1. finance
2. accounting and auditing

J. OF PUBLIC BUDGETING, ACCOUNTING & FINANCIAL MANAGEMENT, 10(3), 375-397
FALL 1998
FURTHER EVIDENCE ON THE DETERMINANTS
OF LOCAL GOVERNMENT AUDIT DELAY
Laurence E. Johnson*
ABSTRACT. This paper presents a study of the audit delay experienced by 289 U.S. local
governments. The study extends prior research by considering explanatory variables thought
to be correlates of audit quality and by comparing city and county delay. Models of audit
delay and audit fees are estimated using two-stage least squares regression. The study finds
that audit delay is positively associated with correlates of audit quality and that cities
experience less delay than do counties. The results indicate that, while audit fees have no
explanatory power concerning audit delay, delay exerts a positive influence on fees.
INTRODUCTION
The importance of timely financial reporting by local governments is
unequivocally recognized in the professional literature. The Governmental
Accounting Standards Board (GASB) states (1987) that for financial reports
to be useful, "they must be issued soon enough after the reported events to
affect decisions," affirming the importance of timeliness as previously
asserted by the National Council on Governmental Accounting (1982).
Governments face no pressure for the prompt release of the financial
statements from equity shareholders as is the case for business entities
(Bamber, Bamber and Schoderbeck, 1993). Nonetheless, government
managers have incentive to issue the financial reports expeditiously.
The prompt release of government financial reports is viewed as
signaling a strong system of internal control (Canary, 1988) and managerial
competence (Dwyer and Wilson, 1989). The Government Finance Officers
Association (GFOA) provides concrete motivation for
____________________
* Laurence E. Johnson, Ph.D., is Associate Professor, Department of Accounting,
Colorado State University. His teaching and research interests are in state and local
government accounting and financial auditing.
Copyright © 1998 by PrAcademics Press
376
JOHNSON
promptness by requiring governments that apply for the Certificate of
Achievement for Excellence in Finance Reporting to release their financial
reports within six months (GFOA, 1994).
However, the timeliness of financial reporting is materially impacted by
the audit function because the financial statements cannot be issued until the
audit is concluded. The period of time from fiscal year end to the date of the
audit report is known as audit delay. As noted, managers normally prefer
minimal audit delay. Moreover, completion of the audit by a target date
established by the client is perceived as contributing to audit quality (Carcello,
Hermanson and McGrath, 1992). Thus, auditors are presumed to complete
their engagements as quickly as possible within the constraint imposed by
their obligation to perform with due professional care.
Since the audit function has a considerable influence on the timeliness of
financial reporting, it is important to understand the influences that increase or
mitigate local government audit delay. This paper reports a study of local
government (city and county) audit delay that addresses certain factors not
considered in previous research. The study investigates the relationship
between audit delay and fees and thus employs two-stage least squares
(TSLS) regression in addition to ordinary least squares (OLS) regression in
the data analysis. The study contributes to an improved overall
understanding of the causes of governmental audit delay and provides indirect
evidence of a link between delay and audit quality.
PRIOR RESEARCH
Three municipal audit delay studies have been performed within the last
ten years. Dwyer and Wilson (1989) investigated the fiscal 1982 delay of
142 cities. They found a negative association between delay and (1) receipt
of a GFOA Certificate; (2) independent (rather than state-agency) auditors;
(3) responsibility for printing the annual report resting with the auditor; and
(4) state regulation of municipal financial reporting practices. A positive
relationship was observed between delay and state regulation of local
government accounting practices.
Rubin (1992) investigated audit delay as part of a study of auditor
selection (between independent public accountants and the State Auditor) by
Ohio cities. Using fiscal 1986 data, Rubin reported that receipt of a GFOA
Certificate and auditor type were each significant (in separate regressions) in
explaining delay. More recently, Johnson (1996) found fiscal 1993 municipal
audit delay to be negatively related to receipt of a GFOA Certificate and a
DETERMINANTS OF LOCAL GOVERNMENT AUDIT DELAY
377
September 30 fiscal year end. Johnson observed a positive association
between delay and divided auditor responsibility as indicated in the audit
report. His study indicates that delay is a determinant of audit fees, but not
vice versa. Contrary to expectations, Johnson found no association between
delay and auditor size (Big Six versus nonBig Six), the number of component
units comprising the governmental reporting entity, or auditor tenure.
