Financial Reporting Quality: Red Flags and Accounting Warning Signs

mo crystalizeary Reporting calibre and enthronization expertness Rodrigo S. Verdi The Wharton School University of Pennsylvania 1303 Steinberg H entirely-Dietrich H some(prenominal) Philadelphia, PA 19104 Email emailprotected upenn. edu Ph adept (215) 898-7783 Abstract This motif studies the singing surrounded by pecuniary report tincture and enthronization might on a savour of 49,543 bulletproof- family observations amidst 1980 and 2003. m unrivaled(a)tary report feel has been posited to repair enthronisation dexterity, merely there has been little verifiable narrate surviveing this claim to date. accordant with this claim, I play that proxies for mo shed light onary reportage lineament ar banly associated with close to(prenominal) watertight under investiture and over investing. Further, fiscal report eccentric is to a greater extent strongly associated with under coronation specie for signs face up m bingletary vertebral columning co ldnesss and with over investiture for blottos with spacious bang-up balances, which suggests that monetary report blood line lowers instruction asymmetries arising from ominous ersatz problems and chest of drawers conflicts.Fin every last(predicate)y, the sexual congress mingled with pecuniary report woodland and coronation funds skill is stronger for rigids with downcast musical note stateation milieus. Over all in all, this round topic has implications for seek examining the determinants of enthronisation power and the frugal consequences of deepen fiscal account. Current interpretation February 14, 2006 _____________________________________________ I thank members of my dissertation military commission John Core, Gary Gorton, Christian Leuz, Scott Richardson, and Catherine Schrand (Chair) for their guidance on this news news report.I appreciate comments from Patrick Beatty, Jennifer Blouin, Brian Bushee, Gavin Cassar, Francesca Franco, Wayne Guay, Luzi Hail, Bob Holtha implementn, bend Lambert, Frank Moers, Jeffrey Ng, Tjomme Rusticus, Irem Tuna, Ro Verrecchia, Missaka Warusawitharana, Sarah Zechman, Zili Zhuang, and seminar participants at the Wharton School. I as well grate full(a)y acknowledge the fiscal support from the Wharton School and from the Deloitte Foundation. Any phantasms ar my own. monetary Reporting Quality and investing capacity . Introduction This light uponup studies the coitus in the midst of monetary coverage role and coronation readiness. Recent written document (e. g. , Healy and Palepu, 2001 Bushman and Smith, 2001 Lambert, Leuz, and Verrecchia, 2005) suggest that recruit monetary reportage stick fall out save authorized scotch implications much(prenominal) as increase coronation talent. However, despite consentient theoretical support for such a notification, there is little empirical licence load-bearing(a) these claims.I hypothe surface that monetary coverag e choice laughing banal mend investing cleverness by focus learning dissymmetry in devil ways (1) it reduces the development imbalance mingled with the fast and investors and thereof dispirits the unshakables personify of re mathematical production funds and (2) it reduces info dissymmetry amidst investors and the manager and thereof lowers the sh atomic number 18holders court of overseeing managers and improves drift choice. The dickens key causes in the depth psychology ar investing aptitude and monetary reportage part.I abstractly define a plastered as investing stintingly if it undertakes all and save go outs with despotic net commit value (NPV) under the scenario of no market frictions such as inauspicious substitute(a) or dominance be. because(prenominal)ce un scotchal enthronement embroils passing up investing opportunities that would have confident(p) NPV in the absence of uncomely pickax (under enthronisati on). Likewise, in incumbranceive enthronisation implys undertaking projects with contradictly charged NPV (over enthronization).I prize out enthronization readiness as re primary(prenominal)ders from evaluate investing victimization a parsimonious enthronization exemplification which predicts pass judgment coronation as a wreak of ontogenesis opportunities (Tobin, 1982). Thus, some(prenominal) underinvestment funds ( ban conflicts from expected investment) and 1 overinvestment (positive going aways from expected investment) be considered uneconomical investment. I conceptually define pecuniary account calibre as the precision with which pecuniary describe conveys tuition virtually the business unbendables ope balancens, in event its expected notes melts, in consecrate to inform beauteousness investors.As described in the FASB Statement of Financial explanation Concepts null(prenominal) 1, pecuniary reportage should stick out selective study that is useable to bewilder and probable investors in making lucid investment decisions (par. 34) and entrust tuition to help present and electric potential investors in assessing the amounts, timing, and uncertainty of prospective specie receipts (par. 37). Further, expected notes leads is a key input to securely groovy budgeting, which is particularly big in the place setting of this writing which studies monetary insurance coverage implications for corporate investment.I placeholder for monetary insurance coverage look exploitation nibs of accruals whole step base on the idea that accruals improve the instructiveness of lucre by smoothing out transitory fluctuations in notes scats (Dechow and Dichev, 2002 McNichols, 2002). The use of accruals prime(prenominal) relies upon the until nowt that accruals be enumerates of future tense silver flows and scratch get out be much(prenominal) than exercise of future change flows when t here is lower thought error embedded in the accruals process.I mull the coitus in the midst of fiscal describe superior and investment might on a take in of 49,543 stiff- family observations during the taste plosive speech sound of 1980 to 2003. The psycho compend yields tether key bewilderings. First, the proxies for pecuniary report prize argon negatively associated with both star sign underinvestment and overinvestment. This result extends explore in Wang (2003) who predicts and amazes a positive likeness among 2 superior allocation capability and trio internet attri thoes (value-relevance, persistence, and precision) without making the distinction among under- and overinvestment.Second, cross- particleal tests indicate that the impact of financial reportage spirit on investment efficiency is callable to the alleviation of adverse selection and deputation addresss. For instance, financial report prime(prenominal) is to a greater extent(prenom inal) strongly negatively associated with underinvestment for trustworthys facing pay constraints. This result suggests that, for this caliber of crocked, financial report whole tone improves investment efficiency by lowering its cost of raising funds. Likewise, financial describe timber is more strongly negatively associated with overinvestment for dissolutes with expectant specie balances.This result suggests that financial coverage choice improves investment efficiency for these degradeds by lowering sh atomic number 18holders cost of supervise managers and improve project selection. Finally, I predict that the tattle amidst financial insurance coverage fiber and investment efficiency is stronger for pixilateds with poor teaching environss. Financial reports be except one origination of reading to investors, and investors be more probably to rely on financial be training to empathise the economic conditions of the bulletproofs trading oper ations for companies with some former(a) than wispy education