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A class of short-term models for the oil industry addressing speculative storage
No full textThis is a work in progress. The aim is to propose a plausible mechanism for the short term dynamics of the oil market based on the interaction of economic agents. This is a theoretical research which by no means aim at describing all the aspects of the oil market. In particular, we use the tools and terminology of game theory, but we do not claim that this game actually exists in the real world. In parallel, we are currently studying and calibrating a long term model for the oil industry, which addresses the interactions of a monopolists with a competitive fringe of small producers. It is the object of another paper that will be available soon. The present premiminary version does not contain all the economic arguments and all the connections with our long term model. It mostly addresses the description of the model, the equations and numerical simulations focused on the oil industry short term dynamics. A more complete version will be available soon
Prosocial religions as folk-technologies of mutual policing
No full textNational audienceWhy do humans believe in moralizing gods? Leading accounts argue that these beliefs evolved because they help societies grow and promote group cooperation. Yet recent evidence suggests that beliefs in moralizing gods are not limited to large societies and might not have strong effects on cooperation. Here, we propose that beliefs in moralizing gods develop because individuals shape supernatural beliefs to achieve strategic goals in within-group interactions. People have a strategic interest in controlling others’ cooperation, either to extort benefits from them or to gain reputational benefits for protecting the public good. Moreover, they believe, based on their folk-psychology, that others would be less likely to cheat if they feared supernatural punishment. Thus, people endorse beliefs in moralizing gods to manipulate others into cooperating. Prosocial religions emerge from a dynamic of mutual monitoring, in which each individual, lacking confidence in the cooperativeness of conspecifics, attempts to incentivize others’ cooperation by endorsing beliefs in supernatural punishment. We show how variations of this incentive structure explain the variety of cultural attractors toward which supernatural punishment converges, including extractive religions that extort benefits from exploited individuals, prosocial religions geared toward mutual benefit, and forms of prosocial religion where belief in moralizing gods is itself a moral duty. We review evidence for nine predictions of this account and use it to explain the decline of prosocial religions in modern societies. Supernatural punishment beliefs seem endorsed as long as people believe them necessary to ensure others’ cooperation, regardless of their objective effectiveness in doing so
Psychology of Debt in Rural South India
No full textInternational audienceThis study is the first attempt to examine the extent to which the Big Five personality traits and cognitive skills (Raven scores, numeracy, and literacy scores) are correlated with debt negotiation and debt management in a Global South country; and how social identity – in particular caste and gender – channels the effect of cognition on debt outcomes. Using a panel dataset built from an original household survey (called NEEMSIS) conducted in 2016–2017 and 2020–2021 in rural Tamil Nadu, India, and employing multivariate correlation probit analysis with lagged variables, we find the following. Firstly, conscientiousness is an advantage in the negotiation and management of debt, particularly for non-Dalit women, suggesting that, in a rural patriarchal context, women leverage personality traits to overcome the constraints of social identity. Secondly, emotional stability is a disadvantage in both debt negotiation and management. Thirdly, the role of cognition and in particular the Raven score is ambiguous
Government awards to CEOs
No full textInternational audienceThis paper investigates the value and corporate governance consequences of government awards for a sample of French CEOs appointed to the national Order of the Legion ofHonor (Légion d’honneur). Short-term market reactions surrounding award announcements are significantly positive, whereas the valuation of firms with awarded CEOs is greater than that of (matched) firms with nonawarded CEOs. We explore the channels through which government awards create value and find evidence that they provide awarded CEOs and their firms with increased political access. We also observe that government awards are associated with better corporate governance in that awarded CEOs are more likely to be fired for poor performance. The negative effects that have been documented for media awards and are associated with CEOs’ superstar status do not seem to apply to state awards
SOMbrero: SOM Bound to Realize Euclidean and Relational Outputs
No full textThe stochastic (also called on-line) version of the Self-Organising Map (SOM) algorithm is provided. Different versions of the algorithm are implemented, for numeric and relational data and for contingency tables as described, respectively, in Kohonen (2001) &
Polynomial Time Learning-Augmented Algorithms for NP-hard Permutation Problems
