate analysis.
Before we proceed to our empirical tests, we carry out a simulation analysis of the expected relation between growth and accounting choice. The purpose of the simulation analysis is to provide evidence about the statistical power of our tests conditional on the economic strength of the hypothesized relations. We start with all firm-years with Growth3 data in our sample. For each firm-year observation, we then simulate an accounting choice dummy variable that equals 1 (i.e., the income-increasing choice) with a probability P, which is an increasing function in Growth3, and equals 0 (i.e., the income-decreasing choice) with a probability 1–P. Using this simulated data, we then perform portfolio and regressions analysis similar to the actual tests later in the paper.
In Appendix 2, we present three scenarios of simulation, namely Low, Medium and High aggressiveness of accounting choice. In the Low scenario, firms are first sorted by the value of Growth3 and then the firm with the lowest Growth3 is assigned a P of 50% (no aggressiveness in accounting choice) and the P of the firm with the highest Growth3 is 55%. 3 The P of firms in between is linearly increasing in the rank of their Growth3 variable from 50% to 55% to reflect the fact that higher growth firms have higher incentives to use aggressive choices. Note that the aggressiveness modeled in the Low scenario is economically minimal because the highest growth firm has only 5% higher probability of making the aggressive choice as compared to the lowest growth firm, although the highest growth firms (in the top quintile of Growth3 in Appendix 2) have a growth rate of nearly 50%, which implies that making the aggressive choice would lead to great increases in reported earnings. We then sort firms into quintiles based on Growth3 and examine the accounting choice values across the quintiles. Across the quintiles, the mean value of the accounting choice dummy increases monotonically from 0.50 to 0.54. In the regression of Growth3 on the accounting choice dummy, the dummy loads up significantly with a coefficient of 0.023 (t = 6.09).
In the Medium simulation, we change the upper bound of P from 55% to 60%. As one might expect, the accounting choice spread over quintiles doubles and the coefficient on accounting choice is now 0.048 (t = 12.68). The results for the High simulation, which uses an upper bound for P of 70%, show that the economic magnitude of the relation between growth and accounting choice becomes even stronger. Summarizing, the simulation results indicate that even when the impact of growth on the aggressiveness of accounting choice is minimal, we find reliable evidence of a positive relation between growth and aggressive accounting choice in our portfolio and regression settings. This evidence implies that our setting offers great power to detect the hypothesized relations.
3.1. Main results
Table 1 presents summary statistics about sample firm characteristics and the nine accounting choice variables. We have Growth3 observations for almost the entire universe of Compustat firms, as evidenced by the huge variation in firm size and the large sample size (over 218,000 observations). However, there is a great variation in sample size for the accounting choice variables. Four of these variables (DeprMeth, DeprLife, Inventory and Lease) are widely represented, spanning sample sizes from about 121,000 to 221,000 observations. As one might expect, there is a dramatically lower number of observations for FullCost (about 11,000) and Pooling (about 24,000). The coverage of pension variables is between these two extremes, ranging between 25,000 and 50,000 observations.
Summary statistics.
This table shows the summary statistics for the sample firms. Standard Industrial Classification (SIC) is the four-digit SIC code of the firm. Assets is the book value of assets (#6 of Compustat annual file). Sales is #12. Sales_acq is the number of sales that are due to the acquisition (#249). PPE is the gross amount of property, plant and equipment at the end of the fiscal year (#7). Inventory is the value of inventory at the end of fiscal year (#3). The accounting choice variables are defined as in Section 3 of the paper. Growth3 is the three-year average of organic growth in sales and is calculated as [(Salest+1 − Sales_acqt+1)/(Salest − Sales_acqt) + (Salest − Sales_acqt)/(Salest−1 − Sales_acqt−1) + (Salest−1 − Sales_acqt−1)/(Salest−2 − Sales_acqt−2)]/3, winsorized at 0.1 and 10.
The mean for Growth3 is 1.25, indicating an average three-year sales growth rate of 25%. The average DeprMeth is 1.72, indicating that the majority of firms in our sample are using the straight-line depreciation method, consistent with existing evidence (e.g., Mrakovcic, 2001). DeprLife and several other variables have a mean of close to 0.50 because they are dummy variables based on in-sample sorting. About 49% of our sample oil firms use the full-cost method and the rest use the successful effort method. The mean value of Pooling is 0.25, suggesting that most of the sample firms use the purchase method for M&A deals.