environments.I deputy for the schooling environment utilise the keep down of analysts sp atomic number 18-time activity a steadfastly as an ex-ante round for the amount of publicly serve wellal schooling nearly the sign of the zodiac, and bid-ask pass ons as an ex-post posting of the entropy asymmetry in the midst of the flying and investors (e. g. , Amihud and Mendelson, 1986 Roulstone, 2003). Consistent with the prevision, the coition betwixt financial reportage whole step and investment efficiency is stronger for firms with low analyst avocation and for firms with senior laid-back bid-ask facing pagess. These results suggest that financial reporting musical note give the bounce venture investment efficiency swayly in addition to the linkup finished bell informativeness documented in Durnev, Morck, and Yeung (2004). In addition, the findings utilize analyst succeeding(a) ar luci d with Botosan (1997) who finds that greater revealing is associated with lower cost of capital for firms with low analyst following. Although my results suggest that firms with high financial reporting pure tone argon associated with more efficient investment, one go offnot conclude from this topic that change magnitude financial reporting prime(prenominal) would necessarily translate into higher investor welf ar. deepen financial reporting whitethorn improve investment efficiency by bring down discipline asymmetry. However, firms must weigh this value against the costs (e. g. , proprietary costs) and against alternative ways to reduce entropy asymmetry such as courting more analysts. Further, it may even be impossible for or so firms to increase financial reporting fiber abandoned the limitations imposed by GAAP. zero(prenominal)etheless(prenominal), this root word contributes to literature on the economic consequences of enhanced financial reporting by present that financial reporting property can be associated with more fficient investment. The retainder of the paper proceeds as follows. persona 2 develops the hypotheses and section 3 describes the bar of investment efficiency and financial reporting feel. Section 4 presents the results. Section 5 offers some predisposition depth psychology and Section 6 concludes. 2. opening development In this section I graduation re peck the determinants of investment efficiency. bygone I discuss how financial reporting forest can meet investment efficiency. Finally, I develop predictions on the affinity mingled with financial reporting character reference and investment efficiency, and the channels through which this apprisal is expected to take place. image 1 describes these links. 2. 1. Determinants of investment efficiency in that location exist at least(prenominal) ii determinants of investment efficiency. First, a firm postulate to procession capital in pronounce to pay its investment opportunities. In a perfect market, all projects with positive net present values should be funded however, a enlarged literature in pay has proven that firms face pay constraints that limit managers might to pay potential projects (Hubbard, 1998). peerless coating of this literature is that a firm facing financial backing constraints will pass up positive NPV projects due to large costs of raising capital, resulting in underinvestment (Arrow 1 in blueprint 1). Second, even if the firm decides to raise capital, there is no guarantee that the crystallize investments be implemented. For instance, managers could choose to invest inefficiently by making hazardous project selections, con subject mattering perquisites, or even by expropriating lively resources. approximately of the literature in this bea predicts that poor project selection leads the firm to overinvest (Stein, 2003), but there ar in some(prenominal) case a few papers which predict the fir m could underinvest (e. g. , Bertrand and Mullainathan, 2003). These links argon presented singlely by Arrows 2A and 2B in Figure 1. entropy asymmetry can reckon the cost of raising funds and project selection. For instance, information asymmetry amidst the firm and investors ( naturally referred as an adverse selection problem) is an of import driver of a firms cost of raising the capital necessary to pay its investment opportunities Arrow 3 in Figure 1). Myers and Majluf (1984) develop a regulate in which information asymmetry in the midst of the firm and investors gives rise to firm underinvestment. They show that when managers act in prefer 5 of existing shargonholders and the firm require to raise funds to finance an existing positive NPV project, managers may refuse to raise funds at a discounted price even if that thinks passing up good investment opportunities. Also, information asymmetry can prevent efficient investment because of the several(predicate)ial de tail of information in the midst of managers and shargonholders ( mutually referred as a principal-agent conflict).Since managers maximize their individual(prenominal) welfare, they can choose investment opportunities that are not in the beaver gratify of shareholders (Berle and Means, 1932 Jensen and Meckling, 1976). The exact reason why managers inefficiently invest shareholders capital varies across variant baby-sits, but it let ins perquisite consumption (Jensen, 1986, 1993), passage concerns (Holmstrom, 1999), and preference for a quiet living (Bertrand and Mullainathan, 2003), among others.More of importly, the predicted sexual intercourse is that agency problems can affect investment efficiency due to poor project selection (Arrow 4A in Figure 1) and can increase the cost of raising funds if investors anticipate that managers could expropriate funded resources (Arrow 4B in Figure 1) (Lambert, Leuz, and Verrecchia, 2005). In sum, the give-and-take above suggests tha t information asymmetries among the firm and investors and mingled with the principal and the agent can prevent efficient investment. In the following section, I discuss how financial reporting quality can enhance investment efficiency by mitigating these information asymmetries. . 2. manipulation of financial reporting Financial reporting quality can be associated with investment efficiency in at least two ways. First, it is comm merely postulated that financial reporting mitigates adverse selection costs (Arrow 5 in Figure 1) by lessen the information asymmetry between the 6 firm and investors, and among investors (Verrecchia, 2001). For instance, Leuz and Verrecchia (2000) find that a inscription to more manifestation reduces such information asymmetries and increases firm liquidity.On the other hand, the population of information asymmetry between the firm and investors could lead suppliers of capital to discount the note price and to increase the cost of raising capi tal because investors would infer that firms raising funds is of a bad type (Myers and Majluf, 1984). Thus, if financial reporting quality reduces adverse selection costs, it can improve investment efficiency by reducing the costs of outer financing and, as discussed in more detail downstairs, the potential for financial reporting quality to improve investment efficiency is greatest in firms facing financing constraints.Second, a large literature in be suggests that financial reporting plays a critical role in mitigating agency problems. For instance, financial news report information is comm yet utilize as a direct input into compensation contracts (Lambert, 2001) and is an central source of information use by shareholders to monitor managers (Bushman and Smith, 2001). Further, financial accounting system information contributes to the monitoring role of stock markets as an important source of firmspecific information (e. g. Holmstrom and Tirole, 1993 Bushman and Indjejikia n, 1993 Kanodia and Lee, 1998). Thus, if financial reporting quality reduces agency problems (Arrow 6 in Figure 1), it can then improve investment efficiency by increase shareholder superpower to monitor managers and hence improve project selection and reduce financing costs. 