The Relation between Accruals and Uncertainty. Salman Arif Nathan Marshall

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1 The Relation between Accruals and Uncertainty Salman Arif Nathan Marshall Teri Lombardi Yohn 1309 E 10 th Street Kelley School of Business Indiana University Bloomington, IN (812) May 2013

2 The Relation between Accruals and Uncertainty Abstract Accruals are fundamental to accounting; however, there is little theory regarding the behavior of accruals. Most of the accounting literature considers accruals as a component of profitability. In this study, we consider accruals in their role as a form of investment to examine whether extant theories of investment under uncertainty can shed light on the behavior of working capital accruals. The theory suggests that uncertainty plays an important role in firms investment behavior because firms are more cautious about investment when uncertainty is higher. Consistent with theory, we document a significant negative relation between working capital accruals and uncertainty. We find that this negative relation is more pronounced for firms with longer operating cycles and less pronounced for firms in financial distress, and that working capital accruals are more sensitive to uncertainty than long-term investment. Collectively, our findings suggest that theories of investment under uncertainty can enrich our understanding of the factors that shape accrual behavior.

3 The Relation between Accruals and Uncertainty 1. Introduction Accruals are fundamental to financial reporting and are the underlying innovation of accounting. Given their central importance, a vast body of accounting literature disaggregates earnings into its cash flow and accrual components in order to aid in forecasting profitability and to identify earnings management (Dechow [1994], Dechow et. al. [1995], Sloan [1996]). While there is an extensive stream of research that has examined accruals, the literature is inhibited by two weaknesses. First, there is little theory to guide researchers in understanding the economic forces that shape accrual behavior (McNichols [2000]). Second, the prior accounting literature generally considers accruals in their role as a component of profitability. That is, the literature tends to view accruals as a secondary outcome of the reporting process (Dechow et. al. [1998]) or as the result of managerial manipulation (Xie [2001]). In particular, the literature does not explicitly consider the implications of the fact that accruals at least partially reflect deliberate working capital investment decisions by management. 1 In this study, we seek to address these two shortcomings. We consider accruals as a form of investment and rely on extant theories of investment under uncertainty to provide insights into the behavior of accruals based on the economic environment faced by the firm. Accounting research has recently begun to acknowledge the notion that accruals are a form of investment (Fairfield et. al. [2003], Zhang [2007], Bushman et. al. [2011], Arif and Lee [2013]). However, 1 From an economic standpoint, changes in working capital reflect managers decisions to invest in such items as inventory and accounts receivables, i.e. the amount of credit the firm is willing to extend to its customers. From an accounting standpoint, growth in net operating assets can be disaggregated into working capital accruals and growth in long-term net operating assets (Fairfield et. al. [2003]). Thus, accruals can be viewed not only as a component of profitability, but also as a component of investment. 1

4 little is known about whether investment theories in economics and finance also extend to accruals and whether these theories can, in turn, enrich our understanding of accrual behavior. Motivated by the observation that uncertainty plays an important role in investment decisions because managers cannot perfectly forecast the future and must make investment decisions in the face of uncertainty (e.g. Bernanke [1983], Dixit and Pindyck [1994]), we investigate whether one important aspect of the firm s environment uncertainty is associated with accrual behavior. To guide our predictions, we draw on the vast theoretical literature on investment under uncertainty and test whether this theoretical literature can provide insight into the properties of accruals. We develop four hypotheses on the relation between accruals and uncertainty. Our first prediction relates to the sign of the accrual-uncertainty relation. Using a real options approach, theoretical models of investment under uncertainty suggest that the investment-uncertainty relation is negative (e.g., Bernanke [1983], McDonald and Siegel [1986], Ingersoll and Ross [1992], Dixit and Pindyck [1994], Schwartz and Trigeorgis [2004], Grenadier and Malenko [2010]). The underlying intuition is that when firms make investment decisions under uncertainty, they trade off the returns earned from investing today against the benefit from delaying investment to the future, when information or business conditions may be better. The benefit of postponing investment known as the option to wait implies that when uncertainty is higher, the value of the option to wait is higher. Higher uncertainty thereby has a dampening effect on investment as firms prefer to wait and see instead of investing immediately. Based on this theory, and viewing accruals as a form of investment, we predict that 2