We start the presentation of our main results with a portfolio approach in Table 2, which shows the mean values of the accounting choice variables for quintiles sorted on growth. In this case, the presentation of means is close to providing a sufficient statistic for these variables, since they are all ordinal. Note that the results in Table 2 are all based on quintile ranking on the growth variable. The advantage of this specification is consistency of quintile determination across variables and thus easy comparability and interpretation of the results across the choice variables. The disadvantage is possible clustering of observations across quintiles, particularly for variables that have low numbers of available observations. Since untabulated results indicate that the clustering issue has no material effect on the results, we choose the consistent determination of portfolios for the presentation of the main results in the paper.
Accounting choices by quintile of growth portfolios.
This table shows the mean values of accounting choice variables for quintile portfolios sorted on growth. Growth3 is the average organic sales growth over last year, current year and one year ahead. The rest of the variables are as defined in the text.
An examination of Table 2 reveals essentially no reliable relation between growth and accounting choice. For example, consider the results for the depreciation method; the quintile means for DeprMeth do not show any discernible pattern of increases or decreases. As compared to the benchmark simulation results, the variation across DeprMeth means also seems economically trivial, with a low of 1.70 and a high of 1.73. Much the same picture as DeprMeth is observed for FullCost, Lease and Pensions3. The rest of the variables exhibit some discernible patterns but most of them are not of the “smoothly increasing” or “smoothly decreasing” type, and in general it is difficult to identify any pattern of consistency across the results. Two accounting choice variables, Inventory and Pensions1, exhibit U-shaped relations with growth, that is, the extreme high- and low-growth portfolios are more likely to make “income-increasing” choices as compared to the middle quintiles. 4 However, two other variables, DeprLife and Pensions2, exhibit inverted U-shaped relations with growth, that is, the extreme portfolios make less “income-increasing” choices than the middle portfolios.
The only variable that exhibits a pronounced pattern consistent with expectations is the pooling versus purchase choice in M&A accounting. The mean for Pooling increases strongly and monotonically across quintiles, with a low of 0.12 in quintile 1 and a high of 0.32 in quintile 5. This variation across quintiles is clearly economically substantial, for example, it exceeds the corresponding variation for the “High” simulation scenario. In addition, since Pooling is a dichotomous variable, these results imply that high-growth firms are nearly three times more likely to use pooling accounting than low-growth firms. Thus, the Pooling results confirm our conjecture that growth firms have stronger motivations to make income-increasing choices, in spite of the fact that in this case they have no differential ability to do so. The implication is that for the rest of the examined accounting choices, where there is also differential ability to increase income, the absence of a relation between growth and aggressiveness of the choices suggests that these choices are not used for aggressive reporting purposes.
Further and more careful examination of the portfolio results in Table 2 does not change the initial impressions. For example, one could argue that it is reasonable to discount the first quintile results because these firms have declining sales (an average three-year decline of 8%), and are thus “different”. Following this line of reasoning, one could then argue that the important Inventory variable exhibits a moderately strong positive relation between growth and accounting choice (a spread of 0.29 between quintiles 2 and 5). However, applying the same logic to the rest of the variables does not produce any other reliable positive relation between growth and choice, while it produces two choice variables with clear negative relations to growth (DeprLife and Pensions2).
We next turn to the regression approach and results. Our regression specification has two noteworthy features. Firstly, since growth drives accounting choice, the more obvious specification would be to regress accounting choice on growth. Instead, we opt for reverse regressions where growth is the dependent variable and the accounting choices measures serve as independent variables. The main advantage of this specification is that using the same dependent variable allows consistency and comparability across univariate regressions, plus we can have multiple accounting choices in one regression. Secondly, we employ a regression specification that adjusts for both cross-sectional and time-series dependencies in the dependent growth variable. Cross-sectional dependencies arise because of common industry or economy-wide factors, and are a pervasive feature of economic and accounting data. In addition, our growth observations have a time-series dependence because adjacent three-year growth observations have overlapping years of growth included in their computation. We use a Fama–MacBeth specification to control for cross-sectional dependencies and use a Newey and West (1987) correction to control for the remaining time-series dependencies. 5 More specifically, we first run cross-sectional regressions by year. The time-series means of the estimated coefficients are reported and the standard errors calculated using the variation of the coefficients with adjustment for auto-correlation are used to obtain the t-statistics. To provide some feel for the effect of these adjustments, we include the number of yearly cross-sections and the average number of observations in these cross-sections in the reported results.
Table 3 presents the regression results. In univariate regressions (columns 1–9), three out of nine accounting choice variables are insignificant, three are significantly negative at the 5% level (DeprLife, Pensions2 and Pensions3) and only three are significantly positive (Pooling, Inventory and Pensions1) – not what one would expect from a reliably positive relation between growth and income-increasing accounting choices.
