Durcissement des lois sociales et santé des migrants forcés: trois ans après (a Loi sur l'asile (LAsi) [Social policy hardening and forced immigrant's health: 3 years after the Asylum Law (LAsi)'s introduction].

In the canton de Vaud, General Practioners (GPs) caring for asylum seekers under the "aide d'urgence" regime can ask for an adaptation of their housing conditions, by filling out a specific form and addressing it to the medical commission responsible for advising the EVAM (the housing institution for asylum seekers) on these issues. The forms addressed to the commission are indicative of a worrisome state of health in this population, especially for mental health. More than 70% report at least one psychiatric diagnosis. Most frequent are anxiety and depressive disorders, as well as many posttraumatic stress disorders, associated with traumatic events both in the country of origin and in Switzerland. Adapting the housing conditions, based on vulnerabilities that the GP has specifically documented, may contribute to improve the health of the most vulnerable asylum seekers.

Nonclassical measurement error with applications to labor and development issues

Zero correlation between measurement error and model error has been assumed in existing panel data models dealing specifically with measurement error. We extend this literature and propose a simple model where one regressor is mismeasured, allowing the measurement error to correlate with model error. Zero correlation between measurement error and model error is a special case in our model where correlated measurement error equals zero. We ask two research questions. First, we wonder if the correlated measurement error can be identified in the context of panel data. Second, we wonder if classical instrumental variables in panel data need to be adjusted when correlation between measurement error and model error cannot be ignored. Under some regularity conditions the answer is yes to both questions. We then propose a two-step estimation corresponding to the two questions. The first step estimates correlated measurement error from a reverse regression; and the second step estimates usual coefficients of interest using adjusted instruments.