5 firms will invest less in working capital when there is greater uncertainty. Thus, our first hypothesis predicts a negative relation between working capital accruals and uncertainty. 2 Our second hypothesis predicts that the sensitivity of accruals to uncertainty will increase with the length of the firm s operating cycle. The operating cycle measures the average time between the disbursement of cash to produce a product and the receipt of cash from the sale of the product (Dechow [1994]). Firms with longer operating cycles will have a wider range of possible investment outcomes and greater exposure to changing business conditions. This suggests that the option to wait is more valuable for firms with longer operating cycles. Thus, we expect that uncertainty has a stronger dampening effect on investment in working capital in firms where the operating cycle is longer. Accordingly, our second hypothesis predicts that the sensitivity of working capital accruals to uncertainty is increasing in the length of the operating cycle. Our third hypothesis focuses on the role of financial distress in shaping the relation between a firm s accruals and uncertainty. Eisdorfer [2008] develops a model of investment under uncertainty for financially distressed firms. The model is based on the notion that financially distressed firms are able to shift losses to debt holders. Since higher levels of uncertainty raise the likelihood of very positive investment outcomes, and since shareholders reap the rewards if things go well but do not bear the costs if things go badly, distressed firms have an incentive to engage in relatively higher levels of investment when uncertainty is higher. 2 Given the investment perspective of accruals, we expect the predictions of the investment under uncertainty literature will apply to working capital accruals. However, there are reasons to believe that the accrual-uncertainty relation could be positive. For example, if firms manage earnings upward to a greater extent during periods of greater uncertainty, then one would observe a positive relation between uncertainty and accruals. In addition, the empirical asset pricing literature suggests that firms with higher uncertainty earn lower expected returns (e.g. Ang et. al [2006], Diether et. al. [2002]). Thus, higher uncertainty may proxy for lower discount rates and therefore a lower cost of capital. Assuming that managers increase working capital investment when the cost of capital is lower (Wu et. al. [2010]), this would lead to a positive relation between uncertainty and accruals. 3

6 Based on this logic, our third hypothesis predicts that financial distress weakens the negative relation between working capital accruals and uncertainty. Lastly, we examine whether accruals and long-term investment differ in their sensitivity to uncertainty. Ex-ante, it is difficult to predict whether working capital investment or long-term investment is more sensitive to uncertainty. On the one hand, long-term investment may be more sensitive to uncertainty since the payoffs to long-term investment extend far into the future, thereby potentially exposing these investments to large fluctuations in the business environment. On the other hand, theoretical work suggests that investments that have a long investment lag (i.e. a long time-to-build ) will be less sensitive to uncertainty, since firms do not want to take the chance that they are left out of the market if business conditions improve in the future because they had neglected to invest today (Bar-Ilan and Strange [1996], Bar-Ilan et al. [2002]). Investment lag considerations should be relevant for long-term investment decisions but should be less relevant for working capital investment decisions given their short-term nature. Ex-ante, it is unclear which force dominates. Therefore, we do not present a signed prediction for whether the relation between working capital accruals or long-term investment and uncertainty will be more pronounced. We empirically test these hypotheses by examining the relation between working capital accruals as well as growth in long-term net operating assets and uncertainty for firms with available data from 1965 through We define working capital accruals as growth in working capital, and we define long-term investment as growth in long-term net operating assets. We examine three measures of uncertainty; namely, total volatility of stock returns, idiosyncratic volatility of stock returns, and analyst forecast dispersion. These measures of uncertainty are 4

7 consistent with those used in the prior literature to capture uncertainty about the firm s future prospects (e.g. Ang et. al. [2006] and Diether et. al. [2002]). Our findings generally support our hypotheses. First, we document a significant negative relation between uncertainty and working capital accruals. This result is consistent with theoretical models that suggest firms more highly value the option to wait to invest when they face greater uncertainty (e.g. Bernanke [1983], McDonald and Siegel [1986], Ingersoll and Ross [1992], Dixit and Pindyck [1994], Schwartz and Trigeorgis [2004]). Additionally, when we disaggregate working capital accruals into its components, we find that inventory and accounts receivable have the highest sensitivity to uncertainty. This is consistent with the investment perspective of accruals and indicates that firms carry lower levels of inventory and extend less credit to their customers when uncertainty is higher. In untabulated analyses, we also find that the relation between uncertainty and the change in accounts receivables is not driven by the discretionary estimated allowance for bad debts. These results are consistent with the level of working capital accruals being a deliberate choice made by managers and with the level of uncertainty being associated with the investment choice. Second, we document that the sensitivity of working capital accruals to uncertainty increases monotonically with the length of the operating cycle. This is consistent with firms with longer operating cycle having greater exposure to changing business conditions and indicates that these firms are more sensitive to uncertainty when making their accrual investment decisions. Third, we document that the negative relation between working capital accruals and uncertainty is less pronounced for financially distressed firms. This suggests that distressed firms engage in relatively more investment when uncertainty is higher. This is consistent with debt 5

8 holders, and not shareholders, being more likely to bear the cost of bad investment outcomes when the firm is in financial distress. Lastly, we document that the negative relation between working capital accruals and uncertainty is more pronounced than the negative relation between growth in long-term net operating assets and uncertainty. This suggests that investment lags are an important consideration in firms investment decisions under uncertainty (e.g. Bar-Ilan and Strange [1996]). To our knowledge, we are the first to link accounting accruals to the rich literature on investment under uncertainty. Since accruals are fundamental to accounting, it is important to understand their properties and behavior. Establishing the link between accruals and uncertainty accomplishes two goals. First, it emphasizes the importance of acknowledging that accrual behavior is at least partially shaped by deliberate working capital investment choices by management. Second, it incorporates a vast theoretical literature in economics and finance that can aid accounting researchers in understanding the behavior of accruals. Our findings may also provide valuable insights for researchers seeking to separate accruals into normal and discretionary components. A long stream of research has used abnormal accruals as a proxy for earnings management (Healy [1985], DeAngelo [1986], Jones [1991], Dechow et. al. [1995], Dechow et. al. [2003]). Specifically, the research attempts to capture abnormal accruals by estimating a model of expected accruals based on property, plant and equipment, and changes in sales relative to changes in accounts receivables (Dechow et. al. [1995], Dechow et. al. [2003]). We note, however, that these models have few theoretical underpinnings. Consistent with this concern, McNichols [2000] notes that accounting researchers have little understanding of the forces that shape accruals, irrespective of earnings management 6