The remainder of this paper is organized as follows. The next section
provides a brief description of the research method. Following are three
sections describing the study's model of governmental audit delay, the study's
audit fee model, and data collection and analysis. The paper concludes with a
discussion of the study's implications and limitations.
RESEARCH METHOD OVERVIEW
Data were obtained primarily from a review of fiscal 1993 governmental
financial reports and via questionnaire. Separate models of delay and fees
were initially estimated using ordinary least squares regression (OLS). Next,
a test for endogeneity between delay and fees was conducted. Based on this
test, the delay and fee models were respecified to include fees and delay,
respectively, and reestimated using two-stage least squares regression
(TSLS). The delay model considers (1) variables identified in prior research,
(2) potential correlates of audit quality, (3) type of government, and (4) fees.
The fee model is based primarily on variables identified in previous research.
The derivation of the delay model follows.
A Model of Governmental Audit Delay
Variables from Prior Research
Dwyer and Wilson argued that receipt of a GFOA Certificate of
Achievement for Excellence in Financial Reporting is an observable signal of
managerial competence. They further contended that, if minimal delay is
itself a signal of competence, there should be a negative relationship between
audit delay and receipt of a GFOA Certificate. Their study found this to be
the case. Treating receipt of a GFOA Certificate as a control variable in his
model of Ohio city audit delay, Rubin (1992) reported a similar finding.
Johnson observed the same relationship based on univariate tests.
Accordingly, this study treats receipt of a GFOA Certificate as a control
variable (GFOA).
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JOHNSON
Composition of the governmental reporting entity has implications for
audit delay. Statement No. 3 of the National Council on Governmental
Accounting (NCGA, 1981) required that governments be broadly defined for
reporting purposes. Accordingly, government financial reports encompass the
primary government and any legally-separate entities deemed to be
"component units" of the overall reporting entity.(1) The broad definition of
the reporting entity can lead to situations wherein the financial statements of
the various components of the reporting entity are audited by more than one
auditor. In these cases, the auditor's report sometimes indicates a division of
responsibility between the principal (reporting) auditor and the other
auditor(s), a condition that may contribute to delay. Based on Johnson's
finding of a positive association between division of audit responsibility and
audit delay, this study includes division of responsibility (DIVR) as a control
variable.
Dwyer and Wilson (1989) did not find municipal audit delay to differ
between "busy season" year ends (defined as October 31 through March 31)
and other fiscal year ends. The municipalities included in Rubin's (1992)
model of audit delay had a uniform fiscal year end (December 31). In
contrast, Johnson found audit delay to be minimal for governments with
September 30 fiscal year ends. Accordingly, this study controls for the effect
of September 30 year ends (SYE) on audit delay.
Audit Quality
There is some evidence that audit quality and audit delay are related in
the governmental sector. Arguing for a positive correlation between delay
and quality, Brown and Margavio (1994) found delay to be significant in
explaining small-city audit fees. Deis and Hill (1995) observed a positive
relationship between audit quality (directly measured) and delay in a study of
Texas school district audits.
Direct measures of individual city and county audit quality are not
readily available.(2) However, the association between audit delay and quality
for cities and counties can be investigated in terms of hypothesized correlates
of audit quality. Two such correlates considered in this study are a "time and
materials" or "variable" fee arrangement and state-agency influence on
independent auditors of cities and counties.
In the mid 1980s, the U.S. General Accounting Office (GAO) studied
the quality of audits of federal programs conducted by independent audit
DETERMINANTS OF LOCAL GOVERNMENT AUDIT DELAY
379
firms. Based on the GAO data, Copley and Doucet (1993) found a positive
relationship between fixed fee arrangements and the incidence of substandard
audits of federal programs. Their finding implies that, under a fixed fee
arrangement, audit quality may suffer because the auditor has incentive to
limit the amount of audit testwork to a level that will not impair profitability of
the audit engagement. Auditor-imposed limits on testwork, in turn, may
cause fixed-fee audits to be completed comparatively quickly. Conversely, a
"time and materials" or "variable" basis for billing the client provides
economic incentive for auditors to perform all audit procedures deemed
necessary, likely contributing to delay. Thus, it is expected that audits for
which the fees are based on time expended by the auditors (VAR) will entail
more delay than audits for which fees are not based on time expended.
