Description
This paper aims to investigate factors which may influence or bias judges’ decisions to
exclude or admit the testimony of accounting expert witnesses, under the US judicial guidelines
commonly known as the Daubert/Kuhmo standards. Accounting experts are increasingly providing
expert testimony as a part of financial litigation support services.
Accounting Research Journal
Factors which may bias judges’ decisions to exclude accounting expert witnesses
testimony
Madeline Ann Domino Matthew Stradiot Mariah Webinger
Article information:
To cite this document:
Madeline Ann Domino Matthew Stradiot Mariah Webinger , (2015),"Factors which may bias judges’
decisions to exclude accounting expert witnesses testimony", Accounting Research J ournal, Vol. 28
Iss 1 pp. 59 - 77
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Factors which may bias judges’
decisions to exclude accounting
expert witnesses testimony
Madeline Ann Domino
Department of Accounting, Mercer University, Macon, Georgia, USA
Matthew Stradiot
Assurance Department, PricewaterhouseCoopers LLC, Cleveland,
Ohio, USA, and
Mariah Webinger
Accountancy Department, John Carroll University,
University Heights, Ohio, USA
Abstract
Purpose – This paper aims to investigate factors which may infuence or bias judges’ decisions to
exclude or admit the testimony of accounting expert witnesses, under the US judicial guidelines
commonly known as the Daubert/Kuhmo standards. Accounting experts are increasingly providing
expert testimony as a part of fnancial litigation support services.
Design/methodology/approach – Judges’ decisions, in which opposing council evoked a Daubert/
Kuhmo challenge to the testimony provided by 130 professional accountants serving as expert
witnesses, were analyzed. The period of study was 2010 through 2014. Based on prior research, three
variables believed to potentially infuence or bias judges to systematically exclude expert testimony
were examined: gender, complexity and familiarity.
Findings – The results of binary logistic regression show that none of the variables has a signifcant
relationship to the accounting expert witnesses’ probability of surviving a challenge to Daubert/Kuhmo
standards. Findings suggest that judges are objective in evaluating the testimony provided by
accounting experts under Daubert/Kuhmo guidelines and that they may be immune to biases based
solely on gender, complexity and familiarity.
Originality/value – These results will be of interest to judges, lawyers and forensic accountants
acting as expert witnesses.
Keywords Forensic accounting, Daubert challenge, Expert witness, Judge bias, Jury bias,
Kumho challenge
Paper type Research paper
Introduction
Accounting professionals are increasingly involved in providing expert testimony in
fnancial litigation support. The increasing demand for qualifed professional
accounting experts prompted the American Institute of Certifed Public
Accountants’ (AICPA) Business Valuation/Forensic Litigation Services Executive
Committee to focus on forensic accountants, stating that their responsibilities
include collecting, analysis and evaluation of evidence, as well as interpreting and
communicating their fndings (AICPA, 2006). Additionally, accounting expert
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1030-9616.htm
Accounting
expert
witnesses
testimony
59
Received1 November 2014
Revised15 April 2015
Accepted17 April 2015
Accounting Research Journal
Vol. 28 No. 1, 2015
pp. 59-77
©Emerald Group Publishing Limited
1030-9616
DOI 10.1108/ARJ-11-2014-0097
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witnesses must be objective in presenting their fndings (Weil et al., 2001; Michaelson,
2005; DiGabriele, 2011).
Using an accountant’s expertise often adds substantial value and enhances the
chance of winning a client’s lawsuit (Ponemon, 1995). Serving as a fnancial expert
requires accountants to review working papers, prepare valuations, testify in
depositions, generate opinions as to whether generally accepted accounting and
generally accepted auditing standards were followed, assist in providing an
understanding of accounting issues to solve disputes and to serve as expert witnesses in
court (Ricchiute, 2004; DiGabriele, 2008; Muehlmann et al., 2012). In the accounting
literature, these activities are often identifed with forensic accountants.
This research investigates factors which may infuence or bias judges’ decisions to
exclude testimony provided by accounting expert witnesses, when it is challenged by
opposing council. A sample of US court cases from 2010 to 2014 where an expert was
challenged based on specifc guidelines for determining the admissibility of evidence
under the US Federal Rules of Evidence 702, Testimony of an Expert (USFRE 702) was
identifed and studied. Specifc guidelines have been provided in what is commonly
known as the Daubert Standard and Kuhmo Standard (Daubert/Kuhmo). Using
Daubert/Kuhmo criteria, judges act as gatekeepers in determining the exclusion or
admissibility of expert witnesses’ testimony, when opposing councils raise objections
(e.g. a Daubert/Kuhmo challenge).
Three variables believed to infuence or bias judges’ decisions to systematically
exclude expert evidence under the guidelines specifed under Daubert/Kuhmo were
examined: gender, complexity and familiarity. These variables are empirically studied
to determine their impact, if any, on the judges’ determination of excluding or admitting
the accounting expert’s testimony. Findings suggest that judges are objective in
evaluating the testimony provided by accounting experts under the guidelines of
Daubert/Kuhmo and that they may be immune to biases based solely on gender,
complexity and familiarity biases.
This research makes several contributions to the literature on accounting experts
providing testimony in fnancial litigation support. First, the study provides empirical
evidence on variables believed to infuence or bias judges’ decisions to systematically
exclude the accounting experts’ testimony. Second, with the growth in accounting
expert witnessing, the study directly contributes to this area of research in the
accounting literature. Finally, the research flls a void of the lack of research exploring
the exclusion of evidence under the Daubert/Kuhmo. To date, minimal research has
explored these topics.
Literature review
Judges’ potential biases
Instances of judges rejecting accounting experts’ testimony are replete in the both the
legal and accounting literature. According to DiGabriele (2008, p. 4), “accountants
regularly offer expert testimony services to the litigation community and there
testimony is frequently scrutinized by the court and at time excluded”. In Wagner v. CRI
(2001) the judge determined that the experts were biased and lacked impartiality. In an
empirical study, DiGabriele (2008) fnds that in fnancial litigation support services,
accounting expert witnesses’ often present valuations that differ signifcantly from one
another, as well as differ from the valuations made by the court. Bosland (1963) and
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Englebrecht and Jamison (1979) fnd that tax courts tended to reject experts’ valuations
and to rule somewhere in the middle.
There is also evidence to suggest varying interpretations of the Daubert/Kuhmo
standards, depending upon who is the judge. For example, in the 2014 ruling on
Manpower, Inc. v. Insurance Company of the State of Pennsylvania, an appeals court
judge reversed a lower court judge’s decision to exclude the testimony presented by an
accounting expert witness. In addition to interpretive differences, opposing decisions
may refect infuences or biases by judges’ who decide which challenged testimony
survives and which is excluded.
Thus, an important and understudied topic is the identifcation of factors which may
infuence or bias judges’ decisions to exclude the testimony of an accounting expert
witness when it is challenged by the opposing council under Daubert/Kuhmo. In these
instances, judges as the gatekeeper ensure that Daubert/Kuhmo guidelines are followed.
Prior research has shown that judges may be infuenced by biases that relate to
gender, complexity and familiarity. Based on these fndings, it is proposed that because
judges may be infuenced by the gender of the expert witness, they decide unfavorably
against accounting expert witnesses. If the case has many technical accounting
elements and computations that judges do not understand, the complexity of the case
may infuence judges in determining when to deny a motion to exclude an accounting
experts’ testimony and when to grant it. If judges are not familiar with the specialized
feld of law or and lack expertise in the area of law, judges may also be infuenced to
accept or reject the accounting experts’ testimony. By determining the factors which
may potentially infuence or bias judges’ decisions to accept or reject the testimony of an
accounting expert witness, it may be possible to determine if the Daubert/Kuhmo
guidelines are being followed appropriately and are free of gender, complexity and
familiarity biases.
Expert witness testimony
Since the landmark Daubert v. Merrell Dow Pharmaceuticals Inc. (Daubert) US Supreme
Court case in 1993, and the later Kumho Tire Company LTD, et al. Petitioners v. Patrick
Carmichael et al. (1999) (Kuhmo), which addressed nonscientifc experts, federal judges,
as well as the majority of state judges, have held a large amount of power. Judges are
nowrequired to act as an amateur expert and to determine whether an expert is, in fact,
an expert (Kuhmo, 1999). Potential problems may be created when expert testimony and
questions of fact are very technical, i.e. complex. Judges may also be asked to evaluate
testimony that is outside their areas of law or expertise. In these instances, judges may
be required to evaluate testimony for which they have not been suffciently trained or
which is outside their normal knowledge base.
USFRE 702 provides criteria for determining the admissibility of an expert
witnesses’ testimony. Further clarifcation has been provided by the US Supreme Court,
under what is commonly known as the Daubert standard. Under Daubert, judges may
decide to exclude expert testimony for a number of reasons, such as:
• an expert is not necessary;
• the expert’s techniques are not generally accepted by the expert community; and
• the expert is not qualifed to present testimony on the question of fact.
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Daubert standard. The 1993 landmark US Supreme Court case Daubert v. Merrell Dow
Pharmaceuticals Inc., (Daubert) established a new framework for determining the
admissibility of fndings for expert scientifc witnesses in federal trials, replacing the
guidelines of the Frye standard (Mahle, 2012). According to PricewaterhouseCoopers,
LLP (PwC) (2011), all but a handful of state courts have adopted Daubert.
Opposing lawyers commonly fle pretrial motions in limine to prevent evidence from
being introduced in trial (Crumbley and Cheng, 2014). Daubert offers guidelines for
judges to use in determining if an expert witness’ testimony should be partially, or
wholly, excluded (USFRE702). Daubert greatly expanded the responsibility of judges in
their gatekeeper role (Kozinski, 2001) and introduced a unique change to the analyses of
expert witnesses’ testimony. According to Daubert, expert testimony will be accepted if
the following criteria are met.
• The expert’s scientifc, technical or other specialized knowledge will help the Trier
of Fact to understand the evidence or to determine a fact in issue.
• The testimony is based on suffcient facts or data.
• The testimony is the product of reliable principles and methods.
• The expert has reliably applied the principles and methods to the facts of the
case.
Prior to Daubert, judges would accept expert testimony if it was generally accepted in
the relevant professional community. Thus, judges’ gatekeeping function was restricted
to determining if experts’ testimony includes theories or techniques that would be
generally accepted in the relevant community. Daubert requires judges to determine if
the testimony is both relevant and reliable (USFRE 702).
