Collective Models of Labor Supply with Nonconvex Budget Sets and Nonparticipation: A Calibration Approach

We suggest a methodology to calibrate a collective model with household-specific bargaining rules and marriage-specific preferences that incorporate leisure externalities. The empirical identification relies on the assumption that some aspects of individual preferences remain the same after marriage, so that estimation on single individuals can be used. The procedure maps the complete Pareto frontier of each household in the dataset and we define alternative measures of a power index. The latter is then regressed on relevant bargaining factors, including a set of variables retracing the potential relative contributions of the spouses to household disposable income. In its capacity to handle complex budget sets and labor force participation decisions of both spouses, this framework allows the comparison of unitary and collective predictions of labor supply reactions and welfare changes entailed by fiscal reforms in a realistic setting (see Michal Myck et al., 2006; Denis Beninger et al., 2006).

All agreed: Aumann meets DeGroot

We represent consensus formation processes based on iterated opinion pooling (DeGroot in J Am Stat Assoc 69:118–121, 1974; Lehrer and Wagner in Rational consensus in science and society: a philosophical and mathematical study. Springer, Berlin, 1981) as a dynamic approach to common knowledge of posteriors (Aumann in Ann Stat 4(6):1236–1239, 1976; Geanakoplos and Polemarchakis in J Econ Theory 28:192–200, 1982). We thus provide a concrete and plausible Bayesian rationalization of consensus through iterated pooling. The link clarifies the conditions under which iterated pooling can be rationalized from a Bayesian perspective, and offers an understanding of iterated pooling in terms of higher-order beliefs.     

Semiparametric inference for the recurrent events process by means of a single-index model

In this paper, we introduce new parametric and semiparametric regression techniques for a recurrent event process subject to random right censoring. We develop models for the cumulative mean function and provide asymptotically normal estimators. Our semiparametric model which relies on a single-index assumption can be seen as a dimension reduction technique that, contrary to a fully nonparametric approach, is not stroke by the curse of dimensionality when the number of covariates is high. We discuss data-driven techniques to choose the parameters involved in the estimation procedures and provide a simulation study to support our theoretical results.     

The role of mutuals and community-based insurance in social health protection systems: International experience on delegated functions

The institutional architecture for the provision of social health protection varies across countries, as do the actors and organizations involved. In some countries, mutual benefit societies and community-based health insurance organizations (CBHI) play a role in this area. In the 1990s, these were promoted particularly as a means of extending social security coverage, especially in sub-Saharan Africa. In the current context, the adoption of the 2030 Agenda for sustainable development, as well as renewed political will to realize universal coverage, has led to a questioning of the role of mutuals/CBHI. However, the literature on the roles they play in national social security systems remains limited. For this scoping review, 49 documents were analysed, covering 18 countries worldwide, focused on the delegation of functions to mutuals/CBHI in national social health protection systems. The results reveal the dynamics of the delegation of functions within social protection systems over time and their implementation processes. These provide areas for reflection that can inform policy processes.     

Welfare analysis and redistributive policies

Applied welfare analyses of redistributive systems nowadays benefit from powerful tax-benefit microsimulation programs combined with administrative data. Arguably, most of the distributional studies of that kind focus on social welfare defined as a function – typically inequality or poverty indices – of household equivalized income. In parallel, economic research has made considerable progress in the measurement of welfare along several dimensions. Distinct but related branches of the literature have attempted (i) to model different behavior (in a way that matter for incidence and redistribution of tax-benefit policies), (ii) to go beyond income, (iii) to better define and estimate equivalence scales, (iv) to open the household black box and measure welfare at the individual level. I suggest a general framework to critically review these streams of literatures and to discuss whether recent advances in each of these fields have been or could be readily operationalized in welfare analyses and policy simulations.     

Comprehensive maternity support and shared care in Switzerland: Comparison of levels of satisfaction

Background

According to the woman-centred care model, continuous care by a midwife has a positive impact on satisfaction. Comprehensive support is a model of team midwifery care implemented in the large Geneva University Hospitals in Switzerland, which has organised shared care according to the biomedical model of practice. This model of care insures a follow up by a specific group of midwives, during perinatal period.

Non‐parametric Copula Estimation Under Bivariate Censoring

In this paper, we consider non‐parametric copula inference under bivariate censoring. Based on an estimator of the joint cumulative distribution function, we define a discrete and two smooth estimators of the copula. The construction that we propose is valid for a large range of estimators of the distribution function and therefore for a large range of bivariate censoring frameworks. Under some conditions on the tails of the distributions, the weak convergence of the corresponding copula processes is obtained in l^∞([0,1]²). We derive the uniform convergence rates of the copula density estimators deduced from our smooth copula estimators. Investigation of the practical behaviour of these estimators is performed through a simulation study and two real data applications, corresponding to different censoring settings. We use our non‐parametric estimators to define a goodness‐of‐fit procedure for parametric copula models. A new bootstrap scheme is proposed to compute the critical values.