Loan, security, and dividend choices by
individual (unconsolidated) public and private
commercial banks
Frederick Niswander
a,*, Edward P. Swanson
baDepartment of Accounting, School of Business, East Carolina University, GCB 3204 Greenville,
NC 27858, USA
bLowry Mays College and Graduate School of Business, Texas A&M University, College Station,
TX 77843-4353, USA
Abstract
Using call report data, we consider whether the discretionary portion of loan loss provisions, loan charge-os, securities gains and losses, and dividends are in¯uenced by the bank's level of capital, earnings, and taxes. We studied more than 11,000 banks. We ®nd that banks below a capital adequacy threshold often make discretionary choices that reduce earnings and capital. Banks above the threshold exhibit dierent discre-tionary outcomes, with evidence of income smoothing and tax-advantaged actions. Ó 2000 Elsevier Science Ltd. All rights reserved.
1. Introduction
The United States (US) savings and loan crisis and questions about the viability of banks in some Asian countries serve as reminders of the importance of realistic reporting of the economic condition of ®nancial institutions (White, 1991, pp. 82±87). Several studies have investigated whether bank managers use their discretion in making accounting and ®nancing choices to manage reported accounting information (Moyer, 1990; Scholes et al., 1990; Collins et al., 1995; Wahlen, 1994; Beatty et al., 1995; Beatty and Harris, 1999). These
*Corresponding author. Tel.: +1-252-328-6970; fax: +1-252-328-4091.
E-mail address:niswanderf@mail.edu.ecu (F. Niswander).
studies suggest that bank managers often make accounting and ®nancing choices to manage capital levels, earnings, and taxes. These choices can in turn have a substantial eect on the evaluation of economic condition.
Our study uses data from Consolidated Reports of Condition and Income (call reports) provided by the Federal Deposit Insurance Corporation (FDIC) for each bank insured by the FDIC. For more than 11,000 banks, we examined four accounting and ®nancing choices that allow bank managers substantial discretion over the amount recorded. The four choices are the amount of the loan loss provision, loan charge-os, securities gains and losses, and dividends. For each choice, we ®t an ordinary least squares (OLS) regression model with variables to control for non-discretionary behavior and examine whether the remaining (discretionary) variation is associated with capital level, earnings, and marginal tax rate. The OLS regression equations were estimated as a system of simultaneous equations using seemingly unrelated regression (SUR) for each sample year 1987, 1988, and on a pooled basis. During this period, capital adequacy regulations did not vary (Koch, 1995, p. 389; Collins et al., 1995, p. 266).
Our study contributes to understanding bank accounting and auditing in four ways. First, we explicitly consider the roles of bank auditors and regu-lators as well as bank managers in our hypothesis development.1;2
As more fully explained in Section 2.2, we suggest that, for low capital banks, auditors and regulators prefer conservative accounting estimates which are usually at variance with the preferences of managers. We predict that, for banks below a capital adequacy threshold used by regulators, the conservative preferences of auditors and regulators will prevail for accounting choices subject to year-end adjustment. In particular, auditors and regulators close scrutiny of a low capital bank's loan portfolio lead managers to exercise discretion conserva-tively.
Second, previous studies (e.g., Moyer, 1990; Beatty et al., 1995; Collins et al., 1995) have investigated one or more of these four choices using data for ap-proximately 150 consolidated public banks. Our research examines public banks at the unconsolidated level, thereby including over 1,500 individual, unconsolidated, public banks.3These individual banks are important because
1
Throughout our paper, auditor refers to independent auditors while regulator or examiner refers to the governmental agency or agencies responsible for regulation of the bank.
2
It should be noted that, by design, bank examiners do not perform ®nancial statement audits. Examiners spend considerable time appraising asset quality (particularly the loan portfolio) and management (Koch, 1995, pp. 40±42). For an overview of the examination process, see Cocheo (1986).
regulatory capital constraints apply to subsidiary banks, as well as to the consolidated bank holding company. The use of call report data also allows us to include private banks, which have been omitted from other studies despite their economic importance.4 Our sample includes over 9,800 private banks. The ability to examine choices of private ®rms on a large scale is probably unique to the banking industry.
Third, literature (e.g., Moyer, 1990; Beatty et al., 1995; Collins et al., 1995) suggests that the extent of audit and regulatory scrutiny is in¯uenced by a capital adequacy threshold that distinguishes between potentially troubled banks and those with a safe margin of capital. Managers may be less able to use discretion to manage the capital level, earnings, and taxes for banks below this threshold. Consistent with prior research (e.g., Moyer, 1990), we use a research design that allows a separate analysis of choices by banks below and above a capital threshold (proforma capital of 7.5%).5 Four subgroups of banks are considered: below-capital-threshold public, below-capital-threshold private, above-capital-threshold public, and above-capital-threshold private. Below-capital-threshold banks have greatest implications for public policy due to the high cost of audit failure to taxpayers, stockholders, and others. Some of our most important results are for these banks.
Fourth, we investigate whether discretionary choices dier depending upon whether a bank is publicly or privately held. We examine whether dierences occur in the magnitude and direction of their response to incentives provided by capital levels, earnings, and taxes.
To our knowledge, our study is the ®rst to combine an extensive set of jointly determined accounting and ®nancing choices, a research design that permits detection of dierential discretionary choices across capital adequacy thresholds, and a large sample of public and private unconsolidated banks. Our expectations and primary ®ndings are summarized below. We organize the discussion by below-capital-threshold banks, above-capital-threshold banks, and the dierences between public and private banks.
The loan loss provision and loan charge-o decisions are the most material discretionary choices and literature indicates that auditors and regulators monitor these choices closely. For below-capital-threshold banks, we expect auditors and regulators want conservative choices that reduce earnings or capital and we expect their preferences will prevail. We found that banks with proforma capital less than 7.5% use accounting discretion in a manner that
4To the best of our knowledge, the only other studies to use call report data to investigate any of these choices are Carey (1994) and Beatty and Harris (1999). Both examine only the securities gain and loss choice.
further reduces capital (earnings) by recognizing a larger discretionary loan charge-o (loan loss provision). These ®ndings are consistent with auditors mandating the use of estimates of earnings and capital for below-capital-threshold banks that are conservative. (For the loan loss provision, in which earnings and capital level provide con¯icting incentives, earnings dominates capital.) The results are robust and apply to both public and private banks.
The results for discretionary securities gains and losses are less robust.6 Consistent with auditor and regulator conservatism, we found that below-capital-threshold public and private banks with the lowest capital realize smaller net security gains, thereby further reducing capital. Marginal tax rates are not related to discretionary securities gains and losses. For discretionary dividends, there is no systematic relationship between capital level and divi-dends for below-threshold banks, possibly because most of these banks pay little or no dividends.
For high-capital-threshold banks, we found that accounting and ®nancing choices are often dierent than for below-capital-threshold banks. Of partic-ular importance, there is little evidence of the auditor conservatism we found for below-capital-threshold banks. Instead, we found evidence that public and private banks with low (high) earnings tend to realize more (fewer) net secu-rities gains, thereby smoothing income. Public banks also use the discretionary portion of the loan provision choice in a manner consistent with smoothing income. In addition, tax minimization has an in¯uence: contrary to our ®nd-ings for below-capital-threshold banks, we found evidence that higher marginal tax rates result in more loan charge-os and fewer net securities gains by both public and private banks above the capital threshold.
And ®nally, we provide evidence about the dierences in discretionary ac-counting and ®nancing choices between public and private banks. For below-capital-threshold banks, we found that the magnitude of the conservative use of accounting discretion for the loan loss provision (to reduce earnings) and for the loan charge-os (to reduce capital) are larger for public than private banks. These two dierences may be due to the greater potential legal liability to external auditors from failure of a public bank.
In contrast, for above-capital-threshold banks, we found several dierences. The magnitudes of the tax savings from realizing fewer net securities gains and from greater loan loss charge-os are larger for public than private banks. This dierence likely re¯ects more sophisticated tax-savvy managers at public banks. The magnitude of income smoothing using the loan loss provision is also greater for public than private banks above the capital threshold, probably
6This observation is generally true of prior research as well. For example, Collins et al. (1995, pp. 265, 266), comment ``. . .the relation between capital and securities gains and losses is less
due to greater pressure for public banks to meet expected earnings levels. And ®nally, as capital levels increase, public banks increase dividend payouts more than private banks. Private banks may be retaining funds to minimize the personal tax payments of the owners and to increase bank capital.