9 considerations. Our analysis shows that at least one component of the theoretical financial literature explaining investment choices uncertainty extends to working capital accruals. Future research could perhaps combine the investment under uncertainty predictions with other relevant economic theories to further enhance models of expected accruals. Our findings on the relation between working capital accruals and uncertainty also contribute to the economics and finance literature on investment under uncertainty. This literature has tended to focus on firms long-term investment decisions. In contrast, accrualbased investment has received little attention in this literature. We find that the relation between uncertainty and accruals is more pronounced than the relation between uncertainty and long-term investments. We believe that exploiting the information embedded in firms accruals provides a fertile testing ground for a number of theories that have been proposed in the economics literature. The paper proceeds as follows. Section 2 presents the background and hypothesis development. Section 3 presents variable definitions and descriptive statistics. Section 4 presents empirical results, and Section 5 concludes. 2. Background and Hypotheses Development 2.1. PRIOR LITERATURE ON ACCRUALS Accruals are fundamental to financial reporting and are the underlying innovation of accounting. The accounting literature generally considers the role of accruals as a component of profitability. Dechow [1994] focuses on the role of accruals in mitigating the timing and matching problems associated with cash flows as a performance metric. Sloan [1996] focuses on accruals as the component of profitability that is subject to management discretion. He finds that 7

10 accruals are less persistent than cash flows and that the market does not fully incorporate this differential persistence. A long stream of subsequent literature asserts that the lower persistence of accruals is attributable to their measurement subjectivity and lower reliability (e.g., Richardson et. al. [2005]). We note, however, that this literature only considers accruals as a component of profitability and views accruals as secondary outcome of the reporting process or as a result of managerial manipulation. Another more limited stream of research examines the role of accruals as a component of investment. Fairfield et. al. [2003] note that growth in net operating assets can be disaggregated into accruals and growth in long-term net operating assets. They note, therefore, that accruals are not only a component of profitability but also a component of investment. Zhang [2007] supports the investment role of accruals and concludes that the accrual anomaly documented by Sloan [1996] is primarily attributable to the role of accruals as a form of investment. Bushman et al. [2011] note that working capital accruals reflect investment decisions and examine the implications of this for investment-cash flow sensitivities. Viewing accruals as a form of investment recognizes that levels of inventory, accounts receivables, and other current assets and liabilities may not merely reflect residuals from the earnings reporting process but may instead reflect deliberate investment choices by management. In fact, it is likely that management makes deliberate decisions regarding the level of inventory that the company should hold and the amount of credit the company should provide to customers based on the economic environment that the company faces. We argue that viewing accruals as a deliberate investment choice can provide important insights into the behavior of accruals. In particular, a large literature in economics and finance examines investment under uncertainty (e.g. Bernanke [1983], McDonald and Siegel [1986], 8

11 Ingersoll and Ross [1992], Dixit and Pindyck [1994], Ferderer [1993], Schwartz and Trigeorgis [2004], Bloom et. al. [2007], Bloom [2009], and Grenadier and Malenko [2010]). Consequently, we argue that this literature can provide important insights into the relation between accruals and uncertainty. We attempt to provide insights into the behavior of accruals by relying on and extending the models and empirical findings in finance regarding the relation between a firm s investment and uncertainty in order to develop and test hypotheses regarding the relation between accruals and uncertainty HYPOTHESES DEVELOPMENT Real-world investment decisions tend to share three features, which collectively motivate theories of investment under uncertainty (Dixit [1992]). First, firms cannot perfectly forecast the future because the business environment has ongoing uncertainty and information arrives gradually. Second, investment is costly and difficult to reverse, i.e. investment tends to be irreversible. Third, an investment opportunity does not generally disappear if no investment is made immediately, i.e. firms generally have the option to postpone investment to the future. Motivated by these observations, a large theoretical literature examines investment under uncertainty and generally finds a negative relation between investment and uncertainty (e.g. Bernanke [1983], McDonald and Siegel [1986], Ingersoll and Ross [1992], Dixit and Pindyck [1994], and Schwartz and Trigeorgis [2004]). Relying on real options logic, the general intuition underlying theoretical models of investment under uncertainty is as follows. A manager s investment decision involves a tradeoff between investing immediately or instead postponing investment to the future. The benefit of immediate investment is that the firm is able to start enjoying returns from the investment. On 9

