In recent work, Gregory Clark and coauthors argue that rates of social mobility are constant across countries and generally much lower than traditionally estimated. The main explanation is that traditional estimates of intergenerational persistence are heavily attenuated because they use only one proxy measure (e.g., earnings) of underlying status. We examine this hypothesis within a suitable latent-variable framework, incorporating multiple proxy measures into a single "least-attenuated" estimate of persistence in latent status. With rich administrative data for Sweden, we exploit detailed proxy measures to test this proposition, and also conduct a Sweden-U.S. comparison. We find no evidence of substantial bias in prior estimates, or that the Sweden-U.S. difference in persistence is smaller than found in previous research. We further explore the concept of family status by incorporating mothers, thereby also contributing to the literature on intergenerational transmission for women. We find that while mothers' income is a poor proxy for status, incorporating information on mothers' occupation improves the ability to capture transmission from mothers to both sons and daughters.

Recent work by Gregory Clark and co-authors uses a new surnames approach to examine intergenerational mobility, finding much higher persistence rates than traditionally estimated. Clark proposes a model of social mobility to explain the diverging estimates, including the crucial but untested hypothesis that traditional estimates of intergenerational persistence are biased downward because they use only one measure (e.g. earnings) of underlying status. I test for evidence of this using an approach from Lubotsky and Wittenberg (2006), incorporating information from multiple measures into an estimate of intergenerational persistence with the least attenuation bias. Contrary to Clark's prediction, I do not find evidence of substantial bias in prior estimates. . et al. (2007) is an oft cited recent example providing intergenerational correlation and regression coefficients in educational attainment for 42 countries; Bj€ orklund and Salvanes (2011) also provide a succinct review of related literature. Additionally, another subset of the literature is concerned with intergenerational persistence in occupation or occupational prestige. Hodge (1966) is an early example studying intergenerational occupational mobility in the US, while Ferrie (2007, 2013) are more recent examples; see also Black and Devereux (2011) for a brief discussion of related studies.3 See Clark (2014) for a comprehensive list of these studies, as well as the more recent papers and . 4 For the data sources containing explicit socio-economic measures, such as probated wealth at death, (1) is estimated using the group averages of wealth for rare surnames. For data without such measures, the approach instead looks at persistence in the representation of the rare surname in an 'elite' group relative to representation in the population as a whole. 5 G€ uell et al. (2015) show that rare surnames do contain such information, and propose a method using the joint distribution of surnames and economic status to explore intergenerational transmission of status in Spain.

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Intergenerational persistence estimates are susceptible to several well-documented biases arising from income measurement, and it has become standard practice to construct income measures to mitigate these. However, remaining bias can lead to a spurious grandparent coefficient estimate in multigenerational regressions, a recent focus of the mobility literature. We show with theory and simulations that even using a 30-year income average can result in a small positive spurious grandfather coefficient estimate. We further propose an IV approach, showing that it is not susceptible to this spillover bias in simplified settings and that it can provide bounds on the parameters in a more general scenario. With administrative data from Norway, we reveal a positive spillover bias in the grandfather coefficient estimates, and the combined evidence from our OLS and IV approaches suggest the preferred small positive OLS estimate could still be upward biased.

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