Daubert also requires judges to focus on the principles and methodologies used by
the expert to generate testimony, and not on the conclusions themselves. In 1997,
Daubert guidelines were amended by the US Supreme Court by recognizing that
conclusions reached and methodology used are not entirely distinct from one another
(General Electric Co. v. Joiner, 522 USA 136, 146, 1997). If an expert claims to have
applied methodologies accepted within the relevant community, but reached a
conclusion other experts in the feld would not reach, the court can suspect the methods
were not properly applied (USFRE 702).
Kuhmo standard. Daubert applied only to testimony of a scientifc nature. In 1999,
the US Supreme Court attempted to provide clarifcation to the application of Daubert in
its ruling on Kumho Tire Company LTD., et al. Petitioners v. Patrick Carmichael et al.,
which focused on specialized knowledge and non-scientifc evidence. Commonly known
as the Kumho Standard (Kumho), clarifcation provided guidelines for expert
witnessing for all felds of “specialized knowledge”. Consequently, an expert may be
viewed as any person who possesses relevant knowledge, skill, experience, training or
education (Kumho, 1999).
Thus, professional accountants are now considered experts, who are subject to the
same gatekeeping standards as scientifc experts. Depending on the circumstances of
the case, a non-exclusive reliability checklist may be applicable in determining the
reliability of a non-scientifc expert. Crumbley and Cheng (2014) fnd that the most
common factors applied from the checklist are:
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• whether the technique or theory has been subject to peer review and publication;
and
• whether the technique or theory has been generally accepted in the scientifc
community.
Accounting expert witnesses must meet the standards of both Daubert/Kumho.
Applicationof Daubert/Kumho. Each year, PwC, LLPconducts a study which focuses
on Daubert/Kuhmo challenges to non-scientifc expert witnesses. PwC’s most current
study spans the years 2000-2013. Results indicate that the number one reason for
exclusion of non-scientifc evidence provided by an expert, whether in whole or part,
was lack of reliability. For the time period covered, PwC found 718 Daubert/Kumho
challenges, resulting in either whole or partial exclusions of expert witness testimony.
Of that number, 309 (or 43 per cent) challenges were based solely on the result of lack of
reliability, compared to 163 (or 23 per cent) challenges based on instances of the lack of
relevance and 59 (or 8 per cent) challenges based on the lack of qualifcations. Of the
remaining challenges, 171 (or 24 per cent) were excluded for multiple reasons, and 16 (or
2 per cent) were excluded due to missed deadlines (PricewaterhouseCoopers, LLP, 2013).
PwC also found that the type of witness appears to affect the frequency of Daubert/
Kuhmo challenges, as well as the success, with success defned as a partial or whole
exclusion. Over the 14-year study period, the analyses of fnancial expert witnesses
found that economists and accountants most frequently challenged fnancial experts.
Economists were least likely to result in a successful exclusion (41 per cent), followed by
accountants (43 per cent), despite accountants being challenged most frequently.
According to PwC, the type of case (area of law) also affects the frequency and
outcome of Daubert/Kumho challenges. Cases involving breach of contract or
fduciary duty were most likely to be challenged. Cases involving fraud and
intellectual property were most likely to have a successful exclusion under Daubert/
Kuhmo (PricewaterhouseCoopers, LLP, 2013).
Potential biases in applying Daubert/Kumho
An important and understudied topic is the identifcation of factors which may infuence
or bias judges’ decisions to exclude the testimony of an accounting expert witness when
it is challenged by the opposing council under Daubert. The 2014 ruling on Manpower,
Inc. v. Insurance Company of the State of Pennsylvania (Manpower) illustrates that
judges may reach different conclusions in applying Daubert/Kumho.
In Manpower, Inc. v. Insurance Company of the State of Pennsylvania (2016), an
appeals court judge reversed a lower court judge’s decision to exclude the testimony of
an accounting expert witness. The case centered upon Manpower Inc.’s insurance
coverage claim stemming from a building collapse, located in France. Manpower hired
Eric Sullivan, an accounting expert witness, to establish the amounts of the loss claims
against the Insurance Company of the State of Pennsylvania (ISOP). The claims were
made under a “master” policy’s business interruption and personal property loss
provisions and were based upon a projected growth rate of 7.6 per cent for a fve-month
period preceding the collapse of the building. ISOP refuted the claim amount, stating
that historical performance indicators showed a much lower growth rate (3.8 per cent)
during this time period.
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The initial ruling was favorable to Manpower. However, ISOPfled a motion in limine
to exclude the accounting expert’s opinion, arguing that “the business interruption loss
was not a product of reliable methodology” (Manpower, Inc. v. Insurance Company of
the State of Pennsylvania, 2016, p. 7.) The district court judge subsequently excluded Mr
Sullivan’s calculations citing the reliability of his methods. The judge questioned
“whether Sullivan used reliable methods when selecting the numbers used in his
calculations – specifcally projected total revenues and projected total expenses”
(Manpower, Inc. v. Insurance Company of the State of Pennsylvania, 2016, p. 7.)
Manpower appealed the exclusion Mr Sullivan’s testimony, the adverse ruling and
the district court’s interpretation of policy interpretations relative to the losses. The
appeals court judge reversed the exclusion of the accounting expert witnesses’
testimony and the judgment against Manpower.
This case illustrates that judges may vary in their interpretations of the expert
witness guidelines provided by Daubert/Kuhmo. This line of reasoning is studied
relating it to the gender of the expert witness, the complexity of the case and the
familiarity with the area of law, as these factors may infuence judges’ decisions to
accept or reject an accounting expert witness’ testimony, when it is challenged under
Daubert/Kuhmo. These variables are now discussed.
Gender. Gender bias has been described as a “predisposition to treat people according
to sex stereotypes” (Abrahamson, 1993, p. 1209) and has been recognized and discussed
extensively in the legal system since the 1990s. Gender bias is common in
decision-making and also in the courtroom (Abrahamson, 1993; Czapanskiy, 1993).
According to Schafran (1990), gender bias in the court room denies woman equal
treatment and opportunity.
In a study of randomly selected practicing attorneys, 75 per cent of female compared
with 50 per cent of males reported experiencing some formof gender-related misconduct
in the previous fve years (Cortina, 2002). Johnson and Scheuble (2006) fnd evidence of
gender bias in the dispositions of punishment rendered by the court in juvenile cases,
with greater punishment given to girls than boys, even if the boys were repeat offenders
committing more serious offenses. Gender bias has been well documented in a number
of courtroom studies. A compilation of ten courtroom studies confrms that, during
litigation, judges exhibit gender bias in the ways they treat women lawyers and women
litigants (Czapanskiy, 1993).
Thus, the gender of the expert witness is anticipated to have a positive relationship
with the witness’ chance of survival for males and a negative relationship as females. It
is proposed that judges may unconsciously doubt or discredit the testimony of female
accounting expert witnesses, resulting in a lower acceptance rate of accounting expert
testimony presented by female accountants.
Complexity. Complexity has been defned by high amounts of technical language and
computational information and has been shown to affect receivers’ cognitive
satisfaction, comprehension and perception of the speaker’s credibility. Prior research
that shows cognitive satisfaction, comprehension and recall scores are substantially
lower in technical conditions than in the non-technical conditions (Jackson, 1992).
When a decision-maker faces a complex problem, frequently the problem is reduced
to a simpler problem. Heuristics are simplifed decision rules developed to deal with
complex situations. These heuristics are effcient and often work well but, in some
circumstances, may lead to systematic biases (Libby, 2002). Prior accounting research
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shows the importance of considering information attributes, such as complexity, as it
relates to accounting information (Plumlee, 2003).
Arnold (2002) fnds that, in complex accounting problems, simple biases exist, even
if the decision-makers are experienced professional accountants. When ranking
complex tax information, tax analysts were able to assimilate less complex information
to a greater extent, as compared to more complex information (Plumlee, 2003). Smith and
Talfer (1992) fnd that complex fnancial information inhibits the ability of
sophisticated readers to understand the annual reports. Thus, it is proposed that judges,
who are required to evaluate complex accounting expert witness testimony, may be
susceptible to complexity bias.
Familiarity. According to Awasthi (1990), an individual’s ability to abstract complex
information from an unfamiliar setting to more familiar components is related to
decision performance. Prior research suggests that judges may abstract, from facts
presented in expert testimony, something that is relevant to their own expertise,
creating a bias toward or against certain areas of expertise or certain areas of law (e.g.
familiarity bias).
Birnbaum (1979) conducted an experiment, in which judges were asked to estimate
the hypothetical value of cars based on blue-book values and on the values provided by
others who examined the cars. The experiment shows judges were biased toward the
value presented by the expert who has the highest association, or familiarity, to the
judge(s). Choi and Gulati (2008) also fnd judges are more likely to be biased in
high-stake situations in which they are actively familiar.
In Daubert/Kuhmo challenges, judges may make determinations on the testimony
presented by an accounting expert witness, yet the judge may have no or little
familiarity with this type of evidence. Thus, it is proposed that judges may be
systematically biased toward or against areas of law and expertise for which they are
familiar.
Methodology
Data sources
The Daubert Tracker database (www.dauberttracker.com/) was used to select the
sample data used in the study, but not recorded by variable. A case search was
performed on the Daubert Tracker Web site using the following criteria: Disciplines:
accounting; Gate-keeping Authority: Kumho; and Years: 2010-2014.
The Daubert Tracker will produce data on every court case within the designated
period with at least one expert witness with an accounting discipline challenged. It
should be noted that all witnesses within the case are listed by the Daubert Tracker, not
only the witnesses with an accounting discipline.
Sample. The initial sample selected from the Daubert Tracker included 237
challenges to expert witnesses with an accounting discipline between 2010 and 2014. Of
the 237 samples, 101 witnesses were excluded because the motion to exclude was
partially granted and partially denied, or the disposition could simply not be
determined. Another six witnesses were excluded, as their gender could not be
determined from their name, leaving a fnal sample of 130 challenges to be included in
the study.
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For a case to be included in the sample, only one of the experts had to be an
accounting expert. Cases in which the expert was a non-accountant (i.e. disciplines
outside of accounting) were excluded from the sample.
Variable selection
Based on prior research, three independent variables believed to infuence or bias
judges’ decisions in Daubert/Kuhmo challenges are studied: gender, complexity and
familiarity. The dependent variable selected was the disposition of the case, i.e. the
accounting experts’ testimony was accepted or rejected by the judge.