12 the other hand, the benefit of waiting is that the manager can gain more information about the value of the investment and take advantage of any improvements in business conditions that occur in the meantime. This benefit of waiting introduces an opportunity cost to investing today. At the point when the benefits of waiting equal the costs of waiting, investment occurs. 3 When uncertainty is higher, the benefit of waiting (commonly referred to in the literature as the option to wait ) is higher. Firms therefore become more cautious in their investment behavior because they prefer to wait and see what happens in the future. Thus, the models predict a negative investment-uncertainty relation. Empirical research in finance generally supports the negative relation between investment and uncertainty (e.g. Leahy and Whited [1996], Guiso and Parigi [1999], Minton and Schrand [1999], and Bond and Cummins [2004]). Given that accruals are a component of investment, we expect working capital accruals (i.e., growth in working capital) to also be negatively associated with uncertainty. This leads to our first hypothesis: H1: The level of working capital accruals is negatively associated with the level of uncertainty. Our second hypothesis predicts an increasing relation between the sensitivity of accruals to uncertainty and the length of the firm s operating cycle. The operating cycle measures the average time between the disbursement of cash to produce a product and the receipt of cash from the sale of the product (Dechow [1994]). A firm with a longer operating cycle has greater exposure to changing business conditions. More specifically, the longer the operating cycle, the wider the range of possible investment outcomes, and the more valuable the option to wait. Thus, 3 This logic demonstrates that in the presence of uncertainty, investment decisions are not simply based on the common net present value rule that suggests investment in a project when the net present value of the project is positive. Instead, investment occurs if the net present value of the investment project exceeds the value of the option to wait. Thus, incorporating uncertainty into the decision process leads to a more nuanced approach to investment. 10

13 we expect that uncertainty has a stronger dampening effect on working capital accruals in firms with longer operating cycles. This leads to our second hypothesis: H2: The negative association between the level of working capital accruals and uncertainty is more pronounced for firms with longer operating cycles. Third, we consider the role of the firm s financial condition in shaping the relation between accruals and uncertainty. Eisdorfer [2008] develops a model of investment under uncertainty for financially distressed firms. The model is based on the notion that financially distressed firms are able to shift losses to debt holders. Therefore, the model predicts that financially distressed firms have a greater incentive to invest when uncertainty is higher because the losses associated with bad outcomes are borne by the debt holders while the gains associated with good outcomes are enjoyed by shareholders. In other words, since higher levels of uncertainty raise the likelihood that new investments are highly profitable, and since shareholders reap the rewards if things go well but do not bear the costs if things go badly, the asset substitution problem (Galai and Masulis [1976], Jensen and Meckling [1976]) provides distressed firms with an incentive to engage in higher levels of investment when uncertainty is higher. Thus, we predict that the negative relation between working capital accruals and uncertainty is less pronounced for financially distressed firms. H3: The negative association between the level of working capital accruals and uncertainty is less pronounced for firms facing financial distress. Lastly, we examine whether accruals and long-term investment differ in their sensitivity to uncertainty. We note that working capital accruals capture growth in short-term net assets. Exante, it is difficult to predict whether working capital accruals or long-term investment will be more sensitive to uncertainty. On the one hand, long-term investment may be more sensitive to 11

14 uncertainty, since the payoffs to long-term investment extend far into the future, thereby potentially exposing these investments to large fluctuations in the business environment. On the other hand, current uncertainty may be less relevant to long-term investment decisions as the payoffs are likely to occur further in the future. In addition, Bar-Ilan and Strange [1996] show that the negative relation between investment and uncertainty is attenuated when there are investment lags. Investment lag also commonly referred to as time-to-build or construction lag - is the length of time it takes for an investment to come on line and start generating returns. Bar-Ilan and Strange [1996] note that considering investment lags fundamentally changes a firm s investment decision because when the investment lag is long, the firm cannot enter the market immediately to earn cash flows from the investment. Investment lags reduce the value of waiting, because if the manager postpones investment to the future and chooses to invest at a later stage when conditions are better, the firm will be unable to immediately benefit from the investment since it takes time to build. Bar-Ilan and Strange [1996] argue, therefore, that when there is an investment lag, the opportunity cost of waiting to invest increases with uncertainty and that uncertainty may actually hasten investment. Investment lag considerations should be relevant for long-term investment decisions but should be less relevant for accrual investment decisions given their short-term nature. Ex-ante, it is unclear which force dominates the relation. Therefore, we do not provide a signed prediction and present our fourth hypothesis in the null form: H4: Working capital accruals and long-term investment have equivalent sensitivities to uncertainty. 12