Results indicate audits and regulatory oversight counter the incentives that managers at banks below a regulatory capital threshold have to use their discretion to increase capital or earnings. The strong contrast between banks above and below the capital threshold in their use of discretion emphasizes the importance of auditor and regulator scrutiny. These conservative results exist for both public and private banks. The issue of whether this conservative bias is desirable is left to policy makers.7
The remainder of the paper is organized as follows. Section 2 develops our expectations about the in¯uence of auditor monitoring. Section 3 describes the sample, and Section 4 reviews the research design. The empirical results are presented in Section 5. Section 6 summarizes our results.
2. Eect of auditor and regulator monitoring on manager's use of accounting discretion
2.1. Introduction
In this section, we examine whether the discretionary portion of accounting numbers is likely to re¯ect the preferences of auditors, regulators, or managers in speci®c settings. We ®rst consider banks with capital below a threshold that increases regulatory scrutiny. Next, we discuss how accounting discretion may be used dierently in banks above this capital threshold. Finally, we consider whether accounting discretion is likely to be used dierently in public and private banks.
2.2. Low capital banks
2.2.1. Preferences of managers, auditors, and regulators
The costs of regulation can be substantial (Darnell, 1982, pp. 9±10; Chang, 1982, pp. 19±20). Costs are clearly higher for banks with substandard or marginal capital ratios: regulators can impose costly restrictions on managerial ¯exibility by refusing to permit establishment of a branch; refusing to approve a merger; disapproving a change in ownership or control; requiring higher
minimum capital requirements than required of other banks; and requiring changes to ®nancial statement data (Code of Federal Regulations, 1990, paras. 3.10, 325.3, and 325.4). Ultimately, regulators have the authority to close a bank (Code of Federal Regulations, 1990, paragraph 3.14). Because these steps reduce or eliminate managerial control and managers' wealth is reduced by many of these costs, managers of banks at or near regulatory capital con-straints are expected to prefer accounting and ®nancing choices that increase reported capital and/or earnings. This expectation is consistent with the views of Moyer (1990, p. 153), Beatty et al. (1995, p. 232), and Collins et al. (1995, p. 267).
Although managers of a bank with low capital may wish to reduce regu-latory costs, banks that are close to their capital constraints come under in-creased supervision by regulatory authorities (Thomson, 1991, pp. 9±10; Carroll, 1989, p. 16; Whalen and Thomson, 1988, pp. 17±19), including an increased likelihood of a regulatory examination (Federal Deposit Insurance Corporation, 1988, p. 4). Managers of a bank that is under increased regula-tory scrutiny have less ¯exibility in using accounting or ®nancing discretion, since available options would then be in¯uenced by the preferences of auditors and regulators. As further explained below, we suggest that auditors and regulators are likely to favor conservative estimates that fall within the range of probable outcomes.
Extant banking literature (e.g., Koch, 1995) and regulatory guidance (e.g., Federal Deposit Insurance Corporation, 1990), speci®cally as pertains to loan-related items, clearly indicates that regulators prefer conservative out-comes. Many bank management texts express the view of Koch (1995) who states:
Regulators prefer that the banks err by overestimating potential losses. In contrast, banks often prefer to report the lowest possible reserve that still protects against losses because this provides the highest possible reported net income (Koch, 1995, p. 742).
Koch's (1995) views are reenforced by Federal regulations. The FDIC Manual of Bank Examination Policies requires banks to maintain a level of loan loss allowance which is not only adequate, but is also conservative, re¯ecting the diculty inherent in estimating future credit losses (Federal Deposit Insurance Corporation, 1990, Section 3.1, Loans).
In accounting and auditing, there exists a long tradition of conservatism as a response to uncertainty. Independent auditors are concerned with the risk and consequences of audit failure, including its eect on their professional repu-tation and legal liability (Davis and Simon, 1992, pp. 66±67; Stice, 1991, p. 516; Palmrose, 1988, p. 57). Accounting researchers have found that auditor con-servatism plays a role in many empirical and experimental settings, including: auditor switching (DeFond and Subramanyam, 1998, p. 37; Krishnan and Stephens, 1995, pp. 195±196; Krishnan, 1994, p. 214); audit reporting (Francis and Krishnan, 1999, p. 157); audit evidence search (McMillan and White, 1993, p. 444; Trotman and Sng, 1989, pp. 566±568; Kida, 1984); analytical review (Kinney and Uecker, 1982, pp. 66±68); and auditor accountability (Homan and Patton, 1997, p. 228; Peecher, 1996, pp. 133±139). In particular, Hack-enbrack and Nelson (1996, p. 45) found that ``. . .auditors tend to require high-engagement risk clients to adopt conservative reporting methods.'' Thus, for low capital banks, we expect auditors and bank examiners prefer conservative measures of capital and earnings.
An alternative argument can be made that audits and examinations result in unbiased, rather than conservative, accounting estimates. By demanding con-servative estimates, independent auditors may be criticized by bank managers and could lose future audit engagements. Regulatory examiners could be forced to justify conservative actions to supervisors.8 The argument for un-biased estimates has some merit, but since the accurate (unun-biased) amounts are unknown and the risk that auditors will be criticized for a bank failure is higher if capital or earnings have been overstated, we believe a risk adverse auditor would prefer conservative estimates for low capital banks.
2.2.2. Manager and auditor power
Limits on managers' use of their accounting discretion are in¯uenced by the extent to which managers and auditors have con¯icting preferences and whether one of the parties is in a position of power to strongly in¯uence or dictate the outcome.
Con¯icts occur between an auditor and their client during the course of an audit. Resolution of auditor/client con¯icts is often eected through a bar-gaining process (Lev, 1979, p. 166), wherein each of the participants can be viewed as possessing a certain amount of power to enforce their respective positions (Goldman and Barlev, 1974, pp. 707±711; Nichols and Price, 1976, pp. 335±336). Given that disagreements occur and that management and auditors may have con¯icting incentives, especially when the client is facing
®nancial distress, the issue becomes: which party would be expected to prevail in a given situation? To answer that question, extant literature suggests two factors that must be evaluated.
The ®rst one concerns the audit service contract. Early theoretical work in generalized audit settings suggests that managers are in a powerful position relative to auditors, primarily because managers can in¯uence audit fees and hire or ®re the auditor (Emerson, 1962; Goldman and Barlev, 1974, p. 710; Nichols and Price, 1976, pp. 338±340). However, in bank audits, management's position is much weaker. Unlike most businesses, banks are faced with two sets of outside evaluators ± the external auditor hired by the bank and the bank examiner. Although bank managers have a measure of economic power over their external auditor, they cannot ®re the bank examiner. Further, although non-bank management generally has wide latitude in negotiating the fees of external auditors, bank examiners do not charge a separate fee that can be threatened.9 As a consequence, the power of bank management in an ac-counting con¯ict is likely much more limited than the power of non-bank management.
The second factor aecting power is the ®nancial health of the client. Survey and empirical research suggest that client ®nancial distress results in a shift of power to the auditor. Knapp (1985, p. 202) found that clients in good ®nancial condition are perceived as having the upper hand, while those in poor shape are unlikely to prevail in a con¯ict with auditors. Using audit quality review ®ndings for government entities, Deis and Giroux (1992, pp. 467±469) devel-oped an audit quality score. Deis and Giroux (1992, p. 476) found that audit quality increased as ®nancial health of the client declined. Petroni and Beasley (1996, p. 156) oer a maintained hypothesis that auditing eort is greater for clients in poor ®nancial health. Hackenbrack and Nelson (1996, p. 45) also support the notion that auditors prevail when clients are in poor ®nancial health.
For these reasons, we believe that auditors' preferences are more likely to dominate managers' preferences for banks below a capital threshold that re-sults in increased regulatory scrutiny. In the next section, we relax this con-clusion when the accounting or ®nancing choice is not subject to audit adjustment.
