Estimating the intergenerational elasticity and rank association in the US : overcoming the current limitations of tax data

Ideal estimates of the intergenerational elasticity (IGE) in income require a large panel of income data covering the entire working lifetimes for two generations. Previous studies have demonstrated that using short panels and covering only certain portions of the lifecycle can lead to considerable bias. A recent influential study by Chetty et al (2014) using tax data estimates the IGE in family income for the entire U.S. to be 0.344, considerably lower than most previous estimates. Despite the seeming advantages of extremely large samples of administrative tax data, I demonstrate that the age structure and limited panel dimension of the data used by Chetty et al leads to considerable downward bias in estimating the IGE. Specifically I use PSID samples that overcome the data limitations in the tax data to estimate the IGE when using long time averages centered around age 40 in both generations. I demonstrate how imposing the data limitations in Chetty et al (2014) lead to considerable downward bias relative to these preferred estimates. I further demonstrate that the sensitivity checks in Chetty et al regarding the age at which children's income is measured and the length of the time average of parent income used to estimate the IGE are also flawed due to these data limitations. The lack of robustness of the IGE to the treatment of years of zero earnings among children found by Chetty et al is also largely due to data limitations. Estimates of the rank-rank slope on the other hand are much less downward biased and tend to be more robust to the limitations of the tax data. Nevertheless, researchers should continue to use both the IGE and rank based measures depending on which concept of mobility they wish to address. Substantively, I find that the IGE in family income in the U.S. is likely greater than 0.6 and that the rank-rank slope is 0.4 or higher.