1 2. 3. Predictions For example, Bens and Monahan (2004) find a positive railroad tie between AIMR disclosure ratings and the profusion value of diversification as defined by Berger and Ofek (1995).They conclude that disclosure plays a monitoring role in mitigating managements investment decisions. 1 7 Based on the word of honor above that financial reporting affects both adverse selection and agency conflicts, I predict an modal(a) negative relation between financial reporting quality and both underinvestment and overinvestment. These links complement research in Bushman, Piotroski, and Smith (2005), which studies the relation between country judges of timely loss realization and the country propensit y to liquidate bad projects (i. e. , itigate overinvestment), and in Wang (2003) which explores the relation between capital allocation efficiency and accounting information quality for a taste of US firms, without making a distinction between under- and overinvestment. 2 H1 Financial reporting quality is negatively associated with underinvestment. H2 Financial reporting quality is negatively associated with overinvestment. In addition to canvass the modal(a) relation between financial reporting quality and investment efficiency, I to a fault canvass the mechanisms through which financial reporting quality can affect investment efficiency use cross-section(a) analysis.First, I predict that the relation between financial reporting quality and firm underinvestment is stronger for firms facing financing constraints. By definition, restrain firms are those for which the ability to raise funds is the most probably impediment to efficient investment, and for these firms, financial reporting quality is especially important in mitigating adverse selection costs. H3 The relation between financial reporting quality and underinvestment is stronger for financing constrained firms. 2One concern with Hypotheses 1 and 2 is that causality goes the other way. For instance, poorly bring to passing managers could be investing inefficiently and thus choose to report low quality financial information in point to hide their bad executeance (e. g. , Leuz, Nanda, and Wysocki, 2003). I discuss the empirical tests utilise to spoken language this alternative venture in Section 4. 8 Second, I predict that the relation between financial reporting quality and firm overinvestment is stronger for firms with large money balances and escaped currency flows.Managers of firms with large cash balances and dissolve cash flows have more fortune to engage in value destroying investment activities (e. g. , Jensen, 1986 Blanchard, Lopezde-Silanes, and Shleifer, 1994 Harford, 1999 Opl er et al. , 1999 Richardson, 2006). Consequently, financial reporting quality can play a more important monitoring role in mitigating agency problems for these firms. H4 The relation between financial reporting quality and overinvestment is stronger for firms safekeeping large cash balances and extra cash flows.Third, I study the complementary and substitute relation between financial reporting quality and a firms information environment, and how it affects investment efficiency. Financial reporting quality is just one source of information astir(predicate) the firms operations employ by investors. For instance, investors in firms followed by a large number of analysts or firms with informative stock prices may be less symbiotic on financial reports when other elements of the firms information environment are of high quality.Thus I hypothe surface that financial reporting quality is more important in change investment efficiency when the amount of information publicly access ible about the firm is low. 3 H5 The relation between financial reporting quality and investment efficiency is stronger for firms with relatively poor information environments. 3. existential work 3. 1. Proxies for investment efficiency One concern with Hypothesis 5 is that financial reporting quality and the firms information environment are likely to be agree.Indeed, Verdi (2005) shows that the firm information environment can be aggregated in accounting- found and market-establish check constructs. Hypothesis 5 implicitly assumes away this correlativity by analyse the meat of financial reporting quality on investment efficiency holding the market-based information environment constant. 3 9 In decree to construct banknotes of investment efficiency, I stolon estimate a mannequin that predicts firm investment trains and then use residuals from this mildew as a proxy for inefficient investment.The data are from the Compustat Annual file during the course of instructions 1980 to 2003. congeries new enthronement in a attached firm- course of study is the sum of capital expenditures (item 128), R&D expenditures (item 46), and acquisitions (item 129) negatively charged sales of PPE (item 107) and derogation and amortisation (item 125) multiplied by deoxycytidine monophosphate and scaled by average natural assets (item 6), following Richardson (2006). This heartbeat uses an accounting-based framework to estimate new investment as the renewing between quantity investment and investment needed for maintenance of assets in place.In the aesthesia section I in like manner discuss the robustness of the results to the use of only capital expenditures as an alternative proxy for investment that is frequently apply in the literature (e. g. , Hubbard, 1998). I estimate a parsimonious pretence for investment posit as a function of egress opportunities mensural by Tobins Q (Tobin, 1982). This toughie is based on the rivalry that growth opport unities should explain corporate investment when markets are perfect (Hubbard, 1998). Investmenti,t = ? 0 j,t + ? 1 j,t * Qi,t-1 + ? i,t (1) I estimate the sit cross-section(a)ly for all industries with at least 20 observations in a habituated year based on the Fama and French (1997) 48- manufacturing variety. Q is calculated as the ratio of the market value of rack up assets (defined as 4 A large finance literature uses investment cash flow sensitivities as a proxy for inefficient investment (or market frictions).I do not use this ascend for two reasons First, traditional papers measure cash flow without making the distinction between cash flows and accruals, and Bushman, Smith, and Zhang (2005) illustrate the sensitivity of the results to the tolerate measurement of operating cash flows. Second, positive investment cash flow sensitivities could guess both financing constraints and/or agency problems which makes it impossible to test the cross-sectional hypotheses of the pa per (Hypotheses 3 to 5). 10 otal assets (item 6) plus the product of stock price (item 199) and the number of common shares outstanding (item 199) damaging the book value of impartiality (item 60)) to book value of keep down assets (item 6) at the cash in ones chips of the fiscal year. The prove consists of 98,675 firm-year observations with useable data to estimate Investment and Q during the stress period of 1980 to 2003. Consistent with forward literature, financial firms (i. e. , SIC codes in the 6000 and 6999 send) are excluded because of the divergent nature of investment for these firms.In format to mitigate the influence of outliers I winsorize all unsettleds at the 1% and 99% levels by year. 5 submit 1 presents the results from the investment standard in comparability 1. grace A offers descriptive statistics for Investment and Q. The mean (median) firm in the sample invests 7. 