2.2.3. Whether the accounting choice is subject to audit adjustment
The resolution (or even the very existence) of a con¯ict is in¯uenced by the nature of the item being examined. Absent errors or irregularities, the ac-counting treatment of most transactions which occur during the year is not
subject to change. An example is the gain or loss recorded on the sale of marketable securities. The securities portfolio of a bank serves a number of purposes: it is a storehouse of liquidity; it is an integral part of asset±liability management; and the interest generated is an important contributor to bank earnings (Sinkey, 1989, chapters 13, 15, and 16; Hempel and Simonson, 1991, chapter 11). One or more of these purposes often dictates the purchase and sale of securities throughout the year. If prudent bank management requires the sale of securities, managers have considerable choice as towhichsecurities to sell; thus managers can in¯uence the magnitude of any gain or loss realized. Since securities gains and losses are not subject to ex post audit adjustment, regulators have little control over the level of securities gain or loss (Beatty and Harris, 1999, p. 304, also make this argument). Accounting for dividend payments is similar, since once the transaction has occurred, the ®nancial eect is recorded and not subject to adjustment. Further, some evidence indicates that bank regulators do not systematically intervene during the year to force reduced dividend payments (French, 1991, p. 7; Horne, 1991, p. 15).
Unlike completed transactions, many accruals and estimates are not ®nal-ized until year-end and are subject to auditor adjustment. Important accruals and estimates for banks include loan loss provisions and loan charge-os. Signi®cant judgement is involved in estimating these loan-related items (Sin-key, 1989, pp. 543±546; Wahlen, 1994, pp. 457±458; Beaver et al., 1989, p. 162). The vast majority of regulatory oversight time is spent on the loan portfolio, including loan classi®cation (as performing vs. non-performing), loan loss provision, and loan charge-os (Mitchell, 1984, p. 19; May, 1991, p. 61; Koch, 1995, pp. 40±43). In the 1980s, regulatory pressure was increased in the areas of loan portfolios and the allowance process (Walter, 1991, pp. 24±25; Spinard, 1992, p. 59). This regulatory pressure leads to potential disagreements with bank managers whose judgement may be questioned (Fleischer, 1991, pp. 33± 35; Nadler, 1991, p. 19). The extent of con¯ict can be substantial over loan charge-os, since an increased amount reduces capital dollar-for-dollar. A change in the loan loss provision also directly aects earnings, but it has a smaller, and opposite, eect on capital.10
To summarize, for banks below a capital threshold that results in increased regulatory scrutiny, we expect auditor conservatism to prevail in con¯icts with
10
managers that involve accounting discretion over items subject to year-end adjustment (e.g., loan loss provisions and loan charge-os). For completed transactions (e.g., securities gains and losses, and dividends), we expect audi-tors are not able to restrict managers' use of discretion.
2.3. High capital banks
The shift of power to auditors that occurs when a bank is in poor ®nancial health should shift back towards managers when a bank is in good ®nancial condition. Further, since federal bank examiners operate in a resource-con-strained environment, they concentrate their scarce audit resources on low capital banks, not those with high capital (e.g., Federal Deposit Insurance Corporation, 1988, p. 4). For example, during the period of this study (1987 and 1988), a goal of the FDIC was to audit troubled banks on a yearly basis, but only to perform ®eld audits on non-troubled banks every two years (Federal Deposit Insurance Corporation, 1988, p. 4). These two factors suggest that managers' incentives should become dominant for all discretionary accounting and ®nancing choices when capital is relatively high.
Yet, we expect managers of ®nancially healthy banks to no longer focus on increasing capital and/or earnings. Managers may make positive or negative discretionary accruals to maximize payments under a bonus plan (Healy, 1985, pp. 86±87), to comply with accounting provisions in contracts (Watts and Zimmerman, 1986, pp. 179±199), or to smooth income (Beatty and Harris, 1999, p. 30; Ronen and Sadan, 1981). Depending upon a bank's incentives, managers may want to increase or decrease income. As explained in Section 2.4, we expect above-threshold public banks to manage earnings to a greater extent than above-threshold private banks.
We also expect mangers of above-capital-threshold banks to incorporate the eect of taxes in their discretionary choices. The marginal corporate tax rate should aect the level of loan charge-os and realized securities gains and losses but not loan loss provisions and dividends since these items do not aect corporate taxable income (Collins et al., 1995, pp. 268±270). Following Scholes et al. (1990, p. 633), we estimated relative marginal tax rates using the pro-portion of assets represented by municipal bond holdings. Higher levels of municipal bonds are a surrogate for a higher marginal tax rate. As the marginal tax rate increases, each dollar of loan charge-o provides a greater tax shield and each dollar of realized securities gain costs more in taxes. As a result, we expect a positive (negative) relationship between the marginal rate and loan charge-os (net security gains).11These relationships are consistent with extant
literature (Scholes et al., 1990, p. 645; Collins et al., 1995, p. 270; Beatty et al., 1995, p. 242; Beatty and Harris, 1999, p. 309).
2.4. Public and private bank comparisons
Empirical accounting research that explores dierences between public and private ®rms is limited ± primarily because data are extremely dicult to obtain.12 Further, the banking literature contains relatively little theo-retical work to guide our tests. Our analysis is therefore somewhat explor-atory.
Unlike our tests for below- and above-capital-threshold banks, for public and private banks we are not interested in whether the discretionary actions are dierent from zero, but whether the actions of public and private banks are dierent from one another. Our expectations are stated accordingly.
For banks with capital below the threshold, we do not expect any sub-stantial dierences between the discretionary actions of public and private banks. Auditors would continue to seek conservative numbers, and managers would prefer to report higher capital and/or earnings. However, for above-capital-threshold banks, we expect the discretionary actions of public and private banks will diverge.
The manager and/or owner of a private bank typically has a greater pro-portion of his or her personal wealth concentrated in bank ownership (Sullivan and Spong, 1998, p. 22). Hughes and Mester (1998, pp. 314±317) show man-agers use capital to signal risk and that there is a negative relationship between capital and risk. Thus, compared to public banks, we expect private banks to have higher capital (signaling lower risk) and to take discretionary actions to maintain or improve capital. This can be accomplished by above-threshold private banks recording a larger loan loss provision, more net securities gains, fewer loan charge-os, and lower dividend payouts when compared to above-threshold public banks.
In the case of the earnings incentive for banks above the capital threshold, consistent with Beatty and Harris (1999, p. 302), we argue that information asymmetry between managers and stockholders and/or agency cost issues will result in greater earnings management by public banks when compared to private banks. This could result in public banks making greater use than private banks of the loan loss provision and net securities gains to smooth income.
In Section 2.3 we argued that, ceteris paribus,banks seek to maximize the tax shield provided by deductions and minimize the tax cost imposed on
income. Cloyd et al. (1996, pp. 25±26) present evidence consistent with the notion that private ®rms are more inclined to make decisions that increase tax-related cash ¯ows when compared to public ®rms. Thus, we expect above-threshold private banks will record greater loan charge-os and fewer net securities gains than will above-threshold public banks, for a given a marginal tax rate.
Our expectations for public and private banks are summarized at the bot-tom of Table 9.
3. Sample
The sample data were obtained from annual FDIC tapes. These tapes report ®nancial and other data for each bank covered by FDIC deposit insurance (substantially all banks in the US). Data are provided at the individual bank level, rather than as a consolidated group. The data are from 1987 and 1988. These years were chosen because they are in the middle of a time period in which capital ratio rules were stable (e.g., Koch, 1995, p. 389). Capital ade-quacy rules changed in 1985 and risk-adjusted capital standards were adopted in late 1989 (to become fully eective in 1992) (e.g., Koch, 1995, p. 389). Thus, 1987 and 1988 are years in which bank data should be relatively free from non-recurring adjustments for changes in capital adequacy regulations.13
Table 1, panel A reports the number of banks used in the analysis, the number removed, and the reasons for their removal. We ®rst deleted mutual savings banks, foreign banks, banks in US possessions, and non-banks (banks with Bank Charter Codes of 30 and above).14 Next, new banks, those not in existence for at least four years as of the end of the year, were removed because evidence suggests that they are structured and operated in a dierent manner than established banks (e.g., Avery and Belton, 1987, p. 252).15Small banks,
13As suggested by a reviewer, the in¯uence of proposed changes in capital adequacy requirements on bank accounting and ®nancing choices is also a subject worthy of study. Knowledge of behavior under capital requirements that do not vary provides a benchmark for studying the eect of changes.