Independent variables. By reviewing data, the gender of the accounting expert
witness was determined to be either male or female. These data were used to measure
gender bias.
To measure complexity, two variables, “Number of Judges” and “Number of Experts
Challenged”, were consolidated into broader categories for ease of analysis and serve as
proxy variables to measure the complexity of the case.
The number of judges to preside over a case can reasonably be assumed to
measure complexity. The greater the number of judges involved in the case, the
more complex the case. The complexity may lead to more witnesses being
challenged. However, more complex cases maybe more likely to feature
higher-quality witnesses. As such, the direction of the relationship of the number of
judges in a case to the accounting experts’ testimony surviving a Daubert/Kuhmo
challenge is not predicted.
The number of accounting expert witnesses challenged in a case also serves as a
proxy for complexity, as more complex cases are likely to have more advanced legal
teams that are utilizing more witnesses, and may be more likely to challenge an
accounting expert of the opposing side. More complex cases may also be more likely to
feature higher-quality witnesses. Judges may have more diffculty evaluating a complex
case as compared to a less complex case. Arelationship is expected between the number
of accounting experts challenged and the chance of an accounting expert witnesses’
surviving a Daubert/Kuhmo challenge. Thus, it is proposed that in complex cases,
judges’ decisions may be biased in evaluating a Daubert/Kuhmo challenge to either
accept the testimony or reject the testimony.
To measure familiarity bias, two independent variables, “Area of Expertise” and
“Area of Law”, were consolidated into broader categories for ease of analysis. Area of
expertise was reclassifed into six categories: Valuation/Damages, Auditing, Tax,
Financial Accounting, Cost Accounting and Other. As not all witnesses have an area of
expertise, a “none” variable is also technically present within the analysis. Area of law
was reclassifed into eight categories; Liability, Intellectual Property, Contracts,
Banking, Regulatory, Construction, Fraud/Criminal and Other.
Five areas of expertise were tested for effects on accounting expert witnesses
Daubert/Kuhmo challenge survival rates. Auditing, Tax and Financial Accounting –
the areas of expertise that are strongly guided by regulations – are expected to have a
positive relationship with an expert’s chance of survival. Areas without as much
guidance to procedures – Valuation/Damages, Cost Accounting and Other – are
expected to have a negative relationship with the probability of survival.
Eight areas of law are tested for effects on accounting expert witness survival rates.
Areas of lawmore likely involving the interpretation of already-established accounting
ARJ
28,1
66
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rules, such as Contracts, Banking, Regulatory, Construction and Fraud/Criminal, are
proposed to have a positive relationship with an expert’s survival rate. Areas of law
more likely to involve valuation services and expert opinions, as opposed to
interpretations of existing regulations, include Liability and Intellectual Property.
These areas of laware expected to have a negative relationship with the survival rate of
a Daubert/Kuhmo challenge to an accounting expert’s testimony, as the accounting
function provided in the cases is expected to be more subjective.
Dependent variable. The dependent variable, the disposition of the of
Daubert/Kuhmo challenges “Disposition”, was also consolidated. The Daubert Tracker
database does not have a standardized method for reporting the results of a challenge.
The disposition of Daubert/Kuhmo challenges was consolidated into two categories:
motion to exclude granted and motion to exclude denied.
Table I shows the detail of all variable consolidations.
Data analysis
Descriptive statistics
Descriptive statistics on each variable are shown in Table II. The sample of accounting
expert witnesses is overwhelmingly male (85.35 per cent). Whether this is a result of
more male expert witnesses being challenged or a larger population of male expert
witnesses is something that needs to be determined in future research. In most instances,
only one judge was assigned to a case; however, the mean for number of expert
witnesses challenged is almost three. The most common area of law is
Valuation/Damages (24.62 per cent). The majority of experts (66.92 per cent) listed no
area of expertise.
Binary logistic regression analysis
Binary logistic regression analysis was performed to analyze the effects of the variables
on the probability of an expert witness surviving a challenge. Binary logistic
regressions create models in which the dependent variable is bound between zero and
one, producing a probability of survival of a Dalbert/Kuhmo challenge.
The regression was run in IBM SPSS, as well as calculated using the Solver tool in
Microsoft Excel. Three variables, Auditing, Financial Accounting and Cost Accounting,
produced substantial standard errors in the SPSS regression. Likewise, the signifcance
level of each of the variables is either 0.999 or 1.000. As shown in Table II, Auditing,
Financial Accounting and Cost Accounting produced standard deviations of 0.2106,
0.1733 and 0.0877, respectively, within normal ranges.
When the binary logistic regression was run in Microsoft Excel, the coeffcients for
these three variables were the only differences than the SPSS fgures. SPSS determines
the Log Likelihood – used to calculate the coeffcients in a binary logistic regression –
with a maximum of 20 iterations, whereas Excel will run only 5 iterations. The
difference in the values was unable to be determined, but was hypothesized to have
occurred due to either the lack of signifcance of the variables and number of iterations
performed or multicollinearity between the variables.
Table III shows the correlation matrix. No large correlation between variables was
identifed, suggesting that multicollinearity is not the explanation.
Each program utilized its maximum number of iterations attempting to fnd a
solution with signifcant variables, resulting in the different coeffcient values as well as
67
Accounting
expert
witnesses
testimony
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ARJ
28,1
68
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69
Accounting
expert
witnesses
testimony
D
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(
P
T
)
the unusual signifcance level. A sensitivity analysis, without the area of law or area of
expertise variables, was also performed. No differences in results were noted, as the
results were similar to those of the full model binary logistic regression.
The results of the binary logistic regression are shown in Table IV.
Results
The gender of an accounting expert witness was found to have no signifcant effect on
whether an expert’s testimony survives a Daubert/Kuhmo challenge. Males were far
more likely to be expert witnesses, comprising 85.39 per cent of the sample. Unlike prior
research fndings, results of the statistical analysis do not refect a gender bias in judges’
decisions to accept or reject the accounting experts’ testimony under Daubert/Kuhmo.
Female accounting expert witnesses are not more likely or less likely to be retained.
Complexity is frequently associated with biases. The complexity of the case did not
appear to infuence or bias judges’ decisions on Daubert/Kuhmo challenges. Complexity
was measure in two ways: by the number of judges presiding over a case and by the
number of accounting experts assigned to the case. Neither of the complexity variables
has a signifcant statistical effect on the probability of being the challenged being
granted or denied.
Table II.
Descriptive statistics
Variable Mean SD n
Number of judges
Number of judges 1.19231 0.544118003 130
Number of experts challenged
Number of experts challenged 2.87692 3.254133649 130
Gender
Male 0.85385 0.354626968 130
Female 0.14615 0.354626968 130
Area of expertise
Valuation/damages 0.24615 0.432435656 130
Auditing 0.04615 0.210629859 130
Tax 0.01538 0.123553044 130
Financial accounting 0.03077 0.173359936 130
Cost accounting 0.00769 0.087705802 130
Other 0.04615 0.210629859 130
None 0.66923 0.472310198 130
Area of law
Liability 0.10000 0.301160546 130
Intellectual property 0.18462 0.389486153 130
Contracts 0.20769 0.40722456 130
Banking 0.08462 0.279385133 130
Regulatory 0.20000 0.401547395 130
Construction 0.10000 0.301160546 130
Fraud/criminal 0.05385 0.226587029 130
Other 0.06923 0.254828154 130
ARJ
28,1
70
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(
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Table III.
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(
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71
Accounting
expert
witnesses
testimony
D
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(
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ARJ
28,1
72
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With the number of judges presiding over a case, complexity was not found to have a
signifcant statistical effect on whether an accounting expert’s testimony survives a
Daubert/Kuhmo challenge. In this sample, typically one judge presided over the court
proceedings. The number of experts challenged in a case was found to have no
signifcant effect on whether an expert witness survives a challenge. It was proposed
that complexity would systematically infuence a judge’s decision to grant or deny a
Daubert/Kumho challenge. The data analysis did not support this prediction.
Like complexity, familiarity is frequently associated with biases. Familiarity was
measured in two ways: by the area of the lawand by the area of expertise. Neither of the
familiarity bias variables has a signifcant statistical effect on the probability of being
the challenged being granted or denied.
The areas of law of Liability, Intellectual Property, Contracts, Banking, Regulatory,
Construction and Fraud/Criminal were all found to have no signifcant effect on whether
an accounting expert witnesses’ testimony survives a Daubert/Kuhmo challenge. The
areas of expertise in Valuation/Damages, Auditing, Tax, Financial Accounting or Cost
Accounting were all found to have no signifcant effect on whether an accounting expert
witness’ testimony survives a Daubert/Kuhmo challenge. Unlike prior research
fndings, results of the statistical analysis do not refect familiarity biases by judges’ in
their decisions to accept or reject the accounting experts’ testimony when evaluated
under Daubert/Kuhmo.
Conclusions
An important and understudied topic is the identifcation of factors which may infuence
or bias judges’ decisions to exclude the testimony of an accounting expert witness when
it is challenged by the opposing council under Daubert/Kuhmo. Judges serve as the
gatekeepers who ensure that Daubert/Kuhmo guidelines are followed. A potential
Table IV.
Binary logistic
regression results
Variables in the equation
Variables B SE Wald df Signifcance
Number of judges 0.184 0.542 0.115 1 0.735
Number of experts challenged 0.106 0.132 0.652 1 0.419
Male ?0.792 1.146 0.478 1 0.49
Valuation/damages ?0.722 0.603 1.433 1 0.231
Auditing 19.689 15011.113 0.000 1 0.999
Tax ?1.37 1.682 0.663 1 0.415
Financial accounting 19.723 17700.144 0.000 1 0.999
Cost accounting 18.861 40192.97 0.000 1 1.000
Other ?0.154 1.36 0.013 1 0.91
Liability ?0.533 1.325 0.162 1 0.688
Intellectual property 0.618 1.331 0.216 1 0.642
Contracts ?0.99 1.199 0.681 1 0.409
Banking ?0.245 1.381 0.031 1 0.859
Regulatory 1.199 1.498 0.641 1 0.423
Construction 0.442 1.541 0.082 1 0.775
Fraud/criminal ?1.336 1.471 0.825 1 0.364
Constant 2.266 1.706 1.765 1 0.184
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problem is that judges, who are not experts, must rule on whether to deny or grant a
Daubert/Kuhmo challenge to exclude accounting experts’ testimony.