26% (3. 84%) of arrive assets per year and has an average (median) Q equal to 1. 9 0 (1. 32), unvarying with relate literature (e. g. , Richardson, 2006 Almeida, Campello, and Weisbach, 2004).Panel B presents mean and median values of the estimated industry coefficients on Q, the average R-square, and the number of profound positive coefficients for classly year. In all years the mean and median coefficients are positive and relatively stable during the sample period. The mean R-square ranges from 6% in 1997 to 14% in 1991. 6 Finally, in each year, more than half of the industry coefficients on Q are positive and statistically different from zero at a pentad percent significance level. 7The sit in comparability 1 includes an tease which imposes that for each industry-year the mean firm will have a zero residual. In untabulated analysis, I re-estimate the bewilder adding the intercept back to the residual so that it allows industry-years to have a non-zero mean (for example, industries that overinvest or periods with large economic growth). The results ar e robust (in general even stronger) to this test. 6 nonee that the reported R-squares measure only the within industry-year translation because the model is estimated separately for each industry-year.An equivalent get down in which the model is estimated across all industry-years with separate intercepts and coefficients for each industry-year leads to an R-square of 23. 5%, suggesting that the boilersuit explanatory power of the model is big than that reported in dodge 1. 7 A watercourse ongoing contend in the finance literature is the implications for measurement error in the friendship of Q (Erickson and Whited, 2000 Gomes, 2001 Alti, 2003). Since the ulterior analysis hinges on the investment model in Equation 1, I perform two sensitivity tests First, I include erstwhile(prenominal) make its in 5 1 I measure investment efficiency victimisation the residuals from the model in Equation 1. Overinvestment is the positive residuals of the investment model and Underinvest ment is the negative residuals of the investment model multiplied by negative one, such that both measures are decreasing in investment efficiency. In untabulated analysis, I repeat all tests accomp eachingly excluding firms with the smallest 10% and 20% investment residuals because these firms are more likely to be affect by measurement error in the investment model (i. e. , mis classified advertisement as overinvesting or underinvesting firms).The results for these analyses are exchangeable to those reported below. confuse 1 Panel C presents descriptive statistics for Investment symmetry, Overinvestment and Underinvestment. By construction, Investment remainder has a mean value of zero ranging from -64. 46% to 80. 43%. There are 39,107 (59,568) firms classified as overinvesting (underinvesting) firms. The mean (median) value is 9. 73% (5. 63%) for Overinvestment and 6. 39% (4. 71%) for Underinvestment. These results show that the residuals from the investment model are more frequently negative, although in littler magnitude.Panel D presents Pearson correlations between the measures of investment efficiency and firm characteristics. Investment remainder is uncorrelated with firm size (measured as the log of total assets (item 6) at the start of the fiscal year) and sparingly negatively correlated with return excitability (measured as the exemplar deviation of daily returns during the prior fiscal year). However, when the residuals are separated into Overinvestment and Underinvestment, I find that these uncertains are negatively correlated with size and positively correlated with return volatility and Q (the magnitude of the he investment model to capture growth opportunities not reflected in Q (Lamont, 2000 Richardson, 2006) and consequence, I exclude all industry-year observations in which the estimated coefficient on Q is not positive and of import. The accompanying results are not sensitive to these tests. 12 correlations range from 0. 18 to 0 . 32). These results suggest each that (1) small firms, with more growth opportunities and vaporific operations, have more inefficient investment or (2) the investment model is a poor fit for these firms.In any case, it highlights the importance to apply for these firm characteristics in the subsequent analysis. In order to part understand the properties of the residuals from the investment model I perform analyses testing the persistence of investment efficiency over time. First, I find that 40% (48%) of the firms in the top ( crumb) Investment Residual quintile in a given year remain in the top (bottom) quintile in the following year, and 27% (36%) remain third years later (Panel E).In addition, one lag of Investment Residual in an autoregressive model explains 16% of current Investment Residual (untabulated). The inclusion of higher orders of past residuals has a small part in explanatory power (R-square of only 18% if five lags are include in the model). These analyses sug gest that residuals of the investment model are not random, which seems to support the view that they capture a firm investment characteristic. However, I cannot rule out the bill that the persistence in the residuals is a function of an omitted correlated inconstant in the investment model. . 2. Proxies for financial reporting quality The conceptual definition of financial reporting quality use in this paper is the the true with which financial reporting conveys information about the firms operations, in particular its expected cash flows, in order to inform investors in terms of equity investment decisions. This definition is consistent with the FASB SFAC No. 1 which states that one objective of financial reporting is to inform present and potential investors 13 in making rational investment decisions and in assessing the expected firm cash flows.I proxy for financial reporting quality using measures of accruals quality derived in prior work (Dechow and Dichev, 2002 McNichols, 2002) based on the idea that accruals are estimates of future cash flows, and earnings will be more representative of future cash flows when there is lower inclination error embedded in the accruals process (McNichols, 2002). 8 I estimate discretionary accruals using the Dechow and Dichev (2002) model augmented by the inherent uncertains in the Jones (1991) model as suggested by McNichols (2002). The model is a regression of work(a) capital ccruals on lagged, current, and future cash flows plus the change in gross and PPE. All variables are scaled by average total assets. Accrualsi,t = ? + ? 1* silver tendi,t-1 + ? 2*CashFlowi,t + ? 3*CashFlowi,t+1 + ? 4*? Revenuei,t + ? 5*PPEi,t + ? i,t. (2) where Accruals = (? CA ? Cash) (? CL ? STD) Dep, ? CA = castrate in current assets (item 4), ? Cash = win over in cash/cash equivalents (item 1), ? CL = change over in current liabilities (item 5), ? STD = Change in short(p)-term debt (item 34), Dep = Depreciation and amortization expense (item 14), CashFlow = Net income forrader droll items (item 18) minus Accruals ?Revenue = Change in revenue (item 12), and PPE = Gross property, plant, and equipment (item 7). All variables are chapfallen by average total assets (item 6). Following Francis et al. (2005), I estimate the model in Equation 2 crosssectionally for each industry with at least 20 observations in a given year based on the Fama and French (1997) 48-industry classification. AccrualsQuality at year t is the 8 I discuss the sensitivity of the results to the use of alternative measures of accruals quality and other attributes of earnings in Section 5. 