The Informational Content of Surnames, the Evolution of Intergenerational Mobility, and Assortative Mating

• 成果类型: Article
• 署名作者: Gueell, Maia; Rodriguez Mora, Jose V.; Telmer, Christopher I.
• 署名单位: University of Edinburgh; Centre for Economic Policy Research - UK; University of Edinburgh; Centre for Economic Policy Research - UK; Carnegie Mellon University
• 刊物名称: REVIEW OF ECONOMIC STUDIES
• ISSN/ISSBN: 0034-6527
• DOI: 10.1093/restud/rdu041
• 发表日期: 2015
• 页码: 693-735
• 关键词: income mobility; sibling correlations; economic-status; UNITED-STATES; earnings; FAMILY; sweden; transmission; INEQUALITY; brothers

摘要

We propose a new methodology for measuring intergenerational mobility in economic well-being. Our method is based on the joint distribution of surnames and economic outcomes. It circumvents the need for intergenerational panel data, a long-standing stumbling block for understanding mobility. It does so by using cross-sectional data alongside a calibrated structural model to recover the traditional intergenerational elasticity measures. Our main idea is simple. If inheritance is important for economic outcomes, then rare surnames should predict economic outcomes in the cross-section. This is because rare surnames are indicative of familial linkages. If the number of rare surnames is small this approach will not work. However, rare surnames are abundant in the highly skewed nature of surname distributions from most Western societies. We develop a model that articulates this idea and shows that the more important is inheritance, the more informative will be surnames. This result is robust to a variety of different assumptions about fertility and mating. We apply our method using the 2001 census from Catalonia, a large region of Spain. We use educational attainment as a proxy for overall economic well-being. A calibration exercise results in an estimate of the intergenerational correlation of educational attainment of 0.60. We also find evidence suggesting that mobility has decreased among the different generations of the 20th century. A complementary analysis based on sibling correlations confirms our results and provides a robustness check on our method. Our model and our data allow us to examine one possible explanation for the observed decrease in mobility. We find that the degree of assortative mating has increased over time. Overall, we argue that our method has promise because it can tap the vast mines of census data that are available in a heretofore unexploited manner.