Immigrant Selection in the OECD

The selection of immigrants by skill and education is a central issue in the analysis of immigration. Since highly educated immigrants tend to be more successful in host country labour markets and less of a fiscal cost it is important to know what determines the skill-selectivity of immigration. In this paper we examine the proportions of highly educated among migrants from around 80 source countries who were observed as immigrants in each of 29 OECD countries in 2000/1. We develop a variant of the Roy model to estimate the determinants of educational selectivity by source and destination country. We also estimate the determinants of the share of migrants from different source countries in each destination country’s immigrant stock. Two key findings emerge. One is that the effects of the skill premium, which is at the core of the Roy model, can be observed only after we take account of poverty constraints operating in source countries. The other is that cultural links and distance are often more important determinants of the proportion of high educated immigrants in different OECD countries than wage incentives or policy.immigration, migrant selection, migrant skills

Welfare Effects of Employment Protection

Employment protection is often related to costs incurred by the firms when they hire a worker.The stability of the employment relationship, enhanced by employment protection, is also favorable to the productivity of the job.We analyze employment protection focusing on this trade-off between adjustment costs and productivity.We show that from a welfare point of view there is an optimal degree of employment protection. Series: CentER Discussion Paperemployment policy;human capital;welfare

An overall strategy based on regression models to estimate relative survival and model the effects of prognostic factors in cancer survival studies.

Relative survival provides a measure of the proportion of patients dying from the disease under study without requiring the knowledge of the cause of death. We propose an overall strategy based on regression models to estimate the relative survival and model the effects of potential prognostic factors. The baseline hazard was modelled until 10 years follow-up using parametric continuous functions. Six models including cubic regression splines were considered and the Akaike Information Criterion was used to select the final model. This approach yielded smooth and reliable estimates of mortality hazard and allowed us to deal with sparse data taking into account all the available information. Splines were also used to model simultaneously non-linear effects of continuous covariates and time-dependent hazard ratios. This led to a graphical representation of the hazard ratio that can be useful for clinical interpretation. Estimates of these models were obtained by likelihood maximization. We showed that these estimates could be also obtained using standard algorithms for Poisson regression

Incentives and Childrens's Dietary Choices: A Field Experiment in Primary Schools

We conduct a field experiment in 31 primary schools in England to test the effectiveness of different temporary incentive schemes, a standard individual based incentive scheme and a competitive scheme, on increasing the choice and consumption of healthy items at lunchtime. The individual scheme has a weak positive effect that masks significantly differential effects by age whereas all students respond positively to the competitive scheme.For our sample of interest, the competivie scheme increases choice of healthy items by 33% and consumption of healthy items by 48%, twice and three times as much as ain the individual incentive scheme, respectively. The positive effects generally carry over to the week immediately following the treatment but we find little evidence of any effects six months later. Our results show that incentives can work, at least temporarily, to increase healthy eating but that there are large differences in effectiveness between schemes. Furthermore it is important to analyse things at the individual level as average effects appear to be masking significant heterogeneous effects that are predicted by the health literature

Individual frailty excess hazard models in cancer epidemiology

Unobserved individual heterogeneity is a common challenge in population cancer survival studies. This heterogeneity is usually associated with the combination of model misspecification and the failure to record truly relevant variables. We investigate the effects of unobserved individual heterogeneity in the context of excess hazard models, one of the main tools in cancer epidemiology. We propose an individual excess hazard frailty model to account for individual heterogeneity. This represents an extension of frailty modeling to the relative survival framework. In order to facilitate the inference on the parameters of the proposed model, we select frailty distributions which produce closed-form expressions of the marginal hazard and survival functions. The resulting model allows for an intuitive interpretation, in which the frailties induce a selection of the healthier individuals among survivors. We model the excess hazard using a flexible parametric model with a general hazard structure which facilitates the inclusion of time-dependent effects. We illustrate the performance of the proposed methodology through a simulation study. We present a real-data example using data from lung cancer patients diagnosed in England, and discuss the impact of not accounting for unobserved heterogeneity on the estimation of net survival. The methodology is implemented in the R package IFNS