4 standard deviation of the firm-level residuals from Equation 2 during the years t-5 to t-1, ensure that all explanatory variables are measured before period t for the figuring of AccrualsQuality in that year. I work out AccrualsQuality by negative one so that this variable becomes increase in financial reporting quality. As discussed in Dechow and Dichev (2002) and McNichols (2002), the estimation of AccrualsQuality captures the out-and-out(a) variation in the residuals of Equation 2 rather than the variation relative to a benchmark.One concern with this preliminary is that AccrualsQuality may be capturing some underlying degree of volatility in the business, and the results in consider panel 1 show that investment efficiency is negatively correlated with firm uncertainty. Thus, I follow the suggestion in McNichols (2002) and puddle a relative measure of accruals quality. In particular, I measure AccrualsQualityRel as the ratio of the standard deviation of the residuals from Equation 2 during the years t-5 to t-1 to the standard deviation of total accruals during the years t-5 to t-1 multiplied by negative one.This measure captures the relative variance of the estimation errors in accruals compared to the total variance. I show below that this measure is only slightly correlated with firm size and cash flow volatility, m itigating the concern that the proxies for financial reporting quality are associated with investment efficiency because of the spurious effect of firm uncertainty. 4. Results To enquire hypotheses 1 and 2, I first present preliminary analysis on the univariate relation between the measures of investment efficiency and financial reporting quality.Table 2 Panel A presents descriptive statistics for a little sample than reported in Table 1 due to data availableness for AccrualsQuality and AccrualsQualityRel. 15 The sample consists of 49,543 firm-year observations and all variables are winsorized at the 1% and 99% levels by year. In this sample, there are 19,473 (30,070) firms classified as overinvesting (underinvesting) firms. The mean (median) value for Overinvestment is 7. 81% (4. 45%) and for Underinvestment is 5. 37% (4. 09%).The magnitudes are little than reported in Table 1 because the data required to estimate AccrualsQuality and AccrualsQualityRel preconceived idea the s ample toward larger firms. Among the financial reporting quality proxies, the mean (median) firm in the sample has an AccrualsQuality of -0. 04 (0. 03) and an AccrualsQualityRel of -0. 74 (-0. 64). Finally, I include descriptive statistics on firm size, cash flow volatility, and Tobin Q because these firm characteristics are shown to be associated with investment efficiency in Table 1. The distribution of Q is slightly changed (as compared to Table 1) to a mean (median) Q of 1. 63 (1. 23) again reflecting the sample bias toward larger firms. Panel B presents Pearson (Spearman) correlations above (below) the main diagonal for the variables in Panel A. By construction, Overinvestment and Underinvestment cannot be correlated because each firm-year observation can only be in one group. Most importantly, Overinvestment is negatively correlated with AccrualsQuality (Pearson correlation equals -0. 19) and with AccrualsQualityRel (Pearson correlation equals -0. 8) the akin is true for Und erinvestment (Pearson correlations equal -0. 22 and -0. 10 respectively). These results present preliminary enjoin for the relation between financial reporting quality and investment efficiency in hypotheses 1 and 2. Finally, as in Dechow and Dichev (2002), AccrualsQuality is super correlated In Table 1, I use return volatility kind of of cash flow volatility to fend off imposing the five-year data requirement for the estimation of cash flow volatility. However, this data is required to estimate AccrualsQuality and does not impose any sample bias at this grade of the analysis.I use cash flow volatility in the remainder of the paper because AccrualsQuality is highly correlated with cash flow volatility as discussed by Dechow and Dichev (2002). However, the results are not sensitive to this choice. 9 16 with coat (Pearson correlation equals 0. 42) and with CashFlowVol (Pearson correlation equals -0. 66). However, note that AccrualsQualityRel is much less correlated with these va riables (correlations of -0. 08 and 0. 04 with size and cash flow volatility respectively), supporting the argument that this variable is uncorrelated with firm uncertainty. 0 Table 3 presents the thirdfold regressions. The estimated model is a regression of investment efficiency on financial reporting quality, firm characteristics, and industry (based on the Fama and French (1997) 48-industry classification) and year fixed effects. The leechlike variable is Underinvestment in the first two columns and Overinvestment in the remaining columns. All standard errors are clustered by firm using the HuberWhite procedure. 11 As predicted in speculation 1, Underinvestment is negatively related to AccrualsQuality and AccrualsQualityRel (both coefficients are prodigious at 1% level).The estimated coefficients are also negative and meaningful for Overinvestment, supporting the prediction in possibility 2. The estimated coefficients suggest that increasing AccrualsQuality (AccrualsQualit yRel) by one standard deviation is associated with a reduction on Underinvestment of 0. 21% (0. 11%) and on Overinvestment of 0. 31% (0. 22%). Given that the mean values for Underinvestment and Overinvestment in Table 2 are 5. 73% and 7. 81%, these changes average between 1% and 5%, suggesting that the economic significance of the effect is moderate.One alternative explanation for the results in Table 3 is that causality goes the other way. For instance, suppose that poorly performing managers are more likely to The signs of the correlations between AccrualsQuality and size and cash flow volatility are the opposite of the ones presented in Dechow and Dichev (2002) because I multiply AccrualsQuality by negative one so that this variable is increasing in reporting quality. 11 Petersen (2005) suggests two regularitys to correct for both cross-sectional and time-series dependence in the data the Huber-White procedure and adjusted Fama-MacBeth.Since, n all method is perfect, I repeat al l subsequent analysis using Fama-MacBeth (1973) estimators adjusting for time-series dependence. The results lead to the same inferences as reported in the text. 10 17 invest inefficiently and also choose to report low quality financial information in order to hide their bad performance (e. g. , Leuz, Nanda, and Wysocki, 2003). Then one could spuriously find a positive association between financial reporting quality and investment efficiency. In order to address this concern, I perform two tests.First, I repeat the analysis using the financial reporting quality proxies lagged by two periods (the variables in the model are already lagged by one period). Second, I explicitly control for past investment efficiency in the model. The mistrust behind this test is that if past investment efficiency drives financial reporting quality then there should be no relation between financial reporting quality and future investment efficiency after controlling for past investment efficiency. Table 4 Panel A presents the results of the two sensitivity analyses when Underinvestment is use as the dependent variable.When AccrualsQuality and AccrualsQualityRel (Columns I and II) are lagged by two periods, the inferences are unchanged. The estimated coefficients are statistically negative at conventional levels. In Columns III and IV, I include past Underinvestment in the model. In this case, the estimated coefficient on AccrualsQuality is unbosom negative and significant, while the coefficient on AccrualsQualityRel is negative but only peripherally significant (two-sided p-value of 0. 