14
These banks are included on the tapes because they must report to the FDIC, similar to domestic banks. However, their regulatory structure diers substantially from other banks. Mutual savings banks are similar to savings and loan institutions and are subject to regulations which dier, in many material respects, from those for commercial banks. For the other types of banks listed, their operations and, in many cases, primary regulators dier from those of US banks.
those with less than $10 million in assets, were then removed because they are likely to have a dierent cost curve than other banks (Kolari and Zardkoohi, 1987, pp. 64±72). Finally, we removed banks with zero assets, zero operations, zero loans, or missing data for required variables. The ®nal sample of 11,620 banks from 1987 and 11,332 banks from 1988 was used to ®t regressions that isolate the discretionary portion of the accounting and ®nancing choices.
Table 1, panel B summarizes the number of public and private banks in our sample.
Table 1
Sample informationa
Panel A: Number of observations
1987 1988
Banks on the FDIC tapes each year 14,799 14,246
Less reductions for:
Savings banks, foreign banks, banks in possessions, and non-banks (charter codes 30 or higher)
1,183 1,202
Banks not in existence for 4 years as of 12/31/87 or 12/31/88, as appropriate
853 684
Assets less than $10 million 785 726
Zero assets, zero operations, zero loans, in liquidation, or missing data required to construct regressions
358 302
Total useable observations 11,620 11,332
Panel B: Observations classi®ed as public/private and high/low capital
PFCAP PFCAP
1987 Data <7.5% P7.5% Total
Public banks 444 1,210 1,654
Private banks 1,085 8,881 9,966
Total 1,529 10,091 1,620
PFCAP PFCAP
1988 Data <7.5% P7.5% Total
Public banks 356 1,202 1,558
Private banks 1,089 8,685 9,774
Total 1,445 9,887 11,332
a
4. Research design
4.1. Model development
We use OLS regression to ®t separate models to investigate how managers use their discretion in recording the loan loss provision (LLP), loan charge-os (LCO), security gains and losses (SGL), and dividends (DIV). Because dis-cretionary choice decisions may be determined jointly (Moyer, 1990, p. 142; Beatty et al., 1995, p. 232) the OLS regression models are estimated as a system of simultaneous equations using SUR. To increase the relation to prior re-search, regression variables are similar to Collins et al. (1995, pp. 289±290) as noted in Table 2.
Each of the four regression models includes one or more control variables designed to measure the non-discretionary portion of the choice. The control variables for both the loan provision and loan charge-o choices are beginning loan loss allowance (BLLA), beginning non-performing loans (BNPL), and the change in non-performing loans during the year (CHNPL). The beginning loan allowance is included in the LCO model because a higher allowance would indicate greater charge-os are expected. It is included in the LLP model be-cause accounting practice indicates that provisions over time are auto-corre-lated. Non-performing loans are included in both models as an indicator of loan portfolio default risk. This balance is a relatively non-discretionary risk indicator because interest and principal payments more than 90 days overdue must be classi®ed as non-performing.
For the SGL model, the control variable is the amount of unrealized ap-preciation at the beginning of the period (APPREC). This represents the net pre-tax gain or loss a bank would realize if the entire securities portfolio was sold at that time.16The larger (smaller) the amount of unrealized appreciation, the larger (smaller) the net gain likely to be realized in the absence of manager bias.
The prior year's dividends (PYDIV) serve as a control variable for the DIV model. Bank dividends have been shown to be relatively stable over time (French, 1991, pp. 6±7) and dividend payments have been shown to be sticky even when capital is low (French, 1991, p. 7; Horne, 1991, p. 15). This suggests that the level of dividends paid in the prior year is a reasonable estimate of an unbiased dividend payment.
The models also contain incentive variables to investigate whether manag-ers' choice decisions are biased in the sense that the managers have used their
16Unlike SFAS 115,
discretion to manage the level of proforma capital (PFCAP), earnings (EARN), or corporate taxes (MUNI). Each of the four accounting and ®-nancing choices aect the level of capital; the loan loss provision and securities gains and losses also change earnings; and loan charge-os and securities gains and losses modify taxes. If the capital, earnings, or tax variables are signi®cant
Table 2
Variables used in this studya
Dependent variables
LLP Loan loss provision
LCO Loan charge-os
SGL Securities gains or losses DIV Common stock dividends
Independent variables of interest and dummy variables
PFCAP Proforma capital (following Collins et al., 1995, pp. 289±290) calculated as: primary capital at the beginning of the year, plus operating income before securities gains or losses, loan loss provision, and taxes.
EARN Non-discretionary earnings (following Collins et al., 1995, p. 290) calculated as operating income before securities gains or losses, loan loss provision, and taxes.
MUNI Municipal securities held calculated as percentage of banks' assets held in tax-advantaged municipal bonds as of the beginning of the year.
D1, D2, D3, D4 Dummy variables denoting four categories of banks as follows:
Category D1 D2 D3 D4
BLLA Beginning balance of loan loss allowance BNPL Beginning balance of non-performing loans
CHNPL Change in balance of non-performing loans during the year. APPREC Dierence between the cost and fair market value of the
securities portfolio as of the beginning of the year. A negative number indicates that cost exceeds FMV.
PYDIV Common stock dividends paid in the prior year. a
in explaining a choice, this suggests that managers have made a biased ac-counting or ®nancing choice.
The regression models have been designed to be consistent with prior re-search, as mentioned previously (e.g., Collins et al., 1995, pp. 289±290). The incentive variables are always the same as those used by Collins et al. (1995, pp. 289±290).17The control variables for the LLP and LCO models are also identical to Collins et al. (1995, pp. 289±290).18In order to increase explana-tory power and use the types of data provided in call reports, the control variables for the SGL model and the DIV model dier from Collins et al. (1995).19The incentive and control variables used in each regression model are summarized below.
We have hypothesized that accounting discretion is used dierently by public and private banks and by banks above and below a capital adequacy threshold used by regulators. Thus, we have four categories of banks that may use discretion dierently: threshold public, below-capital-threshold private, above-capital-below-capital-threshold public, and above-capital-below-capital-threshold private. To allow for dierences, we use dummy variables to permit regression coecients for the intercept and for the non-control continuous variables to vary between the four categories.20
Accounting or ®nancing choice
Incentive variables (discretionary portion)
Control variables
(non-discretionary portion)
LLP PFCAP EARN BLLA BNPL CHNPL
LCO PFCAP MUNI BLLA BNPL CHNPL
SGL PFCAP EARN MUNI APPREC
DIV PFCAP PYDIV
17For LCO, both the Collins et al. (1995, p. 290) model and our model use a MUNI variable to capture the eect of taxes on the non-discretionary component of accounting choice. The Collins et al. (1995, p. 290) variable is based on tax-advantaged municipal bonds as a percentage of the banks' investment portfolio. Because we scale all other continuous variables by total assets, we measure MUNI as municipal bonds divided by total assets.
18
However, Collins et al. (1995, p. 264) used these variables in bank-speci®c regressions ®t over a twenty-year period, while we used the variables in cross-sectional models pooled across years.
19
Information on unrealized appreciation in the securities portfolio spread was unavailable in the data used by Collins et al. (1995).
The threshold between low and high capital banks is based upon guidelines established by the FDIC and the Oce of the Comptroller of the Currency (OCC). In 1985, regulators adopted uniform capital adequacy rules that es-tablished certain tiers, or zones, for capital adequacy evaluations (Mitchell, 1984, p. 21). Although regulators established a ¯oor (5.5% of primary capital), in practice, they used a higher threshold: Banks with primary capital over 7% were deemed by regulators to be adequately capitalized and were not examined as closely as those with less capital (Mitchell, 1984, pp. 20±21; Sinkey, 1989, pp. 606±608; Golembe and Holland, 1986, pp. 731±733). Since primary capital includes any discretionary behavior, we need to convert the regulator-derived 7% primary capital standard into our proforma capital metric, PFCAP.
PFCAP is de®ned, consistent with Collins et al. (1995, pp. 289±290), as primary capital from the prior year plus current operating income before discretionary items. To reconcile between regulatory primary capital and an approximation of PFCAP, we must add the loan loss provision, add an esti-mate of income taxes, and subtract securities gains (add losses). Using 1988 medians, regulatory primary capital of 7% of assets equals a PFCAP of 7.52% of assets. For simplicity, we use PFCAP of 7.5% or more to denote an above-capital-threshold bank and less than 7.5% for a below-above-capital-threshold bank.21
5. Empirical results
5.1. Descriptive analysis
Table 2 provides a description of the variables used in the tables. The di-rectional expectations for model variables are set forth in Table 3. Table 4 presents the number of observations and the mean and median values of all variables used in the regression equations. Amounts are presented for the entire sample, for public and private banks, and for banks above and below the capital adequacy threshold. All amounts, except total assets and the number of observations, are de¯ated by total assets. Medians present a more informative picture than means since the values are not normally distributed.