Regressions of growth on accounting choices.
This table shows the regression results of Growth3 on accounting choices. Growth3 is the three-year average of organic growth in sales, winsorized at 0.1 and 10. The accounting choice variables are defined in Section 3 of the paper. Regressions are Fama–MacBeth regressions with Newey-West adjusted standard errors with a lag of 2.
Note: *, **, and *** represent statistical significance in two-tailed tests at the 0.10, 0.05, and 0.01 level, respectively.
Even if one is resigned to looking for a positive relation between growth and accounting choice for individual variables only, the results are not encouraging. Two of the three variables that load up positive and strong are Pooling and Inventory. As discussed earlier, ex ante these variables are less of a good fit for the growth story. In addition, a consideration of the magnitude of the coefficients reveals that the economic significance of the three variables with positive coefficients is close to negligible. Specifically, considering the magnitude of the slope coefficients (all three are at about 0.05) and the typical change in the ordinal choice variables (1) suggests that the corresponding induced variation in the dependent variable is about 0.05, which seems rather small considering the total sample variation in growth (the standard deviation of Growth3 is 0.88 in Table 1). The magnitude and the significance of the coefficients in Panel A (Table 3) are also at or below those for the “Low” and “Medium” aggressiveness simulation results in Appendix 2, which again suggests small economic importance.
Panel A (Table 3)also presents the results from two multivariate specifications. Since the number of available observations varies greatly across the choice variables, including all variables in one regression is not helpful because the resulting set of available observations is extremely small. Instead, we choose two compromise alternatives, where the resulting joint set of observations is still reasonable. The first specification combines the four variables with the widest coverage (DeprMeth, DeprLife, Inventory and Lease) in a joint set of about 40,000 observations. The second multivariate specification combines the three pension-rate variables for a joint set of about 20,000 observations. The results from these multivariate regression are much like those from the univariate regressions, with six out of seven coefficients keeping the same sign and significance and one coefficient (DeprMeth) becoming marginally positive.
The absence of a reliable relation between growth and accounting choice seems somewhat surprising given the strong ex ante arguments that growth captures both the ability and many of the incentives for earnings manipulation. A possible explanation is that aggressive behavior exists but it is confined to limited settings with pronounced incentives for aggressive reporting. Accordingly, we seek to sharpen these tests by interacting the growth variable with three other variables, which the existing literature suggests as more direct and specific proxies for incentives for earnings manipulation. The first measure captures the firm’s ex ante need for financing from Dechow et al. (1996), defined as (cash flow from operations – capital expenditures)/current assets. We choose this measure because Dechow et al. show that security issues are the most common motivation for firms in their sample of SEC accounting enforcement actions and because this variable provides the most reliable differentiation between their sample and control firms. In addition, this variable can be calculated for a wide sample of firms, which is important for our investigation. The second measure of earnings management incentives is financial leverage (total debt to assets), also motivated by Dechow et al. (1996), where it provides a reliable differentiation between sample and control firms. This variable is widely used as a proxy for contractual-based incentives, specifically as a proxy for tightness of debt covenants. Note that while Dichev and Skinner (2002) find that the leverage variable has only moderate correlation with the actual tightness of debt covenants, the leverage variable is a reasonable compromise for our setting because more precise measures are unavailable for the vast majority of firms and years in our sample. The third variable is the market-to-book ratio. As mentioned earlier, Skinner and Sloan (2002) show that stocks with high market-to-book are much more sensitive to earnings surprises, and therefore have stronger incentives for earnings manipulation. Market-to-book can be also viewed as an alternative proxy for the growth construct itself, where market-to-book captures expected long-term growth rather than the more immediate and realized growth specification used otherwise in the paper.
Table 4 provides the results for the ex ante financing variable. We run the same regressions as in Table 3 but here we also interact all choice variables with a dummy for high values of the financing variable. Specifically, the financing variable is coded as 1 if the underlying continuous measure of financing strength given above is above the median, and as 0 below the median. Thus, when the financing dummy is 0, we expect that firms have high financing needs and correspondingly stronger incentives for earnings manipulation. Therefore, the coefficients on the accounting choice variable should be all positive, while the interactive dummies should be negative, because the low financing needs firms have lower incentives for earnings manipulation.
Regressions of growth on accounting choices and external financing needs.
This table shows the regression results of Growth3 on accounting choices and external financing needs. Growth3 is the three-year average of organic growth in sales, winsorized at 0.1 and 10. The accounting choice variables are defined in Section 3 of the paper. LowExfin is a dummy variable that equals 1 if a firm’s free cash flow (defined as cash flows from operations minus capital expenditure and divided by total assets) is above median and zero otherwise. Regressions are Fama–MacBeth regressions with Newey-West adjusted standard errors with a lag of 2.
