An ergodic BSDE approach to forward entropic risk measures: representation and large-maturity behavior
Wing Fung Chong, Ying Hu, Gechun Liang, and Thaleia Zariphopoulou ; Finance and Stochastics, 23(1): 239-273
Using elements from the theory of ergodic backward stochastic differential equations (BSDEs), we study the behavior of forward entropic risk measures in stochastic factor models. We derive general representation results (via both BSDEs and convex duality) and examine their asymptotic behavior for risk positions of large maturities. We also compare them with their classical counterparts and provide a parity result.
Assets and Liabilities: When Do They Exist?
Nicole Cade, Lisa Koonce, and Kim I. Mendoza ; Contemporary Accounting Research, 36(2): 553-587
In this paper, we investigate whether the current references to probability in standard setters' conceptual definitions of assets and liabilities cause individuals to believe that the probability of a future transfer of economic benefits must be above some meaningful threshold for an asset or a liability to exist—a belief that is contrary to standard setters' intent. Results of multiple experiments indicate that the majority of individuals do use a high probability threshold to determine asset existence, whereas for liabilities the majority use a very low threshold. Thus, even under ceteris paribus conditions, liabilities are more frequently judged to exist than assets—a phenomenon analogous to accounting conservatism, as has been discussed in terms of the performance statement. These findings are robust to variation in formal training and in type of liability, and cannot be explained by alternative approaches to judging existence. Consistent with standard setters' intentions, results also suggest that their proposed changes to the definitions of assets and liabilities—changes that attempt to clarify the intended role of probability—do cause a greater proportion of participants to indicate that the relevant financial statement element (asset or liability) exists, relative to participants with no definition. Our study provides important insights for standard setters as they continue work on their missions to update their Conceptual Frameworks and for researchers regarding the role of conservatism on the balance sheet.
Digital Disruption: The Transdisciplinary Future of Marketing Education
Victoria Crittenden and Robert A. Peterson ; Journal of Marketing Education, 41(1): 43894
We are educating our students in an era of digital disruption. The changes in traditional roles of consumers and companies brought on by digital disruption have created the need for educational material that can shape and contribute to the emerging and evolving world of marketing. According to Brennan, Lu, and von der Heidt (2018), digital technologies are contributing to a major change in the practice, promise, and operations of higher education, and these changes are challenging marketing educators to innovate and to refresh program and curriculum designs. Uncles (2018) asserted that there are considerable digital technologies and technology-enabled learning and teaching opportunities in the higher education landscape, with Kerr and Kelly (2017) noting the many challenges with respect to keeping the marketing curriculum updated.
Do Auditors and Audit Committees Lower Fraud Risk by Constraining Inconsistencies between Financial and Nonfinancial Measures?
Joseph F. Brazel and Jaime Schmidt ; Auditing: A Journal of Practice and Theory, 38(1): 103-122
Prior research finds that companies committing fraud exhibit large inconsistencies between reported revenue growth and growth in revenue-related nonfinancial measures (e.g., number of stores, employees, patents). However, prior research also suggests that auditors, on average, are not adept at identifying and constraining these differences. This study investigates whether certain auditors and audit committees are able to lower fraud risk by constraining inconsistencies between financial and related nonfinancial measures (NFMs). For a sample of companies across a variety of industries, we find that auditors with greater industry expertise and tenure and audit committee chairs with greater tenure are less likely to be associated with companies that exhibit large inconsistencies between their reported revenue growth and related NFMs. Surprisingly, we observe that audit committees with industry expert chairs are more likely to be associated with large inconsistencies (higher fraud risk) than audit committees without industry expert chairs.