21
Table 3
Summary of hypothesized eects for all modelsa
Variable of interest Outcome preferred by Hypothesized observed eect
Managers Auditors
LLP model
PFCAP
Below-threshold banks ÿ
Above-threshold banks =ÿ =ÿ =ÿ EARN
Below-threshold banks ÿ ÿ
Above-threshold banks =ÿ =ÿ =ÿ
LCO model
PFCAP
Below-threshold banks ÿ ÿ
Above-threshold banks =ÿ =ÿ =ÿ MUNI
All banks =ÿ
SGL model
PFCAP
Below-threshold banks ÿ ÿ
Above-threshold banks =ÿ =ÿ =ÿ EARN
Below-threshold banks ÿ ÿ
Above-threshold banks =ÿ =ÿ =ÿ MUNI
all banks ÿ =ÿ ÿ
DIV model
PFCAP
Below-threshold banks
Above-threshold banks =ÿ =ÿ =ÿ
aBelow-threshold banks are those with proforma capital (PFCAP) <7.5% while above-threshold banks have proforma capital P7:5%.
As more fully explained in the text, the above eects are consistent with:
Below-threshold banks
± managers have a preference for exercising capital- and earnings-increasing discretion. ± auditors have a preference for capital- and earnings-decreasing discretion (conservatism). ± auditors are successful in constraining manager actions for those variables which are deter-mined at year end (LLP and LCO models), but not for those which are made throughout the year (SGL and DIV models).
Above-threshold banks
± no systematic direction.
All banks
Mean and median values of variables (all values, except observations and total assets, are shown as a percentage of total assets
All observations All observations split into All observations split into
Public banks Private banks Proforma capital
<7.5%
Proforma capital P7.5%
1987 1988 1987 1988 1987 1988 1987 1988 1987 1988
Number of observations
11,620 11,332 1,654 1,558 9,966 9,774 1,529 1,445 10,091 9,887
Total assets (in millions)
Mean 244.0 263.1 1,220.2 1,423.0 82.0 78.3 538.6 411.7 199.4 241.4
Median 45.5 46.7 125.6 162.2 40.2 40.8 65.7 60.5 43.2 45.4
LLP Mean 0.68% 0.53% 0.74% 0.60% 0.67% 0.51% 0.90% 0.93% 0.64% 0.47%
Median 0.34% 0.25% 0.35% 0.28% 0.34% 0.24% 0.40% 0.35% 0.33% 0.24%
PFCAP Mean 10.11% 10.16% 8.68% 8.90% 10.34% 10.36% 6.21% 5.98% 10.70% 10.77%
Median 9.74% 9.76% 8.57% 8.75% 9.96% 9.95% 6.71% 6.56% 10.10% 10.14%
EARN Mean 1.39% 1.42% 1.33% 1.44% 1.40% 1.41% 0.48% 0.43% 1.53% 1.56%
Median 1.46% 1.49% 1.44% 1.57% 1.47% 1.47% 0.79% 0.83% 1.54% 1.55%
BLLA Mean 0.79% 0.84% 0.91% 0.98% 0.77% 0.82% 0.95% 1.07% 0.77% 0.81%
Median 0.62% 0.66% 0.73% 0.76% 0.59% 0.64% 0.65% 0.69% 0.62% 0.66%
BNPL Mean 1.54% 1.30% 1.42% 1.19% 1.55% 1.32% 2.11% 2.09% 1.45% 1.19%
Median 0.93% 0.76% 0.87% 0.68% 0.94% 0.78% 1.00% 0.97% 0.93% 0.74%
CHNPL Mean )0.13% )0.06% )0.11% 0.01% )0.13% )0.07% )0.12% 0.07% )0.13% )0.08%
Median )0.05% )0.02% )0.04% )0.00% )0.05% )0.02% )0.02% 0.03% )0.06% )0.03%
LCO Mean 0.58% 0.46% 0.59% 0.51% 0.58% 0.45% 0.81% 0.84% 0.55% 0.41%
Median 0.27% 0.19% 0.26% 0.21% 0.27% 0.19% 0.33% 0.29% 0.26% 0.18%
MUNI Mean 5.80% 4.96% 4.45% 4.19% 6.02% 5.09% 2.85% 2.23% 6.25% 5.36%
Median 4.66% 3.83% 3.74% 3.55% 4.88% 3.91% 1.70% 1.22% 5.23% 4.36%
F.
Niswander,
E.P.
Swanson
/
J.
Accounting
and
Public
Policy
19
(2000)
201±235
Table 4 (continued)
All observations All observations split into All observations split into
Public banks Private banks Proforma capital
<7.5%
Proforma capital P7.5%
1987 1988 1987 1988 1987 1988 1987 1988 1987 1988
SGL Mean 0.03% 0.00% 0.03% 0.00% 0.03% 0.00% 0.04% )0.01% 0.03% 0.00%
Median 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%
APPREC Mean 0.82% )0.13% 0.45% )0.09% 0.88% )0.13% 0.31% )0.33% 0.89% )0.10%
Median 0.60% )0.07% 0.32% )0.06% 0.68% )0.07% 0.18% )0.13% 0.69% )0.05%
DIV Mean 0.37% 0.42% 0.46% 0.56% 0.36% 0.39% 0.13% 0.14% 0.41% 0.46%
Median 0.25% 0.28% 0.36% 0.42% 0.24% 0.26% 0.00% 0.00% 0.29% 0.32%
aVariables are as described in Table 2.
F.
Niswander,
E.P.
Swanson
/
J.
Accounting
and
Public
Policy
19
(2000)
In 1987, the median unconsolidated bank had total assets of just over $45.5 million, proforma capital of 9.7% of assets ($4.4 million), and proforma earnings of 1.46% of assets ($664,000).22With regard to the accounting choices investigated in our study, the median bank had a beginning loan loss allowance of $282,000, took $123,000 of loan charge-os, recorded a current loan loss provision of $153,000, net securities gains of $1,000, and paid dividends of $114,000.
Public and private banks exhibit similar median levels of loan loss provi-sions, loan charge-os, proforma earnings, change in non-performing loans, and realized securities gains. In contrast, private banks have fewer assets, more proforma capital, lower beginning loan loss allowance, higher beginning non-performing loans, greater municipal bond holdings, greater unrealized appre-ciation in the securities account (in 1987, but not in 1988), and lower dividend payments.
When the observations are dichotomized into banks with proforma capital above and below 7.5%, the two groups have similar levels of loan loss provi-sion, beginning loan loss allowance, beginning non-performing loans (in 1987 but not in 1988), and realized securities gains/losses. Below-capital-threshold banks have more assets, lower earnings, less improvement in non-performing loans, slightly more loan charge-os, a much lower marginal tax rate, less unrealized securities appreciation, and lower dividend payments.
5.2. Results by choice model
5.2.1. Overview
The results for each choice model are set forth in Tables 5±8. For each detailed model, the control variables (BLLA, BNPL, CHNPL, APPREC, and PYDIV, as appropriate) explain the non-discretionary component of variation in the choice decision. Each model incorporates dummy variables to classify banks into one of four categories based on whether PFCAP (a measure of pre-discretionary bank capital) is over or under the 7.5% threshold and whether the bank is public or private. The discretionary variables of interest re¯ect the variation associated with the capital, earnings, or tax incentives for each cat-egory of bank. The dummy variables are constructed to discern whether the variable of interest is dierent from zero rather than dierent from the actions of a base group. In the tables, data on the incentive variables are presented ®rst because they are the variables of interest, followed by the control variables, and then the intercepts.
