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...

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...

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,...

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...

Purpose The purpose of this study is to investigate the impact of behavioral biases on investment decisions through a serial mediation of overconfidence and disposition effects. Design/methodology/approach The authors assess the behavioral biases affecting the investment decisions of life...

Textbook theory predicts that t-ratios decline towards zero in regressions when there is increasing collinearity between two independent variables. This article shows that this rarely happens if the two variables are endogenous, and coefficients increase greatly with more collinearity. The...

Generative artificial intelligence (GenAI) refers to machines that can create new ideas and generate outputs similar to human cognition. This technology has ushered in a new era, offering remarkable learning capabilities and producing unique results. In this paper, we explore the role of GenAI...

Multiple Price Lists (MPLs) or Choice Lists (CLs) are widely used to elicit risk and time preferences, yet are prone to cognitive biases, particularly among respondents with limited numeracy skills. This paper compares three elicitation approaches; row-by-row from the top, from the bottom, and a...

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...

This paper studies linear time‐series regressions with many regressors. Weak exogeneity is the most used identifying assumption in time series. Weak exogeneity requires the structural error to have zero conditional expectation given present and past regressor values, allowing errors to...