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标题：Intergenerational Mobility and the Informative Content of Surnames
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作者：Maia Güell ; José V. Rodríguez Mora ; Chris Telmer 等
期刊名称：CEP Discussion Paper
出版年度：2007
卷号：2007
期号：jul
出版社：Centre for Economic Performance
摘要：We propose an alternative method for measuring intergenerational mobility. Traditional methods based on panel data provide measurements that are scarce, difficult to compare across countries and almost impossible to get across time. In particular this means that we do not know how intergenerational mobility is correlated with growth, income or the degree of inequality. Our proposal is to measure the informative content of surnames in one census. The more information does the surname have on the income of an individual, the more important is background in determining outcomes; and thus, the less mobility there is. The reason for this is that surnames inform on family relationships because the distribution of surnames is necessarily much skewed. A large percentage of the population is bound to have a very unfrequent surname. For them the partition generated by surnames is very informative on family linkages. First, we develop a model whose endogenous variable is the joint distribution of surnames and income. Then we explore the relationship between mobility and the informative content of surnames. We allow for assortative mating to be a determinant of both. Then, we use our methodology to show that in a large Spanish region the informative content of surnames is large and consistent with the model. We also show that it has increased over time, indicating a substantial drop in the degree of mobility. Finally, using the peculiarities of the Spanish surname convention we show that the degree of assortative mating has also increased over time, in such a manner that might explain the decrease in mobility observed. Our method allows us to provide measures of mobility comparable across time. It should also allow us to study other issues related to inheritance.
关键词：inheritance, birth-death processes, cross-sectional data, population genetics