No full textInternational audienceWe consider a learning-augmented framework for NP-hard permutation problems. The algorithm has access to predictions telling, given a pair u, v of elements, whether u is before v or not in an unknown fixed optimal solution. Building on the work of Braverman and Mossel (SODA 2008), we show that for a class of optimization problems including scheduling, network design and other graph permutation problems, these predictions allow to solve them in polynomial time with high probability, provided that predictions are true with probability at least 1/2 + ϵ, for any given constant ϵ > 0. Moreover, this can be achieved with a parsimonious access to the predictions. </div
Everything You Always Wanted to Know About JSON Schema (But Were Afraid to Ask)
No full textInternational audienceThe last few years have seen the ubiquitous diffusion of JSON as one of the most widely used formats for publishing and interchanging data, as it combines the flexibility of semistructured data models with well-known data structures like records and arrays. While various schema languages for describing JSON data have been proposed in the past, e.g., JSound and Joi, JSON Schema established itself as de-facto standard schema language for JSON data.The main aim of this tutorial is to provide the audience with the basic notions for exploiting JSON Schema while processing and manipulating JSON data. This tutorial focuses on four main aspects: (1) we first describe Classical JSON Schema and introduce the features that are shared with the latest versions of the specification; (2) we introduce, then, Modern JSON Schema, explain why it differs from Classical JSON Schema, and discuss its novel evaluation model; (3) we analyze tools that support or exploit JSON Schema, like, for example, validators and data generators; and (4) we highlight open research challenges and opportunities related to JSON Schema.</div
She works hard for the money : debt burden and labour supply in India
No full textFor over 40 years, labour supply has been at the heart of empirical microeconomics, but few studies have examined the impact of household debt burdens on labour supply, and almost none on countries of the Global South. This research fills this gap by examining how debt burden - measured by the debt service ratio - affects labour supply, in particular hours worked, among more than 3200 individuals in rural Tamil Nadu, India, between 2016-17 and 2020-21. Using a Heckman correction with lagged debt ratios and fixed effects to account for unobserved factors and limit reverse causality, the study highlights a striking result: women increase their labour supply to repay household debt, regardless of which household member incurred it. Our results challenge the commonly held view in the South that women's work is synonymous with empowerment, suggesting that it may be the result of economic pressuresrather than a move towards autonomy
Improving Discriminator Guidance in Diffusion Models
No full textInternational audienceDiscriminator Guidance has become a popular method for efficiently refining pre-trained Score-Matching Diffusion models. However, in this paper, we demonstrate that the standard implementation of this technique does not necessarily lead to a distribution closer to the real data distribution. Specifically, we show that training the discriminator using Cross-Entropy loss, as commonly done, can in fact increase the Kullback-Leibler divergence between the model and target distributions, particularly when the discriminator overfits. To address this, we propose a theoretically sound training objective for discriminator guidance that properly minimizes the KL divergence. We analyze its properties and demonstrate empirically across multiple datasets that our proposed method consistently improves over the conventional method by producing samples of higher quality
The impact of recovery rate heterogeneity in achieving herd immunity
No full textInternational audienceHerd immunity is a critical concept in epidemiology, describing a threshold at which a sufficient proportion of a population is immune, either through infection or vaccination, thereby preventing sustained transmission of a pathogen. In the classic susceptible-infectious-recovered (SIR) model, which has been widely used to study infectious disease dynamics, the achievement of herd immunity depends on key parameters, including the transmission rate and the recovery rate, where represents the inverse of the mean infectious period. While the transmission rate has received substantial attention, recent studies have underscored the significant role of in determining the timing and sustainability of herd immunity. Additionally, it is becoming increasingly evident that assuming as a constant parameter might oversimplify the dynamics, as variations in recovery times can reflect diverse biological, social, and healthcare-related factors. In this paper, we investigate how heterogeneity in the recovery rate affects herd immunity. We show empirically that the mean of the recovery rate is not a reliable metric for determining the achievement of herd immunity. Furthermore, we provide a theoretical result demonstrating that it is instead the mean recovery time, which is the mean of the inverse of the recovery rate that is critical in deciding whether herd immunity is achievable within the SIR framework. A similar result is proved for the SEIR model. These insights have significant implications for public health interventions and theoretical modeling of epidemic dynamics.Boll Unione Mat Ital (2025