Wenfeng Wang
Robert H. Smith School of Business, University of Maryland
3330E Van Munching Hall College Park, Maryland 20742
413-835-5933 | wenfengwang@rhsmith.umd.edu
EDUCATION
UNIVERSITY OF MARYLAND, COLLEGE PARK
Ph.D. Accounting (Expected May 2016)
College Park, MD
UNIVERSITY OF MASSACHUSETTS, AMHERST
Master of Applied Mathematics (2011)
Amherst, MA
UNIVERSITY OF FLORIDA
Master of Accounting (2009)
CENTRAL UNIVERSITY OF FINANCE AND ECONOMICS
Bachelor of Arts, Accounting (2007)
Gainesville, FL
Beijing, CHINA
RESEARCH INTERESTS
• Audit market structure; Real effects of financial reporting; Capital market; Applied econometrics
WORKING PAPER
• “Industry Linkages, Audit Firms’ Industry Portfolio Decisions: Evidence from Product Language”
(Dissertation)
− Committee: Rebecca Hann (Chair), Michael Kimbrough, Oliver Kim, Richmond Mathew, and Andrew Sweeting
• “Financial Reporting Quality and Productivity Dispersion”
− With Rebecca Hann and Yue Zheng, 2015
• “Measuring Information Overlap Across Sequential Forecasts”
− With Oliver Kim and Donal Byard, 2015
• “Do Managers’ Timely Loss Recognition Choices Reflect Private Information?”
− With Yi Cao, Ruyun Feng, and Michael D. Kimbrough, 2015
CONFERENCE PARTICIPATION
• AAA Annual Meeting, Chicago IL, August 2015 (Presenter, Ad-hoc Reviewer)
• AAA FARS Meeting, Nashville TN, January 2015 (Presenter, Ad-hoc Reviewer)
• AAA Annual Meeting, Atlanta GA, August 2014 (Presenter, Ad-hoc reviewer, Discussant)
CONFERENCES ATTENDED
• FARS Midyear Meeting 2014, 2015
• AAA Annual Meeting 2011, 2012, 2013, 2014, 2015
• AAA/Deloitte/J. Michael Cook Doctoral Consortium 2015
• Journal of Accounting and Public Policy Conference 2014
• DC Area Accounting Symposium 2012, 2013, 2014, 2015
November 2015 | Wenfeng Wang
TEACHING INTERESTS
• Principles of Accounting, Intermediate Accounting, Financial Statement Analysis, Auditing
TEACHING EXPERIENCE
University of Maryland, College Park
• Instructor, Intermediate Financial Accounting I, (BMGT 310, Spring 2015), Evaluation (3.83/4.0)
• Instructor, Intermediate Financial Accounting I, (BMGT 310, Summer 2014), Evaluation (3.19/4.0)
University of Massachusetts, Amherst
• Recitation Section Leader, Linear Methods and Probability for Business,
(MATH 121, Fall 2009- Spring 2011), Department Interval Evaluation (No Rating)
PROFESSIONAL AFFILIATION
• American Accounting Association
HONORS AND AWARDS
• AAA/Deloitte/J. Michael Cook Doctoral Consortium Fellowship, 2015
• Robert H. Smith School of Business Doctoral Fellowship, 2011 - 2016
• University of Massachusetts, Amherst Teaching Assistantship, 2009 - 2011
• First Classification Honor by ESC Rennes School of Business, 2007
• Top Level Bachelor Thesis by ESC Rennes School of Business, 2007
• First Prize of National Chemistry Competition, 1999
• First Prize of Wood Plane Model Competition, 1999
• Outstanding Member of Student Government, 1998
PROFESSIONAL QUALIFICATIONS
• CPA Exam, IL, US, Aug. 2010
PROGRAMMING SKILLS
• Software: STATA, SAS, R
REFERENCES
Professor Rebecca Hann
Associate Professor & KPMG Faculty Fellow
University of Maryland, R.H. Smith School of Business
rhann@rhsmith.umd.edu
(301) 405-7132
Professor Michael Kimbrough
Associate Professor & Cohn-Reznick Fellow
University of Maryland, R.H. Smith School of Business
mkimbrough@rhsmith.umd.edu
(301) 405-8522
Professor Oliver Kim
Professor
University of Maryland, R.H. Smith School of Business
okim@rhsmith.umd.edu
(301) 405-2243
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November 2015 | Wenfeng Wang
WORKING PAPER ABSTRACT
“Industry Linkages, Audit Firms’ Industry Portfolio Decisions: Evidence from Product Language”
(Dissertation, 2015)
Motivation:
Audit firms fiercely compete on industry expertise. How do Big Four audit firms choose which industry
portfolio to specialize in? How do small audit firms choose which industry combination to jointly operate
in?
Abstract:
The organizational structure of audit firms is often described as a professional service network; yet, we
know little about how this network is formed. In this study, I examine an important dimension of this
network—the linkages between industries in the product space, and in particular, how across-industry
relations affect audit firms’ client portfolio choice and hence the audit market structure. Using text-based
product space measures, I examine Big Four and small audit firms’ decisions to jointly specialize in or enter
a portfolio of industries, respectively. For the Big Four audit firms, I find that they tend to specialize in 1)
industry-pairs that are close to each other in the product space, which tend to enjoy greater synergies, 2)
industry-pairs with more between-industry, which provide greater mobility and entry synergies to expand in
the product space, and 3) industry-pairs with higher within-industry similarity, which tend to experience
greater benefits of economies of scale. Using the collapse of Arthur Andersen as an exogenous supply shock
in the audit market, I find that former Arthur Andersen clients are more likely to be matched with the Big
Four audit firm whose industry specialty portfolio is more closely aligned with the firm in the product space.
