Publications

Abstract We provide the first analysis of the risk-sharing implications of altruism networks. Agents are embedded in a fixed network and care about each other. We explore whether altruistic transfers help smooth consumption and how this depends on the shape of the network. We find that altruism networks have a first-order impact on risk. Altruistic transfers generate efficient insurance when the network of perfect altruistic ties is strongly connected. We uncover two specific empirical implications of altruism networks. First, bridges can generate good overall risk sharing, and, more generally, the quality of informal insurance depends on the average path length of the network. Second, large shocks are well-insured by connected altruism networks. By contrast, large shocks tend to be badly insured in models of informal insurance with frictions. We characterize what happens for shocks that leave the structure of giving relationships unchanged. We further explore the relationship between consumption variance and centrality, correlation in consumption streams across agents, and the impact of adding links.
Keywords Informal Insurance, Risk sharing, Networks, Altruism
Publication HAL Google Scholar
Abstract La mondialisation est-elle responsable des pandémies ? En ce cas, faut-il en défaire les fils tissés depuis plusieurs siècles ? Depuis toujours, les routes commerciales ont coïncidé avec l’apparition, la disparition et la réémergence des nouveaux virus. Ce livre explique pourquoi les évolutions de la mondialisation ont renforcé ces liens : la déforestation, l’agriculture intensive, la perturbation des cycles géologiques et géophysiques, le réchauffement climatique, ainsi que les atteintes à la biodiversité, animale et végétale, ont accru les risques sanitaires. Ce livre propose de repenser la mondialisation en inventant des mécanismes de résilience face aux crises épidémiques. Loin des solutions simplistes, ses auteurs lèvent le voile sur la complexité des enjeux que soulève l’articulation des objectifs sanitaires avec les règles du commerce international. Avec une conviction : pour faire face aux risques épidémiques du XXIe siècle, il sera nécessaire de privilégier une approche associant mondialisation, environnement et santé.
Keywords Déforestation, Déglobalisation, Globalisation, Pandémie, Surdensité humaine, Zoonose
HAL Google Scholar
Abstract Corruption is a barrier to entrepreneurship in emerging countries, justifying to investigate its determinants. Using data on 1,250 entrepreneurs across Indonesian regions, We analyze the effects of social capital on individual corruption. 2-levels ordered probit regressions evidence that weak-ties discourage entrepreneurs’ bribing, strong-ties encourage it, whereas this latter effect is moderated by the quality of access to formal credit. Bribing banks or turning to relatives for external funding are alternative solutions for entrepreneurs facing a poor access to formal credit, a common feature in emerging countries, and the second solution is preferred given the risk and psychological costs of corruption.
Keywords Indonesia, Social capital, Indonesia, Entrepreneurship, Credit access, Corruption, Entrepreneurship, Corruption, Social capital, Credit access, Indonesia, Entrepreneurship
Publication HAL Google Scholar
Abstract The paper models evolution in pecunia—in the realm of finance. Financial markets are explored as evolving biological systems. Diverse investment strategies compete for the market capital invested in long-lived dividend-paying assets. Some strategies survive and some become extinct. The basis of our paper is that dividends are not exogenous but increase with the wealth invested in an asset, as is the case in a production economy. This might create a positive feedback loop in which more investment in some asset leads to higher dividends which in turn lead to higher investments. Nevertheless, we are able to identify a unique evolutionary stable investment strategy. The problem is studied in a framework combining stochastic dynamics and evolutionary game theory. The model proposed employs only objectively observable market data, in contrast with traditional settings relying upon unobservable investors’ characteristics (utilities and beliefs). Our method is analytical and based on mathematical reasoning. A numerical illustration of the main result is provided.
Keywords Local stability, Stochastic dynamics, Survival, Evolutionarily stable investment strategies, Evolutionary finance
Publication HAL Google Scholar
Abstract This paper examines how the degree of gender-egalitarianism embedded in inheritance rules impacts state capacity at its early stages during medieval times. We present a theoretical model in which building state capacity enables nobles to raise taxes and overcome rivals. The model addresses the use of inheritance to consolidate landholding dynasties, also accommodating interstate marriages between landed heirs. On the one hand, dynastic continuity—of utmost importance to medieval lords—directly encourages state-building. Male-biased inheritance rules historically maximize the likelihood of dynastic continuity. We weigh this effect against the indirect impact of the more frequent land-merging marriages under gender-egalitarian rules. Contrary to the literature, our results suggest that gender-egalitarian norms—offering a low probability of dynastic continuity—promote state capacity in the short run more than gender-biased norms. In the long run, results are reversed, providing a rationale for the pervasive European tradition of preference for men as heirs.