In several states, the state audit agency oversees the audits of local
governments performed by independent certified public accountants. Such
oversight includes "desk reviews" of audit reports, reviews of workpapers,
and/or a requirement that independent auditors follow a state-developed audit
guide.
Because state oversight of independent auditors reduces
"opportunistic" auditor behavior (i.e., intentional minimization of audit
testwork), audits conducted under state oversight can be expected to be of
higher quality than those that are not. In turn, compliance with stateprescribed audit procedures may contribute to audit delay. Based on this
reasoning, state auditor influence (SAI) on the performance of local
government audits by independent auditors is expected to be associated with
increased delay.
Type of Local Government
The extant governmental audit delay research is based on city data;
whether delay differs between cities and counties has not been previously
investigated. Though cities and counties are subject to the same financial
accounting and reporting requirements, differences in their organizational
characteristics imply differential delay. Cities generally are organized such
that their various service functions are closely coordinated. In contrast,
various county functions are often administered by separately elected and
relatively independent officials (e.g., sheriff, treasurer, clerk of the court, tax
assessor). Indeed, Quiko (1981) characterizes county governments as
"fragmented" and "headless." Similarly, Steadman (1976) observes the
following: "Generally, county administration may best be viewed as a
collection of relatively independent agencies which are rarely coordinated in
380
JOHNSON
their operations." The comparatively uncoordinated nature of county
operations may generally lead to delays and difficulties in the performance of
county audits.
Jakubowski (1995) found counties to have higher occurrences of
material weaknesses in internal control, compared with cities. Jakubowski's
finding suggests that, relative to city audits, county audits require increased
substantive testwork to reduce the risk of material misstatement in the
financial statements to an acceptably low level. This finding further implies
that a higher proportion of audit procedures are performed near or after the
balance sheet date for counties than is the case for cities. Ashton, Willingham
and Elliot (1987) and Craig (1992) have found audit delay to proxy for the
proportion of audit testwork performed after fiscal year end. The preceding
discussion implies that mean audit delay for cities (CITY) is less than that for
counties.
Audit Fees
The final issue investigated in this study is whether audit fees influence
delay. Canary (1988) argued that governments may accept increased audit
delay in exchange for reduced fees, (the complement of the condition
suggested by Dyer and McHugh (1975) wherein auditees "buy" reduced
delay). Rubin (1992) made a case for either a positive and negative
relationship between fees and delay. He suggested that promptly-completed
audits might be more expensive because they involve concentrated audit
resources (e.g., additional staff, overtime) or higher auditor opportunity cost
or that audits involving more delay might be more costly because they reflect
increased audit testwork.
Rubin (1992) found fees per capita insignificant in explaining municipal
audit delay and vice-versa. However, there is other evidence of positive
covariance between public-sector audit delay and fees, and evidence that
delay and fees are endogenous. As previously noted, Brown and Margavio
found audit delay significant (positive coefficient) in explaining fees, using
OLS. Using simultaneous regression, Deis and Hill (1995) found a positive
relationship between audit fees and audit delay in a study of Texas school
district audits. Delay was significant in explaining fees, and vice-versa.
Also using simultaneous regression, Johnson (1996) found audit delay
significant (positive coefficient) in explaining audit fees per capita; fees per
capita were not significant in explaining delay, albeit the sign of the fee-per-
DETERMINANTS OF LOCAL GOVERNMENT AUDIT DELAY
381
capita coefficient was positive. A fee-per-capita specification may not be
optimal, though, because it assumes a linear relationship between population
and fees. (3) Thus, the present study investigates whether total audit fees
(AFEE, logarithmically transformed, LAFEE) help explain audit delay. Fees
and population are highly correlated, but no prior governmental delay study
has found population to be significant. Accordingly, interpretation of the
estimated coefficient of LAFEE in the delay model should not be confounded
by population. Based on prior research, the sign of LAFEE is expected to be
positive.
