USING MARKOV-CHAINS TO MODEL HUMAN MIGRATION IN A NETWORK EQUILIBRIUM FRAMEWORK

In this paper, we develop a multistage network equilibrium model of human migration. The model provides a general framework for describing the dynamics of populations, and takes advantage of the special network structure of the problem. Unlike earlier network equilibrium models of migration, the model allows for chain migration in that humans can move from location to location in a ''chaining'' fashion, which is more realistic from an application perspective, than simply allowing for migration from a given origin to a direct destination in a single step. For the purpose of modeling and analysis, we utilize finite state nonhomogeneous Markov chains to handle the migration. A stable population distribution is then shown to exist under certain assumptions.