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A Markov Chain Model for Population Distribution Prediction Considering Spatio-Temporal Characteristics by Migration Factors
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이동요인별 시·공간적 인구이동 특성을 고려한 인구분포 예측: 마르코프 연쇄 모형을 활용하여

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Type
Academic journal
Author
Journal
The Economic Geographical Society Of Korea 한국경제지리학회지 한국경제지리학회지 제22권 제3호 KCI Accredited Journals
Published
2019.1
Pages
351 - 365 (15page)

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A Markov Chain Model for Population Distribution Prediction Considering Spatio-Temporal Characteristics by Migration Factors
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This study aims to predict the changes in population distribution in Korea by considering spatio- temporal characteristics of major migration reasons. For the purpose, we analyze the spatio-temporal characteristics of each major migration reason(such as job, family, housing, and education) and estimate the transition probability, respectively. By appling Markov chain model processes with the Chapman- Kolmogorov equation based on the transition probability, we predict the changes in the population distribution for the next six years. As the results, we found that there were differences of population changes by regions, while there were geographic movements into metropolitan areas and cities in general. The methodologies and the results presented in this study can be utilized for the provision of customized planning policies. In the long run, it can be used as a basis for planning and enforcing regionally tailored policies that strengthen inflow factors and improve outflow factors based on the trends of population inflow and outflow by region by movement factors as well as identify the patterns of population inflow and outflow in each region and predict future population volatility.

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