However, an inspection of Table 4 reveals that the results for firms with high financing needs are in line with the main results above, with most of the variables keeping their sign and significance. In addition, the coefficients on the interactive dummies are more often positive than negative, inconsistent with the incentive expectation. An additional and more extreme version of this analysis using only the top and bottom 20% of the firms to define the financing dummy does not change the tenor of the results. We repeated the same tests by using leverage and book-to-market as alternative incentive variables, both in the 50%/50% dummy specification and in the more extreme 20%/20% specification. These results were also in line with the main results, and are for parsimony omitted here. 6 Overall, sharpening the research specification by using various more specific incentive variables has little effect on the results.
3.2. Robustness of the main results
In this section we check for alternative test specifications and probe the robustness of the results using different subsamples. Like in the multivariate specifications above, we focus on DeprMeth, DeprLife, Inventory and Lease to make sure we have enough firms in the subsample tests, as these accounting choices apply to most firms. Specifically, we examine the following subsamples.
Industrial firms. Some of the accounting choices are more applicable to industrial firms. For instance, choices of depreciation and inventory methods may affect earnings more for industrial firms than firms in service industries. Therefore, we examine the relation between accounting choices and growth for a subsample of industrial firms (firms with SIC codes between 2000 and 3999).
PPE-intensive firms. We also consider a subsample of PPE-intensive firms, defined as firms with the amount of PPE greater than 80% of total assets. To the extent that depreciation is likely to be a more important determinant of income, we expect a more positive relation between income-increasing depreciation accounting choices and growth.
Inventory-intensive firms. We examine inventory-intensive firms defined as firms with more inventory than the gross amount of PPE. The motivation is that the choice of inventory accounting is more relevant for these firms.
Large firms. A consideration of large firms (firms with market value of equity greater than US$100 million) helps to ensure that the lack of relation between growth and accounting choices is not due to the idiosyncratic nature of small firms.
Firms with low versus high profitability. Level of profitability is possibly associated with firms’ sensitivity to income-increasing behavior. We use a cutoff of 5% of return on assets (ROA) to specify the low versus high profitability subsamples.
Early versus late years in the sample. It is also possible that income-increasing behavior is a function of time; for example, contractual incentives to increase income have potentially increased in the last 10–20 years with the proliferation of performance-based managerial compensation. We use a heuristic cutoff of year 1990 to split the sample into early and late years. This cutoff provides a reasonable tradeoff between ensuring a comparable number of cross-sections and a comparable total number of observations between the two samples, that is, the “late years” sample has fewer cross-sections but many more available observations per year.
The results for all of these specifications are presented in Table 5. An examination of Table 5 reveals that although there is some variation in specific samples and regressions, the tenor of the results remains the same. The coefficient on Inventory is always positive and significant and the coefficient on DeprLife is always negative and significant. In addition, the magnitude of the coefficients does not vary that much and there is little pattern consistent with the predicted incentives. For example, the coefficient on Inventory is not much larger or stronger in the inventory-intensive sample. The coefficient on Lease largely remains small and insignificant throughout all specifications. There is more variation in the coefficient on DeprMeth, which bounces between significantly positive, insignificant and significantly negative. However, again there is not much discernible pattern in this variation; for example, it is hard to make a coherent argument for why the DeprMeth coefficient becomes positive and significant for Industrial firms but is negative and significant for firms with high PPE as a percentage of assets. Average R2 values remain low, all in the 0.01–0.02 range. Overall, the results from these robustness checks largely confirm the tenor of the primary results.
Regressions of growth on accounting choices – subsamples.
This table shows the regression results of Growth3 on accounting choices in various subsamples. Growth3 is the three-year average of organic growth in sales, that is, growth adjusted for the effect of acquisitions. Growth3 is winsorized at 0.1 and 10. The accounting choice variables are defined in Section 3 of the paper.
PPE: property, plant and equipment; ROA: return on assets
*, **, and *** represent statistical significance in two-tailed tests at the 0.10, 0.05, and 0.01 level, respectively.
