Belief‐updating biases hinder the correction of inaccurate beliefs and lead to suboptimal decisions. We complement Rabin and Schrag's (1999) portable extension of the Bayesian model by including conservatism in addition to confirmatory bias. Additionally, we show how to identify these two...

A popular approach to perform inference on a target parameter in the presence of nuisance parameters is to construct estimating equations that are orthogonal to the nuisance parameters, in the sense that their expected first derivative is zero. Such first-order orthogonalization may, however,...

While content moderation began as a solution to online abuse, it has increasingly been framed as a source of abuse by a diverse coalition of users, civil society organisations, and politicians concerned with platform bias. The resulting crisis of legitimacy has motivated interest in more...

We investigate whether artificial intelligence can address the peer review crisis in economics by analyzing 27,090 evaluations of 9,030 unique submissions using a large language model (LLM). The experiment systematically varies author characteristics (e.g., affiliation, reputation, gender) and...

This paper introduces a novel multivariate composite estimator for the Labour Force Survey (LFS). Unlike the univariate composite estimators used in some countries, the multivariate estimator takes into account the different probabilities of transitioning between labour market categories, such...

Written self-promotion is crucial in numerous decision-making scenarios, including job applications, securing funds for start-ups, or academic grant proposals. In two experiments, we study the effects of written self-promotion on decision quality and gender bias. We show that, if anything,...

Probabilistic editing has been introduced to enable valid inference using established survey sampling theory in situations when some of the collected data points may have measurement errors and are therefore submitted to an editing process. To reduce the editing effort and avoid over-editing, in...

We study the objectivity of officiating under extreme pressure by analysing additional time played at the 2022 FIFA World Cup and 2024 UEFA European Championship. Controlling for within-match events, rules should be applied consistently across both halves of a football match. However, we argue...

How do perceptions of AI versus human authorship affect engagement with creative work? In an incentivized experiment, participants (N=654) assessed the content of a short story labeled as either human or AI-generated and reported their willingness to pay and work to finish reading it. Consistent...

We investigate a bracketing property that purports to yield upper- and lower bounds on the treatment effects obtained from a fixed effects- and lagged dependent variable model. Referencing both analytical results and a Monte Carlo simulation, we explore the conditions under which the bracketing...

The increasing integration of technological aids, such as the video assistant referee (VAR), is fundamentally transforming decision-making processes in professional football, especially influencing critical match moments. Penalty kicks, characterised by technical simplicity but intense...

We analyze whether teachers discriminate against ethnic minority students in terms of grading. Using comprehensive data on students in German primary and secondary schools, we compare students’ scores in standardized, anonymously graded achievement tests with non-anonymous teacher ratings...

In this study we explore the knowledge and beliefs regarding behavioral biases among behavioral scientists, financial professionals, and the general population. We investigate knowledge about ten prominent biases and collect beliefs about the knowledge levels of each of these subject pools by...

We test for state-dependent bias in the European Central Bank's inflation projections. We show that the ECB tends to underpredict when the observed inflation rate at the time of forecasting is higher than an estimated threshold of 1.8%. The bias is most pronounced at intermediate forecasting...

Purpose - The study attempts to investigate the relationship between emotional biases (loss aversion bias, overconfidence bias, and regret aversion bias) and investment decisions through a meta-analysis approach. Design/methodology/approach - A meta-correlation analysis was done using sample...