New techniques for estimating migration

Household characteristics such as age, size, occupation, socio-economic status, etc. play vital role in deciding the movement of adult members. A study of movement process at the household level is useful for the prediction of future size of the households as well as to study the imbalances in sex-ratio occurred due to such migration. Motivated by the fact that the data related to migration is influenced by the number of the adult members present in household, under certain assumptions some probability models (inflated binomial and beta binomial distributions) have been proposed to describe the migration pattern and it has been applied to the observed distribution of adult migrants from the households among fixed number of adult members present in household. Data have been taken from a survey conducted in the most flooded area of Bihar, India in 2010. Findings reveal that proposed model explains satisfactorily the pattern of rural out migration of Adults from the household. Also we have observed that the risk of migration is increasing with increasing number of adult member in the household.

Abstract.
Many researchers and organisations pursue disparate approaches to document the environmentally displaced persons (EDPs). Such approaches do not adequately match the predictions and estimations of EDPs that climate change would trigger in the future. This letter proposes a model dubbed Conceptual Model for Environmentally Displaced Persons Information Systems (CoMEDiPIS) to complement global agenda for solution-oriented research and policy. The CoMEDiPIS is designed to complement the existing science and policy responses to the EDPs. It stresses bridge building between international and local relief and disaster management agencies through a participatory approach. The model’s approach emphasises sharing of data using social media and online GIS for better policy and response.

Keywords: displacement, EDPs, climate change, conceptual model

In this paper, we explore the application of the Lee-Carter type models to forecast migration. The Lee-Carter model and its variants are considered to be a flexible approach to modelling age-specific mortality and fertility. However, its usefulness for forecasting migration is unknown. For application, we forecast age-specific immigration counts and emigration rates for the United Kingdom. To overcome irregularities exhibited in the sample-based migration data, we include smoothing in the model. Various specifications are presented to show the differences in predicted levels and measures of uncertainty.