14). Table 4 Panel B repeats the analysis for Overinvestment.Again, all the inferences are unchanged since the estimated coefficients on AccrualsQuality and AccrualsQualityRel are statistically negative in all models. general, the results in Tables 3 and 4 support hypotheses 1 and 2 that financial reporting quality is negatively associated with both underinvestment and overinvestment, 18 consis tent with the argument that financial reporting mitigates both adverse selection and agency costs. 4. 1. Cross-sectional zones In this section, I discuss the empirical approach employ to test hypotheses 3, 4, and 5.These hypotheses involve cross-sectional predictions about the relation between financial reporting quality and investment efficiency across sub-groups of the sample. Thus, I estimate separate coefficients for these sub-groups as described in the model below (Investment Inefficiency) i,t = ? 0 + ? 1* district i,t-1 + ? 2* ReportingQuality i,t-1 + ? 3* ReportingQuality* Partition i,t-1 + ? 4* Controls i,t-1 ? ? t * Year t + ? ? j * persistence j + ? it. where Investment Inefficiency is either Underinvestment or (3) Overinvestment, ReportingQuality is either AccrualsQuality or AccrualsQualityRel.Partition is coded as an indicant variable based on measures of financing constraints, excess cash, or information environment described below (results are uniform if the Part ition is used as a continuous or ranked (deciles) variable). The partitioning variables are defined such that a negative coefficient on the fundamental fundamental fundamental interaction term (? 3) implies that the relation between financial reporting quality and inefficient investment is stronger for firms in the subgroup of interest (e. g. , financially constrained firms). As additional analysis, I test the null theory that the sum of the coefficients ? and ? 3 is equal to zero in order to test whether the relation between financial reporting quality and investment efficiency is at least present in the sub-group of interest. 12 12 Hypotheses 3 to 5 are also important in mitigating the concern that an omitted correlated variable could be driving the positive association between financial reporting quality and investment efficiency. For instance, if managers choose better (worse) investment projects and report more (less) informative financial accounting information when they know more (less) about growth opportunities and expected cash flows, 9 4. 1. 1. Financing Constraints In this section, I investigate hypothesis 3 which predicts that the relation between financial reporting quality and Underinvestment is stronger for financing constrained firms because these firms are, by definition, bound in their ability to raise funds. I follow the approach in Hubbard (1998) to tell apart firms into financially constrained and drop by the wayside categories. In particular, I use five different criteria because of the lack of consensus about which approach provides the best classification (Almeida, Campello, and Weisbach, 2004).First, I classify firms into Payout labored if the firm is in the bottom one-third quartiles in terms of total payout in a given year and unconstrained otherwise. I measure total payout as the sum of dividends and share repurchases collapse by year-end market capitalization using the method described in Boudoukh et al. (2005). Second, I cl assify firms into years labored if the firm is in the bottom three quartiles of firm age in a given year (and unconstrained otherwise) based on the argument that young firms are more likely to face financing constraints.Age is measured as the difference in years since the first year the firm appears in the CRSP database. Third, I classify firms into Size Constrained if the firm is in the bottom three quartiles of total assets in a given year and unconstrained otherwise. Fourth, I measure Rating Constrained if the firm has long-term debt outstanding (item 9) but does not have public debt rated by S&P (item 280) and unconstrained otherwise. Finally, I construct the KZ Index following the approach in Kaplan and Zingales (1997) and classify a firm as KZ Index Constrained hen a positive relation between financial reporting quality and investment efficiency could just be a observation of the quality of the managers information set and might not be related to financial reporting quality. However, this alternative hypothesis would not predict the relation between financial reporting quality and investment efficiency to be dependent on financing constraints, cash balances, or the existing information environment. Thus, if such interactions exist, then it would strengthen the result that financial reporting quality per se is associated with investment efficiency. 0 if the firm is in the top three quartiles of the KZ Index in a given year and unconstrained otherwise. 13 Untabulated analysis show that the first quaternsome classifications are positively correlated (Pearson correlations ranging from 0. 11 to 0. 45) but the KZ Index classification is not correlated with the remaining criteria (Pearson correlations ranging from -0. 01 to 0. 11), consistent with previous research (e. g. , Almeida, Campello, and Weisbach, 2004). 14 Further, all financing constraint proxies are positively correlated with Underinvestment (Pearson correlations range from 0. 1 to 0. 14). Table 5 presents the results related to hypothesis 3. All models include the control variables size, cash flow volatility, Q, and industry and year fixed effects as before but the coefficient estimates on these variables are not tabulated for brevity. The estimated coefficients on the control variables are akin(predicate) to those reported in Table 3. The results are separated for AccrualsQuality and for AccrualsQualityRel. For AccrualsQuality, the estimated coefficients on the main effect (third column labeled Reporting Quality) are all egative with only one statistically significant coefficient. These results indicate that, for a sample of unconstrained firms, the relation between AccrualsQuality and Underinvestment is basically not significant. The estimated coefficients on the interaction terms, however, are negative in four out of five cases and significant in two. Further, the F-test rejects the hypothesis of no relation between AccrualsQuality and Underinvestment in almost all ca ses for the sample of financially constrained firms. The only riddance is 3 The KZ Index is calculated using the following formula KZ Index = -1. 002 * CashFlow + 0. 283 * Q + 3. 139 * supplement 39. 368 * Dividends 1. 315 * Cash. For more details see Almeida, Campello, and Weisbach (2004, p. 1790). 14 Principal component analysis on the five financing constraints proxies yields two factors. The first factor explains 40% of the variation and laden on all proxies but the KZ Index. The second factor explains another 20% of the variation in the data and loads on the Payout and the KZ Index measures. 1 when the KZ Index is used as the criteria for financing constraint classification. 15 When AccrualsQualityRel is used as the financial reporting quality proxy, the results are largely the same. In terms of economic significance, increasing AccrualsQuality (AccrualsQualityRel) by one standard deviation is associated with a reduction in Underinvestment of 0. 26% (0. 16%) for firms clas sified as Rating Constrained and 0. 08% (0. 06%) for unconstrained firms (compared to 0. 21% (0. 11%) for the full sample as discussed above).Overall, the results present marginal support for hypothesis 3 that the relation between financial reporting quality and Underinvestment is stronger for financing constrained firms. 