LLP model and OLS regression results solved using SURa;b;c;d
Variable N22;952 N11;332 N11;620
Pooled 1988 1987
Ho Par. Est. t-value p-value Par. Est. t-value p-value Par. Est. t-value p-value
Discretionary variables: PFCAP
b5: Public, PFCAP <7.5% 0.00797 0.384 0.3506 0.00770 0.276 0.3914 ÿ0.00775 ÿ0.248 0.4020 b6: Private, PFCAP <7.5% ÿ0.01052 ÿ0.842 0.2000 ÿ0.01646 ÿ1.024 0.1528 0.01559 0.795 0.2134
b7: Public, PFCAPP7.5% =ÿ 0.00337 0.503 0.6152 ÿ0.00314 ÿ0.428 0.6683 0.01413 0.939 0.3480
b8: Private, PFCAPP7.5% =ÿ 0.01618 6.176 0.0001 0.01932 5.471 0.0001 0.01306 3.386 0.0007
EARN
b9: Public, PFCAP <7.5% ÿ ÿ0.31937 ÿ21.849 0.0001 ÿ0.43884 ÿ23.428 0.0001 ÿ0.12685 ÿ5.470 0.0001
b10: Private, PFCAP <7.5% ÿ ÿ0.02615 ÿ3.087 0.0010 ÿ0.09165 ÿ8.491 0.0001 0.06418 4.761 0.0001
b11: Public, PFCAPP7.5% =ÿ 0.04235 4.147 0.0001 0.09277 6.948 0.0001 ÿ0.01583 ÿ1.011 0.3123
b12: Private, PFCAPP7.5% =ÿ 0.00282 0.586 0.5577 ÿ0.01508 ÿ2.270 0.0232 0.02168 3.128 0.0018
Control variables:
b13: BLLA 0.04467 3.930 0.0001 0.05019 3.312 0.0009 0.07143 4.137 0.0001
b14: BNPL 0.36954 79.701 0.0001 0.36740 54.869 0.0001 0.36699 56.319 0.0001
b15: CHNPL 0.32581 67.340 0.0001 0.33813 49.397 0.0001 0.31715 46.815 0.0001
Intercept variables:
b1: Public, PFCAP <7.5% 0.00433 3.396 0.0007 0.00513 3.076 0.0021 0.00382 1.950 0.0512
b2: Private, PFCAP <7.5% 0.00110 1.382 0.1671 0.00145 1.422 0.1550 ÿ0.00074 ÿ0.588 0.5566 b3: Public, PFCAPP7.5% 0.00013 0.205 0.8376 ÿ0.00081 ÿ1.105 0.2690 0.00057 0.400 0.6894 b4: Private, PFCAPP7.5% ÿ0.00120 ÿ4.105 0.0001 ÿ0.00175 ÿ4.451 0.0001 ÿ0.00077 ÿ1.797 0.0723 aVariables are described in Table 2. All variables, except dummy variables, are divided by total assets.
b
p-values are one-tailed for Ho with a directional expectation; two-tailed otherwise. c
Models in Tables 5±8 are solved as a system of regression equations using SUR. The system-weightedR2for the SUR system of equations is 0.4114 for 1987, 0.4235 for 1988, and 0.4115 for the pooled model.
d
LLPib1D1ib2D2ib3D3ib4D4ib5 PFCAPiD1i b6 PFCAPiD2i b7 PFCAPiD3i b8 PFCAPiD4i b9 EARNiD1i
b10 EARNiD2i b11 EARNiD3i b12 EARNiD4i b13BLLAib14BNPLib15CHNPLiei:
F.
Niswander,
E.P.
Swanson
/
J.
Accounting
and
Public
Policy
19
(2000)
LCO model and OLS regression results solved using SUR
b5: Public, PFCAP <7.5% ÿ ÿ0.12031 ÿ7.626 0.0001 ÿ0.13736 ÿ6.426 0.0001 ÿ0.11115 ÿ4.721 0.0001
b6: Private, PFCAP <7.5% ÿ ÿ0.03377 ÿ3.413 0.0003 ÿ0.08312 ÿ6.545 0.0001 0.03341 2.140 0.0162
b7: Public, PFCAP P 7.5% =ÿ 0.01419 2.616 0.0089 0.01562 2.614 0.0090 0.00929 0.767 0.4429
b8: Private, PFCAP P7.5% =ÿ 0.01179 5.394 0.0001 0.01119 3.726 0.0002 0.01288 4.067 0.0001
MUNI
b9: Public, PFCAP <7.5% ÿ0.01040 ÿ2.004 0.0226 0.00024 0.028 0.4888 ÿ0.00537 ÿ0.811 0.2086
b10: Private, PFCAP <7.5% ÿ0.00239 ÿ0.885 0.1880 ÿ0.00066 ÿ0.163 0.4353 ÿ0.00367 ÿ1.013 0.1556
b11: Public, PFCAP P7.5% 0.00760 3.719 0.0001 0.00380 1.229 0.0969 0.01053 3.685 0.0001
b12: Private, PFCAPP7.5% 0.00210 3.481 0.0003 0.00294 3.324 0.0005 0.00059 0.710 0.2388
Control variables:
b13: BLLA 0.43015 44.860 0.0001 0.44968 34.539 0.0001 0.42137 29.491 0.0001
b14: BNPL 0.26277 67.842 0.0001 0.25597 44.955 0.0001 0.26153 48.736 0.0001 b15: CHNPL 0.16427 40.434 0.0001 0.15811 27.031 0.0001 0.16784 29.761 0.0001
Intercept variables:
b1: Public, PFCAP <7.5% 0.00647 6.404 0.0001 0.00660 4.932 0.0001 0.00621 4.048 0.0001
b2: Private, PFCAP <7.5% 0.00045 0.692 0.4890 0.00306 3.694 0.0002 ÿ0.00328 ÿ3.239 0.0012
b3: Public, PFCAP P7.5% ÿ0.00391 ÿ7.034 0.0001 ÿ0.00436 ÿ6.790 0.0001 ÿ0.00312 ÿ2.648 0.0081
b4: Private, PFCAP P7.5% ÿ0.00327 ÿ13.292 0.0001 ÿ0.00384ÿ11.394 0.0001 ÿ0.00269 ÿ7.552 0.0001
a
Variables are described in Table 2. All variables, except dummy variables, are divided by total assets. b
p-values are one-tailed for Ho with a directional expectation; two-tailed otherwise. c
Models in Tables 5±8 are solved as a system of regression equations using SUR. The system-weightedR2for the SUR system of equations is 0.4114 for 1987, 0.4235 for 1988, and 0.4115 for the pooled model.
Table 7
SGL model and OLS regression results solved using SURa;b;c;d
Variable N22;952 N11;332 N11;620
Pooled 1988 1987
Ho Par. Est. t-value p-value Par. Est. t-value p-value Par. Est. t-value p-value
Discretionary variables:
PFCAP
b5: Public, PFCAP <7.5% ) 0.01187 2.020 0.0217 0.00567 0.660 0.2548 0.01541 1.891 0.0293
b6: Private, PFCAP <7.5% ) 0.00538 1.613 0.0533 0.00716 1.512 0.0653 0.00394 0.837 0.2015
b7: Public, PFCAP P7.5% =ÿ 0.00048 0.284 0.7765 ÿ0.00040 ÿ0.197 0.8441 0.00008 0.023 0.9813
b8: Private, PFCAP P 7.5% =ÿ ÿ0.00018 ÿ0.261 0.7941 ÿ0.00020 ÿ0.204 0.8382 ÿ0.00121 ÿ1.285 0.1990
EARN
b9: Public, PFCAP <7.5% ÿ ÿ0.01003 ÿ1.550 0.0606 ÿ0.01057 ÿ1.195 0.1162 ÿ0.00477 ÿ0.494 0.3106
b10: Private, PFCAP <7.5% ÿ ÿ0.00393 ÿ1.063 0.1440 ÿ0.00906 ÿ1.781 0.0375 0.00114 0.209 0.4173
b11: Public, PFCAPP 7.5% =ÿ ÿ0.01422 ÿ3.144 0.0017 ÿ0.00282 ÿ0.446 0.6555 ÿ0.02487 ÿ3.828 0.0001
b12: Private, PFCAP P7.5% =ÿ ÿ0.01403 ÿ6.690 0.0001 ÿ0.00517 ÿ1.646 0.0997 ÿ0.02178 ÿ7.802 0.0001
MUNI
b13: Public, PFCAP <7.5% ÿ ÿ0.00315 ÿ1.143 0.1266 ÿ0.00572 ÿ1.189 0.1172 ÿ0.00286 ÿ0.850 0.1976
b14: Private, PFCAP <7.5% ÿ ÿ0.00151 ÿ1.058 0.1452 0.00030 0.133 0.4472 ÿ0.00306 ÿ1.672 0.0473 b15: Public, PFCAPP7.5% ÿ ÿ0.00299 ÿ2.764 0.0029 ÿ0.00065 ÿ0.398 0.3453 ÿ0.00467 ÿ3.233 0.0006 b16: Private, PFCAP P7.5% ÿ ÿ0.00056 ÿ1.709 0.0437 0.00062 1.254 0.1049 ÿ0.00126 ÿ2.860 0.0022
Control variables:
b17: Public, APPREC 0.03565 24.928 0.0001 0.05354 19.590 0.0001 0.03209 15.786 0.0001
F.
