The Retirement Migration Puzzle in China

Chen, Simiao; Jin, Zhangfeng; Prettner, Klaus

doi:10.2139/ssrn.3526088

Cited by 4 publications

(2 citation statements)

References 39 publications

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“…We adopt a FRD design as our identification strategy. Specifically, we follow previous literature (Chen et al., 2020a, 2020b, 2021; Li et al., 2015; Zang, 2020; Zhang et al., 2018; Zhao et al., 2022) and exploit the exogenous changes in parental retirement likelihood caused by China's statutory retirement requirement (SRA = 60 for men and SRA = 50 for women) to identify the causal effect of parental retirement on adult children's health outcomes.…”

Section: Empirical Strategy: Fuzzy Regression Discontinuity Designmentioning

confidence: 99%

The effects of parental retirement on adult children's health: Evidence from China

Hao,

Cheng,

Bärnighausen

et al. 2023

Health Economics

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Using representative data from China, we examine the causal effects of parental retirement on the health of adult children. To do so, we adopt a fuzzy regression discontinuity design and exploit the mandatory retirement ages in China as cut‐off points. We find no evidence that parental retirement has significant effects on the mental health, healthcare utilization, or risky health behaviors of adult children. However, paternal retirement and maternal retirement have different effects on adult children's Self‐reported health (SRH). Paternal retirement has a significantly negative effect only on the SRH of sons, while maternal retirement does not induce such effects. Potential mechanisms of intergenerational transfer through which parental retirement might affect adult children's health are also explored.

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Section: Empirical Strategy: Fuzzy Regression Discontinuity Designmentioning

confidence: 99%

The effects of parental retirement on adult children's health: Evidence from China

Hao,

Cheng,

Bärnighausen

et al. 2023

Health Economics

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“…A substantial literature has studied the determinants of migration decisions. These studies have found factors such as income prospects, financial constraints, social networks and risk sharing are important for migration decisions (Kennan and Walker 2011;Angelucci 2015;Munshi 2003;Munshi and Rosenzweig 2016;Morten 2019;Dustmann and Okatenko 2014;Chen, Jin, and Prettner 2020). However, the impact of welfare benefits on migration decisions is far from clear cut.…”

Section: Introductionmentioning

confidence: 99%

Welfare Magnets and Internal Migration in China

Jin

Zhang

2020

SSRN Journal

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This study examines the causal effects of welfare benefits on internal migration decisions. Using a quasi-experimental migration reform across 283 Chinese cities from 2002 to 2015, combined with a difference-indifferences setup, I show that improved welfare benefits substantially increase migration. The observed impact is more pronounced for individuals such as the young, women and medium-low-skilled workers. It is relatively smaller in destinations exposed to larger positive demand shocks, suggesting that improved welfare benefits reduce migration costs. And it persists over the long term. All these findings confirm the existence of sizable welfare magnet effects.

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