While prior research has shown that judges’ decisions may be infuenced or biased
gender (Schafran, 1990; Abrahamson, 1993; Czapanskiy, 1993; Cortina, 2002; Johnson
and Scheuble, 2006), complexity (Smith and Taffer, 1992; Jackson, 1992; Libby, 1992;
Arnold, 2002; Plumlee, 2003) and familiarity (Birnbaum, 1979; Awasthi, 1990; Chio and
Gulati, 2008), the results of this study do not support prior academic fndings. Statistical
analysis shows no signifcant effects in judges’ decisions to accept or reject a Daubler/
Kumho challenge based on gender, complexity or familiarity biases. While, the
statistical analysis produces no signifcant results, the fndings of the study are
particularly interesting.
Several contributions are made to the academic literature on accounting experts
providing testimony in fnancial litigation support. First, the study provides empirical
evidence that gender, complexity and familiarity do not infuence or bias judges’
decisions to systematically exclude the accounting experts’ testimony under Daubert/
Kuhmo. Second, with the growth in accounting expert witnessing, the study directly
contributes to the literature on accounting expert witnessing. Finally, the research flls
a void in the research which explores the exclusion of evidence under Daubert/Kuhmo.
Minimal research to date has explored these topics empirically.
The fndings are also relevant to a number of practitioner groups. Accountants
serving as expert witnesses and lawyers representing clients will be interested to know
that judges’ decisions are not biased by gender, complexity or familiarity. Judges will
also fnd the study results of interest.
Opportunities for future research
This study highlights areas for future research. Additional research on other biases and
infuences on judges’ decisions relative to Daubert/Kuhmo is needed. More evaluation of
Daubert challenges may identify what is being challenged and where testimony is being
excluded or included.
Research models or theories that focusing on the testimony most likely to be
challenged or more likely to lead to dismissal, is another fruitful avenue. Such models or
theories may provide lawyers and judges with additional criteria upon which to
evaluate accounting experts’ testimony. It may also provide accounting experts with
valuable information needed to make their testimony more effective.
Lastly, the research looks at judges’ biases on accounting expert witnesses, but not
on the biases of the experts (Champagne, 1990). It is generally accepted that a signifcant
gap exists in resources between prosecution and most defendants (Bernstein, 2008).
This suggests that many defendants are able to hire a more sophisticated expert and the
distinction of prosecution/defendant may be a signifcant predictor of whether
testimony is accepted or denied.
Limitations
The results of this study are limited to US court cases using accounting expert
witnesses and may not be generalizable to other countries’ legal situations and to
other types of expert witnesses. The majority of experts in the study were male. It is
not known if different results would be found if a greater proportion of accounting
expert witnesses were female. Complexity was measured by looking at the number
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of judges assigned to a case and the number of expert witnesses challenged in a case.
The extent to which different measures of complexity may capture complexity bias
is not known. Finally, other areas or different classifcations schemas may also
identify familiarity bias.
References
Abrahamson, S.S. (1993), Toward a courtroom of one’s own: an appellate court judge looks at
gender bias; 61 U. Cin. L. Rev. 1209.
American Institute of Certifed Public Accountants (2006), available at: www.aicpa.org/
InterestAreas/ForensicAndValuation/Community/Pages/Forensic%20and%20Valuation
%20Services%20Executive%20Committee.aspx
Arnold, V.C. (2002), “The effect of experience and complexity on order and recency bias in decision
making by professional accountants”, Accounting and Finance, Vol. 40, pp. 109-134.
Awasthi, V.A. (1990), “The effects of monetary incentives on effort and decision performance: the
role of cognitive characteristics”, The Accounting Review, Vol. 65, pp. 797-811.
Bernstein, D. (2008), “Expert witnesses, adversarial bias, and the (partial) failure of the Daubert
revolution”, Iowa Law Review, Vol. 93, pp. 451-1949.
Birnbaum, M.A. (1979), “Source credibility in social judgement: bias, expertise, and the judge’s
point of view”, Journal of Personality and Social Psychology, Vol. 37 No. 1, pp. 48-74.
Bosland, C. (1963), “Tax valuation by compromise”, The Tax Law Review, Vol. 19, pp. 77-89.
Champagne, A.S. (1990), “An empirical examination of the use of expert witnesses in American
courts”, Jurimetrics Journal, Vol. 31, pp. 375-392.
Choi, S.J. and Gulati, G.M. (2008), “Bias in judicial citations: a window into the behavior of
judges?”, The Journal of Legal Studies, Vol. 37 No. 1, pp. 87-130.
Cortina, L.L. (2002), “What’s gender got to do with it? Incivility in the federal courts”, Law&Social
Inquiry, Vol. 27 No. 2, pp. 235-270.
Crumbley, L.D. and Cheng, C.C. (2014), “Avoid losing a Daubert challenge: some best practices for
expert witnesses”, The ATA Journal of Legal Tax Research, Vol. 12 No. 1, pp. 41-53.
Czapanskiy, K. (1993), “Domestic violence, the family, and the lawyering process: lessons from
studies on gender bias in the courts”, Family Law Quarterly, Vol. 27, pp. 247-277.
DiGabriele, J.A. (2008), “The adversarial bias of accounting experts in fnancial litigation: an
empirical analysis of compromised objectivity in accounting expert testimony”, Journal of
Accounting, Ethics and Public Policy, Vol. 8 No. 1, pp. 1-22.
DiGabriele, J.A. (2011), “An Observation of differences in the transparent objectivity of forensic
accounting expert witnesses”, Journal of Forensic & Investigative Accounting, Vol. 3 No. 2,
pp. 390-416.
Englebrecht, T. and Jamison, R. (1979), “An empirical inquiry into the role of the tax court in the
valuation of property for charitable contribution purposes”, The Accounting Review,
Vol. 54, pp. 554-562.
Jackson, L. (1992), “Information complexity and medical communication: the effects of technical
language and amount of information in a medical message”, Health Communication, Vol. 4
No. 3, pp. 197-210.
Johnson, D.R. and Scheuble, L.K. (2006), “Gender bias in the disposition of juvenile court Referrals:
the effects of time and location”, Criminology, Vol. 29 No. 4, pp. 677-699.
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Kozinski, A. (2001), “Meeting reliability standards in case A doesn’t give a CPA witness a leg up
in case B: Expert Testimony After Daubert”. Journal of Accountancy, available at: www.
questia.com/library/journal/1G1-76728081/expert-testimony-after-daubert
Kumho Tire Company, LTD, et al., Petitioners v. Patrick Carmichael, etc. et al., 97-1709 (Supreme
Court of the United States March 23, 1999).
Libby, R.B. (2002), “Experimental research in fnancial accounting”, Accounting, Organizations
and Society, Vol. 27 No. 8, pp. 775-810.
Mahle, S.E. (2012), “The ‘pure opinion’ exception to the Florida Frye standard”, The Florida Bar
Journal, Vol. 86 No. 2, pp. 41-45.
Manpower, Inc. v. Insurance Company of the State of Pennsylvania (2016), in the United States
Court of Appeals for the Seventh Circuit, No. 12-2688.
Michaelson, W.M. (2005), in Pagano, W.J. and Buckhoff, T.A(Eds), Expert Witnessing in Forensic
Accounting, pp. 63-70.
Muehlmann, B.W., Burnaby, P. and How, M. (2012), “The use of forensic accounting experts in tax
cases as identifed in court opinions”, Journal of Forensic &Investigative Accounting, Vol. 4
No. 5, pp. 1-34.
Plumlee, M.A. (2003), “The effect of information complexity on analysts’ use of that information”,
The Accounting Review, Vol. 78 No. 1, pp. 275-296.
Ponemon, L.A. (1995), “The objectivity of accountants’ litigation support judgments”, The
Accounting Review, Vol. 70 No. 1, pp. 467-488.
PricewaterhouseCoopers, LLP. (2011), Daubert Challenges to Financial Experts: An 11-year Study
of Trends and Outcomes, PricewaterhouseCoopers, LLP, New York, NY.
PricewaterhouseCoopers, LLP. (2013), Daubert Challenges to Financial Experts: AYearly Study of
Trends and Outcomes, PricewaterhouseCoopers, LLP, New York City, NY.
Ricchiute, D.N. (2004), “Effects of an attorney’s line of argument on accountants’ expert witness
testimony”, The Accounting Review, Vol. 79 No. 1, pp. 221-245.
Schafran, L.H. (1990), “Overwhelming evidence: reports on gender bias in the courts”, Trial,
Vol. 26 No. 2, pp. 28-30, 30-35.
Smith, M. and Taffer, R. (1992), “Readability and understandability: different measures of the
textual complexity of accounting narrative”, Accounting, Auditing & Accountability
Journal, Vol. 5 No. 4, pp. 84-98.
Weil, R., Wagner, M. and Frank, P. (2001), Litigation Services Handbook: The Role of the Financial
Expert, 3rd ed., John Wiley & Sons, New York, NY.
Further reading
Bassett, W.R., Clare, S.M. and Rodell, S.A. (2013), “Evidence”, Mercer Law Review, Vol. 64,
pp. 929-952.
Begley, S. (2003). “‘Junk science’ ban also keeps jurors from sound evidence”. The Wall Street
Journal, available at:http://online.wsj.com/articles/SB105666035267101800 (accessed 16
September 2014).
Dolman, M.A. and McGrath, J.N. (2014). “Five ways to survive a Daubert challenge against your
expert”, The National Trial Lawyers, available at: www.thenationaltriallawyers.org/2014/
06/fve-ways-to-survive-a-daubert-challenge-against-your-expert/ (accessed 16 September
2014).
Huber, D. (2012), “Is forensic accounting in the United States becoming a profession?”, Journal of
Forensic & Investigative Accounting, Vol. 4 No. 1, pp. 255-284.
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Pepper, P. (2012), “Particular evidence problems with appraisals, part III: expert witnesses”,
Bankruptcy & Insolvency Litigation, Vol. 18 No. 1, pp. 18-19.
Manpower, Inc. v. Insurance Company of the State of Pennsylvania (2016), in the United States
Court of Appeals for the Seventh Circuit, No. 12-2688.