Niswander,
E.P.
Swanson
/
J.
Accounting
and
Public
Policy
19
(2000)
b1: Public, PFCAP <7.5% ÿ0.00044 ÿ1.244 0.2136 ÿ0.00005 ÿ0.096 0.9237 ÿ0.00064 ÿ1.268 0.2049
b2: Private, PFCAP <7.5% ÿ0.00008 ÿ0.420 0.6744 ÿ0.00025 ÿ0.904 0.3659 0.00015 0.528 0.5974
b3: Public, PFCAP P 7.5% 0.00042 2.679 0.0074 0.00015 0.793 0.4278 0.00079 2.518 0.0118
b4: Private, PFCAP P 7.5% 0.00028 4.180 0.0001 0.00017 1.745 0.0810 0.00052 5.637 0.0001
aVariables are described in Table 2. All variables, except dummy variables, are divided by total assets.
bp-values are one-tailed for Ho with a directional expectation; two-tailed otherwise.
cModels in Tables 5±8 are solved as a system of regression equations using SUR. The system-weighted
R2for the SUR system of equations is 0.4114 for 1987, 0.4235 for 1988, and 0.4115 for the pooled model.
dSGLib
1D1ib2D2ib3D3ib4D4ib5 PFCAPiD1i b6 PFCAPiD2i b7 PFCAPiD3i b8 PFCAPiD4i b9 EARNiD1i b10 EARNiD2i b11 EARNiD3i b12 EARNiD4i b13 MUNIiD1i b14 MUNIiD2i b15 MUNIiD3i
b16 MUNIiD4i b17APPRECiei:
F.
Niswander,
E.P.
Swanson
/
J.
Accounting
and
Public
Policy
19
(2000)
201±235
Table 8
DIV model and OLS regression results solved using SURa;b;c;d
Variable N22;952 N11;332 N11;620
Pooled 1988 1987
Ho Par. Est. t-value p-value Par. Est. t-value p-value Par. Est. t-value p-value
Discretionary variables:
PFCAP
b5: Public, PFCAP <7.5% 0.00312 0.318 0.3753 ÿ0.00282 ÿ0.196 0.4224 0.01598 1.191 0.1169
b6: Private, PFCAP <7.5% 0.00219 0.359 0.3598 0.00197 0.233 0.4078 0.00262 0.295 0.3839
b7: Public, PFCAPP 7.5% =ÿ 0.05956 17.480 0.0001 0.04579 11.241 0.0001 0.10975 15.793 0.0001
b8: Private, PFCAPP7.5% =ÿ 0.03485 25.933 0.0001 0.04092 20.501 0.0001 0.02839 15.888 0.0001
Control variable:
b9: PYDIV 0.32918 58.743 0.0001 0.33413 40.564 0.0001 0.32266 42.817 0.0001
Intercept variables:
b1: Public, PFCAP <7.5% 0.00129 2.090 0.0366 0.00205 2.322 0.0202 0.00017 0.194 0.8462
b2: Private, PFCAP <7.5% 0.00047 1.214 0.2246 0.00049 0.923 0.3562 0.00044 0.776 0.4379
b3: Public, PFCAPP 7.5% ÿ0.00146 ÿ4.272 0.0001 0.00014 0.323 0.7466 ÿ0.00651 ÿ9.649 0.0001
b4: Private, PFCAPP7.5% ÿ0.00092 ÿ6.124 0.0001 ÿ0.00137 ÿ6.116 0.0001 ÿ0.00042 ÿ2.108 0.0351
a
Variables are described in Table 2. All variables, except dummy variables, are divided by total assets. b
p-values are one-tailed for Ho with a directional expectation; two-tailed otherwise.
cModels in Tables 5±8 are solved as a system of regression equations using SUR. The system-weighted
R2for the SUR system of equations is 0.4114 for 1987, 0.4235 for 1988, and 0.4115 for the pooled model.
dDIVib
1D1ib2D2ib3D3ib4D4ib5 PFCAPiD1i b6 PFCAPiD2i b7 PFCAPiD3i b8 PFCAPiD4i b9PYDIViei:
F.
Niswander,
E.P.
Swanson
/
J.
Accounting
and
Public
Policy
19
(2000)
The system-weighted R2 for the SUR system of equations is 0.4114 for
1987, 0.4235 for 1988, and 0.4115 for the pooled model. P-values presented are one-tailed for variables with a directional expectation and two-tailed for all others. In the interest of concise exposition, the following commentary will discuss the pooled model unless one of the individual year model is sub-stantively dierent.
It should be noted that, in all models, the statistical signi®cance and mag-nitude of the parameter estimates of the control variables, when compared to the discretionary variables, suggest that a signi®cant proportion of the exam-ined accounting and ®nancing choices are non-discretionary. This factor, along with the high system-weighted R2 suggest that the non-discretionary
compo-nents of the models are reasonably well-speci®ed.
5.2.2. The loan loss provision (LLP) Model
The LLP models are reported in Table 5. The control variables, BLLA, BNPL, and CHNPL, are positive and signi®cant at 0.0009 or better in all models.
Proforma capital is not related to the discretionary loan loss provision for below-capital-threshold public and private banks (p0:3506 and 0.20, re-spectively). As hypothesized, earnings is negatively related to the loan loss provision for below-capital-threshold public and private banks (p0:001 or better), although the annual regressions are inconsistent for private banks. The eect of earnings is the dominant discretionary eect in the model ± a $1 de-crease in proforma earnings results in a 32! public bank (3! private bank) increase in discretionary loss provision, whereas the capital eect on discre-tionary provision is not signi®cantly dierent from zero. Overall, these results support the income-decreasing eect of close auditor scrutiny for below-capi-tal-threshold banks.
The use of discretion by above-capital-threshold public and private banks is mixed. Private banks demonstrate a positive relationship between the loan loss provision and proforma capital p0:0001, while the relationship for public banks is also positive but not signi®cant p0:6152. For the earnings incentive, annual regressions are inconsistent which clouds infer-ences which could be drawn from the pooled regression. Estimates for 1987 and 1988 for private banks are signi®cant, but are of opposite sign, resulting in no overall systematic relationship in the pooled model p0:5577. The pooled model for public banks shows a signi®cant positive relationship p0:0001 which is a function of strong 1988 results. The latter ®nding suggests public banks use the loan loss provision to smooth earnings, at least in some years.
379:2; p-value0:0001 but not for capital F-value0:764; p-value 0:382.23
Overall, the results for earnings suggest auditor conservatism is in¯uential for below-capital-threshold banks, but such conservatism is not evident at high capital levels.
5.2.3. The loan charge-o (LCO) model
The LCO models are presented in Table 6. Again, the control variables, BLLA, BNPL, and CHNPL, are consistently positive and signi®cant at
p0:0001 in all models. These results are as expected and consistent with prior research (e.g., Moyer, 1990; Collins et al., 1995).
As hypothesized, there is a negative relationship (p0:0003) between proforma capital level and loan charge-os for banks with capital below the 7.5% threshold (except for private banks in 1987 where the relationship is positive). A negative relationship indicates that discretion is reducing capital for below-capital-threshold banks, consistent with auditors' preference for conservative estimates. Using the pooled model coecients, a $1 drop in proforma capital results in a 12!and 3!increase in discretionary loan charge-os for public and private banks, respectively. For above-capital-threshold banks, the relationship between proforma capital and loan charge-os is pos-itive and the pooled model is signi®cant (p0:0089 or better) for both public and private banks (public banks in 1987 are not signi®cant). For PFCAP, the dierence in discretion between banks above and below the capital threshold is striking F-value84:470; p-value0:0001.
Above-capital-threshold banks show a positive relationship for MUNI (p0:0003 or better), as hypothesized, suggesting banks seek to eciently utilize tax writeos by taking more discretionary charge-os as the tax rate increases. As was evident in the case of PFCAP, the actions of banks above and below the capital threshold are very dierent with regard to the tax rate sur-rogate, MUNI F-value13:178; p-value0:0003.