Firms with low volatility of growth. Finally, we check the robustness of our results by focusing on a subsample of firms with low volatility of their growth rate. The motivation is that firms with low volatility of their growth rate face less uncertainty in making their accounting choices with respect to their growth. A related motivation is that we use realized rates of growth, while one could argue that the more relevant construct here is some measure of expected growth. Using a sample of firms with low volatility of growth ensures that there is a better match between expected and realized measures of growth. In operational terms, we keep firms with at least 10 years of data and calculate the standard deviation of growth over this period. Only firms with volatility of growth in the bottom one-third are used in the tests. The results in Table 6 are mostly consistent with previous results, although they are marginally more in line with the hypothesized positive relation between growth and aggressive accounting choices. Specifically, there is one more positive and significant variable (Lease) and two previously negative and significant variables have become insignificant. However, a consideration of the magnitude of the coefficients and R2 again suggests that these relations remain rather weak.
Alternative measures of growth. Recall that our main tests rely on sales growth as a primary measure of firm and asset growth. This specification can be problematic if some firms experience asset-specific growth, which is considerably different from sales growth. To guard against this possibility, we re-do the main tests using alternative measures of firm growth based on asset-specific variables. For each accounting choice variable that we examine, we explore the growth in the item that is directly related to the choice. Specifically, PPEGrowth3 is the three-year average growth in gross PPE; InventoryGrowth3 is the three-year average growth in inventory; CapLsGrowth3 is the three-year average growth in capital leases and (capitalized) operating leases; and PboGrowth3 is the three-year average growth in the defined benefit pension obligation, where all alternative growth measures are winsorized at 0.1 and 10. Table 7 presents the univariate regressions of the alternative growth measures on their related accounting choice variables using the Fama–MacBeth approach. An examination of Table 7 reveals that the basic results remain much the same – there is no systematic positive relation between growth and income-increasing accounting choices. In fact, all variables in Table 7 retain the same sign and significance as in Table 3, except for Pensions2 and Pensions3, which are significantly negative in Table 3 but become insignificant in Table 7. Thus, the evidence in Table 7 reveals that the results are robust to alternative specifications of the growth variable.
Regressions of growth on accounting choices – low volatility of growth firms.
This table shows the regression results for Growth3 on accounting choices for low volatility of growth firms. Growth3 is the three-year average of organic growth in sales, winsorized at 0.1 and 10. The accounting choice variables are defined in Section 3 of the paper.
Note: *, **, and *** represent statistical significance in two-tailed tests at the 0.10, 0.05, and 0.01 level, respectively.
Regressions of alternative growth measures on accounting choices.
This table shows the regression results of different growth variables on accounting choices. PPEGrowth3 is the three-year average growth in gross property, plant and equipment (PPE), winsorized at 0.1 and 10. InventoryGrowth3 is the three-year average growth in inventory, winsorized at 0.1 and 10. CapLsGrowth3 is the three-year average growth in capital leases and (capitalized) operating leases, winsorized at 0.1 and 10. PboGrowth3 is the three-year average growth in defined benefit pension obligation, winsorized at 0.1 and 10. The accounting choice variables are defined in Section 3 of the paper. Regressions are Fama–MacBeth regressions with Newey-West adjusted standard errors with a lag of 2.
Note: *, **, and *** represent statistical significance in two-tailed tests at the 0.10, 0.05, and 0.01 level, respectively.
3.3. Additional results
Our main results of essentially no reliable relation between growth and accounting choice seem surprising given much existing evidence of opportunistic accounting choice, and therefore we provide some additional analyses to corroborate them. An important consideration for these additional analyses is that they are completely independent of the growth approach, and therefore they provide a nice way to “triangulate” our results. Our first additional analysis maps out the correlations among the accounting choices in our sample. The motivation is based on the observation that a firm which has an incentive to increase income through accounting choices will be driven to take an aggressive stance on a number of available accounting choices rather than on just one. The reason is that taking an aggressive stance on a number of available choices allows the firm to produce more income-increasing effects. Alternatively, holding income-increasing goals constant, spreading the income-increasing effects among a number of accounting choices allows the firm to achieve its goal using less extreme and visible choices. In other words, there are reasons to believe that income-increasing benefits increase in the number of accounting choices employed and income-increasing costs decrease in the number of choices employed, so there should be a strong tendency for joint use of income-increasing choices . In empirical terms, since all our choice variables are coded so that higher values signify more income-increasing effect, the prediction is for a predominance of positive correlations between our choice variables.
Table 8 provides a Pearson correlation matrix for our nine choice variables. Given the ordinal nature of the variables, the Spearman correlations are nearly the same, and are therefore omitted. Correlations that are significant at 5% or better are denoted with an asterisk. Since the number of available observations differs greatly across correlations, we provide parsimonious indication of sample size by bolding all correlations where the number of available observations exceeds 10,000.
