In the new CAMP Working Paper 03/2024, Chang, Durlauf, Hu and Park propose a fully nonparametric model to investigate the dynamics of intergenerational income mobility. In their model, an individual’s income class probabilities depend on parental income in a manner that accommodates nonlinearities and interactions among various individual characteristics and parental characteristics, including race, education, and parental age at childbearing. Consequently, the authors offer a generalization of Markov chain mobility models. They employ kernel techniques from machine learning and further regularization for estimating this highly flexible model. Utilizing data from the Panel Study of Income Dynamics (PSID), they find that race and parental education play significant roles in determining the influence of parental income on children’s economic prospects.
CENTRE FOR APPLIED MACROECONOMICS AND COMMODITY PRICES (CAMP) 