Jang Joy Bohyun, Casterline John B, Snyder Anastasia
University of Michigan, 2345 ISR 426 Thompson, Ann Arbor, MI 48104,
Ohio State University, 60 Townshend Hall, 1885 Neil Ave Mall Columbus, OH 43210
Demogr Res. 2014 Jan-Jun;30:1339-1366. doi: 10.4054/DemRes.2014.30.47. Epub 2014 Apr 30.
Previous research on inter-relations between migration and marriage has relied on overly simplistic assumptions about the structure of dependency between the two events. However, there is good reason to posit that each of the two transitions has an impact on the likelihood of the other, and that unobserved common factors may affect both migration and marriage, leading to a distorted impression of the causal impact of one on the other.
We will investigate relationships between migration and marriage in the United States using data from the National Longitudinal Survey of Youth 1979. We allow for inter-dependency between the two events and examine whether unobserved common factors affect the estimates of both migration and marriage.
We estimate a multi-process model in which migration and marriage are considered simultaneously in regression analysis and there is allowance for correlation between disturbances; the latter feature accounts for possible endogeneity between shared unobserved determinants. The model also includes random effects for persons, exploiting the fact that many people experience both events multiple times throughout their lives.
Unobserved factors appear to significantly influence both migration and marriage, resulting in upward bias in estimates of the effects of each on the other when these shared common factors are not accounted for. Estimates from the multi-process model indicate that marriage significantly increases the hazard of migration while migration does not affect the hazard of marriage.
Omitting inter-dependency between life course events can lead to a mistaken impression of the direct effects of certain features of each event on the other.
先前关于移民与婚姻之间相互关系的研究,依赖于对这两个事件之间依存结构过于简单化的假设。然而,有充分理由假定,这两个转变中的每一个都会对另一个的可能性产生影响,并且未被观察到的共同因素可能会影响移民和婚姻两者,从而导致对其中一个对另一个的因果影响产生扭曲的印象。
我们将使用1979年全国青年纵向调查的数据,研究美国移民与婚姻之间的关系。我们考虑这两个事件之间的相互依存性,并检验未被观察到的共同因素是否会影响移民和婚姻的估计。
我们估计一个多过程模型,在回归分析中同时考虑移民和婚姻,并允许扰动项之间存在相关性;后一特征考虑了共享未被观察到的决定因素之间可能存在的内生性。该模型还包括个体的随机效应,利用了许多人在其一生中多次经历这两个事件这一事实。
未被观察到的因素似乎对移民和婚姻都有显著影响,当不考虑这些共享的共同因素时,会导致对彼此影响的估计出现向上偏差。多过程模型的估计表明,婚姻显著增加了移民的风险,而移民并不影响结婚的风险。
忽略生命历程事件之间的相互依存性,可能会导致对每个事件的某些特征对另一个事件的直接影响产生错误印象。