A Model of Governmental Audit Fees
Because of possible joint endogeneity between delay and fees,
determining whether fees influence delay also requires investigating whether
delay influences fees. This necessitates estimating a governmental audit fee
model. The model employed in this study incorporates four independent
variables identified in prior studies and two new variables, all of which are
expected to exhibit a positive relationship with fees. Based on Rubin (1988)
and Copley (1989), respectively, the model controls for population (POP,
logarithmically transformed, LPOP) and auditor size (B6). Following
Johnson (1996), the fee model controls for a September 30 fiscal year end
(SYE) and the number of component units comprising the governmental
reporting entity (CU). The model also includes a delay-related variable, stateagency influences on the audit (SAI), and a variable related to audit
complexity, the number of pension trust funds maintained by the government
(PTF).
DATA COLLECTION AND ANALYSIS
The data include municipal observations and certain explanatory
variables previously employed by Johnson (1996), additional observations
representing counties, and additional independent variables for all
observations. Comprehensive Annual Financial Reports (CAFRs) of 436
U.S. local governments (with populations of 20,000 or more) for fiscal 1993
on file at a U.S. university were reviewed to determine audit delay (in days),
several independent variables, and the names and addresses of each city's
chief financial officer. Questionnaires were sent to each government's
finance officer requesting total fees for fiscal 1993. Follow-up questionnaires
requested information concerning the basis on which the 1993 audit fee was
computed. Two hundred eighty nine (289) usable responses (66 percent)
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JOHNSON
were received. A list of states in which the state auditor influences the scope
and nature of local government audits performed by independent accountants
was obtained from the National Association of State Auditors, Comptrollers
and Treasurers (NASACT, 1996).
Table 1 summarizes the variables measured in this study and the sources
from which they were obtained. Table 2 presents descriptive statistics for the
study's continuous and discrete variables. Table 3 presents descriptive
statistics for audit delay sorted by dummy variable. The data represent all
Big Six audit firms, numerous regional and local firms, and four state audit
agencies. June 30, September 30, and December 31 fiscal year ends
comprise about 55 percent, 17 percent, and 25 percent of the data,
respectively.
Table 4 presents Pearson correlation coefficients for the variables. Most
correlations are much less than .30. The correlations greater than .30 are
related largely to fees; two other fairly high correlations reflect (1) the
relatively lower mean population of the cities vis-a-vis the counties in the
sample and (2) the proclivity of state audit agencies to charge fees on a
variable basis.
DETERMINANTS OF LOCAL GOVERNMENT AUDIT DELAY
383
TABLE 1
Summary of Variables
Variable
Name Purpose of
Source
Variable
-----------------------------------------------------------------------------------------Audit delaya
LDELAY
Audit feea
LAFEE Endogenous
Government successfully
participates in GFOA Certificate
of Achievement program
GFOA
Divided auditor responsibility
DIVR
September 30 fiscal year end
SYE
Fee based on per hour charges
State auditor influences
the independent audit
Type of government
(city or county)
State-agency auditor
a
Questionnaire
Exogenous--delay
CAFR
Exogenous--delay
CAFR
Exogenous--delay
and fees
VAR
SAI
CITY
STA
CAFRb
Endogenous
CAFR
Exogenous--delay
Questionnaire
Exogenous--delay
and fees
NASACTc
Exogenous--delay
Exogenous--delay
CAFR
CAFR
Population
LPOP
Exogenous--fees
CAFR
Auditor size (Big Six/
nonBig Six)
B6
Exogenous--fees
CAFR
Number of component units
CU
Exogenous--fees
CAFR
Number of pension trust funds
PTF
Exogenous--fees CAFR
(a)
Logarithmically transformed for analysis.
(b)
Obtained from review of Comprehensive Annual Financial Report (CAFR).
(c)
Obtained from National Association of State Auditors, Comptrollers and Treasurers
(NASACT) (1996).
