Documents de travail

Résumé We propose a new approach to measure the sensitivity of economic growth to natural disasters in developing countries at different time horizons (short, medium, and long term). We allow for heterogeneous effects across growth regimes and intensities of disaster shocks using quantile-on-quantile regressions and wavelet decomposition.Our findings yield several insights. First, small disaster shocks boost GDP per capita growth in low-growth countries across all horizons. By contrast, in high-growth countries, such shocks cause sharp short-term growth declines, followed by a rapid recovery in the medium term, albeit without regaining the pre-disaster growth trajectory in the long term. Second, severe disaster shocks lead to long-term growth losses in highgrowth countries, despite their initial resilience. Conversely, low-growth countries experience immediate and persistent growth declines that worsen over time. Third, the role of macroeconomic variables in mitigating or amplifying growth losses varies depending on the growth regime, disaster severity, and time horizon.
Mots clés Natural disasters, Growth, Developing countries, Quantile-on-quantile
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Résumé I study how a significant increase in the compulsory schooling leaving age, from 15 to 18 years old, can contribute to reducing early school leaving and changing students’ educational paths. I analyse the Portuguese reform of 2009, exploiting the fact that grade retention in the 7th grade in this year provides quasi-experimental variation in exposure to the new policy. While effects for the overall student population are small or null, lower-achieving students significantly increase their schooling duration. Additionally, some sub-groups of lower-achieving students, particularly boys and those enrolling in upper-secondary school, increased their graduation probabilities. At the same time, I do not find that school quality decreased. These findings carry implications for research using compulsory schooling reforms as instruments for education, and inform policies aimed at supporting at-risk students.
Mots clés Grade retention, Differencein- differences, Early school leaving, School dropout, Compulsory schooling age
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Résumé Anxiety and depression may have serious disabling consequences for health, social, and occupational outcomes for people who are unaware of their actual health status and/or whose mental health symptoms remain undiagnosed by physicians. This article provides a big picture of unrecognised anxiety and depressive troubles revealed by a low score on the Mental Health Inventory-5 (MHI-5) with the help of machine learning methods using the 2012 French National Representative Health and Social Protection Survey (Enquête Santé et Protection Sociale, ESPS) matched with yearly healthcare consumption data from the French Sickness Fund. Compared to people with no latent symptoms who did not declare any depression over the last 12 months, those with unrecognised anxiety or depression were found to be older, more deprived, more socially disengaged, at a higher probability of adverse working conditions, and with higher healthcare expenditures backed, to some extent, by chronic conditions other than anxiety or mood disorder.
Mots clés Tree-based methods, SHAP values, Workplace outcomes, Healthcare consumption, Mental health inventory-5 MHI-5, Unrecognised mental disorders
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Résumé This paper uses French data to simultaneously estimate the impact of two types of connections on government subsidies allocated to municipalities. Investigating different types of connection in a same setting helps to distinguish between the different motivations that could drive pork-barreling. We differentiate between municipalities where ministers held office before their appointment to the government and those where they lived as children. Exploiting ministers' entries into and exits from the government, we show that municipalities where a minister was mayor receive 30% more investment subsidies when the politician they are linked to joins the government, and a similar size decrease when the minister departs. In contrast, we do not observe these outcomes for municipalities where ministers lived as children. These findings indicate that altruism towards childhood friends and family does not fuel pork-barreling, and suggest that altruism toward adulthood social relations or career concerns matter. We also present complementary evidence suggesting that observed pork-barreling is the result of soft influence of ministers, rather than of their formal control over the administration they lead.
Mots clés Personal connections, Political connections, Distributive politics, Local favouritism
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Résumé As large language models (LLMs) become integrated to decision-making across various sectors, a key question arises: do they exhibit an emergent "moral mind" -a consistent set of moral principles guiding their ethical judgments -and is this reasoning uniform or diverse across models? To investigate this, we presented about forty different models from the main providers with a large array of structured ethical scenarios, creating one of the largest datasets of its kind. Our rationality tests revealed that at least one model from each provider demonstrated behavior consistent with stable moral principles, effectively acting as approximately optimizing a utility function encoding ethical reasoning. We identified these utility functions and observed a notable clustering of models around neutral ethical stances. To investigate variability, we introduced a novel non-parametric permutation approach, revealing that the most rational models shared 59% to 76% of their ethical reasoning patterns. Despite this shared foundation, differences emerged: roughly half displayed greater moral adaptability, bridging diverse perspectives, while the remainder adhered to more rigid ethical structures.
