Andrea Aparicio-Castro , University of Manchester
Arkadiusz Wisniowski, University of Manchester
Francisco Rowe, University of Liverpool
Mark Brown, University of Manchester
Migration is the most complex demographic event to estimate. It is that difficult that not even the UN provides (probabilistic) estimates regarding migration flows as they do so for fertility and mortality. The difficulty of providing migration flow estimates comes from the fact that the available data are usually incomplete and incomparable. These issues in data are sharper in regions such as South America, in which the data are much more sparse than in Europe or North America, and the data are potentially of lower quality. In order to overcome the difficulties with South American data, this paper aims to develop a statistical model for estimating bilateral migration flows amongst South American countries through integrating different types of data. In particular, the various types of administrative data extracted from South American migration offices. Each kind of data differs not only in how they define migrants and their population coverage, but also in their systematic bias, accuracy and measurement methods. In order to overcome the inadequacies of South America data, this study generalises the Raymer et.al.’s model (2013), which enables the combination of data through a measurement model that corrects for those inconsistencies. The resulting outcome will be a set of synthetic annual estimates of migration flows with measures of uncertainty for South American countries from 1990 to 2017. Further contribution is the extension of Raymer et. al. (2013) and Wisniowski et. al. (2016) models, which have been developed for other regions with more abundant data.
Presented in Session P3. Poster Session Migration, Economics, Environment, Methods, History and Policy