Markovian Migrational Models a Dynamics of Repeat Migration: A Markov Chain Analysis and Application

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Author(s) M. Roungu Ahmmad | Md. Sanwar Hossain | Md. Matair Rahman | Azizur Rahman
Pages 285-290
Volume 2
Issue 4
Date April, 2013
Keywords Markov Model, Transition Probabilities, MMM
Abstract

We develop a systematic approach to Markovian Model onto an effective displaced diffusion (Migration), and work out a set of computationally efficient formulas valid for a large class of Markovian underlying processes. While the literature has established that there is substantial and highly selective return migration, the growing importance of repeat migration has been largely ignored. Using Markov chain analysis, this paper provides a modeling framework for moves of migrants between the host and home place. The Markov transition matrix between the states in two consecutive periods is parameterized. Using a variant of maximum likelihood estimation technique, this paper utilizes data to provide estimates of transition probability matrices. The probability of rural to rural migration (0 →0) is the lowest (0.2583) whereas the probability of making from urban to urban migration (1 →1) is the highest (0.8499). The rural to urban migration (0.7417) is greater than the urban to rural migration (0.1898). Again we fit the Markovian Migration Model (MMM) to find the effect of the explanatory variable which is influenced to migration. Simulations with our estimated models have shown that while the probability to return home remains low as time passes. Our results point to the fact that repeat migrants are indeed labor migrants, who go to home to work and earn money, and that there is no evidence that they finally attempt to return to the home place.

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