NBER Working Papers · 2026 · Kirill Borusyak、Rafael Dix-Carneiro、Brian K. Kovak
中文摘要
一种常用的迁移回归将人口变化与本地劳动力需求冲击相联系,尽管这类冲击对劳动力市场结果的影响相当可观,所得系数却往往较小或统计不显著。我们认为,此类发现未必意味着劳动力流动对本地经济状况没有反应。相反,传统的迁移回归可能存在偏误,因为它们未能反映工人如何在相互竞争的区位之间进行选择。在一个简洁的均衡模型中,本地人口增长取决于本地冲击与相关目的地冲击之间的差异;当这些冲击相互关联时,估计出的反应会被衰减。此外,当冲击处于行业层面时,标准的移动份额(shift-share)度量会错误刻画各地区所受的有效暴露,从而导致进一步的衰减。基于巴西和德国行政数据的模拟实验表明,衰减幅度可超过50%,且传统回归估计可能高度不精确。我们提出了基于理论的实证方法,这些方法能够校正上述偏误、给出具有清晰结构性解释的估计,并提高所估计的流动反应的精确度。
Abstract
A commonly used migration regression relates population changes to local labor demand shocks, often yielding small or statistically insignificant coefficients despite sizable effects on labor market outcomes. We argue that such findings need not imply that mobility is unresponsive to local economic conditions. Rather, conventional migration regressions can be biased, as they do not reflect how workers choose among competing locations. In a parsimonious equilibrium model, local population growth depends on differences between local shocks and those in relevant destinations; when these shocks are correlated, estimated responses are attenuated. Moreover, with industry-level shocks, standard shift-share measures misrepresent locations’ effective exposure, leading to further attenuation. Using simulation experiments based on Brazilian and German administrative data, we show attenuation can exceed 50% and that conventional regression estimates can be highly imprecise. We propose theory-grounded empirical approaches that correct the biases, deliver estimates with a clear structural interpretation, and improve the precision of estimated mobility responses.