A New General Equilibrium Welfare Measure, with Application to Labor Income Taxes

In this paper we extend the Hicksian compensating variation welfare measure in two directions. First, we adjust the size of the compensating variation in order to account for the fact that the compensating transfers will result in changes in output, as well as in prices, because labor and, in dynamic models, capital will adjust in response to these transfers. Second, we extend the measure to a dynamic setting with possibly time non-separable preferences. We find that these considerations become more significant for the welfare cost of higher labor income taxes as one moves from static to dynamic models, to models with time non-separable preferences, and finally to models with uncertainty.

Dominance in a socially dynamic setting: hierarchical structure and conflict dynamics in ravens' foraging groups

Dominance hierarchies typically emerge in systems where group members regularly encounter and compete for resources. In birds, the ‘open’ and dynamic structure of foraging groups may prevent the emergence of structured hierarchies, although this assumption have hardly been tested. We report on agonistic data for ravens Corvus corax , collected over two 18-month periods for 183 marked individuals of a wild (fluid) population and 51 birds from six captive (stable) groups. We show that the dominance structure (steep and transitive) in wild foraging groups is strikingly similar to that found in captivity. In the wild, we found that higher ranks are mainly occupied by males, older and more aggressive individuals that also tend to receive fewer aggressions. Exploring the mechanisms sustaining the wild dominance structure, we confirmed that males are more aggressive than females and, with age, tend to receive fewer aggressions than females. Males that are about to leave the foraging groups for some months are less aggressive than newcomers or locals, while newcomers are specifically targeted by aggressions in their first year (as juveniles). Taken together, our results indicate that the socially dynamic conditions ravens face during foraging do not hinder, but provide opportunities for, using (advanced) social cognition. This article is part of the theme issue ‘The centennial of the pecking order: current state and future prospects for the study of dominance hierarchies’.

Intellectual Impact of Spiritual Wellbeing, Self-Determination, and Employee Outlook on Industry 5.0

The industrial revolution and advancement in field of artificial intelligence in term of Industry 4.0 has reduced the need of human intervention at workplace. That is why murmur has started around Industry 5.0 where the focus is collaborative interaction between human and machines/robots for sustainable development of industries. The objective of this study is to assess the effects on the well-being of the employees in the dynamic setting through spirituality training. The study includes the detailed analysis of 392 responses collected from employees working in high-tech and high-automated organisations such as automobiles, FMCG, and IT with the help of structured questionnaire. This study might help improve the employee wellbeing and reduce the uncertainty in workforce participation and provide more creative, innovative, and engaging mindset in Industry 5.0. The research results have presented a significant interaction between the employee wellbeing, outlook, and self-determination at workplace in the presence of spirituality training.

The Times They Are A-Changing: Experimenting with Dynamic Adverse Selection

We examine a common value dynamic matching environment where adverse selection accrues slowly over time. Theoretical best responses are therefore time varying, and the prior experimental literature suggests that sequential environments might lead to greater understanding of adverse selection in this dynamic setting. However, while a sophisticated minority in our experiment do condition on time and are close to a best response, the majority use a stationary response, even after extended experience. In an environment with persistent uncertainty, our results indicate that sequentiality is insufficient for the large majority of participants to recognize the effects of adverse selection. (JEL C78, C92, D82, D91)

Extracting fictional truth from unreliable sources

A fictional text is commonly viewed as constituting an invitation to play a certain game of make-believe, with the individual sentences written by the author providing the propositions we are to imagine and/or accept as true within the fiction. However, we can’t always take the text at face value. What narratologists call ‘unreliable narrators’ may present a confused or misleading picture of the fictional world. Meanwhile, there has been a debate in philosophy about ‘imaginative resistance’ in which we resist imagining (or even accepting as true in the fiction) what’s explicitly stated in the text. But if we can’t take the text’s word for it, how do we determine what’s true in a fiction? The chapter proposes an account of fiction interpretation in a dynamic setting (a version of Discourse Representation Theory (DRT) with a mechanism for opening, updating, and closing temporary ‘workspaces’) and combines this framework with belief revision logic.

Driver Surge Pricing

Ride-hailing marketplaces like Uber and Lyft use dynamic pricing, often called surge, to balance the supply of available drivers with the demand for rides. We study driver-side payment mechanisms for such marketplaces, presenting the theoretical foundation that has informed the design of Uber’s new additive driver surge mechanism. We present a dynamic stochastic model to capture the impact of surge pricing on driver earnings and their strategies to maximize such earnings. In this setting, some time periods (surge) are more valuable than others (nonsurge), and therefore trips of different time lengths vary in the induced driver opportunity cost. First, we show that multiplicative surge, historically the standard on ride-hailing platforms, is not incentive compatible in a dynamic setting. We then propose a structured, incentive-compatible pricing mechanism. This closed-form mechanism has a simple form and is well approximated by Uber’s new additive surge mechanism. Finally, through both numerical analysis and real data from a ride-hailing marketplace, we show that additive surge is more incentive compatible in practice than is multiplicative surge. This paper was accepted by David Simchi-Levi, revenue management and market analytics.