中国的就业前景和劳动力流动
Job Prospects and Labour Mobility in China
摘要：
中国的结构性变化对其区域就业结构带来了新的挑战，需要进行劳动力再分配。目前，我国对人口迁移决策的前瞻性研究和对地级市层面的双向纵向影响因素的研究几乎是空白。本文考察了基于行业的就业前景对个人跨县迁移决策的影响。为此，我们为就业前景创建了一个代理变量，编制了一个由1997- 2017年期间来自283个城市的66，427人组成的独特准面板，在顺序设置中将参考依赖引入到移民的随机效用最大化模型中，推导出具有理论微观基础的经验规范，并应用各种一元和二元固定效应来解决对移徙的多边阻力。采用多水平logit模型和两步系统GMM估计进行稳健性检验。我们的主要发现是，在目的地城市和原籍城市中，基于部门的就业前景比率每增加10%，迁移概率就会增加1.281- 2.185个百分点，并且比率的规模越大，效果越明显。拥有一个家庭移徙网络会使移徙概率增加约6个百分点。此外，劳工移民更可能是男性、未婚、年轻或受过更多教育。我们的研究结果表明，中国正在进行的工业改革影响了城市之间的劳动力流动，为区域政策制定者防止人才流失和吸引相关人才提供了重要的见解。
英文摘要：
China's structural changes have brought new challenges to its regional employment structures, entailing labour redistribution. By now Chinese research on migration decisions with a forward-looking stand and on bilateral longitudinal determinants at the prefecture city level is almost non-existent. This paper investigates the effects of sector-based job prospects on individual migration decisions across prefecture boundaries. To this end, we created a proxy variable for job prospects, compiled a unique quasi-panel of 66,427 individuals from 283 cities during 1997--2017, introduced reference-dependence to the random utility maximisation model of migration in a sequential setting, derived empirical specifications with theoretical micro-foundations, and applied various monadic and dyadic fixed effects to address multilateral resistance to migration. Multilevel logit models and two-step system GMM estimation were adopted for the robustness check. Our primary findings are that a 10% increase in the ratio of sector-based job prospects in cities of destination to cities of origin raises the probability of migration by 1.281--2.185 percentage points, and the effects tend to be stronger when the scale of the ratio is larger. Having a family migration network causes an increase of approximately 6 percentage points in migratory probabilities. Further, labour migrants are more likely to be male, unmarried, younger, or more educated. Our results suggest that the ongoing industrial reform in China influences labour mobility between cities, providing important insights for regional policymakers to prevent brain drain and to attract relevant talent.
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