An examination of Table 8 reveals no reliable pattern of positive correlations among aggressiveness in accounting choices. In fact, negative correlations outnumber positive correlations by a count of 19 to 17, and the mean of all 36 correlations is −0.003. In addition, the majority of the correlations are rather low in absolute magnitude; specifically, 28 out of 36 correlations have an absolute value of less than 0.10. Indeed, the only reliable cluster of correlations occurs for the three pension-rate variables in the right-hand corner of the correlation matrix, and seems to be driven by straightforward economic factors rather than accounting choice. For example, the highest correlation in the table (0.489) is between Pensions2 and Pensions3. Since the Pensions2 variable increases with the expected rate of return on pension assets and the Pension3 variable increases with the pension discount rate, it is not surprising that the two move together because both have a common economy-wide component that fluctuates over time. Thus, Table 8 reveals no evidence that companies take any sort of systematic income-increasing stance across the menu of available accounting choices, which is consistent with the main results above. To our knowledge, the analysis in Table 8 is also novel, and it seems that this approach can be helpful in other investigations of accounting choice.
Correlation matrix for accounting choice variables.
This table includes the Pearson correlations between accounting choice variables. All variables are as defined in Section 3 of the paper. Correlations that are significant at the 5% level or better are denoted with an asterisk. Bolded correlations are for variable pairs for which the sample comprises 10,000 observations or more.
Number of positive correlations: 17.
Number of negative correlations: 19.
Average correlation: −0.003.
Number of correlations with absolute magnitude less than 0.10 = 28 (out of 36).
Our second additional analysis investigates five-year growth rates before and after accounting changes. The motivation is that our main results are from cross-sectional “levels” specifications, which are frequently subject to various endogeneity and omitted variable problems (Berger, 2011), and thus a “changes” specification can potentially provide cleaner or at least useful alternative results. Specifically, we expect that income-increasing changes in accounting choice occur before higher future growth and income-decreasing changes occur before lower future growth. To provide a cleaner test on changes, we concentrate on the three accounting method choices (DeprMeth, FullCost and Inventory), which provide unambiguous measures of changes. In contrast, more transaction-based choices such as Leases and DeprLife change every period, often driven by factors beyond managerial control, such as technological innovations and economy-wide interest rate changes. We require that change observations have at least three years’ ahead and three years’ back growth variables to ensure some comparability across our wide time-series window. Note that the growth observations in Table 9 are on a yearly basis, unlike the preceding specifications that use a three-year basis.
Growth rates in sales for five years before and after a change in accounting choice.
This table presents descriptive statistics for growth rates in sales for five years before and after a change in accounting choice. All accounting choices are as defined in Section 3 of the paper, and are coded so that higher values represent more “income-increasing” accounting choices, for example, straight-line depreciation is coded higher than accelerated depreciation. Thus, increases in accounting choice signify movement towards more “income-increasing” choices, and the converse for decreases. The sales growth variables are presented by year, and represent the one-year growth in organic sales rate (note that this is different from most other tables where the primary variable is Growth3, which represents a three-year average growth rate). For example, “lg3growth” represents the sales growth three years before the change, while “ld2growth” represents sales growth two years after the year of the accounting choice change. N is the number of available observations, which generally decreases further away from the year of the change.
The results for DeprMeth are presented in Table 9, Panel A. Some of the most useful evidence in this panel relates to the number of accounting changes in proportion to the total number of accounting choice observations. We find a total of 2270 changes, which is only 2.2% of the corresponding available observations for depreciation choice (with non-missing growth rate between t−3 and t+3). Essentially, accounting changes in DeprMeth are so rare that it seems unlikely that they are commonly used for strategic purposes. If a change in DeprMeth happens only once in 50 years, then this is simply a rather blunt and unwieldy tool to use to maximize a stock offering or to boost bonus compensation.
Note that even this low rate is essentially the upper bound on what the actual rate of discretionary changes can be, because existing research documents that accounting method changes are commonly driven by economy-wide and business fundamentals. For example, Keating and Zimmerman (2000) show that tax law changes and M&As are a substantial factor in depreciation method changes. Thus, the effective rate of discretionary changes is likely to be much lower than the total rate of changes computed from Compustat data.
Panel A also includes data for the mean, median, the 25th percentile and the 75th percentile of growth over five years before and after the change in DeprMeth, for both increases and decreases in DeprMeth. An inspection of the results for increases in DeprMeth reveals no increase in growth rates; if anything, growth rates exhibit a slight decline after the increase. There is a slight decline in growth rates after a decrease in DeprMeth as well, but the magnitude is small. In addition, the similarity of the results for increases and decreases is more suggestive of a secular time-series decline in growth rather than of something to do with the strategic use of accounting choice.