Dynamic Credit-Collections Optimization
Naveed Chehrazi, Peter W. Glynn, and Thomas A. Weber ; Management Science, 65(6): 2737-2769
Based on a dynamic model of the stochastic repayment behavior exhibited by delinquent credit-card accounts in the form of a self-exciting point process, a bank can control the arrival intensity of repayments using costly account-treatment actions. A semi-analytic solution to the corresponding stochastic optimal control problem is obtained using a recursive approach. For a linear cost of treatment effort, the optimal policy in the two-dimensional (intensity, balance) space is described by the frontier of a convex action region. The unique optimal policy significantly reduces a bank’s loss given default and concentrates the collection effort onto the best possible actions at the best possible times so as to minimize the sum of the expected discounted outstanding balance and the discounted cost of the collection effort, thus maximizing the net value of any given delinquent credit-card account.
A Fresh Look at Return Predictability Using a More Efficient Estimator
Travis L. Johnson ; Review of Asset Pricing Studies, 9: 1-46
I assess time-series return predictability using a weighted least squares estimator that is around 25% more efficient than ordinary least squares (OLS) because it incorporates time-varying volatility into its point estimates. Traditional predictors, such as the dividend yield, perform better in- and out-of-sample when using my estimator, indicating the insignificant OLS estimates may be false negatives driven by a lack of power. Some newer predictors, such as the variance risk premium and the president’s political party, are insignificant when using my estimator, indicating the significant OLS estimates may be false positives driven by a few periods with high expected volatility.
Received March 31, 2018; editorial decision September 26, 2018 by Editor Jeffrey Pontiff. Authors have furnished an Internet Appendix and supplementary data and code, which are available on the Oxford University Press Web site next to the link to the final published paper online.
Commentary on Varun Grover, Michelle Carter, and Dan Jiang’s “Trends in the conduct of information systems research”
Sirkka L. Jarvenpaa ; Journal of Information Technology, 34(2): 178-180
Coordinated Patient Appointment Scheduling for a Multistation Healthcare Network
Dongyang Wang, Kumar Muthuraman, and Douglas J. Morrice ; Operations Research, 67(3): 599-618
Current healthcare reforms advocate significantly to improve the coordination of services around a patient-centric model. With most patient care delivered through outpatient services, the need to coordinate scheduling between different services in a hospital or colocated clinics becomes central to successful reform. Currently, outpatient services require independent appointment decisions, and the coordination is left to the patient. This approach causes several inefficiencies, including an increase in missed appointments and unacceptable access delays. This paper proposes a multistation network model that carefully strikes a balance between assumptions that allow tractability and assumptions that disallow real-world adoption. To allow for real-world applicability, we consider sequential appointment scheduling in a network of stations with exponential service times, no-show possibilities, and overbooking. We argue and present evidence that a heuristic myopic scheduling policy is close to optimal. However, because it is not simple enough for practical implementation, we explore a sequence of approximations and find one that offers a significant computational advantage. We also provide several managerial insights and discuss how network structures affect complexity.
Design and Dynamic Pricing of Vertically Differentiated Inventories
Ioannis Stamatopoulos and Christos Tzamos ; Management Science, 65(9): 4222-4241
We study a model in which a monopoly firm designs the quality profile of its inventory and then dynamically updates its pricing menu for a finite selling horizon to maximize revenue. In a counterfactual scenario, a social planner goes through the same process to maximize total welfare. We show that in both scenarios the problem of dynamically pricing heterogeneous-quality (vertically differentiated) inventories is equivalent to that of dynamically pricing homogeneous-quality inventories, in the sense that a solution to one implies a solution to the other. Moreover, we prove a strong scarcity result, which suggests that the sale of a product drives up the prices on all remaining products, whether of higher or lower quality. We then consider product line design under a production technology that utilizes costly and potentially limited resources. We show that with unlimited (but costly) resources, the revenue maximizer undersupplies quality to all products compared with the social planner. With limited resources, we show that the revenue maximizer exhibits elitism: he overallocates (underallocates) resources on the production of high-quality (low-quality) products. However, as the volume of expected consumer arrivals increases to infinity, both the revenue maximizer and the welfare maximizer allocate resources equally across products.
Do Investors Respond to Explanatory Language Included in Unqualified Audit Reports?