Table 6 also shows that the relationship between MUNI and discretionary loan charge-os is negative for below-threshold banks (p0:0226 for public banks and a non-signi®cantp0:1880 for private banks in the pooled model, although annual regressions are weaker). The result for below-capital-thresh-old banks is contrary to our expectations. Both our hypothesis and our result for these banks are consistent with Collins et al. (1995, p. 281) who also expected a positive relationship and found the opposite.
5.2.4. The securities gain and loss (SGL) model
The model for SGL is given in Table 7. As expected, the control variable APPREC is positive and signi®cant atp0:0001.
Proforma capital for below-capital-threshold banks is positive and signi®-cant in the pooled model (p0:0533 or better). Individual year results are also positive, but weaker. A positive sign indicates fewer (more) gains are recorded as the level of capital declines (increases). This result is consistent with the conservative preferences of auditors, but not with the preferences of managers, which were expected to prevail. It is possible that auditors and examiners have a greater in¯uence on the realization of securities gains and losses than we expected. Earnings is negatively related to securities gains for below-capital-threshold banks, as hypothesized, but the signi®cance level is p0:06 for public banks, not signi®cant for private banks at p0:144, and annual re-gressions are generally weak.
Among above-capital-threshold banks, changes in the level of capital are not associated with securities gains and losses. For changes in earnings, a strong response in 1987 is combined with a weaker relationship in 1988 to provide pooled results which are signi®cantly negative for both public and private banks (p0:0017 or better). A negative sign suggests that more (fewer) gains are realized when earnings decline (increase), consistent with income smooth-ing.
The marginal tax rate is negative but not signi®cant for below-capital-threshold banks. Above-capital-below-capital-threshold banks demonstrate a signi®cant negative relationship (although 1988 has a p-value of 0.1049), as hypothe-sized, which is consistent with managing the after-tax bene®ts of securities sales.
Finally, banks above and below the capital threshold use their discretion dierently in the case of capital F-value5:902; p0:0151 and earnings F-value4:422; p0:038, but not for taxes F-value0:114; p-value 0:7355.
5.2.5. The dividends (DIV) model
The DIV models are presented in Table 8. Prior year dividends are positively related to current dividend levels (p0:0001), consistent with prior research and the notion that dividend payments are sticky from year-to-year.
dividends for banks above the capital threshold with public banks demon-strating a stronger eect than private banks (6!for each additional dollar of capital versus 3:5!).
Banks below and above the capital threshold use their discretion very dif-ferently F-value54:499; p-value0:0001. The coecient estimates for private banks are less than 10 percent of the level indicated for their above-threshold counterparts: 0:2! per $1 of additional proforma capital for low capital private banks versus 3:5! for high capital banks, with public banks showing an even greater disparity.
5.2.6. Public/private bank comparisons
Table 9 compares the choices of public and private banks, using parameter estimates previously reported on Tables 5±8. An F-test is used to discern whether the coecients are signi®cantly dierent. In the interest of concise exposition, results are presented only for the pooled model.
For below-capital-threshold banks, we hypothesized there would be no dierence between the choice of public and private banks. In six of the eight comparisons, we cannot reject a null hypothesis of no dierence in the dis-cretionary actions of public and private banks. Our large sample size ensures we have sucient statistical power to have con®dence in this ®nding. In the two cases where the use of discretion diers between public and private banks, below-capital-threshold public banks take larger loan loss provisions and larger loan charge-os. In each case, the sign of the coecient indicates a greater level of conservatism for choices by public banks. The greater con-servatism may result because public banks have more depositors and more external stakeholders than private banks, which would increase the potential legal liability of auditors. In addition, engagement risk (Hackenbrack and Nelson, 1996, p. 44) may be greater for public banks.
For above-capital-threshold banks, the size of the discretionary actions of public and private banks diers in ®ve of eight instances at the 0.075 signi®-cance level. In the LLP model, private banks use their discretion over the loan loss provision to increase capital by a larger amount than public banks. In contrast, the earnings incentive plays a larger role for public banks than private banks. Since a positive sign suggests income smoothing, public banks likely use the provision to smooth to a greater extent than private banks. These expected ®ndings provide some support for the notion that earnings are more important to public banks (consistent with Beatty and Harris, 1999, p. 301, and others), while capital is of more concern to private banks (as suggested by Sullivan and Spong, 1998, pp. 17±23).
pri-vate banks. Large, usually public, banks have been shown to have greater operational sophistication than smaller, generally private, banks in the areas of credit risk analysis (English and Nelson, 1998, pp. 2±6) and derivatives
Table 9
Public versus private bank comparisons (pooled model)a
Below-capital-threshold Banks Above-capital-threshold Banks
Public vs Private Public vs Private
Par. Est. F-value p-value Par. Est. F-value p-value
LLP model:
PFCAP, public 0.00797 0.00337
PFCAP, private ÿ0.01052 0.591 0.4420 0.01618 3.195 0.0739
EARN, public ÿ0.31937 0.04235
EARN, private ÿ0.02615 311.890 0.0001 0.00282 12.605 0.0004
LCO model:
PFCAP, public ÿ0.12031 0.01419
PFCAP, private ÿ0.03377 22.060 0.0001 0.01179 0.170 0.6803
MUNI, public ÿ0.01040 0.00760
MUNI, private ÿ0.00239 1.895 0.1687 0.00210 6.768 0.0093
SGL model:
PFCAP, public 0.01187 0.00048
PFCAP, private 0.00538 0.929 0.3351 ÿ0.00018 0.131 0.7176 EARN, public ÿ0.01003 ÿ0.01422
EARN, private ÿ0.00393 0.674 0.4118 ÿ0.01403 0.001 0.9700 MUNI, public ÿ0.00315 ÿ0.00299
MUNI, private ÿ0.00151 0.283 0.5950 ÿ0.00056 4.710 0.0300
DIV model:
PFCAP, public 0.00312 0.05956
PFCAP, private 0.00219 0.006 0.9356 0.03485 46.024 0.0001 aAs more fully explained in the text, the expectations for coecients are as follows:
Below-capital-threshold banks: No Dierences
Above-capital-threshold banks: LLP Model:
PFCAP: Coecient for private banks larger than public banks EARN: Coecient for private banks smaller than public banks LCO Model:
PFCAP: Coecient for private banks smaller than public banks MUNI: Coecient for private banks larger than public banks SGL Model:
PFCAP: Coecient for private banks larger than public banks EARN: Coecient for private banks larger than public banks MUNI: Coecient for private banks smaller than public banks DIV Model:
PFCAP: Coecient for private banks smaller than public banks
(Heinecke and Shen, 1995, pp. 1±2). If this sophistication carries over to tax-related decisions, then public banks are likely to implement more eective strategies to minimize taxes.
The ®nal dierence among above-capital-threshold banks arises from the eect of capital level on the amount of dividends paid out. Private banks pay out less in dividends as the level of capital increases than do public banks. This result was anticipated and likely re¯ects an attempt to reduce the taxes paid by the owners of private banks. Lower dividends also increase capital, which is a greater concern for private than public banks (as discussed previously).
6. Concluding remarks
Our study contributes to recent literature which examines accounting and ®nancing choices by banks. The literature to-date (e.g., Moyer, 1990; Collins et al., 1995; Beatty et al., 1995) has focused on the choices of public banks at the consolidated (holding company) level. We use call report data to examine public banks at the individual (subsidiary) level and to include a large sample of privately held banks ± the latter have not been included in prior studies. In addition, we speci®cally examine the interplay of auditor and manager pref-erences among banks below a capital adequacy threshold. Our ®ndings are summarized in Section 1.
With regard to future research, we chose, as noted earlier, to study a time period in which capital requirements did not vary. Future research could ex-amine the eects of changes in capital requirements on accounting and ®-nancing choices. The current movement toward bank consolidation could also in¯uence accounting and ®nancing choices. For example, an acquired bank may be under considerable pressure to report higher earnings to show the managers made a wise purchase. In general, the use of call report data has great potential for future research.
Acknowledgements
The authors would like to thank participants at the Annual Meeting of the American Accounting Association (Niswander and Swanson, 1998), the Uni-versity of Wisconsin Accounting Doctoral Alumni Conference, Bruce Behn, Don Fraser, Terry War®eld, and especially the insightful comments of the two anonymous reviewers
References