Keywords Primogeniture, State capacity, Inheritance, Gender equality, Marriage
Publication HAL Google Scholar
Abstract An acceleration index is proposed as a novel indicator to track the dynamics of COVID-19 in real-time. Using data on cases and tests in France for the period between the first and second lock-downs-May 13 to October 25, 2020-our acceleration index shows that the pandemic resurgence can be dated to begin around July 7. It uncovers that the pandemic acceleration was stronger than national average for the [59-68] and especially the 69 and older age groups since early September, the latter being associated with the strongest acceleration index, as of October 25. In contrast, acceleration among the [19-28] age group was the lowest and is about half that of the [69-78]. In addition, we propose an algorithm to allocate tests among French "dé partements" (roughly counties), based on both the acceleration index and the feedback effect of testing. Our acceleration-based allocation differs from the actual distribution over French territories, which is population-based. We argue that both our acceleration index and our allocation algorithm are useful tools to guide public health policies as France might possibly enter a third lock-down period with indeterminate duration.
Keywords France, Sub-national allocation of tests, Real-time Analysis, Acceleration Index, Indicator of epidemic dynamics, COVID-19
Publication HAL Google Scholar
Abstract This paper estimates trade barriers in government procurement, a market that accounts for 12% of world GDP. Using data from inter-country input-output tables in a gravity model, we find that home bias in government procurement is significantly higher than in trade between firms. However, this difference has been shrinking over time. Results also show that trade agreements with provisions on government procurement increase cross-border flows of services, whereas the effect on goods is small and not different from that in private markets. Provisions containing transparency and procedural requirements drive the liberalizing effect of trade agreements.
Keywords Government procurement, Trade agreements, Gravity equation
HAL Google Scholar
Abstract Workers' propensity to migrate to another local labor market varies a lot by occupation. We use the model developed by Schmutz and Sidibé (2019) to quantify the impact of mobility costs and search frictions on this mobility gap. We estimate the model on a matched employer-employee panel dataset describing labor market transitions within and between the 30 largest French cities for two groups at both ends of the occupational spectrum and find that: (i) mobility costs are very comparable in the two groups, so they are three times higher for blue-collar workers relative to their respective expected income; (ii) Depending on employment status, spatial frictions are between 2 and 3 times higher for blue-collar workers; (iii) Moving subsidies have little (and possibly negative) impact on the mobility gap, contrary to policies targeting spatial frictions; (iv) Mobility-enhancing policies have almost no impact on the unemployment gap.
Keywords Occupation, Local labor markets, Migration, Spatial frictions, Mobility costs
Publication HAL Google Scholar
Abstract Background: In high-dimensional data analysis, the complexity of predictive models can be reduced by selecting the most relevant features, which is crucial to reduce data noise and increase model accuracy and interpretability. Thus, in the field of clinical decision making, only the most relevant features from a set of medical descriptors should be considered when determining whether a patient is healthy or not. This statistical approach known as feature selection can be performed through regression or classification, in a supervised or unsupervised manner. Several feature selection approaches using different mathematical concepts have been described in the literature. In the field of classification, a new approach has recently been proposed that uses the γ-metric, an index measuring separability between different classes in heart rhythm characterization. The present study proposes a filter approach for feature selection in classification using this γ-metric, and evaluates its application to automatic atrial fibrillation detection. Methods: The stability and prediction performance of the γ-metric feature selection approach was evaluated using the support vector machine model on two heart rhythm datasets, one extracted from the PhysioNet database and the other from the database of Marseille University Hospital Center, France (Timone Hospital). Both datasets contained electrocardiogram recordings grouped into two classes: normal sinus rhythm and atrial fibrillation. The performance of this feature selection approach was compared to that of three other approaches, with the first two based on the Random Forest technique and the other on receiver operating characteristic curve analysis. Results: The γ-metric approach showed satisfactory results, especially for models with a smaller number of features. For the training dataset, all prediction indicators were higher for our approach (accuracy greater than 99% for models with 5 to 17 features), as was stability (greater than 0.925 regardless of the number of features included in the model). For the validation dataset, the features selected with the y-metric approach differed from those selected with the other approaches; sensitivity was higher for our approach, but other indicators were similar. Conclusion: This filter approach for feature selection in classification opens up new methodological avenues for atrial fibrillation detection using short electrocardiogram recordings.
Keywords Y-metric, Atrial fibrillation detection, Classification, Clinical decision making, Feature selection, Machine learning, Γ-metric, Machine learning, Feature selection, Classification, Clinical decision making, Atrial fibrillation detection
Publication HAL Google Scholar