Keith Czerney, Jaime Schmidt, and Anne M. Thompson ; Contemporary Accounting Research, 36(1): 198-229
This article investigates whether investors respond to explanatory language (EL) added to unqualified audit reports. Although prior research finds an association between auditor EL and lower financial reporting quality, surveys suggest that many investors limit their attention to the unqualified nature of the opinion. We use three‐day abnormal returns and abnormal trading volume to measure investor response to EL in unqualified audit reports issued from 2000 to 2014. We find little evidence to indicate that investors respond to auditor EL at the audit report release date. In further analyses, we find that the lack of investor response is attributable both to incomplete investor reactions (55 percent of EL occurrences) and previous incorporation of EL (40 percent of EL occurrences). Overall, the results support policymakers’ initiatives to improve the usefulness of unqualified audit reports.
A national experiment reveals where a growth mindset improves achievement
A National Experiment Reveals Where a Growth Mindset Improves Achievement. Nature 573, 364-369.
A global priority for the behavioural sciences is to develop cost-effective, scalable interventions that could improve the academic outcomes of adolescents at a population level, but no such interventions have so far been evaluated in a population-generalizable sample. Here we show that a short (less than one hour), online growth mindset intervention—which teaches that intellectual abilities can be developed—improved grades among lower-achieving students and increased overall enrolment to advanced mathematics courses in a nationally representative sample of students in secondary education in the United States. Notably, the study identified school contexts that sustained the effects of the growth mindset intervention: the intervention changed grades when peer norms aligned with the messages of the intervention. Confidence in the conclusions of this study comes from independent data collection and processing, pre-registration of analyses, and corroboration of results by a blinded Bayesian analysis.
Auditor Perceptions of Audit Workloads, Audit Quality, and Job Satisfaction
Auditor Perceptions of Audit Workloads, Audit Quality, and Job Satisfaction. Accounting Horizons 33(4), 95-117.
In this study, we use a survey instrument to obtain perspectives from over 700 auditors about present-day audit workloads and the relationship between audit workloads, audit quality, and job satisfaction. Our findings indicate that auditors are working, on average, five hours per week above the threshold at which they believe audit quality begins to deteriorate and often 20 hours above this threshold at the peak of busy season. Survey respondents perceive deadlines and staffing shortages as two of the primary reasons for high workloads and further believe that high workloads result in decreased audit quality via compromised audit procedures, impaired audit judgment, and difficulty retaining staff with appropriate knowledge and skills. We also find that auditors’ job satisfaction and their excitement about auditing as a career are negatively impacted by high audit workload, particularly when the workload exceeds a threshold that is perceived to impair audit quality. Overall, our findings provide support for the PCAOB’s recent concern that heavy workloads are continuing to threaten audit quality, and suggest that the primary drivers of workload (i.e., deadlines and staffing problems) might be the actual “root cause” of workload-related audit deficiencies.
Capital Share Dynamics When Firms Insure Workers
Capital Share Dynamics When Firms Insure Workers. Journal of Finance 74(4), 1707-1751.
Although the aggregate capital share of U.S. firms has increased, capital share at the firm‐level has decreased. This divergence is due to mega‐firms that produce a larger output share without a proportionate increase in labor compensation. We develop a model in which firms insure workers against firm‐specific shocks, with more productive firms allocating more rents to shareholders, while less productive firms endogenously exit. Increasing firm‐level risk delays exit and increases the measure of mega‐firms, raising (lowering) the aggregate (average) capital share. An increase in the level of rents magnifies this effect. We present evidence that supports this mechanism.
Austin, Boston, Silicon Valley, and New York: Case studies in the location choices of entrepreneurs in maintaining the Technopolis
Austin, Boston, Silicon Valley, and New York: Case Studies in the Location Choices of Entrepreneurs in Maintaining the Technopolis. Technological Forecasting and Social Change 146, 267-280.
