Publications
We surveyed economists’ attitudes toward adjusting discount rates to the risk profile of public programs. Three-quarters of respondents recommend to use project-specific discount rates. For example, on average, respondents discount railway infrastructures more than hospitals and climate mitigation. But the degree of discount discrimination between distinct risk profiles of different projects is fairly limited in our sample given the differences in risk profiles for these projects. Economic experts thus penalize risky public projects far less than financial markets penalize private investments. We call this the ”discount premium puzzle”. Finally, among experts in favor of a single discount rate, there is no consensus on whether it should be based on the average cost of capital in the economy, the sovereign borrowing cost, or the Ramsey rule, which gives rise to disagreement over the level of the recommended discount rate.
We revisit the question of colonial legacies in education by focusing on quality rather than quantity. We study Cameroon, a country where a Francophone education system with French colonial origins coexists with an Anglophone system with British colonial origins. This allows us to investigate the impact of different teaching practices on students’ test scores. We find that pupils schooled in the Francophone system perform better in mathematics in Grade 5, with test scores higher by two thirds of a standard deviation. Thanks to detailed school survey data, we are able to account for a wide array of inputs of the education production function, such as the economic and social conditions of students, the material conditions of the schools and classrooms, as well as some information on the teachers’ practices and pedagogical culture. We find that Francophone schools have better classroom equipment and that Francophone teachers use more vertical teaching methods, but that these differences cannot explain why Francophone students perform better in mathematics. In the end, we cannot pin down the exact mechanism behind our result.
With the low adherence to voluntary mutual health insurance, Senegal’s policymakers have sought to understand the feasibility of compulsory health insurance membership. This study aims to measure the acceptability of mandatory membership in community-based mutual health insurance (CBHI) and to understand its possible administrative modalities. The study consists of a national survey among a representative population sample selected by marginal quotas. The survey was conducted in 2022 over the phone, with a random composition method involving 914 people. The questionnaire measured the socio-economic characteristics of households, their level of acceptability concerning voluntary and compulsory membership, and their level of confidence in CBHIs and the health system. Respondents preferred voluntary (86%) over mandatory (70%) membership of a CBHI. The gap between voluntary and compulsory membership scores was smaller among women (p = 0.040), people under 35 (p = 0.033), and people with no health coverage (p = 0.011). Voluntary or compulsory membership was correlated (p = 0.000) to trust in current CBHIs and health systems. Lack of trust in the CBHI management has been more disadvantageous for acceptance of the mandatory than the voluntary membership. No particular preference emerged as the preferred administrative channel (e.g. death certificate, identity card, etc.) to enforce the mandatory option. The results confirmed the well-known challenges of building universal health coverage based on CBHIs—a poorly appreciated model whose low performance reduces the acceptability of populations to adhere to it, whether voluntary or mandatory. Suppose Senegal persists in its health insurance approach. In that case, it will be essential to strengthen the performance and funding of CBHIs, and to gain population trust to enable a mandatory or more systemic membership.
Under triopoly and Cournot competition, we study an infinite horizon Markov perfect equilibrium merger game in which in each period one of the firms (“the Buyer”) selects a bid price and then the two sellers accept or reject this offer with some probability. The possibility of a “war of attrition” equilibrium in which the seller who outlasts the other is then able to sell in the following period at a greater price, is a distinct feature of the model. Delayed monopolization is all the more likely when the discount factor is small and the ratio duopoly/ triopoly profits is important. Two other equilibria are shown to be possible: an unmerged and an immediate monopolization equilibrium. Each equilibrium is shown to correspond to a different set of parameter values. The two special cases of linear and constant price elastic demand functions are fully characterized.
How does the mother’s labour supply affect the household’s demand for childcare? And thus are formal and informal childcare substitutable? In this paper, we address these two questions using micro-data for 14 European countries observed over the period between 2010 and 2017. Relying on a Control Function Approach to account for the endogeneity between childcare and the mothers’ labour supply, we identify different factors affecting the demand for formal and informal childcare. The results show that the mother’s labour supply is a key element in understanding the demand for childcare and suggest that the more the mother participates in the labour market, the higher the household’s demand for childcare services. Moreover, our results support the substitutability hypothesis between formal and informal childcare. Policymakers aiming to promote mothers’ employment should increase the availability of formal childcare services, as this will increase labour supply by mothers and reduce the use of informal care arrangements.
The sustainability of resource use and the management of public finances are both long-run issues that are linked to each other through savings decisions. To study them conjointly, this paper introduces a public debt stabilization constraint in an overlapping generation model in which nonrenewable resources constitute a necessary input in the production function and belong to agents. It shows that stabilization of public debt at a high level (as share of capital) may prevent the existence of a sustainable development path, that is, a path on which per capita consumption is not decreasing. Public debt thus appears as a threat to sustainable development. It also shows that higher public debt-to-capital ratios (and public expenditures-to-capital ones) are associated with lower growth. Two transmission channels are identified. As usual, public debt crowds out capital accumulation. In addition, public debt tends to increase resource use which reduces the rate of growth. We also provide a numerical analysis of the dynamics that shows that the economy is characterized by saddle path stability. Finally, we show that the public debt-to-capital ratio may be calibrated to implement the social planner optimal allocation according to which the growth rate is increasing in the degree of patience.
Sans résumé.
Two recent contributions have found conditions for large dimensional networks or systems to generate long memory in their individual components. We build on these and provide a multivariate methodology for modeling and forecasting series displaying long range dependence. We model long memory properties within a vector autoregressive system of order 1 and consider Bayesian estimation or ridge regression. For these, we derive a theory-driven parametric setting that informs a prior distribution or a shrinkage target. Our proposal significantly outperforms univariate time series long-memory models when forecasting a daily volatility measure for 250 U.S. company stocks over twelve years. This provides an empirical validation of the theoretical results showing long memory can be sourced to marginalization within a large dimensional system.
In France, the national health insurance (NHI) covers the majority of health expenses, the rest being more or less covered by the complementary health insurance (CHI). But do insured persons really know their CHI contract? This empirical work explores administrative data matched with survey data providing information on usually unobserved characteristics (health status or risk aversion). First, we identify the factors that influence policyholders’ knowledge of their contract, then we analyze the gap between reimbursements and contributions using quantile regressions. Paradoxically, this gap does not seem to be widened by the consumption of so-called “comfort” care but rather by hospital care. Moreover, a better knowledge of one’s contract seems to be beneficial.
In the Design of Experiments, we seek to relate response variables to explanatory factors. Response Surface methodology (RSM) approximates the relation between output variables and a polynomial transform of the explanatory variables using a linear model. Some researchers have tried to adjust other types of models, mainly nonlinear and nonparametric. We present a large panel of Machine Learning approaches that may be good alternatives to the classical RSM approximation. The state of the art of such approaches is given, including classification and regression trees, ensemble methods, support vector machines, neural networks and also direct multi-output approaches. We survey the subject and illustrate the use of ten such approaches using simulations and a real use case. In our simulations, the underlying model is linear in the explanatory factors for one response and nonlinear for the others. We focus on the advantages and disadvantages of the different approaches and show how their hyperparameters may be tuned. Our simulations show that even when the underlying relation between the response and the explanatory variables is linear, the RSM approach is outperformed by the direct neural network multivariate model, for any sample size (<50) and much more for very small samples (15 or 20). When the underlying relation is nonlinear, the RSM approach is outperformed by most of the machine learning approaches for small samples (n ≤ 30).