15 3. Variable Definitions, Sample, and Descriptive Statistics 3.1 MODEL AND VARIABLE DEFINITIONS We examine the relation between working capital accruals and uncertainty and the relation between long-term investment and uncertainty. To test our first three hypotheses, we run variations of the following regression model: WIC i,t = α + β 1 UNCERTAINTY i,t + β 2 CFO i,t + β 3 LAGCFO i,t + β 4 ANNRET i,t + β 5 LAGANNRET i,t + β 6 BTM i,t + β 7 SIZE i,t + β 8 LEV i,t + ε i,t (1) where the dependent variable is WIC, which reflects operating accruals before depreciation for the firm and year, defined as growth in operating working capital (other than tax liabilities) scaled by average total assets. These definitions of accruals are consistent with prior research (Sloan [1996], Fairfield et. al. [2003]). 4 UNCERTAINTY reflects one of three different measures of uncertainty: total stock return volatility (TOTVOL), idiosyncratic stock return volatility (IVOL), and analyst forecast dispersion (DISPERSION). TOTVOL is calculated as the standard deviation of daily returns over the current fiscal year. IVOL is calculated as the standard deviation of residuals from a regression of daily firm returns on the Fama and French [1993] three factors. DISPERSION is calculated as the standard deviation of analyst forecasts as of the fourth month of the fiscal year, scaled by the mean of the same forecasts. 5 The use of these measures and our definitions of these measures is consistent with prior finance research (e.g. Diether et. al. [2002] and Ang et. al. [2006]). 4 We note that the results are qualitatively similar when we examine alternative definitions of working capital accruals, such as the statement of cash flow approach suggested in Hribar and Collins [2002]. This suggests that our results are not driven by measurement error in the accrual estimates. Further, results are also qualitatively similar when we examine total operating accruals, defined as growth in working capital less depreciation and amortization expense, scaled by total assets. We report the results for working capital accruals in order to focus on the component of accruals that is more likely to reflect short-term investment decisions rather than the depreciation/amortization component that is related to long-term investment decisions. 5 We include analyst forecasts as of the fourth month of the year to ensure that the information from the previous fiscal year s annual report (10-K) has been released and incorporated into the forecasts. 13

16 In our analyses of investment, we control for past and current performance as well as expected growth, size, and leverage. Specifically, we control for current and lagged cash flows from operations (CFO and LAGCFO) as well as current and lagged annual stock returns (ANNRET and LAGANNRET) in order to control for current and prior firm performance. We also control for expected growth (BTM), firm size (SIZE) and firm leverage (LEV) as prior finance research suggests that these are important determinants of investment. We also include industry and year fixed effects and cluster the standard errors by firm and year. To test our fourth hypothesis, we run a similar regression with growth in long-term net operating assets as the dependent variable: GrLTNOA i,t = α + β 1 UNCERTAINTY i,t + β 2 CFO i,t + β 3 LAGCFO i,t + β 4 ANNRET i,t + β 5 LAGANNRET i,t + β 6 BTM i,t + β 7 SIZE i,t + β 8 LEV i,t + ε i,t (2) where GrLTNOA is defined as growth in net operating assets less working capital accruals and depreciation and amortization expense, scaled by average total assets SAMPLE AND DESCRIPTIVE STATISTICS Table 1 provides the details of our sample selection. Our sample begins with all observations on Compustat from 1965 to 2010 that meet the data requirements for the dependent and explanatory variables. This leads to 181,064 firm-year observations. We delete 48,512 firmyear observations that do not have CRSP data available. We also delete 6,296 observations that are not U.S. corporations or that have other than ordinary common stock. We exclude 5,870 (138) firm-year observations that do not have data to calculate size or book to market (Z-score) at the beginning of the fiscal year. Finally, we delete 7 (35) observations that do not have returns 6 We note that the results are qualitatively similar if we exclude depreciation and amortization expense, consistent with Fairfield et al. [2003]. 14

17 (volatility) measures available during the year. This leads to 120,206 firm-year observations for our analyses of uncertainty that are based on return volatility measures. We delete an additional 66,196 observations that do not have at least two analyst forecasts to result in 54,010 firm-year observations for our analyses of uncertainty that are based on analyst dispersion measures. We winsorize the remaining observations as the first and 99 th percentiles to control for extreme observations. [Please place table 1 about here] The Appendix presents the detailed variable definitions. Table 2 presents the descriptive statistics for our measures of uncertainty, operating accruals, growth in long-term net operating assets, the components of accruals (working capital accruals and depreciation/amortization expense), the components of working capital accruals, and the control variables. Panel A reports the statistics on the variables. The mean (median) total volatility is (0.0305) and the mean (median) idiosyncratic volatility is (0.0283). The mean (median) analyst forecast dispersion is (0.0571). Consistent with prior research, the mean (median) of operating accruals ( ) is negative while the mean (median) of working capital accruals of (0.0090) is positive, suggesting that total operating accruals is negative due to depreciation and amortization. The mean (median) growth in long-term net operating assets is (0.0181), suggesting positive long-term investment over the sample period. With respect to the control variables, we find a mean (median) cash flow from operations of (0.1100) and lagged cash flow from operations of (0.1099), suggesting slight improvement in operating cash flows from year to year during the sample period. Similarly, we find a mean (median) annual stock return of (0.0575) and lagged annual stock return of (0.0456), suggesting slightly increased stock returns from year to year over the sample 15

