A Nonparametric Nonclassical Measurement Error Approach to Estimating Intergenerational Mobility Elasticities

Yonghong An, Le Wang and Ruli Xiao

Journal of Business & Economic Statistics, 2022, vol. 40, issue 1, 169-185

Abstract: This article provides a framework for estimating intergenerational mobility elasticities (IGEs) of children’s income with respect to parental income. We allow the IGEs to be heterogeneous, by leaving the relationship of parental and child incomes unspecified, while acknowledging and addressing the latent nature of both child and parental permanent incomes and the resulted life-cycle bias. Our framework enables us to test the widely imposed assumption that the intergenerational mobility function is linear. Applying our method to the Panel Studies of Income Dynamics data, we decisively reject the commonly imposed linearity assumption and find substantial heterogeneity in the IGEs across the population. We confirm an important finding that the IGEs with respect to parental income exhibit a U-shape pattern, which is occasionally highlighted in the analysis using transition matrices. Specifically, there is a considerable degree of mobility among the broadly defined middle class, but the children of both high- and low-income parents are more likely to be high- and low-income adults, respectively. This result also provides insights into the (intertemporal) Great Gatsby curve, suggesting that a higher level of inequality within one generation may lead to a higher level of social immobility in the next generation in the United States.

Date: 2022
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DOI: 10.1080/07350015.2020.1787176

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