US Federal Rule of Evidence Rule 702. Testimony by Expert Witness. (2015). Retrieved from
Cornell University LawSchool Legal Information Institute: www.law.cornell.edu/rules/fre/
rule_702
Corresponding author
Mariah Webinger can be contacted at: [email protected]
For instructions on how to order reprints of this article, please visit our website:
www.emeraldgrouppublishing.com/licensing/reprints.htm
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doc_193897815.pdf
This paper aims to investigate factors which may influence or bias judges’ decisions to
exclude or admit the testimony of accounting expert witnesses, under the US judicial guidelines
commonly known as the Daubert/Kuhmo standards. Accounting experts are increasingly providing
expert testimony as a part of financial litigation support services.
Accounting Research Journal
Factors which may bias judges’ decisions to exclude accounting expert witnesses
testimony
Madeline Ann Domino Matthew Stradiot Mariah Webinger
Article information:
To cite this document:
Madeline Ann Domino Matthew Stradiot Mariah Webinger , (2015),"Factors which may bias judges’
decisions to exclude accounting expert witnesses testimony", Accounting Research J ournal, Vol. 28
Iss 1 pp. 59 - 77
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ARJ -04-2015-0047
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ARJ -08-2014-0071
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Factors which may bias judges’
decisions to exclude accounting
expert witnesses testimony
Madeline Ann Domino
Department of Accounting, Mercer University, Macon, Georgia, USA
Matthew Stradiot
Assurance Department, PricewaterhouseCoopers LLC, Cleveland,
Ohio, USA, and
Mariah Webinger
Accountancy Department, John Carroll University,
University Heights, Ohio, USA
Abstract
Purpose – This paper aims to investigate factors which may infuence or bias judges’ decisions to
exclude or admit the testimony of accounting expert witnesses, under the US judicial guidelines
commonly known as the Daubert/Kuhmo standards. Accounting experts are increasingly providing
expert testimony as a part of fnancial litigation support services.
Design/methodology/approach – Judges’ decisions, in which opposing council evoked a Daubert/
Kuhmo challenge to the testimony provided by 130 professional accountants serving as expert
witnesses, were analyzed. The period of study was 2010 through 2014. Based on prior research, three
variables believed to potentially infuence or bias judges to systematically exclude expert testimony
were examined: gender, complexity and familiarity.
Findings – The results of binary logistic regression show that none of the variables has a signifcant
relationship to the accounting expert witnesses’ probability of surviving a challenge to Daubert/Kuhmo
standards. Findings suggest that judges are objective in evaluating the testimony provided by
accounting experts under Daubert/Kuhmo guidelines and that they may be immune to biases based
solely on gender, complexity and familiarity.
Originality/value – These results will be of interest to judges, lawyers and forensic accountants
acting as expert witnesses.
Keywords Forensic accounting, Daubert challenge, Expert witness, Judge bias, Jury bias,
Kumho challenge
Paper type Research paper
Introduction
Accounting professionals are increasingly involved in providing expert testimony in
fnancial litigation support. The increasing demand for qualifed professional
accounting experts prompted the American Institute of Certifed Public
Accountants’ (AICPA) Business Valuation/Forensic Litigation Services Executive
Committee to focus on forensic accountants, stating that their responsibilities
include collecting, analysis and evaluation of evidence, as well as interpreting and
communicating their fndings (AICPA, 2006). Additionally, accounting expert
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1030-9616.htm
Accounting
expert
witnesses
testimony
59
Received1 November 2014
Revised15 April 2015
Accepted17 April 2015
Accounting Research Journal
Vol. 28 No. 1, 2015
pp. 59-77
©Emerald Group Publishing Limited
1030-9616
DOI 10.1108/ARJ-11-2014-0097
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witnesses must be objective in presenting their fndings (Weil et al., 2001; Michaelson,
2005; DiGabriele, 2011).
Using an accountant’s expertise often adds substantial value and enhances the
chance of winning a client’s lawsuit (Ponemon, 1995). Serving as a fnancial expert
requires accountants to review working papers, prepare valuations, testify in
depositions, generate opinions as to whether generally accepted accounting and
generally accepted auditing standards were followed, assist in providing an
understanding of accounting issues to solve disputes and to serve as expert witnesses in
court (Ricchiute, 2004; DiGabriele, 2008; Muehlmann et al., 2012). In the accounting
literature, these activities are often identifed with forensic accountants.
This research investigates factors which may infuence or bias judges’ decisions to
exclude testimony provided by accounting expert witnesses, when it is challenged by
opposing council. A sample of US court cases from 2010 to 2014 where an expert was
challenged based on specifc guidelines for determining the admissibility of evidence
under the US Federal Rules of Evidence 702, Testimony of an Expert (USFRE 702) was
identifed and studied. Specifc guidelines have been provided in what is commonly
known as the Daubert Standard and Kuhmo Standard (Daubert/Kuhmo). Using
Daubert/Kuhmo criteria, judges act as gatekeepers in determining the exclusion or
admissibility of expert witnesses’ testimony, when opposing councils raise objections
(e.g. a Daubert/Kuhmo challenge).
Three variables believed to infuence or bias judges’ decisions to systematically
exclude expert evidence under the guidelines specifed under Daubert/Kuhmo were
examined: gender, complexity and familiarity. These variables are empirically studied
to determine their impact, if any, on the judges’ determination of excluding or admitting
the accounting expert’s testimony. Findings suggest that judges are objective in
evaluating the testimony provided by accounting experts under the guidelines of
Daubert/Kuhmo and that they may be immune to biases based solely on gender,
complexity and familiarity biases.
This research makes several contributions to the literature on accounting experts
providing testimony in fnancial litigation support. First, the study provides empirical
evidence on variables believed to infuence or bias judges’ decisions to systematically
exclude the accounting experts’ testimony. Second, with the growth in accounting
expert witnessing, the study directly contributes to this area of research in the
accounting literature. Finally, the research flls a void of the lack of research exploring
the exclusion of evidence under the Daubert/Kuhmo. To date, minimal research has
explored these topics.
Literature review
Judges’ potential biases
Instances of judges rejecting accounting experts’ testimony are replete in the both the
legal and accounting literature. According to DiGabriele (2008, p. 4), “accountants
regularly offer expert testimony services to the litigation community and there
testimony is frequently scrutinized by the court and at time excluded”. In Wagner v. CRI
(2001) the judge determined that the experts were biased and lacked impartiality. In an
empirical study, DiGabriele (2008) fnds that in fnancial litigation support services,
accounting expert witnesses’ often present valuations that differ signifcantly from one
another, as well as differ from the valuations made by the court. Bosland (1963) and
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Englebrecht and Jamison (1979) fnd that tax courts tended to reject experts’ valuations
and to rule somewhere in the middle.
There is also evidence to suggest varying interpretations of the Daubert/Kuhmo
standards, depending upon who is the judge. For example, in the 2014 ruling on
Manpower, Inc. v. Insurance Company of the State of Pennsylvania, an appeals court
judge reversed a lower court judge’s decision to exclude the testimony presented by an
accounting expert witness. In addition to interpretive differences, opposing decisions
may refect infuences or biases by judges’ who decide which challenged testimony
survives and which is excluded.
Thus, an important and understudied topic is the identifcation of factors which may
infuence or bias judges’ decisions to exclude the testimony of an accounting expert
witness when it is challenged by the opposing council under Daubert/Kuhmo. In these
instances, judges as the gatekeeper ensure that Daubert/Kuhmo guidelines are followed.
Prior research has shown that judges may be infuenced by biases that relate to
gender, complexity and familiarity. Based on these fndings, it is proposed that because
judges may be infuenced by the gender of the expert witness, they decide unfavorably
against accounting expert witnesses. If the case has many technical accounting
elements and computations that judges do not understand, the complexity of the case
may infuence judges in determining when to deny a motion to exclude an accounting
experts’ testimony and when to grant it. If judges are not familiar with the specialized
feld of law or and lack expertise in the area of law, judges may also be infuenced to
accept or reject the accounting experts’ testimony. By determining the factors which
may potentially infuence or bias judges’ decisions to accept or reject the testimony of an
accounting expert witness, it may be possible to determine if the Daubert/Kuhmo
guidelines are being followed appropriately and are free of gender, complexity and
familiarity biases.
Expert witness testimony
Since the landmark Daubert v. Merrell Dow Pharmaceuticals Inc. (Daubert) US Supreme
Court case in 1993, and the later Kumho Tire Company LTD, et al. Petitioners v. Patrick
Carmichael et al. (1999) (Kuhmo), which addressed nonscientifc experts, federal judges,
as well as the majority of state judges, have held a large amount of power. Judges are
nowrequired to act as an amateur expert and to determine whether an expert is, in fact,
an expert (Kuhmo, 1999). Potential problems may be created when expert testimony and
questions of fact are very technical, i.e. complex. Judges may also be asked to evaluate
testimony that is outside their areas of law or expertise. In these instances, judges may
be required to evaluate testimony for which they have not been suffciently trained or
which is outside their normal knowledge base.
USFRE 702 provides criteria for determining the admissibility of an expert
witnesses’ testimony. Further clarifcation has been provided by the US Supreme Court,
under what is commonly known as the Daubert standard. Under Daubert, judges may
decide to exclude expert testimony for a number of reasons, such as:
• an expert is not necessary;
• the expert’s techniques are not generally accepted by the expert community; and
• the expert is not qualifed to present testimony on the question of fact.
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Daubert standard. The 1993 landmark US Supreme Court case Daubert v. Merrell Dow
Pharmaceuticals Inc., (Daubert) established a new framework for determining the
admissibility of fndings for expert scientifc witnesses in federal trials, replacing the
guidelines of the Frye standard (Mahle, 2012). According to PricewaterhouseCoopers,
LLP (PwC) (2011), all but a handful of state courts have adopted Daubert.
Opposing lawyers commonly fle pretrial motions in limine to prevent evidence from
being introduced in trial (Crumbley and Cheng, 2014). Daubert offers guidelines for
judges to use in determining if an expert witness’ testimony should be partially, or
wholly, excluded (USFRE702). Daubert greatly expanded the responsibility of judges in
their gatekeeper role (Kozinski, 2001) and introduced a unique change to the analyses of
expert witnesses’ testimony. According to Daubert, expert testimony will be accepted if
the following criteria are met.
• The expert’s scientifc, technical or other specialized knowledge will help the Trier
of Fact to understand the evidence or to determine a fact in issue.
• The testimony is based on suffcient facts or data.
• The testimony is the product of reliable principles and methods.
• The expert has reliably applied the principles and methods to the facts of the
case.
