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.