Predicting Migration System Dynamics with Conditional and Posterior Probabilities
Traditional models of migration assume that migrants move to places of greatest economic incentive, and are more likely to move when current economic conditions ‘push’ migrants from their origin. Although prospective income at a destination has been a major determining factor for migration in preexisting migration models, and distance between origin and destination is also a major consideration, we take a new approach with a model that reflects migration ‘chaining’, where migrants to a city B send information back to their origin city A, and interest other members of A to migrate to B. We isolate the social factors of place-pair synergies through components from Bayes’ Law: conditional probability and posterior probability of unique origin/destination migrant volume, and a system-wide probability of unique O/D transfer. These allow us to model social space as well as physical space, rather than physical space alone. We test these variables’ power for predicting future migration against four other predictive models: the traditional gravity model, transit data, airline and trip data, and linear trends. We use a case study of U.S. Migration flows in a system of major cities, given annual data from 1996-2004 to predict city-to-city flows annually for 2005-2008, and find that conditional and posterior probabilities outperform system-wide probabilities, gravity, transit and linear forecast models. These probabilities also exhibit a surprising level of steady-state stationarity, and therefore are a promising avenue for more accurately modelling future migration flows.
Migration Probability Flows System Dynamics BayesLaw United States
Clio Andris Samuel Halverson Frank Hardisty
Department of Urban Studies and Planning,Massachusetts Institute of Technology 77 Massachusetts Ave. Department of Astronomy and Astrophysics, The Pennsylvania State University 525 Davey Lab, Universit Department of Geography, The Pennsylvania State University 210 Walker Building,University Park, PA 1
国际会议
福州
英文
192-197
2011-06-29（万方平台首次上网日期，不代表论文的发表时间）