384
JOHNSON
TABLE 2
Descriptive Statistics: Continuous and Discrete Variables
Total
Cities
Counties
(n=289)
(n=184)
(n=105)
-----------------------------------------------------------------------------------------Delay (in days)*
Mean
121.30
114.43
133.33
Standard deviation
34.80
33.83
33.33
Range
53-253
53-253
55-224
Audit fee (in $1,000)*
Mean
81.64
70.16
101.80
Standard deviation
74.86
71.38
Range
5.70-565
76.89
5.70-
8.65-565
428
Population (in 1,000)*
Mean
Standard deviation
Range
Component units
Mean
256.25
349.84
20-2907
150.71
167.70
33-1036
3.09
2.84
Standard deviation
2.92
2.52
Range
0-21
0-16
441.21
484.96
20-2907
3.54
3.48
0-21
Pension trust funds
Mean
.79
.98
1.19
1.35
.45
Standard deviation
.72
Range
0-8
0-8
0-5
* log transformed for analysis
DETERMINANTS OF LOCAL GOVERNMENT AUDIT DELAY
385
TABLE 3
Delay in Days by Dummy Variable
(N=289)
Dummy=0
Condition indicated
Dummy=1
by Dummy=1
Mean Std Dev. n % Mean Std Dev. n %
-----------------------------------------------------------------------------------------------Government awarded
GFOA Certificate*
118.77 32.59 256 88 140.88 44.62 33 12
Divided auditor
responsibility*
137.48 33.34 65 19 116.60 33.87 224 81
September 30 fiscal
year end*
101.96
Audit fee computed on
"time and materials" basis* 151.31
State auditor influences
the independent audit
*
Government is a city
33.09
37.23
49 17 125.25
16 5
33.87
240 83
119.54
33.91
273 95
33.92
223 77
127.58
37.23
66 23 119.44
114.43
33.83
184
63 133.33
33.32
105 37
*
State audit agency
160.27 24.66 11 4
119.76 34.27 278 96
* means of dummy variable conditions are significantly different at á # .01
OLS Analysis--Delay and Fees
The initial step in the analysis was to estimate the model of audit delay
(not including fees) using OLS. However, one adjustment to the model was
necessitated by the sample data. The sample includes 11 counties audited by
state audit organizations. Prior research (Dwyer and Wilson, 1989; Rubin,
1992) shows that state auditors are associated with maximal delay, a finding
replicated in this study (see Table 3). Further, as noted in the preceding
paragraph, state auditors account for a disproportionately large number of the
variable-fee engagements in the sample (six of the total of 16). To prevent
the influence of state agency-performed county audits from confounding the
coefficient estimates of VAR and CITY, the delay model included a dummy
variable for state
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JOHNSON
DETERMINANTS OF LOCAL GOVERNMENT AUDIT DELAY
387
agency-performed audits (STA). Thus, the structural delay model was
estimated as follows:
LDELAY = â0 + â1 GFOA + â2 DIVR + â3 SYE + â4 VAR
+ â5SAI + â6CITY + â7STA + å
(1)
where:
GFOA:
DIVR:
SYE:
VAR:
1 for receipt of a GFOA certificate, otherwise 0;
1 for divided auditor reporting responsibility, otherwise 0;
1 indicating a September 30 fiscal year end, otherwise 0;
1 if the audit fee was computed on a time and materials basis,
otherwise 0;
SAI: 1 if a state agency prescribed the scope and nature of the audit,
otherwise 0;
CITY: 1 if the government is a city, 0 if the government is a county;
STA: 1 if the auditor is a state audit agency, otherwise 0.
The estimated regression model is presented at Table 5. White's test
(Gujarati, 1995) indicates that heteroschedasticity is not affecting the standard
errors and t-statistics for the coefficient estimates. Inspection of residuals and
the Wilk-Shapiro test (test statistic = .996) suggest that the residuals are
normally distributed. No variance inflation factor exceeds 1.3, indicating that
collinearity is not a problem. Thus, the estimated model can be interpreted
straightforwardly. Six coefficient estimates are significant at conventional
levels and all coefficient signs are consistent with expectations. (4) The
adjusted R2 of this model is .214.
The structural audit fee model (excluding delay) was estimated using
OLS as follows:
LAFEE = â0 + â1LPOP + â2B6 + â3SYE + â4CU + â5SAI
+ â6PTF + å
(2)
The results of the fee regression estimate appear in Table 6. As with the
delay model, White's test indicated no heteroschedasticity in the estimate.