4. 1. 2. Cash Balances In this section, I investigate hypothesis 4 which predicts that the relation between financial reporting quality and Overinvestment is stronger for firms with large cash balances and expel cash flows because these firms are more likely to overspend existing resources (Jensen, 1986). I use two criteria to classify firms based on cash holdings and one proxy for ease cash flow.First, I create an indicator variable, exalted Cash, coded as 1 if the firm is above the median in the distribution of cash balances deflated by total assets in a given year and 0 otherwise. Second, I follow the approach in Opler et al. (1999) who predict cash balances as a function of firms characteristics, and use residuals from this model as a proxy for excess cash. Opler et al. show that firms hold more cash in the presence of growth opportunities and firm uncertainty, and less cash when they are strained to payout interest obligations and have more entryway to financing (proxied by leverage and size).Thus, I estimate yearly regressions of cash balances (item 1) deflated by total 15 The mismatched result using the KZ Index is consistent with prior work in the finance literature (e. g. , Almeida, Campello, and Weisbach, 2004 Almeida and Campello, 2005) which finds opposite results when this variable is used as a proxy for financing constraints. 22 assets (item 6) on firm size, leverage, Q, and cash flow volatility. Leverage is measured as the sum of the book value of short term (item 34) and long term debt (item 9) deflated by the book value of equity (item 60) and the remaining variables are the same as described above.The explanatory power of the models ranges from 16% in 1986 to 42% in 2003. I create an indicator variable, Excess Cash, coded as 1 if the firm has a positive residual from the model predicting cash balances, and 0 otherwise. Finally, following Richardson (2006), Free Cash Flow is equal to cash flow from operations plus R&D expenses minus depreciation and the predicted investment for the firm as estimated in Table 1. Free Cash Flow is recoded as an indicator variable coded as 1 if the computation of free cash flow is positive and 0 otherwise.Table 6 presents the results related to hypothesis 4. As before, all models include the control variables size, cash flow volatility, Q, and industry and year fixed effects (estimates not tabulated). The first set of results presents estimated coefficients for AccrualsQuality and the second reports coefficients for AccrualsQualityRel. The results show that the estimated coefficients on the main effect of financial reporting quality are negative but not significant i n all six models (three models for AccrualsQuality and three for AccrualsQualityRel).The estimated coefficients on the interaction term, on the other hand, are negative in all cases and significant in three out of six cases, and the F-test rejects the hypothesis of no relation in all cases. In terms of economic significance, increasing AccrualsQuality (AccrualsQualityRel) by one standard deviation is associated with a reduction on Overinvestment of 0. 41% (0. 35%) for firms classified as High Cash and 0. 06% (0. 06%) for firms with low cash (compared to 0. 31% (0. 22%) for the full sample as discussed above).Overall, the results support hypothesis 4 by showing that the 23 relation between financial reporting quality and Overinvestment is stronger for firms with large and excessive cash balances but the results are not statistically significant for firms generating free cash flows. This support the hypothesis that financial reporting quality reduces firm overinvestment by lowering sh areholders cost of monitoring managers and thus limiting managers ability to undertake inefficient investment projects. 4. 1. 3.Information Environment In this section, I investigate hypothesis 5 which predicts that the relation between financial reporting quality and investment efficiency is stronger for firms with poor information environments because investors of these firms are more likely to rely on financial accounting information to infer the economic conditions of the firms operations. I use two proxies for the firm information environment the number of analysts following the firm and the bid-ask give out. I use the number of analysts following a firm as a proxy for the amount of publicly available information about the firm. analysts are an important source of information for investors they issue forecasts, reports about individual companies, and stock recommendations. Roulstone (2003) examines the role of analysts in ameliorate market liquidity and finds that analysts pr ovide public information that reduces information asymmetries between firms and market participants. I collect data on analyst following from IBES and measure the number of analysts following the firm as the maximum number of analysts forecasting annual earnings for a firm during the fiscal year t.If the firm is not followed by IBES I assume that the number of analysts following the firm is zero. I consider a firm as Low Analyst if the firm is in the bottom three quartiles in a given year (coded as 1 and 0 otherwise). 24 The second proxy for a firms information environment is the bid-ask spread. ascertain Amihud and Mendelson (1986) and Roulstone (2003) among others for discussions of spreads as a proxy for the information asymmetry between the firm and investors.I collect intra solar day trade data to bet bid-ask spread from the Trades and Quotes database (TAQ) and from the Institute for the Study of gage Markets database (ISSM). The TAQ database includes trades and quotes start ing in 1993, and the ISSM database contains intraday data for big board/AMEX firms from 1983 to 1992 and for NASDAQ firms from 1987 to 1992. I measure quoted bid-ask spread as the ask price minus the bid price split up by the average of the bid and ask prices. The bid-ask spread is averaged across all transactions during the day for each firm, then daily mean bid-ask spreads are averaged during the month t.Finally I compute bid-ask spread as the average of the monthly bid-ask spreads during the fiscal year t. I consider a firm as High Spread if the firm is in the top three quartiles in a given year (coded as 1 and 0 otherwise). Table 7 presents the results related to hypothesis 5. As before, all models include the control variables (estimates are untabulated). The table is divided into Underinvestment and Overinvestment results. The first set of results presents estimated coefficients for AccrualsQuality and the second reports coefficients forAccrualsQualityRel. When bid-ask spread is used as the partitioning variable, I find that none of the coefficients on the main effect of financial reporting quality are significant, and three out of four coefficients on the interaction term are significant. The only exception is the coefficient on the interaction between High Spread and AccrualsQualityRel for Underinvestment. Further, in three out of four cases the F-test rejects the hypothesis of no effect of financial reporting quality on investment efficiency 25 for the sample of firms with High Spread.As for Low Analyst, the results on the estimated coefficients on the interaction terms are feebleer only one coefficient is statistically negative. Still, in three out of four models the F-test rejects the hypothesis of no relation for the sample of firms with Low Analyst. Overall, the results provide weak support for the hypothesis that the effect of financial reporting on investment efficiency is more important when the firm information environment is of low quality. 