This study uses institutional theory and the “Technopolis” wheel to investigate the movement of technology entrepreneurs and why they “stick” to well-established entrepreneurial ecosystems in Silicon Valley, Austin, Boston, and New York City. We detail the historical development of the entrepreneurial ecosystem in each location, with a particular focus on the institutions and support structures that link and sustain key resources that are central to technology clusters. We operationalize key segments of the Technopolis wheel including (1) networks and connectedness, (2) investment capital, and (3) innovation and R&D. The empirical analysis specifies models testing for location-specific variation in the influence of these factors on entrepreneur location choice. We supplement this with analysis of interview data from 45 technology entrepreneurs with direct experience in these locations. We find that higher degrees of connectedness in Austin and Silicon Valley are an important factor in retaining potential entrepreneurs and several institutions were linked to facilitating tie formation and accessing key resources within the Technopolis. We also find that the frequency of funding opportunities positively influences entrepreneurs moving to Austin, Boston, and Silicon Valley to immediately start a company. In Boston, we find a positive association between patents and staying in Boston to launch a startup and we find that older entrepreneurs living in New York and Silicon Valley are less likely to remain and start a company.
Combating Fake News on Social Media with Source Ratings: The Effects of User and Expert Reputation Ratings
Combating Fake News on Social Media with Source Ratings: The Effects of User and Expert Reputation Ratings. Journal of Management Information Systems 36(3), 931-968.
As a remedy against fake news on social media, we examine the effectiveness of three different mechanisms for source ratings that can be applied to articles when they are initially published: expert rating (where expert reviewers fact-check articles, which are aggregated to provide a source rating), user article rating (where users rate articles, which are aggregated to provide a source rating), and user source rating (where users rate the sources themselves). We conducted two experiments and found that source ratings influenced social media users’ beliefs in the articles and that the rating mechanisms behind the ratings mattered. Low ratings, which would mark the usual culprits in spreading fake news, had stronger effects than did high ratings. When the ratings were low, users paid more attention to the rating mechanism, and, overall, expert ratings and user article ratings had stronger effects than did user source ratings. We also noticed a second-order effect, where ratings on some sources led users to be more skeptical of sources without ratings, even with instructions to the contrary. A user’s belief in an article, in turn, influenced the extent to which users would engage with the article (e.g., read, like, comment and share). Lastly, we found confirmation bias to be prominent; users were more likely to believe — and spread — articles that aligned with their beliefs. Overall, our results show that source rating is a viable measure against fake news and propose how the rating mechanism should be designed.
A Dynamic Model of Characteristic-Based Return Predictability
A Dynamic Model of Characteristic-based Return Predictability. Journal of Finance 74(6), 3187-3216
We present a dynamic model that links characteristic‐based return predictability to systematic factors that determine the evolution of firm fundamentals. In the model, an economy‐wide disruption process reallocates profits from existing businesses to new projects and thus generates a source of systematic risk for portfolios of firms sorted on value, profitability, and asset growth. If investors are overconfident about their ability to evaluate the disruption climate, these characteristic‐sorted portfolios exhibit persistent mispricing. The model generates predictions about the conditional predictability of characteristic‐sorted portfolio returns and illustrates how return persistence increases the likelihood of observing characteristic‐based anomalies.
A new perspective on post-earnings-announcement-drift: Using a relative drift measure
A New Perspective on Post-earnings-announcement-drift: Using a Relative Drift Measure. Journal of Business Finance and Accounting 46(9/10), 1123-1143.
Prior research finds that there is a delayed reaction to both analyst‐based earnings surprises and random‐walk‐based earnings surprises. Focusing on the market reaction from the post‐announcement window, prior studies show that analyst‐based drift is larger than random walk‐based drift. This finding is counter‐intuitive if we believe large, sophisticated investors tend to trade on analysts’ forecast earnings news and thus react faster and more completely than smaller and less sophisticated investors react to random walk earnings news. In this study, we construct a relative measure of post‐earnings‐announcement drift (PEAD) (i.e., drift as a proportion of total market reaction to earnings news) which we refer to as the ‘drift ratio’, and we provide evidence, consistent with our intuition, that analyst‐based drift ratio is smaller (not greater) than random‐walk‐based drift ratio. We find that this difference is more pronounced in more recent periods and for firms with more sophisticated investors. Our approach to measure the PEAD is more intuitive than that in traditional PEAD literature. Our results thus complement existing research findings by utilizing the drift ratio measure to generate new insights about the drift phenomenon.