Prior to Daubert, judges would accept expert testimony if it was generally accepted in
the relevant professional community. Thus, judges’ gatekeeping function was restricted
to determining if experts’ testimony includes theories or techniques that would be
generally accepted in the relevant community. Daubert requires judges to determine if
the testimony is both relevant and reliable (USFRE 702).
Daubert also requires judges to focus on the principles and methodologies used by
the expert to generate testimony, and not on the conclusions themselves. In 1997,
Daubert guidelines were amended by the US Supreme Court by recognizing that
conclusions reached and methodology used are not entirely distinct from one another
(General Electric Co. v. Joiner, 522 USA 136, 146, 1997). If an expert claims to have
applied methodologies accepted within the relevant community, but reached a
conclusion other experts in the feld would not reach, the court can suspect the methods
were not properly applied (USFRE 702).
Kuhmo standard. Daubert applied only to testimony of a scientifc nature. In 1999,
the US Supreme Court attempted to provide clarifcation to the application of Daubert in
its ruling on Kumho Tire Company LTD., et al. Petitioners v. Patrick Carmichael et al.,
which focused on specialized knowledge and non-scientifc evidence. Commonly known
as the Kumho Standard (Kumho), clarifcation provided guidelines for expert
witnessing for all felds of “specialized knowledge”. Consequently, an expert may be
viewed as any person who possesses relevant knowledge, skill, experience, training or
education (Kumho, 1999).
Thus, professional accountants are now considered experts, who are subject to the
same gatekeeping standards as scientifc experts. Depending on the circumstances of
the case, a non-exclusive reliability checklist may be applicable in determining the
reliability of a non-scientifc expert. Crumbley and Cheng (2014) fnd that the most
common factors applied from the checklist are:
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• whether the technique or theory has been subject to peer review and publication;
and
• whether the technique or theory has been generally accepted in the scientifc
community.
Accounting expert witnesses must meet the standards of both Daubert/Kumho.
Applicationof Daubert/Kumho. Each year, PwC, LLPconducts a study which focuses
on Daubert/Kuhmo challenges to non-scientifc expert witnesses. PwC’s most current
study spans the years 2000-2013. Results indicate that the number one reason for
exclusion of non-scientifc evidence provided by an expert, whether in whole or part,
was lack of reliability. For the time period covered, PwC found 718 Daubert/Kumho
challenges, resulting in either whole or partial exclusions of expert witness testimony.
Of that number, 309 (or 43 per cent) challenges were based solely on the result of lack of
reliability, compared to 163 (or 23 per cent) challenges based on instances of the lack of
relevance and 59 (or 8 per cent) challenges based on the lack of qualifcations. Of the
remaining challenges, 171 (or 24 per cent) were excluded for multiple reasons, and 16 (or
2 per cent) were excluded due to missed deadlines (PricewaterhouseCoopers, LLP, 2013).
PwC also found that the type of witness appears to affect the frequency of Daubert/
Kuhmo challenges, as well as the success, with success defned as a partial or whole
exclusion. Over the 14-year study period, the analyses of fnancial expert witnesses
found that economists and accountants most frequently challenged fnancial experts.
Economists were least likely to result in a successful exclusion (41 per cent), followed by
accountants (43 per cent), despite accountants being challenged most frequently.
According to PwC, the type of case (area of law) also affects the frequency and
outcome of Daubert/Kumho challenges. Cases involving breach of contract or
fduciary duty were most likely to be challenged. Cases involving fraud and
intellectual property were most likely to have a successful exclusion under Daubert/
Kuhmo (PricewaterhouseCoopers, LLP, 2013).
Potential biases in applying Daubert/Kumho
An important and understudied topic is the identifcation of factors which may infuence
or bias judges’ decisions to exclude the testimony of an accounting expert witness when
it is challenged by the opposing council under Daubert. The 2014 ruling on Manpower,
Inc. v. Insurance Company of the State of Pennsylvania (Manpower) illustrates that
judges may reach different conclusions in applying Daubert/Kumho.
In Manpower, Inc. v. Insurance Company of the State of Pennsylvania (2016), an
appeals court judge reversed a lower court judge’s decision to exclude the testimony of
an accounting expert witness. The case centered upon Manpower Inc.’s insurance
coverage claim stemming from a building collapse, located in France. Manpower hired
Eric Sullivan, an accounting expert witness, to establish the amounts of the loss claims
against the Insurance Company of the State of Pennsylvania (ISOP). The claims were
made under a “master” policy’s business interruption and personal property loss
provisions and were based upon a projected growth rate of 7.6 per cent for a fve-month
period preceding the collapse of the building. ISOP refuted the claim amount, stating
that historical performance indicators showed a much lower growth rate (3.8 per cent)
during this time period.
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The initial ruling was favorable to Manpower. However, ISOPfled a motion in limine
to exclude the accounting expert’s opinion, arguing that “the business interruption loss
was not a product of reliable methodology” (Manpower, Inc. v. Insurance Company of
the State of Pennsylvania, 2016, p. 7.) The district court judge subsequently excluded Mr
Sullivan’s calculations citing the reliability of his methods. The judge questioned
“whether Sullivan used reliable methods when selecting the numbers used in his
calculations – specifcally projected total revenues and projected total expenses”
(Manpower, Inc. v. Insurance Company of the State of Pennsylvania, 2016, p. 7.)
Manpower appealed the exclusion Mr Sullivan’s testimony, the adverse ruling and
the district court’s interpretation of policy interpretations relative to the losses. The
appeals court judge reversed the exclusion of the accounting expert witnesses’
testimony and the judgment against Manpower.
This case illustrates that judges may vary in their interpretations of the expert
witness guidelines provided by Daubert/Kuhmo. This line of reasoning is studied
relating it to the gender of the expert witness, the complexity of the case and the
familiarity with the area of law, as these factors may infuence judges’ decisions to
accept or reject an accounting expert witness’ testimony, when it is challenged under
Daubert/Kuhmo. These variables are now discussed.
Gender. Gender bias has been described as a “predisposition to treat people according
to sex stereotypes” (Abrahamson, 1993, p. 1209) and has been recognized and discussed
extensively in the legal system since the 1990s. Gender bias is common in
decision-making and also in the courtroom (Abrahamson, 1993; Czapanskiy, 1993).
According to Schafran (1990), gender bias in the court room denies woman equal
treatment and opportunity.
In a study of randomly selected practicing attorneys, 75 per cent of female compared
with 50 per cent of males reported experiencing some formof gender-related misconduct
in the previous fve years (Cortina, 2002). Johnson and Scheuble (2006) fnd evidence of
gender bias in the dispositions of punishment rendered by the court in juvenile cases,
with greater punishment given to girls than boys, even if the boys were repeat offenders
committing more serious offenses. Gender bias has been well documented in a number
of courtroom studies. A compilation of ten courtroom studies confrms that, during
litigation, judges exhibit gender bias in the ways they treat women lawyers and women
litigants (Czapanskiy, 1993).
Thus, the gender of the expert witness is anticipated to have a positive relationship
with the witness’ chance of survival for males and a negative relationship as females. It
is proposed that judges may unconsciously doubt or discredit the testimony of female
accounting expert witnesses, resulting in a lower acceptance rate of accounting expert
testimony presented by female accountants.
Complexity. Complexity has been defned by high amounts of technical language and
computational information and has been shown to affect receivers’ cognitive
satisfaction, comprehension and perception of the speaker’s credibility. Prior research
that shows cognitive satisfaction, comprehension and recall scores are substantially
lower in technical conditions than in the non-technical conditions (Jackson, 1992).
When a decision-maker faces a complex problem, frequently the problem is reduced
to a simpler problem. Heuristics are simplifed decision rules developed to deal with
complex situations. These heuristics are effcient and often work well but, in some
circumstances, may lead to systematic biases (Libby, 2002). Prior accounting research
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shows the importance of considering information attributes, such as complexity, as it
relates to accounting information (Plumlee, 2003).
Arnold (2002) fnds that, in complex accounting problems, simple biases exist, even
if the decision-makers are experienced professional accountants. When ranking
complex tax information, tax analysts were able to assimilate less complex information
to a greater extent, as compared to more complex information (Plumlee, 2003). Smith and
Talfer (1992) fnd that complex fnancial information inhibits the ability of
sophisticated readers to understand the annual reports. Thus, it is proposed that judges,
who are required to evaluate complex accounting expert witness testimony, may be
susceptible to complexity bias.
Familiarity. According to Awasthi (1990), an individual’s ability to abstract complex
information from an unfamiliar setting to more familiar components is related to
decision performance. Prior research suggests that judges may abstract, from facts
presented in expert testimony, something that is relevant to their own expertise,
creating a bias toward or against certain areas of expertise or certain areas of law (e.g.
familiarity bias).
Birnbaum (1979) conducted an experiment, in which judges were asked to estimate
the hypothetical value of cars based on blue-book values and on the values provided by
others who examined the cars. The experiment shows judges were biased toward the
value presented by the expert who has the highest association, or familiarity, to the
judge(s). Choi and Gulati (2008) also fnd judges are more likely to be biased in
high-stake situations in which they are actively familiar.
In Daubert/Kuhmo challenges, judges may make determinations on the testimony
presented by an accounting expert witness, yet the judge may have no or little
familiarity with this type of evidence. Thus, it is proposed that judges may be
systematically biased toward or against areas of law and expertise for which they are
familiar.
Methodology
Data sources
The Daubert Tracker database (www.dauberttracker.com/) was used to select the
sample data used in the study, but not recorded by variable. A case search was
performed on the Daubert Tracker Web site using the following criteria: Disciplines:
accounting; Gate-keeping Authority: Kumho; and Years: 2010-2014.
The Daubert Tracker will produce data on every court case within the designated
period with at least one expert witness with an accounting discipline challenged. It
should be noted that all witnesses within the case are listed by the Daubert Tracker, not
only the witnesses with an accounting discipline.
Sample. The initial sample selected from the Daubert Tracker included 237
challenges to expert witnesses with an accounting discipline between 2010 and 2014. Of
the 237 samples, 101 witnesses were excluded because the motion to exclude was
partially granted and partially denied, or the disposition could simply not be
determined. Another six witnesses were excluded, as their gender could not be
determined from their name, leaving a fnal sample of 130 challenges to be included in
the study.
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For a case to be included in the sample, only one of the experts had to be an
accounting expert. Cases in which the expert was a non-accountant (i.e. disciplines
outside of accounting) were excluded from the sample.
