Two-sided intergenerational moral hazard,long-term care insurance,and nursing home use

Two-sided intergenerational moral hazard occurs (i) if the parent’s decision to purchase long-term care (LTC) coverage undermines the child’s incentive to exert effort because the insurance protects the bequest from the cost of nursing home care, and (ii) when the parent purchases less LTC coverage, relying on child’s effort to keep him out of the nursing home. However, a “net” moral hazard effect obtains only if the two players’ responses to exogenous shocks fail to neutralize each other, entailing a negative relationship between child’s effort and parental LTC coverage. We focus on outcomes out of equilibrium, interpreting them as a break in the relationship resulting in no informal care provided and hence high probability nursing home admission. Changes in the parent’s initial wealth, LTC subsidy received, and child’s expected inheritance are shown to induce “net” moral hazard, in contradistinction to changes in child’s opportunity cost and share in the bequest.     

Assessing the pattern of covariance matrices via an augmentation multiple testing procedure

This paper extends the scedasticity comparison among several groups of observations, usually complying with the homoscedastic and the heteroscedastic cases, in order to deal with data sets laying in an intermediate situation. As is well known, homoscedasticity corresponds to equality in orientation, shape and size of the group scatters. Here our attention is focused on two weaker requirements: scatters with the same orientation, but with different shape and size, or scatters with the same shape and size but different orientation. We introduce a multiple testing procedure that takes into account each of the above conditions. This approach discloses a richer information on the data underlying structure than the classical method only based on homo/heteroscedasticity. At the same time, it allows a more parsimonious parametrization, whenever the patterned model is appropriate to describe the real data. The new inferential methodology is then applied to some well-known data sets, chosen in the multivariate literature, to show the real gain in using this more informative approach. Finally, a wide simulation study illustrates and compares the performance of the proposal using data sets with gradual departure from homoscedasticity.     

The Probability of Teenage Parenthood: Parental Predictions and Their Accuracy

Teenage parenthood is an often-discussed topic in family economics since it has been shown to affect many outcomes for the teen, child, and household. Using a nationally representative longitudinal panel of American teenagers and their parents, two questions related to the probability of teenage parenthood are examined. First, how do predictions of this occurrence made by the teenager’s parents vary across the population? Second, how does the accuracy of these predictions vary? The actual prevalence and variance of teenage parenthood are also examined, and the determinants of its occurrence are estimated. Among other results, expectations and their accuracy are found to differ substantially across socioeconomic status and some demographics such as race and religion. The average American parent underestimates the probability their child will become a teen parent by only a small amount, but within certain demographic groups this outcome is considerably underestimated, and in others it is overestimated. These differences help explain the variability in teen parenthood effects, and more broadly, the analysis serves as a test of parents’ ability to judge their childrens’ future outcomes.     

Ecohydrological model for the quantification of ecosystem services provided by urban street trees

Urban green spaces have been recognized as an important source of ecosystem services, whose quantification requires the determination of quantities related to energy, water, carbon and soil nutrient content. In this paper we propose a stochastic ecohydrological model that couples two existing models for water and nutrients in urban soil at the single street-tree scale. The model input are rainfall and irrigation, for water, and deposition and fertilization, for nitrogen, while the output are evapotranspiration, runoff and deep percolation, for water, and plant uptake and leaching, for nitrogen. The various terms are related to the amount of paved and impervious surfaces that surround the tree trunk and regulate the water and nutrient fluxes in and out the soil. Particular attention is paid to the effects of seasonal variations on plant water and nutrients through a temporal variation of the hydrologic variables (i.e., temperature and rainfall intensity and frequencies). The average model outputs are preliminarily compared with the scant existing literature data, supporting the model application to cities with different climatic conditions. The model results are used to estimate the potential for ecosystem services like tree cooling effects, soil carbon sequestration or storm-water management. Because of the minimal structure of the proposed model, it requires a very low amount of data, while accounting for the stochastic input of rainfall. In the context of climate change and increasing urbanization, the model may offer useful indications to urban planners to enhance ecosystem services while minimizing irrigation, fertilization and their related costs.     