Adherence to Clinical Guidelines, Electronic Health Record Use, and Online Reviews
Adherence to Clinical Guidelines, Electronic Health Record Use, and Online Reviews. Journal of Management of Information Systems 36(4), 1071-1104.
To increase transparency of healthcare quality, the Centers for Medicare and Medicaid Services (CMS) initiated the Physician Quality Reporting System (PQRS). However, the impact of PQRS on physicians is unclear, particularly as related to their online reputation. Is there an association between a physician’s online reputation and her adherence to clinical guidelines stipulated in the PQRS? Is online reputation associated with use of electronic health records (EHR)? To investigate these questions, we combine data on online physician reviews with the PQRS data on clinical guideline adherence and EHR use. Unlike prior research, which primarily uses clinical outcomes as proxies for care quality, our study uses adherence to clinical guidelines, a process measure that reflects physician conformance with evidence-based clinical practices. In addition, we focus on EHR use at the physician level, in contrast to the usual approach of examining it at the aggregate institutional level. Consistent with the economic theory of credence goods, we observe no significant relationship between physicians’ adherence to clinical guidelines and their online reviews. Although there is some evidence of association between EHR use and their overall rating, similar relationships are not consistently observed for individual dimensional ratings. Overall, the online reputation of a physician exhibits minimal association with her actual clinical activities — and is mostly driven by latent topics in the textual reviews — implying that the ability of online reviews to inform prospective patients of care quality might be quite limited. Therefore, patients should be cautious when using online physician reviews, and policymakers should increase the accessibility of PQRS and other similar data to help patients make informed physician choices.
Agricultural Partnership for Dairy Farming
Agricultural Partnership for Dairy Farming. Production and Operations Management 28(12), 3042-3059.
This paper studies an innovative agricultural partnership model in the dairy industry. In developing regions, farmers are constrained by limited resources, while it is costly for an enterprise to set up new facilities and raise dairy animals all on its own. Under the partnership model, dairy animals are raised by individual farmers during the maturing stage and then by the enterprise during the milking stage. This can lower the enterprise’s investment cost, ensure milk quality, and also expand the farmers’ capacity given that a new batch can be raised when the old batch goes to the enterprise’s facilities. We find that from the enterprise’s perspective, the performance of this model depends on the farmers’ original capacity and capacity expansion ratio (i.e., how much it can expand under partnership). The profitability of the enterprise can either increase in the farmers’ original capacity if the expansion ratio is small or decreases otherwise. Compared with the conventional decentralized model and the independent integrated model, the partnership model is particularly preferred when the enterprise’s market size is intermediate. Several extensions of our model show that the government quality subsidy offered to the farmers may sometimes lower dairy product quality as well as the enterprise’s profit; when the enterprise aims to maximize the total profit of the partnership, it will contract with more farmers and produce more dairy products; and if the farmers have more bargaining power, the partnership model will benefit the farmers more but be less preferable to the enterprise.
An additive model of decision making under risk and ambiguity
An Additive Model of Decision Making Under Risk and Ambiguity. Journal of Mathematical Economics 85, 78-92.
We extend the mean–variance (risk–value) tradeoff model to decision making under both risk and ambiguity. This model explicitly captures the tradeoff between the magnitude of risk and the magnitude of ambiguity. A measure that ranks lotteries in terms of the magnitude of ambiguity can also be obtained using this separation. By applying our model to asset pricing under ambiguity, we show that the equity premium can be decomposed into two parts: the risk premium and the ambiguity premium. Further, combining this model with the standard risk–value model, we build on the risk–ambiguity tradeoff to provide the value–risk–ambiguity preference model that does not rely on an approximation argument as the mean–variance model.