Mots clés PSM, LLM, Artificial intelligence, Rationality, Revealed Preference, Decision Theory
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Résumé Background. Earlier detection of neurodegenerative diseases may help patients plan for their future, achieve a better quality of life, access clinical trials and possible future disease modifying treatments. Due to recent advances in artificial intelligence (AI), a significant help can come from the computational approaches targeting diagnosis and monitoring. Yet, detection tools are still underused. We aim to investigate the factors influencing individual valuation of AI-based prediction tools. Methods. We study individual valuation for early diagnosis tests for neurodegenerative diseases when Artificial Intelligence Diagnosis is an option. We conducted a Discrete Choice Experiment on a representative sample of the French adult public (N=1017), where we presented participants with a hypothetical risk of developing in the future a neurodegenerative disease. We ask them to repeatedly choose between two possible early diagnosis tests that differ in terms of (1) type of test (biological tests vs AI tests analyzing electronic health records); (2) identity of whom communicates tests’ results; (3) sensitivity; (4) specificity; and (5) price. We study the weight in the decision for each attribute and how socio-demographic characteristics influence them. Results. Our results are twofold: respondents indeed reveal a reduced utility value when AI testing is at stake (that is evaluated to 36.08 euros in average, IC = [22.13; 50.89]) and when results are communicated by a private company (95.15 €, IC = [82.01; 109.82]). Conclusion. We interpret these figures as the shadow price that the public attaches to medical data privacy. The general public is still reluctant to adopt AI screening on their health data, particularly when these screening tests are carried out on large sets of personal data.
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Résumé This paper studies dynamic contracts in illegal addictive markets where individuals' tastes for addictive goods develop through prolonged consumption and contract enforcement is limited. Our theoretical analysis uncovers the optimality of a 'freefirst-dose' strategy where sellers intensify buyers' addiction by offering consumption credit to newcomers. We show that buyers default a certain portion of the debts for early period consumption but are never imposed any penalty on the equilibrium path. This implies that illegal markets might favor non-violent interactions over violent ones, defying the stereotypical association of illegality with violence. Meanwhile, in illegal gambling markets, a distinct equilibrium phenomenon known as the long-shot bias emerges due to the influence of addiction, illustrating another complex dynamic within these markets. We discuss the implications of the model in the context of illegal sports wagering, narcotics, and religious sects.
Mots clés Addiction, Dynamic Contracts, Illegal Markets
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Résumé The modernisation theory of regime change is often perceived to be a murky paradigm, lacking theoretical or empirical foundations. In response, we clarify the links between education and regime change. More specifically, we propose that education contributes indirectly to the collapse of autocratic regimes because educated people engage in non-violent (civil) resistance that reduces the effectiveness of the security apparatus. We empirically test the validity of this ‘defanging effect’ of education. We indeed find that the combination of high autocracy and high education levels tends to trigger non-violent campaigns, which in turn increases the likelihood of a regime change, often associated with political liberalisation and, to a lesser degree, democratisation.
Mots clés Autocracy, Civil resistance, Democratisation, Education, Modernisation, Regime change
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Résumé When estimated from survey data alone, the distribution of high incomes in a population may be misrepresented, as surveys typically provide detailed coverage of the lower part of the income distribution, but offer limited information on top incomes. Tax data, in contrast, better capture top incomes, but lack contextual information. To combine these data sources, Pareto models are often used to represent the upper tail of the income distribution. In this paper, we propose a Bayesian approach for this purpose, building on extreme value theory. Our method integrates a Pareto II tail with a semi-parametric model for the central part of the income distribution, and it selects the income threshold separating them endogenously. We incorporate external tax data through an informative prior on the Pareto II coefficient to complement survey micro-data. We find that Bayesian inference can yield a wide range of threshold estimates, which are sensitive to how the central part of the distribution is modelled. Applying our methodology to the EU-SILC micro-data set for 2008 and 2018, we find that using tax-data information from WID introduces no changes to inequality estimates for Nordic countries or The Netherlands, which rely on administrative registers for income data. However, tax data significantly revise survey-based inequality estimates in new EU member states.
Mots clés Extreme value theory, EU-SILC, Bayesian inference, Pareto II, Top income correction
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Résumé In this paper, we present a critical raw materials index (CRMI) that represents the price dynamics of the raw materials required for the low-carbon transition. Using a unique market and trade dataset covering 29 critical raw materials from 2012 to 2023, we construct a weekly trade weighted price index following a robust methodological framework. The relevance of our index is demonstrated through a validation process including a plausibility analysis and a comparability analysis. In addition, a sensitivity analysis provides empirical evidence of the robustness of our index to alternative data treatment, weighting factors and weighting schemes. Our framework offers policymakers a useful price benchmark to track the underlying metal market dynamics required by the growing clean energy sectors.
Mots clés Critical Raw Materials Index CRMI, Energy Transition, Index Construction, Metal prices
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