生育率
内生性
公共住房
出租
出租房屋
房屋保有权
人口经济学
背景(考古学)
经济
测量数据收集
业务
劳动经济学
经济增长
人口
政治学
人口学
社会学
地理
统计
数学
考古
法学
计量经济学
作者
Haitao Du,Eddie C.M. Hui,Lin Chen
出处
期刊:Cities
[Elsevier]
日期:2024-01-01
卷期号:144: 104643-104643
被引量:2
标识
DOI:10.1016/j.cities.2023.104643
摘要
In the context of declining fertility rates and worsening housing affordability for low-and moderate-income families, many scholars have paid closer attention to the effect of housing on the fertility preferences of vulnerable groups. However, existing studies on the association between housing and fertility are rooted in the private rental or buying housing market. The existing literature on the link between public rental housing sectors and fertility intentions has been surprisingly silent. Furthermore, despite the fact that previous studies have investigated how housing outcomes (housing conditions and housing tenure) reshape fertility intentions, to date, how fertility intentions are influenced by perceptions of housing situations is rarely examined, particularly perceptions of housing stability. More importantly, most previous literature estimating the effects of housing on fertility intentions has ignored the endogeneity issue between housing and fertility intentions, which may result in a biased estimate. Using 2022 public rental housing survey data in Guangzhou, we employ the instrumental variable approach to address the potential endogeneity issue of our equations and investigate whether perceptions of housing stability can encourage fertility intentions of public housing renters. The findings reveal that self-reported perceptions of housing stability are positively and significantly associated with the fertility intentions of public housing renters. Moreover, the housing stability effect is larger for the male and unmarried cohorts. These findings warrant policy consideration as to how public rental housing increases a sense of housing stability for tenants, thereby protecting and supporting their fundamental fertility rights.
科研通智能强力驱动
Strongly Powered by AbleSci AI