18 period. The descriptive statistics also suggest that the mean (median) operating cycle is (117.3) days and that 22.8 percent of firm-year observations are considered to be in financial distress. Panel B reports the Spearman Rank (Pearson) correlation coefficients above (below) the diagonal between the variables. We find that total volatility and idiosyncratic volatility are highly correlated (0.987 Spearman; Pearson), suggesting that these variables capture similar dimensions of uncertainty. We find a positive Spearman (Pearson) correlation of (0.251) between total volatility and analyst forecast dispersion, suggesting that volatility and analyst dispersion capture some similarity in uncertainty. We find that both operating accruals and growth in long-term net operating assets exhibit negative correlations with total volatility, idiosyncratic volatility, and analyst forecast dispersion. We also find that working capital accruals and each of its components exhibit negative correlations with each of the uncertainty measures. Consistent with the finance literature and our assertions, these univariate findings provide initial support for negative associations between uncertainty and operating accruals, working capital accruals, and long-term investment. [please place table 2 about here] 4. Empirical Results 4.1 TEST OF HYPOTHESIS H1 Table 3 provides the results from multivariate analyses to test Hypothesis H1 that working capital accruals are negatively associated with uncertainty using equation (1). 7 The first 7 We also examined the relation between operating accruals and uncertainty. In untabulated results, we find a significant negative relation between accruals and uncertainty. Specifically, we find a negative coefficient of

19 two columns report the results for the regression that includes only the control variables. We find an adjusted R 2 of (0.340 for the analyst dispersion sample), and we find a significant negative coefficient on CFO, suggesting that companies with larger cash flows from operations have smaller working capital accruals. This finding is consistent with the findings in prior research (e.g., Fairfield et. al. [2003]). We find a significant positive coefficient on LAGCFO, ANNRET and LAGANNRET. This suggests that firms with greater prior cash flow performance and firms with greater current and prior stock return performance invest in more working capital accruals. We find a significant negative coefficient on BTM, suggesting that firms with higher expected growth exhibit greater working capital investment. We find mixed results for SIZE. Specifically, SIZE is positively associated with working capital accruals in the volatility sample but is not significantly associated with working capital accruals for the analyst dispersion sample of firms. Finally, we find no association between LEV and working capital accruals. We note that the findings on the control variables, with the exception of SIZE, are consistent across the models. Column (3) in Table 3 provides the results with total volatility included in the model as a proxy for uncertainty. Consistent with our hypothesis, we find a negative coefficient of on TOTVOL which is significant at the one percent significance level. In column (4), we present the results with idiosyncratic volatility included as the proxy for uncertainty. Again, consistent with our first hypothesis, we find a negative coefficient of on IVOL, which is significant at the one percent significance level. Finally, column (5) presents the results when analyst forecast dispersion is included as the measure of uncertainty. We find a coefficient of on DISPERSION, which is significant at the one percent level. on TOTVOL, on IVOL, and on DISPERSION for equation (1) when operating accruals (ACC) is the dependent variable. 17

20 We note that the relation between uncertainty and working capital accruals is not only statistically but also economically significant. For example, moving from the first quartile to the third quartile of uncertainty defined as TOTVOL reduces working capital accruals by 1.77 percent of average of total assets, or 9.5 percent of working capital. The results, therefore, provide strong evidence to support our first hypothesis that there is a negative relation between accruals and the level of uncertainty. [please place table 3 about here] In order to provide greater insight into the sources of the negative relation between working capital accruals and uncertainty, in table 4, we present results of regression analyses in which we examine the components of WIC as the dependent variables. 8 Table 4 provides the regression results when growth in working capital is further disaggregated into growth in accounts receivables ( AR), growth in inventory ( INV), growth in other net current assets ( OTHERNCA), and growth in accounts payable ( AP). Each variable is standardized so that the coefficients can be compared across regressions. Panel A (panel B) reports the results with TOTVOL (DISPERSION) as the proxy for uncertainty. We find that the relation is strongest between AR and uncertainty and between INV and uncertainty when both TOTVOL and DISPERSION are used as proxies for uncertainty. The lower association between uncertainty and other net current assets relative to accounts receivables and inventory could be due to other net current assets being less likely to reflect investment and therefore more likely to be affected by reliability factors as suggested by Richardson et. al. [2005]. The overall results are consistent 8 We also examined the relation between the depreciation and amortization expense component of operating accruals (DEPAMORT) and uncertainty. In untabulated results, we find a significant positive relation between depreciation and amortization expense and uncertainty. We find a larger coefficient on WIC than on DEPAMORT when total volatility is the proxy for uncertainty and similar coefficients on the two components when analyst dispersion is the uncertainty proxy. Therefore, there is either a similar or greater relation between working capital accruals and uncertainty than between depreciation and amortization expense and uncertainty. 18