The corresponding results for FullCost and Inventory are included in Panels B and C of Table 9. The tenor of these results is much the same as for DeprMeth in Panel A. Firstly, changes are rather infrequent with a change rate of 1.8% for FullCost and 1.2% for Inventory, which implies that changes happen only once in 50–80 years, questioning their suitability for income manipulation. Secondly, growth rates decline for both accounting choice increases and decreases, which is again inconsistent with the strategic use of these choices for income management.
In untabulated analyses, we find very similar before-and-after the change results for the remaining more transaction-based accounting choices. 7 Operationally, we examine for patterns of increased growth following sustained and extreme income-increasing changes and for patterns of decreased growth following sustained and extreme income-decreasing changes, where sustained is defined over a three-year horizon and extreme is defined as top and bottom decile. For all of these choices, we find no reliable difference in the behavior of growth following extreme increases and declines in income aggressiveness.
4. Discussion of the combined results
The combined results of this study suggest that a broad group of theories that predict income-increasing motivations for accounting choice have at best only sporadic or weak economic importance. Since this is a far-reaching implication, it is important to carefully consider the advantages and limitations of the results presented above.
The first and most obvious concern for a study like ours is whether the finding of “no results” can be due to low statistical and empirical power. However, this is unlikely to be the case here. Recall that the simulations preceding our main growth tests suggest that our empirical specification detects relations of even minimal economic significance; for example, the simulation tests produce significant statistics even when the firm with the highest incentives is simulated to be only 5% more likely to manage earnings than the firm with the lowest incentive. Relations that lie below this benchmark, even if they exist, can be rightly called economically trivial. In addition, recall that the problem is not so much about insignificant statistics, it is more about having significance but with signs that seem random or not related to reasonable interpretations of the economics of the underlying relations; for example, Inventory and Pooling did have significant positive relation with growth but that seemed strange given the more conflicting incentives for these variables. Lack of narrowly defined statistical power is even more emphatically rejected here because our sample is ten to a hundred or more times larger than the sample of the typical study on accounting choice.
A more subtle concern is whether the simple specifications we use miss important features of the possibly intricate mechanism of accounting choice determination. It is clear that accounting choice is likely to be determined by a variety of other considerations apart from income-increasing motivations. For example, to the extent that firm or industry characteristics determine both growth and accounting choice, failure to control for such characteristics will produce misleading results about the relation between growth and accounting choice. However, several features of our research design largely rule out the more obvious aspects of this interpretation. For example, most of our variables are defined as deviations from industry and economy-wide average which controls for a large class of fundamentals-related omitted variables. A wide variety of alternative specifications and sensitivity analyses further mitigate such concerns, including splitting the sample on many dimensions, using earnings management incentive variables to sharpen the tests, and a “changes” versus “levels” approach. In addition, the analysis of correlations across aggressiveness of individual accounting choices and the evidence on frequency of accounting changes are completely independent of the validity of the ranking-on-growth approach. The large sample and the common tenor of the results across all these specifications provide reasonable assurance that these results are reliable.
In our view, the most natural and plausible interpretation of our results is that income-increasing motivations are simply not that important for the visible and long-term accounting choices considered in this study. Choices such as depreciation method, inventory accounting and pension accounting rates are prominently disclosed and commonly scrutinized, so using them to for aggressive accounting objectives is likely problematic. This pattern of results is also consistent with the arguments of Francis (2001), where a review of a number of sources suggests that the majority of accounting problems occur at the implementation level. Thus, the results of this study suggest that managers avoid using visible income-increasing choices because their effect is easily unraveled by interested stakeholders, and use largely invisible implementation-level actions instead. While some of our variables, such as DeprLife and Leases, capture an implementation aspect of accounting choice, this seems a fertile area for further investigation.
Another implication of our results is that opportunistic accounting choices are more likely at the short-term horizon. Our evidence indicates that choices such as depreciation and inventory method are rather sticky, and companies rarely change them. Thus, such choices are simply too blunt and unwieldy to achieve aggressive accounting objectives, which likely continually change with the evolution of the firm. In addition, the long-run growth trajectory of the firm is difficult to predict, and thus firms are less willing to commit to a long-term accounting choice just because it is currently “income-increasing”, since the disappearance of growth may mean that the income increases have disappeared or are even reversing.
