Educational and gender heterogeneity of the rural-urban earnings premium: New evidence from Norway

IF 3.5 2区 经济学 Q1 ECONOMICS Regional Science and Urban Economics Pub Date : 2024-03-01 DOI:10.1016/j.regsciurbeco.2024.103989
George C. Galster , Liv Osland
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Abstract

We explore urban earnings premiums for young, native, rural-to-urban movers in Norway. Using an augmented difference-in-differences estimator (DiD-TR) on microdata we challenge previous claims about urban earnings premium's size and sources. Conventional econometric estimators understate the static premium and overstate dynamic premiums. We find that migrants exhibit lower mean but faster pre-move earnings growth than non-migrants. Post-move, the static earnings premium dominates. The observed trajectory is related to frequent pre-move changes of industrial sector, presumably to obtain better job-worker matches. Post-move, these changes occur less frequently. Highly educated females exhibit largest static premiums (34%), less-educated females least (24%), males an intermediate amount. Our findings suggest that cities primarily generate earnings premiums through agglomeration-based efficiencies and superior job-worker matches varying heterogeneously by education and gender.

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城乡收入溢价的教育和性别异质性:挪威的新证据
我们探讨了挪威农村向城市迁移的年轻本地人的城市收入溢价。通过使用微观数据的增强差分估算器(DiD-TR),我们对以往有关城市收入溢价的规模和来源的说法提出了质疑。传统的计量经济学估算低估了静态溢价,高估了动态溢价。我们发现,与非移民相比,移民在搬迁前的平均收入增长较低,但增长较快。迁移后,静态收入溢价占主导地位。观察到的轨迹与迁移前频繁更换工业部门有关,这可能是为了获得更好的工作--工人匹配。流动后,这些变化发生的频率降低。受过高等教育的女性表现出最大的静态溢价(34%),受教育程度较低的女性最少(24%),男性介于两者之间。我们的研究结果表明,城市主要通过基于集聚的效率和优越的职工匹配产生收入溢价,这些溢价因教育程度和性别而异。
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来源期刊
CiteScore
5.30
自引率
9.70%
发文量
63
期刊介绍: Regional Science and Urban Economics facilitates and encourages high-quality scholarship on important issues in regional and urban economics. It publishes significant contributions that are theoretical or empirical, positive or normative. It solicits original papers with a spatial dimension that can be of interest to economists. Empirical papers studying causal mechanisms are expected to propose a convincing identification strategy.
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