I further find that the audit fees for the closely matched clients tend to be lower, consistent with Big Four
audit firms offering discounted fees to attract new clients either to strengthen their existing industry
specialty or to expand their industry specialty portfolio. For small audit firms, I find that synergistic value
between industries also explain their industry choice. However, unlike the Big Four audit firms, they are less
likely to have clients in industry-pairs with high within-industry similarity, suggesting that more
resource-constrained small audit firms do not have the capacity to take advantage of the benefits of
economies of scale as the Big Four audit firms do.
“Financial Reporting Quality and Productivity Dispersion”
(with Rebecca Hann and Yue Zheng, 2015)
Motivation:
Information frictions could impede resource allocation efficiency among firms. Would better financial
reporting mitigate information friction and hence facilitate resource allocation efficiency across firms?
Abstract:
Prior research documents large, persistent differences in productivity across firms, suggesting the presence
of market frictions that impede the efficiency with which resources are reallocated from low- to
high-productivity firms. We posit that high-quality financial reporting can mitigate one such
friction—information frictions that prevent market participants from having perfect information about firms’
productivity and hence about their relative productivity within an industry. Using a large sample of firms in
the manufacturing sector, we find that industries with higher reporting quality tend to have smaller
within-industry productivity dispersion, with this relation stronger for industries with greater external capital
needs. In addition, using the change in segment reporting standard (from SFAS 14 to SFAS 131) as an
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November 2015 | Wenfeng Wang
exogenous shock to the reporting environment, we find that industries with a larger increase in reporting
disaggregation after SFAS 131 – i.e., a larger improvement in reporting quality – experience a greater
reduction in productivity dispersion. Taken together, these findings suggest that financial reporting quality
has real effects at the industry level, with higher reporting quality facilitating more efficient allocation of
resources across firms and thereby reducing productivity dispersion, in part through the capital market
channel.
“Measuring Information Overlap Across Sequential Forecasts”
(with Oliver Kim and Donal Byard, 2015)
Motivation:
Financial analysts typically make their forecasts in a sequential order. How are information contained in
such sequentially made forecasts linked? It is natural to think analysts would have incentive to incorporate
information contained in existing forecasts into their forecasts and at the same time would incorporate their
own private information. To what extent are they successful in absorbing information contained in existing
forecasts? To what extent do they contribute their private information to their forecasts?
Abstract:
In the paper, we attempt to answer these questions. This study investigates the information structure among
sequentially made analysts’ forecasts. We outline a new model that can be used to estimate the difference in
information between two sequential earnings forecasts as “new information” that is present only in the
second forecast, and “missing information” that is only in the first. We find that new (missing) information
is 40% (31%) between consecutive daily mean forecasts, and the two are positively correlated (+0.66). We
also find that missing information decreases as the lag between paired forecasts increases. Our results
suggest a number of hitherto unexplored aspects of analysts' information environment, such as: analysts
have difficulty extracting information from prior forecasts, information heterogeneity among analysts arises
from missing as well as new information, and information discovery and interpretation are related. Finally,
we show analytically and empirically that new and missing information are key determinants of the structure
of the optimal (i.e., more accurate) aggregate earnings forecast.
“Do Managers' Timely Loss Recognition Choices Reflect their Private Information?”
(with Yi Cao, Ruyun Feng, and Michael D. Kimbrough, 2015)
Motivation:
The central debate on principles-based versus rules-based accountings is whether more principles-based
accounting standards would allow more effective private information communication from managers to
investors or induce more self-serving opportunistic behavior. In a specific setting, we ask whether managers’
choice of firms’ timely loss recognition reflect their private information about firms’ fundamentals?
Abstract:
Stock returns reflect the market’s assessment of economic news affecting the firm for the period based on
public information. In the case of negative returns, a manager may choose not to record the full extent of bad
economic news reflected in stock returns (i.e. a manager may exercise low timely loss recognition) if he
believes he has private information that justifies a more favorable outlook than the pessimistic outlook
reflected in stock returns. If the managers' more favorable view is ultimately revealed to be correct in
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November 2015 | Wenfeng Wang
subsequent periods then the negative stock returns in the current period will reverse in the subsequent period.
Therefore, we examine the association between managers' choice of timely loss recognition and subsequent
stock return reversals. Using several alternative firm-year measures of timely loss recognition, we document
that firm-years with lower (higher) timely loss recognition are associated with greater (less) subsequent
reversals of negative returns. This finding is consistent with managers basing their choice of timely loss
recognition on their private information. We further find that the relationship between timely loss
recognition and subsequent return reversals varies systematically with factors that affect the likelihood and
extent to which managers' private information dominates the public information in returns. In contrast to
prior empirical studies that highlight the potentially distorting effects of managerial discretion, our study
provides empirical evidence of an instance where managers use their discretion to reflect their private
information in reported earnings.
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