Taking A Closer Look At The Bayesian Truth Serum: A Registered Report

Over the past decades, psychology and its cognate disciplines have undergone substantial reform, ranging from advances in statistical methodology to significant changes in academic norms. One aspect of experimental design that has received comparatively little attention is incentivisation, i.e. the way that participants are rewarded and incentivised monetarily for their participation. While incentive-compatible designs are in use in disciplines like economics, the majority of studies in psychology and experimental philosophy are constructed such that individuals’ incentives to maximise their payoffs in many cases counteract their incentives to state their true preferences honestly. This is in part because the subject matter is often self-report data about subjective topics. One mechanism that allows for the introduction of an incentive-compatible design in such circumstances is the Bayesian Truth Serum (Prelec, 2004), which rewards participants based on how surprisingly common their answer are. Recently, Schoenegger (2021) applied this mechanism in the context of Likert-scale self-reports, finding that the introduction of this mechanism significantly altered response behaviour. In this registered report, we further investigate this mechanism by (i) replicating the original result and (ii) teasing out whether the effect may be explainable by an increase in expected earnings or the addition of a prediction task. We take this project to help introduce incentivisation mechanisms into fields where they were not widely used before.

CTE Teacher Licensure and Long-Term Student Outcomes

We use longitudinal data from Massachusetts that link high school course-taking records in career and technical education (CTE) to postsecondary student outcomes to provide the first empirical evidence linking characteristics of CTE teachers to later student outcomes. We find that CTE teachers who received better scores on subject performance tests required for licensure tend to have students with higher longer-term earnings than CTE teachers who received lower scores on these tests, controlling for other factors. Specifically, we estimate that a 1 standard deviation increase in teacher performance on these tests is associated with about a $1,000 increase in average expected earnings for the teacher's students 5 years after their expected graduation date, controlling for licensure test area and observable differences between students.

Daily Labor Supply and Adaptive Reference Points

This paper provides field evidence on how reference points adjust, a degree of freedom in reference-dependence models. Examining this in the context of cabdrivers’ daily labor-supply behavior, we ask how the within-day timing of earnings affects decisions. Drivers work less in response to higher accumulated income, with a strong effect for recent earnings that gradually diminishes for earlier earnings. We estimate a structural model in which drivers work toward a reference point that adjusts to deviations from expected earnings with a lag. This dynamic view of reference dependence reconciles conflicting “neoclassical” and “behavioral” interpretations of evidence on daily labor-supply decisions. (JEL J22, J31, L94)

Beyond Nudging: Generalisable and transferable learning in human decision-making

Canonical work on human decision-making demonstrates consistent, stereotyped and sub-optimal risk-reward trade-offs. However, recent work on experienced-based-, perceptual- and sensori-motor choice appear to severely restrict the scope of the canonical work, demonstrating trade-offs that are either differently sub-optimal, or much closer to optimal. Such dissociations may reflect highly specific mechanisms, or other confounds between domains; impossible to tease apart with current observational methods. We develop a method for strong causal inference based on experimentally manipulating risk preferences. Using a double-blind randomized control design, we trained people in a single domain, evaluate the extent to which training generalizes beyond the training-set, and more importantly the extent to which training transfers to risk domains in which participants were not trained. Participants were trained to maximize their expected earnings (i.e., to be risk-neutral). In total, we tested for transfer to four different risk domains, all of which are known to dissociate. We find that training is necessary and sufficient to cause reliable changes in decision-making. Importantly, training transfers, with participants becoming more risk-neutral also in domains for which they had had no training, showing that risk-reward trade-offs in different domains and tasks share common substrate. Shared mechanisms open up the opportunity to for practical general-purpose training programmes to improve human decision-making.

Threshold and Group Size Uncertainty in Common-pool Resources: An Experimental Study

Threshold common-pool resources (TCPRs), such as fisheries or groundwater reserves, face irreversible damage if harvesting exceeds a sustainability threshold. Uncertainty about the threshold for sustainable use or the number of resource users can exacerbate the overharvesting problem. Policy makers may therefore seek to reduce threshold or group size uncertainty in TCPRs. Overall, we find that reducing threshold and group size uncertainty (moving from high to low uncertainty) increases expected earnings from the resource. However, complete elimination of group size uncertainty reduces expected earnings. Furthermore, the impact of group size uncertainty on earnings varies by the level of threshold uncertainty. Moving from high to low group size uncertainty increases earnings at low levels of threshold uncertainty but not at high levels of threshold uncertainty. Taken together, we find that reducing threshold uncertainty is beneficial while tackling group size uncertainty requires a more nuanced approach, highlighting the importance of a joint analysis.

Analysis on the Present Situation and Countermeasures of Earnings Management

<p>Earnings management of listed companies has become a very common headache for listed companies in China, and it is also a problem of great concern to the public. Within the scope permitted by accounting standards and relevant laws and regulations, a considerable number of people purposefully planned to realize the expected earnings by choosing accounting policies, changing accounting estimates or arranging transactions and events, and they influence the decision-making of accounting information users through financial reports, thus enabling the company to maximize its own earnings. Paying attention to enterprise earnings management has become the consensus of every decision maker. This paper analyzes the present situation and motivation caused by earnings management, and it puts forward several governance measures of earnings management aiming at the present situation, aiming at making listed companies use earnings management reasonably, avoiding overuse or overuse of earnings management, and showing the public a real business situation.</p>

The Predictability of Future Aggregate Earnings Growth and the Relation between Aggregate Analyst Recommendation Changes and Future Returns

We extend prior research examining the relation between aggregate recommendation changes and future returns by documenting that this relation varies over time as a function of the predictability of future earnings growth. When industry-level earnings growth is more predictable, we find that recommendation changes relate negatively to future returns. Our evidence suggests that this negative relation results from analysts revising recommendations upward for higher expected earnings growth but failing to adjust downward for a related decrease in investor risk aversion and demand for risk premia leading to lower expected returns. In contrast, when industry-level earnings growth is less predictable, we find that recommendation changes relate positively to future returns. However, this positive relation results from analysts and investors similarly underestimating earnings growth persistence. Overall, the evidence fails to support the claim that analysts' recommendation changes incorporate aggregate information in a manner that adds value to investors by predicting future returns.

That’s the ticket: explicit lottery randomisation and learning in Tullock contests

Most laboratory experiments studying Tullock contest games find that bids significantly exceed the risk-neutral equilibrium predictions. We test the generalisability of these results by comparing a typical experimental implementation of a contest against the familiar institution of a ticket-based raffle. We find that in the raffle (1) initial bid levels are significantly lower and (2) bids adjust more rapidly towards expected-earnings best responses. We demonstrate the robustness of our results by replicating them across two continents at two university labs with contrasting student profiles.

On the Expected Earnings Hypothesis Explanation of the Aggregate Returns–Earnings Association Puzzle

We provide strong support for the underappreciated expected earnings hypothesis of a negative correlation between aggregate stock returns and earnings. For 1970–2000, our powerful modeling strategy incorporating macroeconomic information reveals that aggregate returns are significantly and negatively correlated with expected aggregate earnings changes but uncorrelated with unexpected aggregate earnings changes. However, this negative correlation changes after 2000, perhaps from heightened volatility or accounting changes. We also show that underlying macroeconomic information explains the power of aggregate earnings to predict future gross domestic product growth.