Other diagnostic procedures indicated no problems of collinearity or
nonnormal residuals with the fee model. The adjusted R2 of the fee estimate,
.495, is comparable with those reported by Rubin (1988) and Copley (1989).
The above models of delay and fees provide the foundation for investigating
whether fees affect delay and vice-versa.
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JOHNSON
TABLE 5
Ordinary Least Squares Estimate of Audit Delay Model*
Expected Coefficient Standard
Variables
Sign
Estimate
Error t-statistic p-value
----------------------------------------------------------------------------------------------Constant
?
4.902
.054
90.020
.000
Government awarded
GFOA Certificate (GFOA)
! !0.136
.049
!2.764
.006
Divided auditor reporting
responsibility (DIVR)
+
.123
.038
3.228
.001
September 30 fiscal
year end (SYE)
! !0.207
.043
!4.809
.000
Audit fee computed on Atime
and materials" basis (VAR)
+
.075
1.776
.076
.105
.038
State auditor influences the
independent audit (SAI)
.133
+
2.719
Government is a city (CITY)
! !.085
.034
!2.504
.013
State auditor (STA)
+ 0.132
.090
1.456
.146
Model F ratio
Prob (F ratio)
Adjusted R2
.007
12.226
.000
.214
* Dependent variable= the natural logarithm of audit delay in days)
Two-Stage Least Squares Estimation
As indicated, an assumption of this study is joint endogeneity between
delay and fees. If justified, this assumption requires that a simultaneous
regression technique be employed to estimate a delay model that includes fees
and a fee model that includes delay. The joint endogeneity assumption was
tested using a version of the Hausman specification test appropriate for a
two-equation system (Gujarati, 1995). The test involved regressing all
exogenous variables (i.e., the reduced-form model) separately against each
endogenous variable (using OLS) to
DETERMINANTS OF LOCAL GOVERNMENT AUDIT DELAY
389
TABLE 6
Ordinary Least Squares Estimate of Audit Fee Model*
Expected Coefficient Standard
Variables
Sign Estimate Error t-statistic p-value
-----------------------------------------------------------------------------------------------Constant
?
8.569
.168
50.799
.000
ln of population
(LPOP)
+
.403
.034
11.792
.000
Big Six auditor (B6)
+
.329
.063
5.192
+
.181
.084
2.139
.033
Number of component units (CU) +
.041
.011
3.725
.000
State auditor influences
the independent audit (SAI)
+
.150 0.076
1.963
.050
No. of pension funds (PTF)
+
.072 0.026
2.794
.005
Sept. 30, fiscal year end (SYE)
Model F ratio
Prob (F ratio)
Adjusted R2
.000
48.207
.000
.495
* Dependent variable is the natural logarithm of audit fees
generate the residuals. The structural delay model (Equation 1) was then
respecified to include the residuals from the reduced-form fee model.
Likewise, the structural fee model (Equation 2) was respecified to include the
reduced-form delay residuals. Under this test, if the coefficients of the
residuals are significant in the respective regressions, the hypothesis of joint
endogeneity should not be rejected.
The Hausman procedure yields significant fee-model residuals in the
delay regression (t = 3.35, p < .001). and delay-model residuals in the fee
regression (t = 3.11, p = .002). These results indicate that delay and fees are
jointly endogenous, so that simultaneous estimation of delay and fee models
is necessary to avoid biased coefficient estimates. Accordingly, the initial
delay model (Equation 1) was respecified to include the natural logarithm of
fees (LAFEE) as an explanatory variable and reestimated using two-stage
least squares (TSLS) regression. In like fashion, the log of delay (LDELAY)
was added to the initial fee model (Equation 2), which was reestimated using
TSLS.
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JOHNSON
The results of the TSLS estimations appear at Table 7 (for delay) and
Table 8 (for fees). Diagnostic measures indicate that heteroschedasticity,
collinearity, and nonnormally-distributed residuals are not distorting the
estimated coefficients or t-statistics.