Brown rats (<Emphasis Type="Italic">Rattus norvegicus</Emphasis>) in urban ecosystems: are the constraints related to fieldwork a limit to their study?

Nowadays, the majority of human beings live in urban ecosystems, with this proportion expected to continue increasing in the future. With the growing importance of urban rat-associated issues (e.g. damages to urban infrastructures, costs of rat-control programs, rat-associated health risks), it is becoming indispensable to fill the identified gaps in knowledge on the urban brown rat regarding, among others, its density, home range, genetic structure, and infectious status. In this context, live-trapping is a crucial prerequisite to any scientific investigation. This paper assesses the main constraints and challenges regarding the urban field and describes the major steps to be considered when planning research on urban rats. The primary challenges are i) the characterization of the urban experimental unit; ii) the choice of a trapping design: the use of live-trapping in capture-mark-recapture design, in association with modern statistics, is highly recommended to answer ecological questions (although these methods, mostly developed in natural ecosystems, need to be implemented for the urban field); iii) the potential ethical considerations with regard to animal welfare and field-worker safety; iv) the building of mutually-beneficial collaborations with city stakeholders, pest control professionals, and citizens. Emphasis must be put on communication to the public and education of field-workers. One major need of modern urban rat research is a peer-validated field methodology allowing reproducibility, repeatability, and inference from urban field studies and enabling researchers to answer long-standing key questions about urban rat ecology.     

Tests of symmetry with one-sided alternatives in three-way contingency tables

For a two-dimensional contingency table of probabilities, the concept of symmetry around the main diagonal is well defined. Statistical hypothesis test of symmetry versus positive bias have also been explored. For tables of higher (three or more) dimensions, however, different concepts of symmetry are available. In this study, we consider statistical inference procedures of symmetry in partial tables versus various biases in three-dimensional tables. We find the maximum likelihood estimates of the cell probabilities and the asymptotic distribution of the likelihood ratio test statistic in each case. Simulation studies are used to investigate the sizes and powers of the tests. The methodologies developed are applied on real data sets.     

Diffusive nested sampling

We introduce a general Monte Carlo method based on Nested Sampling (NS), for sampling complex probability distributions and estimating the normalising constant. The method uses one or more particles, which explore a mixture of nested probability distributions, each successive distribution occupying ∼e ⁻¹ times the enclosed prior mass of the previous distribution. While NS technically requires independent generation of particles, Markov Chain Monte Carlo (MCMC) exploration fits naturally into this technique. We illustrate the new method on a test problem and find that it can achieve four times the accuracy of classic MCMC-based Nested Sampling, for the same computational effort; equivalent to a factor of 16 speedup. An additional benefit is that more samples and a more accurate evidence value can be obtained simply by continuing the run for longer, as in standard MCMC.     

Beliefs about overconfidence

This experiment elicits beliefs about other people’s overconfidence and abilities. We find that most people believe that others are unbiased, and only few think that others are overconfident. There is a remarkable heterogeneity between these groups. Those people who think others are underconfident or unbiased are overconfident themselves. Those who think others are overconfident are underconfident themselves. Despite this heterogeneity, people overestimate on average the abilities of others as they do their own ability. One driving force behind this result is the refusal to process information about oneself: not only does this lead to overestimation of one’s own ability, but by means of social projection also to overestimation of others’ abilities.     

Female Migration and Child Occupation in Rural El Salvador

This article looks at the consequences of migration in terms of child education and child labor using a unique rural panel dataset for El Salvador. Results suggest gender differences in the consequences of migration on child activities that remain in El Salvador. While female migration tends to reduce child labor, both in domestic and non-domestic activities, male migration seems to stimulate it, in particular in terms of domestic labor. In contrast, while male migration has null or slightly positive impact in terms of school enrollment rates, female migration apparently reduces the likelihood that a particular child stays at school. Some of these results differ according to the gender of the child. The results do not seem to be driven by female migrants remitting more than males, but rather to alternative competing explanations, such as the existence of child–adult male labor substitution, differences in the use of remittances by gender of the recipient person, or limited ability to monitor funds when remitted by female migrants.