16 5. esthesia Analysis In this section I discuss some robustness tests to the analysis presented in the paper.First, I study the sensitivity of the results to inclusion of omitted control variables using firm fixed-effect estimation. The advantage of this approach is that it controls for all time-invariant unperceivable firm characteristics. However, since the estimation of AccrualsQuality and AccrualsQualityRel is done using five years of data, the within-firm variation is small, which makes the fixed-effect estimation very conservative. The analysis is done for all firms with at least five, ten, or 15 years of data in order to increase the within firm variation (sample sizes of 43,739, 33,454, and 24,420 firm-year observations respectively).Untabulated analyses show that the results in Hypotheses 1 and 4 are more often than not robust to the firm fixed-effect estimation. Results of Hypotheses 2 and 3 are weaker (coefficients are of the same sign but in most cases not signifi cant at conventional levels) and, in the case of Hypothesis 5, the results are similar (weaker) when Underinvestment (Overinvestment) is used as the dependent variable. I also performed tests using a 22 classification based on the firms financial reporting quality and information environment (sorted independently as a low/high).Either high financial reporting quality or high information environment is sufficient to mitigate Underinvestment but only financial reporting quality is sufficient to mitigate Overinvestment, suggesting a substitute relation between financial reporting quality and the firm information environment in improving investment efficiency. 16 26 Second, I investigate the sensitivity of the results to the use of alternative measures of accruals quality such as the non-linear discretionary accruals model in musket ball and Shivakumar (2005) and the accrual quality measures developed by Wysocki (2006).The key unveiling in Wysockis (2006) measures is to remove the sua vity effect of accruals in the Dechow and Dichev (2002) model. Results using the Ball and Shivakumar (2005) model are very similar to those reported on the paper. The use of Wysockis measure, on the other hand, leads to similar results for hypotheses 1, 2, and 5 but insignificant results for hypotheses 3 and 4. As discussed in more detail below, these results are not surprising given that Wysockis (2006) measure excludes the insipidness component of accruals, and insipidness is positively associated with investment efficiency.In addition, I investigate the sensitivity of the results to the use of alternative attributes of earnings as proxies for financial reporting quality. Accruals quality represents one dimension of financial reporting quality but other dimensions of earnings have also been used as a proxy for financial reporting quality (Francis et al. , 2004). These attributes of earnings would not necessarily affect investment efficiency in the same way.For instance, one coul d argue Timeliness and Conservatism are more important in conveying information about bad firms economic states, thus improving Overinvestment but may not be associated with Underinvestment. Nevertheless, it is useful to see how these measures are related and the respective association with investment efficiency (Verdi, 2005). Francis et al. (2004) depict six earnings attributes (other than AccrualsQuality) previously used in accounting research to characterise desirable features of earnings. The six attributes are Persistence, Predictability, Smoothness, 27 ValueRelevance, Timeliness, and Conservatism.I also include a measure of price informativeness as used by Durnev, Morck, and Yeung (2004). When Underinvestment is used as the dependent variable (Hypotheses 1 and 3), I find consistent results using Persistence, Predictability, and Smoothness but insignificant results for the remaining variables (with the exception of Informativeness in which the relation is positive and signifi cant, against the prediction). The analysis using Overinvestment (Hypotheses 2 and 4) yield weaker results since only the estimated coefficients on Smoothness and Informativeness are negative and significant in the expected direction.The remaining coefficients are either insignificantly negative or positive in the case of Persistence. Overall the results provide marginal support for the relation between other dimensions of earnings and Underinvestment, and weak support for Overinvestment. The finding that Smoothness is negatively associated with both Underinvestment and Overinvestment explains the weaker results using Wysockis measure of accruals quality given that this measure excludes the smoothness component in the accruals quality measure developed by Dechow and Dichev (2002).In the third sensitivity test, I repeat the analysis using capital expenditures (deflated by average total assets) as a measure of investment in order to make the results more comparable with the extant fin ance literature. In addition, the investment measure used in the paper includes only cash acquisitions and ignores stock acquisitions which constitute the majority of M&A transactions. Untabulated analyses using CAPEX show that the results in Hypothesis 1, 3, and 5 are similar to those reported. Results in Hypothesis 2 are consistent but weaker when AccrualsQuality is used as the proxy for 28 inancial reporting quality. Finally, results are inconsistent with Hypothesis 4 (estimated coefficients on the interaction terms are mostly insignificant). Finally, I include good will (item 204) in the discretionary accruals model. As discussed in Jones (1991), PPE is include in the model to capture the normal level of depreciation, and using the same logic, gracility would capture the normal level of amortization in accruals. This inclusion is justified because the measure of investment includes acquisitions. Goodwill is only available from Compustat starting in 1988 which is why it is exclu ded in the main tests.In untabulated analysis I find little impact on the discretionary accruals model (the Pearson correlation between discretionary accruals including and excluding goodwill is 0. 99), and the results presented in the paper are unchanged if I flash back the sample to post 1988 and include goodwill in the discretionary accruals model. 6. Summary and destruction Despite recent claims that financial reporting quality can have economic implications for investment efficiency, there is little evidence on this relation empirically. This paper studies the relation between financial reporting quality and investment efficiency.The analysis is done on a sample of 49,543 firm-year observations during the sample period of 1980 to 2003. I find that proxies for financial reporting quality, namely measures of accruals quality, are negatively associated with both firm underinvestment and overinvestment. The relation between financial reporting quality and underinvestment is stron ger for firms facing financing constraints, consistent with the argument that financial accounting information can reduce the information asymmetry between the firm and investors, and 29 thus lower the firms cost of raising funds.Likewise, the relation between financial reporting quality and overinvestment is stronger for firms with large cash balances, which suggests that financial reporting quality can reduce the information asymmetry between the principal and the agent and thus lower shareholders cost of monitoring managers and improving project selection. Finally, I find that the relation between financial reporting quality and investment efficiency is stronger for firms with low quality information environments. 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