Variable selection
Based on prior research, three independent variables believed to infuence or bias
judges’ decisions in Daubert/Kuhmo challenges are studied: gender, complexity and
familiarity. The dependent variable selected was the disposition of the case, i.e. the
accounting experts’ testimony was accepted or rejected by the judge.
Independent variables. By reviewing data, the gender of the accounting expert
witness was determined to be either male or female. These data were used to measure
gender bias.
To measure complexity, two variables, “Number of Judges” and “Number of Experts
Challenged”, were consolidated into broader categories for ease of analysis and serve as
proxy variables to measure the complexity of the case.
The number of judges to preside over a case can reasonably be assumed to
measure complexity. The greater the number of judges involved in the case, the
more complex the case. The complexity may lead to more witnesses being
challenged. However, more complex cases maybe more likely to feature
higher-quality witnesses. As such, the direction of the relationship of the number of
judges in a case to the accounting experts’ testimony surviving a Daubert/Kuhmo
challenge is not predicted.
The number of accounting expert witnesses challenged in a case also serves as a
proxy for complexity, as more complex cases are likely to have more advanced legal
teams that are utilizing more witnesses, and may be more likely to challenge an
accounting expert of the opposing side. More complex cases may also be more likely to
feature higher-quality witnesses. Judges may have more diffculty evaluating a complex
case as compared to a less complex case. Arelationship is expected between the number
of accounting experts challenged and the chance of an accounting expert witnesses’
surviving a Daubert/Kuhmo challenge. Thus, it is proposed that in complex cases,
judges’ decisions may be biased in evaluating a Daubert/Kuhmo challenge to either
accept the testimony or reject the testimony.
To measure familiarity bias, two independent variables, “Area of Expertise” and
“Area of Law”, were consolidated into broader categories for ease of analysis. Area of
expertise was reclassifed into six categories: Valuation/Damages, Auditing, Tax,
Financial Accounting, Cost Accounting and Other. As not all witnesses have an area of
expertise, a “none” variable is also technically present within the analysis. Area of law
was reclassifed into eight categories; Liability, Intellectual Property, Contracts,
Banking, Regulatory, Construction, Fraud/Criminal and Other.
Five areas of expertise were tested for effects on accounting expert witnesses
Daubert/Kuhmo challenge survival rates. Auditing, Tax and Financial Accounting –
the areas of expertise that are strongly guided by regulations – are expected to have a
positive relationship with an expert’s chance of survival. Areas without as much
guidance to procedures – Valuation/Damages, Cost Accounting and Other – are
expected to have a negative relationship with the probability of survival.
Eight areas of law are tested for effects on accounting expert witness survival rates.
Areas of lawmore likely involving the interpretation of already-established accounting
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rules, such as Contracts, Banking, Regulatory, Construction and Fraud/Criminal, are
proposed to have a positive relationship with an expert’s survival rate. Areas of law
more likely to involve valuation services and expert opinions, as opposed to
interpretations of existing regulations, include Liability and Intellectual Property.
These areas of laware expected to have a negative relationship with the survival rate of
a Daubert/Kuhmo challenge to an accounting expert’s testimony, as the accounting
function provided in the cases is expected to be more subjective.
Dependent variable. The dependent variable, the disposition of the of
Daubert/Kuhmo challenges “Disposition”, was also consolidated. The Daubert Tracker
database does not have a standardized method for reporting the results of a challenge.
The disposition of Daubert/Kuhmo challenges was consolidated into two categories:
motion to exclude granted and motion to exclude denied.
Table I shows the detail of all variable consolidations.
Data analysis
Descriptive statistics
Descriptive statistics on each variable are shown in Table II. The sample of accounting
expert witnesses is overwhelmingly male (85.35 per cent). Whether this is a result of
more male expert witnesses being challenged or a larger population of male expert
witnesses is something that needs to be determined in future research. In most instances,
only one judge was assigned to a case; however, the mean for number of expert
witnesses challenged is almost three. The most common area of law is
Valuation/Damages (24.62 per cent). The majority of experts (66.92 per cent) listed no
area of expertise.
Binary logistic regression analysis
Binary logistic regression analysis was performed to analyze the effects of the variables
on the probability of an expert witness surviving a challenge. Binary logistic
regressions create models in which the dependent variable is bound between zero and
one, producing a probability of survival of a Dalbert/Kuhmo challenge.
The regression was run in IBM SPSS, as well as calculated using the Solver tool in
Microsoft Excel. Three variables, Auditing, Financial Accounting and Cost Accounting,
produced substantial standard errors in the SPSS regression. Likewise, the signifcance
level of each of the variables is either 0.999 or 1.000. As shown in Table II, Auditing,
Financial Accounting and Cost Accounting produced standard deviations of 0.2106,
0.1733 and 0.0877, respectively, within normal ranges.
When the binary logistic regression was run in Microsoft Excel, the coeffcients for
these three variables were the only differences than the SPSS fgures. SPSS determines
the Log Likelihood – used to calculate the coeffcients in a binary logistic regression –
with a maximum of 20 iterations, whereas Excel will run only 5 iterations. The
difference in the values was unable to be determined, but was hypothesized to have
occurred due to either the lack of signifcance of the variables and number of iterations
performed or multicollinearity between the variables.
Table III shows the correlation matrix. No large correlation between variables was
identifed, suggesting that multicollinearity is not the explanation.
Each program utilized its maximum number of iterations attempting to fnd a
solution with signifcant variables, resulting in the different coeffcient values as well as
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Table I.
Consolidations of
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the unusual signifcance level. A sensitivity analysis, without the area of law or area of
expertise variables, was also performed. No differences in results were noted, as the
results were similar to those of the full model binary logistic regression.
The results of the binary logistic regression are shown in Table IV.
Results
The gender of an accounting expert witness was found to have no signifcant effect on
whether an expert’s testimony survives a Daubert/Kuhmo challenge. Males were far
more likely to be expert witnesses, comprising 85.39 per cent of the sample. Unlike prior
research fndings, results of the statistical analysis do not refect a gender bias in judges’
decisions to accept or reject the accounting experts’ testimony under Daubert/Kuhmo.
Female accounting expert witnesses are not more likely or less likely to be retained.
Complexity is frequently associated with biases. The complexity of the case did not
appear to infuence or bias judges’ decisions on Daubert/Kuhmo challenges. Complexity
was measure in two ways: by the number of judges presiding over a case and by the
number of accounting experts assigned to the case. Neither of the complexity variables
has a signifcant statistical effect on the probability of being the challenged being
granted or denied.
Table II.
Descriptive statistics
Variable Mean SD n
Number of judges
Number of judges 1.19231 0.544118003 130
Number of experts challenged
Number of experts challenged 2.87692 3.254133649 130
Gender
Male 0.85385 0.354626968 130
Female 0.14615 0.354626968 130
Area of expertise
Valuation/damages 0.24615 0.432435656 130
Auditing 0.04615 0.210629859 130
Tax 0.01538 0.123553044 130
Financial accounting 0.03077 0.173359936 130
Cost accounting 0.00769 0.087705802 130
Other 0.04615 0.210629859 130
None 0.66923 0.472310198 130
Area of law
Liability 0.10000 0.301160546 130
Intellectual property 0.18462 0.389486153 130
Contracts 0.20769 0.40722456 130
Banking 0.08462 0.279385133 130
Regulatory 0.20000 0.401547395 130
Construction 0.10000 0.301160546 130
Fraud/criminal 0.05385 0.226587029 130
Other 0.06923 0.254828154 130
ARJ
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71
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ARJ
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With the number of judges presiding over a case, complexity was not found to have a
signifcant statistical effect on whether an accounting expert’s testimony survives a
Daubert/Kuhmo challenge. In this sample, typically one judge presided over the court
proceedings. The number of experts challenged in a case was found to have no
signifcant effect on whether an expert witness survives a challenge. It was proposed
that complexity would systematically infuence a judge’s decision to grant or deny a
Daubert/Kumho challenge. The data analysis did not support this prediction.
Like complexity, familiarity is frequently associated with biases. Familiarity was
measured in two ways: by the area of the lawand by the area of expertise. Neither of the
familiarity bias variables has a signifcant statistical effect on the probability of being
the challenged being granted or denied.
The areas of law of Liability, Intellectual Property, Contracts, Banking, Regulatory,
Construction and Fraud/Criminal were all found to have no signifcant effect on whether
an accounting expert witnesses’ testimony survives a Daubert/Kuhmo challenge. The
areas of expertise in Valuation/Damages, Auditing, Tax, Financial Accounting or Cost
Accounting were all found to have no signifcant effect on whether an accounting expert
witness’ testimony survives a Daubert/Kuhmo challenge. Unlike prior research
fndings, results of the statistical analysis do not refect familiarity biases by judges’ in
their decisions to accept or reject the accounting experts’ testimony when evaluated
under Daubert/Kuhmo.
Conclusions
An important and understudied topic is the identifcation of factors which may infuence
or bias judges’ decisions to exclude the testimony of an accounting expert witness when
it is challenged by the opposing council under Daubert/Kuhmo. Judges serve as the
gatekeepers who ensure that Daubert/Kuhmo guidelines are followed. A potential
Table IV.
Binary logistic
regression results
Variables in the equation
Variables B SE Wald df Signifcance
Number of judges 0.184 0.542 0.115 1 0.735
Number of experts challenged 0.106 0.132 0.652 1 0.419
Male ?0.792 1.146 0.478 1 0.49
Valuation/damages ?0.722 0.603 1.433 1 0.231
Auditing 19.689 15011.113 0.000 1 0.999
Tax ?1.37 1.682 0.663 1 0.415
Financial accounting 19.723 17700.144 0.000 1 0.999
Cost accounting 18.861 40192.97 0.000 1 1.000
Other ?0.154 1.36 0.013 1 0.91
Liability ?0.533 1.325 0.162 1 0.688
Intellectual property 0.618 1.331 0.216 1 0.642
Contracts ?0.99 1.199 0.681 1 0.409
Banking ?0.245 1.381 0.031 1 0.859
Regulatory 1.199 1.498 0.641 1 0.423
Construction 0.442 1.541 0.082 1 0.775
Fraud/criminal ?1.336 1.471 0.825 1 0.364
Constant 2.266 1.706 1.765 1 0.184
73
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problem is that judges, who are not experts, must rule on whether to deny or grant a
Daubert/Kuhmo challenge to exclude accounting experts’ testimony.