The most salient feature of Table 7 is that the t-statistic for the fee
variable (LAFEE), .870, is not significant, indicating that audit fees do
TABLE 7
Two-Stage Least Squares Estimate of Audit Delay Model*
Expected Coefficient Standard
Variables
Sign Estimate Error t-statistic p-value
-----------------------------------------------------------------------------------------------Constant
?
4.575
.379
12.046
.000
Government awarded
GFOA Certificate (GFOA)
!
!0.140
.049
!2.855
.004
Divided auditor reporting
responsibility (DIVR)
+
.111
.040
2.738
.006
Sept. 30 fiscal year end (SYE)
Audit fee computed on Atime
and materials" basis (VAR)
!
+
State auditor influences the
independent audit (SAI)
Government is a city (CITY)
!0.210
.130
+
!
!0.075
.042
!4.910
.074
.100
1.747
.038
.036
.081
2.596
!2.103
.000
.010
.036
State auditor (STA)
+
.139
.090
1.540
.124
Natural logarithm of audit
fee (LAFEE)
+
.029
.034
.870
.385
Model F ratio
10.995
Prob (F ratio)
.000
Adjusted R2
.229
* Dependent variable is the natural logarithm of audit delay in days.
not have explanatory power with respect to audit delay. Otherwise, the OLS
and TSLS estimates of the delay model are comparable. A review of Table 8
indicates that the audit fee model estimated using TSLS is comparable with
DETERMINANTS OF LOCAL GOVERNMENT AUDIT DELAY
391
the OLS estimation (Table 6), except that SAI is not significant under TSLS.
The TSLS estimate further shows that delay is significant in explaining the
observed variation in fees.
DISCUSSION
The preceding analysis indicates that most of the expected influences on
governmental audit delay are significant. Consistent with prior research, this
study finds that successful participation in the Government Finance Officers
Association "Certificate of Achievement for Excellence in Finance Reporting"
program is associated with minimal delay. Also replicated are previous
findings that September 30 fiscal year ends are negatively associated with
delay whereas divided auditor responsibility and delay exhibit a positive
association. From a policy standpoint, adopting a September fiscal year end
to minimize delay is probably not a realistic option for many governments.
On the other hand, the increased delay arising from divided audit
responsibility argues, as a policy matter, in favor of governments retaining
one auditor, whenever possible, to audit the financial statements of all
component units with the reporting entity.
Consistent with Johnson’s results (using fees per capita) but not so with the findings of
the Deis and Hill study, this study’s results show that total audit fees do not explain audit
delay. Consistent with both prior studies, the present research indicates that audit
delay helps explain fees. This finding may indicate a relationship between
audit quality (Brown and Margavio, 1994; Deis and Hill, 1995) and/or audit
risk (Johnson, 1996). Identifying the underlying influence on local
government audit delay and fees is a worthwhile avenue for future research.
The effects of audit quality correlates on delay are consistent with
expectations. As predicted, audits for which the fee was based on audit time
expended (as opposed to being fixed in advance) are positively associated
with delay. In light of Copley and Doucet's finding (1993) of a negative
association between fixed fee audits and audit quality, this result implies a
positive relationship between delay and audit quality. The small number of
strictly variable-fee audits in the sample is in keeping with the trend toward
fixed-fee engagements reported by Margheim and Kelley (1992).
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TABLE 8
Two-Stage Least Squares Estimate of Audit Fee Model
Expected Coefficient Standard
Variables
Sign Estimate Error t-statistic
p-value
-----------------------------------------------------------------------------------------------Constant
?
4.864
1.539
3.159
.002
ln of population (LPOP)
+
.358
.038
9.217
.000
Big Six auditor (B6)
+
.381
.066
5.713
.000
Sept. 30 fiscal year end (SYE)
+
.377
.117
3.225
.001
Number of component units (CU) +
.038
.011
3.401
.000
State auditor influences the
independent audit (SAI)
+
.042
.088
.485
.628
No. of pension funds (PTF)
+
.071
0.026
2.759
.006
Natural logarithm of audit
delay (LDELAY)
+
.821
0.339
2.420
.016
Model F ratio
42.430
Prob (F ratio)
.000
Adjusted R2
.499
* Dependent variable is the natural logarithm of audit fees.