21 with the investment perspective of accruals and suggest that firms respond to uncertainty by carrying lower levels of inventory and extending less credit to their customers. [please place table 4 about here] In untabulated analyses, we also investigated whether the relation between uncertainty and working capital accruals is driven by estimated allowance accounts included within the working capital accounts. For example, the negative relation between uncertainty and changes in accounts receivables ( AR) might not be due to firms granting less credit to customers but may instead be due to firms estimating a greater allowance for bad debts during periods of uncertainty. To address this possibility, we first separate AR into the change in allowance for doubtful accounts ( ADD) and the change in gross accounts receivables ( GAR). We find that for companies with non-missing ADD, the mean (median) ADD is 4.1 (1.6) percent of the mean (median) GAR, suggesting that the estimated allowance is a minor portion of accounts receivables and, therefore, working capital accruals. Second, in untabulated analyses, we examine the relation between uncertainty and AR as well as GAR to assess whether the relations differ. We find that the relation between uncertainty is similar for GAR and AR. The Pearson (Spearman) correlation between GAR and TOTVOL, IVOL, and DISPERION is ( ), ( ) and ( ), respectively which is similar to the correlations for AR reported in table 2. Finally, in untabulated regression analyses similar to those reported in table 4, we find a significant coefficient of on TOTVOL and on DISPERSION when (unstandardized) GAR is the dependent variable and a significant coefficient of on TOTVOL and on DISPERSION when (unstandardized) AR is the dependent variable. These results suggest that 19

22 the negative relation between the change in accounts receivable and uncertainty is not driven by changes in the allowance for doubtful accounts. 4.2 TEST OF HYPOTHESIS H2 Our second hypothesis predicts that the sensitivity of working capital accruals to uncertainty is increasing in the length of the firm s operating cycle. To provide insight into the validity of this prediction, table 5 presents the coefficient on uncertainty when WIC is regressed on each uncertainty proxy and the control variables by operating cycle quintile. The results are reported when TOTVOL, IVOL, and DISPERSION are used as the uncertainty proxy, respectively. Within each set of results, the first column reports the coefficient on the uncertainty measure, the second column reports the t-statistic for the coefficient and the third column reports the adjusted R-squared for the regression. We exclude the coefficients on the other variables in the regression for brevity. In these regressions, we do not include industry fixed effects as the operating cycle is likely clustered by industry. We find, for each measure of uncertainty, that the coefficient on the uncertainty proxy almost consistently decreases monotonically across the operating cycle quintiles. The coefficient on TOTVOL decreases from for the lowest operating cycle quintile to for the highest operating cycle quintile and the coefficient on IVOL decreases from for the lowest to for the highest operating cycle quintile. Similarly, the coefficient on DISPERSION decreases from to across the quintiles based on the firm s operating cycle. These results provide strong support for our second hypothesis that the negative association between working capital accruals and uncertainty is increasing as the operating cycle lengthens. 20

23 [please place table 5 about here] 4.3 TEST OF HYPOTHESIS H3 Our third hypothesis predicts that the relation between working capital accruals and uncertainty is less pronounced for firms in financial distress. The analyses to test these predictions are presented in table 6. To test these predictions, we run equation (1) and include an indicator variable, DISTRESS, which equals one when the Altman s Z-score is below 1.81 at the beginning of the fiscal year, and zero otherwise. This application of Altman s Z-score is consistent with the methodology applied in Eisdorfer [2008]. The regression also includes an interaction term between DISTRESS and UNCERTAINTY which is the variable of interest to test Hypothesis H3. The table reports the results using TOTVOL, IVOL, and DISPERSION as the proxy for uncertainty, respectively. The results are consistent across the proxies for uncertainty. Specifically, we find negative coefficients of on TOTVOL, on IVOL, and on DISPERSION, which are significant at the one percent level. This suggests that, after controlling for DISTRESS, there is a significant negative relation between working capital accruals and uncertainty. We also find negative coefficients on DISTRESS of using TOTVOL, using IVOL, and using DISPERSION as the uncertainty proxy, which are significant at the one percent level. This suggests that companies in financial distress exhibit lower working capital accrual investment. Our variable of interest, DISTRESS*UNCERTAINTY, has a positive coefficient of using TOTVOL, using IVOL, and using DISPERSION as the uncertainty proxy, and all are significant at the one percent level. This 21

24 suggests that, consistent with Hypothesis H3, the negative relation between working capital accruals and uncertainty is mitigated by financial distress. [please place table 6 about here] 4.4 TESTS OF HYPOTHESIS H4 Hypothesis H4 predicts that working capital accruals and long-term investment have equivalent sensitivities to uncertainty. Table 7 presents the results of tests of this hypothesis. Specifically, we present the regression of uncertainty on working capital accruals in the first two columns (as a reference) and the regression of uncertainty on growth in long-term net operating assets (GrLTNOA) in the second two columns. The variables are standardized so that the coefficients can be compared across the regressions. We report three sets of regressions using TOTVOL, IVOL, and DISPERSION as the proxy for uncertainty, respectively. In the first set of analyses, we find a coefficient of on TOTVOL when WIC is the investment measure of interest and a coefficient of on TOTVOL when GrLTNOA is the investment measure. We find that the coefficient on TOTVOL for WIC is significantly different (at the one percent level) from the coefficient on TOTVOL for GrLTNOA using a multivariate multiple regression F-test. 9 In the second set of analyses, we find a coefficient of on IVOL when WIC is the investment measure and a coefficient of when GrLTNOA is the investment measure. Again, the coefficient on the uncertainty measure for WIC is significantly different from the coefficient for GrLTNOA at the one percent level. 9 We also tested the difference in the coefficient estimates by regressing the difference of WIC and GrLTNOA on uncertainty and the control variables using two-way (firm and year) clustered regressions. 22

