This paper shows that the frequency of migration can be best modeled by a zero-inflated Poisson process, because it takes into account the overwhelming presence of zeros (nonmigrants) in the data. A failure to do so can cause the coefficients to be biased and also result in poor prediction. The major finding is that by using a zero-inflated process, the performance of the model in predicting migration behavior is substantially improved. In addition, frequent movers tend to be white, nonunionized, and tend to have fewer children, less stable marriages, and more frequent occupational changes.
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Univ Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R ChinaUniv Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R China
Lim, Hwa Kyung
Li, Wai Keung
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Univ Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R ChinaUniv Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R China
Li, Wai Keung
Yu, Philip L. H.
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Univ Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R ChinaUniv Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R China
机构:
Korea Univ, Coll Med, Inst Human Genom Study, Ansan 425707, Kyunggi Do, South KoreaKorea Univ, Coll Med, Inst Human Genom Study, Ansan 425707, Kyunggi Do, South Korea
Lee, JungBok
Jung, Byoung Cheol
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Univ Seoul, Dept Stat, Seoul 130743, South KoreaKorea Univ, Coll Med, Inst Human Genom Study, Ansan 425707, Kyunggi Do, South Korea
Jung, Byoung Cheol
Jin, Seo Hoon
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Korea Univ, Dept Informat Stat, Younki Gun 339700, Chungnam, South KoreaKorea Univ, Coll Med, Inst Human Genom Study, Ansan 425707, Kyunggi Do, South Korea