The other quality-correlated variable, state auditor influence (SAI) on the
conduct of government audits, also exhibits a positive association with delay.
This suggests that state-mandated audit procedures, presumably in place to
enhance audit quality, require effort beyond that which independent auditors
might otherwise expend, and so contribute to delay. Further, while SAI is
significant in the OLS fee estimate, under TSLS, delay replaces SAI as a
significant variable, indicating that delay captures the effect of state auditor
influences on fees. These findings add support to the argument that audit
delay serves as a proxy, to some extent, for audit quality.
This study finds, as predicted, that counties generally take longer to audit
than do cities. Although the counties in this study's sample are, on average,
more populous than the cities, prior research indicates that this finding is not
driven by population. Neither is the finding driven by auditor type
(independent versus state-agency auditor), since this variable is accounted for
in the regression models. Rather, it appears that the less-coordinated nature
DETERMINANTS OF LOCAL GOVERNMENT AUDIT DELAY
393
of county operations and/or the counties' propensity to have weaker internal
controls, contributes to delay.
The results presented here should be evaluated in light of the study's
limitations. The sample was not randomly drawn, so caution should be used
in attempting to generalize the results reported here to the entire population of
U.S. city and county governments. Moreover, although this study identifies
new influences on governmental audit delay, the estimated model leaves
much of the observed variability in delay unexplained. Accordingly,
additional research is needed.
One possible influence on delay not considered in this study is the Single
Audit Act of 1984. For instance, does the number and/or magnitude of
questioned costs detected in federal grant programs impede completion of the
financial statement audit? Similarly, the number of material weaknesses in
internal control reported by auditors as required by the Single Audit Act may
affect delay. In particular, the tendency of counties to have a higher
incidence of material weaknesses in internal control vis-a-vis cities
(Jakubowski, 1995) may account for some of the difference in delay between
counties and cities observed in this study. As noted, another interesting topic
for future research is the apparent relationship between local government
audit delay and audit quality. However, a direct test of this relationship must
await the availability of a specific governmental audit quality metric.
ACKNOWLEDGMENTS
The author gratefully acknowledges the College of Business, Colorado
State University for financial support for this research; Stephen Davies,
William Mister, and Michael Moore, Colorado State University, for their
helpful comments; Linda Vann, for research assistance; and Robert J.
Freeman, for granting access to the Texas Tech University Governmental
Accounting Research Library.
NOTES
1.
In brief, under NCGA Statement No. 3, a component unit relationship is
assumed if a primary government and subordinate entity are financially
interdependent (although other criteria could also establish such a
relationship). GASB Statement No. 14, The Financial Reporting
Entity, effective for fiscal years beginning after December 15, 1992 with
early application permitted, has revised the reporting entity definition
394
JOHNSON
criteria. (The new criteria are expected to result in governmental
reporting entities being even more broadly defined than was the case
under NCGA Statement 3.) A dummy variable controlling for
governments that early-implemented GASB Statement No. 14 in 1993
was not significant to delay in preliminary data analysis and thus was
dropped from further consideration.
2.
For example, the governmental audit quality data collected by the
Presidents Council on Integrity and Efficiency, analyzed by Brown and
Raghunandan (1995), is not presented for individual governments.
3.
The researcher is grateful to Paul Copley for pointing this out.
4.
Preliminary analysis showed that, consistent with prior research, LPOP
does not significantly explain delay.
5.
Margheim and Kelley (1992) note that audit fee arrangements are not
strictly dichotomous (variable or fixed). A third type of fee arrangement
involves a fixed fee for specified services with the understanding that
additional fees may be charged for extra audit time incurred in special
circumstances (e.g., unforeseen difficulties, nonrecurring complexities
arising from implementation of a new authoritative pronouncement).
Accordingly, for this study, finance officers were asked to indicate
whether their governments' audit fee arrangements were (1) fixed in
total, (2) fixed, but with the understanding that additional billings would
be made in special circumstances, or (3) variable. Approximately 25
percent of the respondents indicated that their governments' audit fees
were fixed in total, 70 percent indicated an arrangement involving basic
fixed fees with a provision for additional fees in special circumstances,
and 5 percent indicated a strict variable arrangement.
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