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一种分析居民流动性反向复发时间数据的方法。

A method for analyzing backward recurrence time data on residential mobility.

作者信息

Baydar N, White M

出版信息

Sociol Methodol. 1988;18:105-35.

Abstract

Data on duration of current residence are used to estimate models of duration-dependent residential mobility rates. "We use the theory of backward recurrence times in renewal processes to infer the hazard rate of residential mobility from the density of the duration of current residence. We demonstrate that the inferences made using the asymptotic solution of the density of the backward recurrence times will be severely biased if the renewal process has not reached stability. We present an unbiased finite time solution and estimate univariate and multivariate models of residential mobility rates using 1980 U.S. census data on duration of current residence. These models include mover-stayer models represented by mixture densities. The multivariate analysis shows that the most important covariates of residential mobility are age, homeownership, race, and presence of school-aged children."

摘要

当前居住时长的数据被用于估计与时长相关的居住流动性率模型。“我们运用更新过程中的反向重现时间理论,从当前居住时长的密度推断居住流动性的风险率。我们证明,如果更新过程尚未达到稳定状态,那么使用反向重现时间密度的渐近解所做的推断将存在严重偏差。我们提出了一个无偏有限时间解,并使用1980年美国人口普查中关于当前居住时长的数据,估计了居住流动性率的单变量和多变量模型。这些模型包括由混合密度表示的迁移者 - 定居者模型。多变量分析表明,居住流动性最重要的协变量是年龄、房屋所有权、种族以及学龄儿童的存在情况。”

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