A critical related point relies on the observation that the typical length of these choice commitments (50–80 years based on the change rates observed in our samples) greatly exceeds the length of the typical income-increasing motivations considered in extant research, for example, capital-raising incentives have horizons of one to a few years and typical bonus and debt contracts have lengths of three to five years. Thus, on a common sense level, it seems inappropriate to consider the contract features as given and the accounting choices as the result, when exactly the opposite seems more likely. In fact, this evidence seems to suggest a new venue for research. It would be interesting to see whether and to what extent contractual features are a function of the largely fixed long-term accounting choices. In contrast, short-term motivations, such as manipulation of accrual estimates to beat earnings thresholds, seem a more natural fit for opportunistic accounting choices. Here, the opportunistic target and rewards are well-defined and immediate, and the manipulation typically does not involve any long-term and visible commitment.
Finally, a remaining question is how the conclusions of this study square with those of a number of existing studies, which find support for opportunistic determinants of accounting choice, especially for contractually based incentives. Since this is a large literature, we cannot fully address this question here. However, the following brief observations may be helpful in this regard. Firstly, the existing literature is diverse and nuanced, and it is important to keep in mind that a number of studies find little support for aggressive accounting choice, for example, DeAngelo et al. (1994) Healy and Palepu (1990). Secondly, the major advantage of existing studies over this study is utilizing small samples and more specialized settings, which allow for potentially more careful analysis and controls. For instance, Boubakri et al. (2008) examine the implication of directors’ and officers’ liability insurance purchases for opportunistic accounting choice decisions, but they only have about 100 observations. The small size of the samples raises real questions about generalizability and broad economic importance of the results of such studies. This concern is particularly valid when one considers the well-known research and editorial biases “against the null” (e.g., Burgstahler, 1987), meaning that researchers are less likely to write up a paper based on initial results that fail to reject the null, and editors are less likely to publish working papers that fail to reject the null. As a result, the published evidence is disproportionately strong, given the nature of the underlying phenomenon; see Bamber et al. (2000) for an illustration of this point in the setting of stock prices reactions to earnings announcements. Notice that this concern about essentially idiosyncratic or accidental results being embraced as large-sample characteristics is particularly acute when the examined samples are rather small compared to the size of the underlying population. Summarizing, our conjecture is that the existing findings are valid, but their validity is probably more circumscribed than previously thought. Thirdly, recent survey evidence reveals little managerial appetite for earnings manipulation using aggressive accounting choices and aggressive accruals in general. Graham et al. (2005) find that managers overwhelmingly prefer real actions over accrual choice to achieve earnings targets. Less than 10% of the managers agree that they would alter accounting assumptions similar to those examined in this study, which represents the lowest propensity of nine potential tools of earnings management examined in the survey. Cohen et al. (2008) show that managers’ preferences of real over accrual earnings management become significantly stronger in the post-Sarbanes–Oxley period. Such more recent and direct evidence about managerial choices also suggest the need to perhaps temper and change some previous impressions.
5. Conclusion
We examine for a positive relation between growth and aggressive accounting choice. Our motivation is that this relation is an unexamined and very general implication of almost any theory and type of aggressive accounting choice. We use a large sample and a wide set of accounting choices to provide a comprehensive investigation of this relation. Our main finding is that there is essentially no reliable relation between growth and accounting choice. Individual accounting choices exhibit negative correlation with growth about as often as positive correlation and the economic strength of most of these relations is negligible. These results hold for a variety of alternative specifications and robustness checks. We also find that there is no reliable positive relation between the aggressiveness of individual accounting choices, which suggests that companies do not take systematic aggressive stances across the available set of choices. Finally, changes in accounting choice are rather rare – on the magnitude of once in 50–80 years – which implies that for all practical purposes such accounting methods are not really a “choice” for short- to intermediate-term objectives.
Taken as a whole, this evidence suggests that income-increasing motivations are not an important determinant of the type of accounting choice we consider. Our investigation focuses on mostly long-term and visible choices, where opportunistic choice is likely easy to identify and unravel. One implication from our findings is that investigations of opportunistic choice should pursue more carefully managerial actions at the largely unobservable level of implementation rather than at the level of hard and observable choices. Another implication is that a more careful consideration of non-opportunistic determinants of long-term accounting choice is warranted.
Footnotes
Appendix 1
Appendix 2
Acknowledgements
We appreciate the comments of workshop participants at the University of Colorado, University of Michigan, Emory University, University of Texas (Austin) and University of Georgia, and especially those of Linda Bamber, Jennifer Gaver, Peter Clarkson, Steve Rock, Katherine Gunny, Roby Lehavy, David Reppenhagen, Greg Waymire, Kathryn Kadous, Kristy Towry, Lil Mills, Steve Kachelmeier, Ross Jennings and Sunny Yang.
Funding
This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.
Date of acceptance of final transcript: 1 November 2012.
Accepted by Associate Editor, Peter Clarkson (Accounting)