25 Finally, we report the regression results when DISPERSION is the proxy for uncertainty. We find a coefficient of on DISPERSION for WIC and a coefficient of for GrLTNOA. The difference between the coefficients for WIC and GrLTNOA is significant at the five percent level. These findings suggest that the negative relation between working capital accruals and uncertainty is more pronounced than the relation between long-term growth in net operating assets and uncertainty. [please place table 7 about here] To provide additional insight into why there is a lower association between uncertainty and GrLTNOA than between uncertainty and WIC, we disaggregate GrLTNOA into PPE, INTAN, and OTHERNA. We find a negative relation between uncertainty and each of the components of long-term investment and we find that the relation is most pronounced for PPE. We note, however, that the relation between uncertainty and PPE is less pronounced than the relations between uncertainty and AR and INV, further reinforcing the investment perspective of accruals. 10 [please place table 8 about here] 4.5 ADDITIONAL TESTS We note that our hypotheses rely on the theory that uncertainty influences the firm s level of investment. However, one could argue that the level of accruals could influence the volatility of stock returns and the dispersion of analyst forecasts. Therefore, in order for the models in finance to be relevant to accrual investment, it is important that we address the issue of the direction of the relation. First, we highlight that if a higher level of accruals leads to a higher 10 For further insight, we also examine the relation between uncertainty and the change in gross property, plant and equipment. These untabulated analyses also reveal a negative relation (coefficient estimates of for TOTVOL and for DISPERSION) that is less pronounced than the relations between uncertainty and AR and INV. 23

26 level of uncertainty, then the direction of the relation would be positive instead of negative as hypothesized in the finance literature and documented above. This provides support for the notion that uncertainty drives accruals rather than the notion that accruals drives uncertainty. To provide additional evidence on this issue, we also performed untabulated analyses where lagged total stock return volatility (LAGTOTVOL) is used as the proxy for uncertainty. We find results that are consistent with those reported in the tables. Specifically, when we run equation (1), we find a coefficient of on LAGTOTVOL which is significant at the one percent level. Second, we find a monotonically decreasing coefficient on LAGTOTVOL for explaining WIC across operating cycle quintiles. Third, we find a negative relation between DISTRESS and WIC and a positive coefficient on the interaction term DISTRESS*UNCERTAINTY for WIC. Finally, in comparing the coefficient on LAGTOTVOL for explaining WIC versus GrLTNOA using standardized variables (as in table 7), we find a coefficient of for the WIC regression and for the GrLTNOA regression, and that the difference is significant at the one percent level. These results are consistent with those reported in the tables and suggest that the level of working capital accruals is associated with lagged uncertainty. 5. Conclusions In the real world, firms cannot perfectly forecast the future. The business environment is continually evolving, and information arrives gradually. Firms must therefore make investment decisions in the face of uncertainty. In this study, we exploit the fact that accruals are a form of investment to examine the relation between working capital accruals and uncertainty. In particular, we are guided by the rich extant literature in economics and finance on investment under uncertainty (e.g. Bernanke [1983], McDonald and Siegel [1986], Ingersoll and Ross 24

27 [1992], Dixit [1992], Dixit and Pindyck [1994], and Schwartz and Trigeorgis [2004]). To our knowledge, we are the first to link the literature on accounting accruals with the literature on investment under uncertainty. The theory predicts a negative relation between investment and uncertainty because firms become more cautious about investing when uncertainty is higher. Consistent with this, we document a significant negative relation between working capital accruals and uncertainty. Furthermore, we find that inventory and accounts receivable have the highest sensitivity to uncertainty and that the negative relation between accounts receivables and uncertainty is not driven by changes in the allowance for bad debts. These results support the view that working capital accruals reflect investment decisions and that these decisions are associated with the level uncertainty faced by the firm. We also predict and find that the negative relation between working capital accruals and uncertainty is more pronounced for firms with longer operating cycles and is less pronounced for financially distressed firms. Finally, we find that the negative relation between working capital accruals and uncertainty is more pronounced than the negative relation between long-term investment and uncertainty. We believe that our findings provide important contributions to the accounting literature on accruals and to the economics and finance literature on investment and uncertainty. Specifically, we believe that our findings are an important initial step in understanding the factors that shape the behavior of accruals. Given that accruals are central to the accounting discipline, understanding accrual behavior is of great importance. Furthermore, we believe that the insights from viewing accruals as a form of investment and taking into account the role of uncertainty in shaping accrual behavior has the potential to 25

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