While prior research has shown that judges’ decisions may be infuenced or biased
gender (Schafran, 1990; Abrahamson, 1993; Czapanskiy, 1993; Cortina, 2002; Johnson
and Scheuble, 2006), complexity (Smith and Taffer, 1992; Jackson, 1992; Libby, 1992;
Arnold, 2002; Plumlee, 2003) and familiarity (Birnbaum, 1979; Awasthi, 1990; Chio and
Gulati, 2008), the results of this study do not support prior academic fndings. Statistical
analysis shows no signifcant effects in judges’ decisions to accept or reject a Daubler/
Kumho challenge based on gender, complexity or familiarity biases. While, the
statistical analysis produces no signifcant results, the fndings of the study are
particularly interesting.
Several contributions are made to the academic literature on accounting experts
providing testimony in fnancial litigation support. First, the study provides empirical
evidence that gender, complexity and familiarity do not infuence or bias judges’
decisions to systematically exclude the accounting experts’ testimony under Daubert/
Kuhmo. Second, with the growth in accounting expert witnessing, the study directly
contributes to the literature on accounting expert witnessing. Finally, the research flls
a void in the research which explores the exclusion of evidence under Daubert/Kuhmo.
Minimal research to date has explored these topics empirically.
The fndings are also relevant to a number of practitioner groups. Accountants
serving as expert witnesses and lawyers representing clients will be interested to know
that judges’ decisions are not biased by gender, complexity or familiarity. Judges will
also fnd the study results of interest.
Opportunities for future research
This study highlights areas for future research. Additional research on other biases and
infuences on judges’ decisions relative to Daubert/Kuhmo is needed. More evaluation of
Daubert challenges may identify what is being challenged and where testimony is being
excluded or included.
Research models or theories that focusing on the testimony most likely to be
challenged or more likely to lead to dismissal, is another fruitful avenue. Such models or
theories may provide lawyers and judges with additional criteria upon which to
evaluate accounting experts’ testimony. It may also provide accounting experts with
valuable information needed to make their testimony more effective.
Lastly, the research looks at judges’ biases on accounting expert witnesses, but not
on the biases of the experts (Champagne, 1990). It is generally accepted that a signifcant
gap exists in resources between prosecution and most defendants (Bernstein, 2008).
This suggests that many defendants are able to hire a more sophisticated expert and the
distinction of prosecution/defendant may be a signifcant predictor of whether
testimony is accepted or denied.
Limitations
The results of this study are limited to US court cases using accounting expert
witnesses and may not be generalizable to other countries’ legal situations and to
other types of expert witnesses. The majority of experts in the study were male. It is
not known if different results would be found if a greater proportion of accounting
expert witnesses were female. Complexity was measured by looking at the number
ARJ
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of judges assigned to a case and the number of expert witnesses challenged in a case.
The extent to which different measures of complexity may capture complexity bias
is not known. Finally, other areas or different classifcations schemas may also
identify familiarity bias.
References
Abrahamson, S.S. (1993), Toward a courtroom of one’s own: an appellate court judge looks at
gender bias; 61 U. Cin. L. Rev. 1209.
American Institute of Certifed Public Accountants (2006), available at: www.aicpa.org/
InterestAreas/ForensicAndValuation/Community/Pages/Forensic%20and%20Valuation
%20Services%20Executive%20Committee.aspx
Arnold, V.C. (2002), “The effect of experience and complexity on order and recency bias in decision
making by professional accountants”, Accounting and Finance, Vol. 40, pp. 109-134.
Awasthi, V.A. (1990), “The effects of monetary incentives on effort and decision performance: the
role of cognitive characteristics”, The Accounting Review, Vol. 65, pp. 797-811.
Bernstein, D. (2008), “Expert witnesses, adversarial bias, and the (partial) failure of the Daubert
revolution”, Iowa Law Review, Vol. 93, pp. 451-1949.
Birnbaum, M.A. (1979), “Source credibility in social judgement: bias, expertise, and the judge’s
point of view”, Journal of Personality and Social Psychology, Vol. 37 No. 1, pp. 48-74.
Bosland, C. (1963), “Tax valuation by compromise”, The Tax Law Review, Vol. 19, pp. 77-89.
Champagne, A.S. (1990), “An empirical examination of the use of expert witnesses in American
courts”, Jurimetrics Journal, Vol. 31, pp. 375-392.
Choi, S.J. and Gulati, G.M. (2008), “Bias in judicial citations: a window into the behavior of
judges?”, The Journal of Legal Studies, Vol. 37 No. 1, pp. 87-130.
Cortina, L.L. (2002), “What’s gender got to do with it? Incivility in the federal courts”, Law&Social
Inquiry, Vol. 27 No. 2, pp. 235-270.
Crumbley, L.D. and Cheng, C.C. (2014), “Avoid losing a Daubert challenge: some best practices for
expert witnesses”, The ATA Journal of Legal Tax Research, Vol. 12 No. 1, pp. 41-53.
Czapanskiy, K. (1993), “Domestic violence, the family, and the lawyering process: lessons from
studies on gender bias in the courts”, Family Law Quarterly, Vol. 27, pp. 247-277.
DiGabriele, J.A. (2008), “The adversarial bias of accounting experts in fnancial litigation: an
empirical analysis of compromised objectivity in accounting expert testimony”, Journal of
Accounting, Ethics and Public Policy, Vol. 8 No. 1, pp. 1-22.
DiGabriele, J.A. (2011), “An Observation of differences in the transparent objectivity of forensic
accounting expert witnesses”, Journal of Forensic & Investigative Accounting, Vol. 3 No. 2,
pp. 390-416.
Englebrecht, T. and Jamison, R. (1979), “An empirical inquiry into the role of the tax court in the
valuation of property for charitable contribution purposes”, The Accounting Review,
Vol. 54, pp. 554-562.
Jackson, L. (1992), “Information complexity and medical communication: the effects of technical
language and amount of information in a medical message”, Health Communication, Vol. 4
No. 3, pp. 197-210.
Johnson, D.R. and Scheuble, L.K. (2006), “Gender bias in the disposition of juvenile court Referrals:
the effects of time and location”, Criminology, Vol. 29 No. 4, pp. 677-699.
75
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Kozinski, A. (2001), “Meeting reliability standards in case A doesn’t give a CPA witness a leg up
in case B: Expert Testimony After Daubert”. Journal of Accountancy, available at: www.
questia.com/library/journal/1G1-76728081/expert-testimony-after-daubert
Kumho Tire Company, LTD, et al., Petitioners v. Patrick Carmichael, etc. et al., 97-1709 (Supreme
Court of the United States March 23, 1999).
Libby, R.B. (2002), “Experimental research in fnancial accounting”, Accounting, Organizations
and Society, Vol. 27 No. 8, pp. 775-810.
Mahle, S.E. (2012), “The ‘pure opinion’ exception to the Florida Frye standard”, The Florida Bar
Journal, Vol. 86 No. 2, pp. 41-45.
Manpower, Inc. v. Insurance Company of the State of Pennsylvania (2016), in the United States
Court of Appeals for the Seventh Circuit, No. 12-2688.
Michaelson, W.M. (2005), in Pagano, W.J. and Buckhoff, T.A(Eds), Expert Witnessing in Forensic
Accounting, pp. 63-70.
Muehlmann, B.W., Burnaby, P. and How, M. (2012), “The use of forensic accounting experts in tax
cases as identifed in court opinions”, Journal of Forensic &Investigative Accounting, Vol. 4
No. 5, pp. 1-34.
Plumlee, M.A. (2003), “The effect of information complexity on analysts’ use of that information”,
The Accounting Review, Vol. 78 No. 1, pp. 275-296.
Ponemon, L.A. (1995), “The objectivity of accountants’ litigation support judgments”, The
Accounting Review, Vol. 70 No. 1, pp. 467-488.
PricewaterhouseCoopers, LLP. (2011), Daubert Challenges to Financial Experts: An 11-year Study
of Trends and Outcomes, PricewaterhouseCoopers, LLP, New York, NY.
PricewaterhouseCoopers, LLP. (2013), Daubert Challenges to Financial Experts: AYearly Study of
Trends and Outcomes, PricewaterhouseCoopers, LLP, New York City, NY.
Ricchiute, D.N. (2004), “Effects of an attorney’s line of argument on accountants’ expert witness
testimony”, The Accounting Review, Vol. 79 No. 1, pp. 221-245.
Schafran, L.H. (1990), “Overwhelming evidence: reports on gender bias in the courts”, Trial,
Vol. 26 No. 2, pp. 28-30, 30-35.
Smith, M. and Taffer, R. (1992), “Readability and understandability: different measures of the
textual complexity of accounting narrative”, Accounting, Auditing & Accountability
Journal, Vol. 5 No. 4, pp. 84-98.
Weil, R., Wagner, M. and Frank, P. (2001), Litigation Services Handbook: The Role of the Financial
Expert, 3rd ed., John Wiley & Sons, New York, NY.
Further reading
Bassett, W.R., Clare, S.M. and Rodell, S.A. (2013), “Evidence”, Mercer Law Review, Vol. 64,
pp. 929-952.
Begley, S. (2003). “‘Junk science’ ban also keeps jurors from sound evidence”. The Wall Street
Journal, available at:http://online.wsj.com/articles/SB105666035267101800 (accessed 16
September 2014).
Dolman, M.A. and McGrath, J.N. (2014). “Five ways to survive a Daubert challenge against your
expert”, The National Trial Lawyers, available at: www.thenationaltriallawyers.org/2014/
06/fve-ways-to-survive-a-daubert-challenge-against-your-expert/ (accessed 16 September
2014).
Huber, D. (2012), “Is forensic accounting in the United States becoming a profession?”, Journal of
Forensic & Investigative Accounting, Vol. 4 No. 1, pp. 255-284.
ARJ
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Pepper, P. (2012), “Particular evidence problems with appraisals, part III: expert witnesses”,
Bankruptcy & Insolvency Litigation, Vol. 18 No. 1, pp. 18-19.
Manpower, Inc. v. Insurance Company of the State of Pennsylvania (2016), in the United States
Court of Appeals for the Seventh Circuit, No. 12-2688.
US Federal Rule of Evidence Rule 702. Testimony by Expert Witness. (2015). Retrieved from
Cornell University LawSchool Legal Information Institute: www.law.cornell.edu/rules/fre/
rule_702
Corresponding author
Mariah Webinger can be contacted at: [email protected]
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