Mitnik, Pablo. 2017.
“Estimators of the Intergenerational Elasticity of Expected Income: A
Tutorial.” Stanford Center on Poverty and Inequality Working Paper. Updated September 2018.

**Abstract**

The
intergenerational income elasticity (IGE) conventionally estimated in the
mobility literature has been widely misinterpreted as pertaining to the
conditional expectation of children’s income, when in fact it pertains to its
conditional geometric mean. In line with recent work, this article focuses on
the estimation of the IGE of expected income. It proposes that, in the
one-sample context, estimation of this IGE be based on the Poisson Pseudo
Maximum Likelihood estimator, or on a Generalized Method of Moments (GMM)
instrumental variable estimator of the Poisson or exponential regression model,
depending on the parental information available. These estimators can also be
used together to generate a set estimate of the IGE of the expectation. In the
two-sample context, the article proposes that estimation be based on a recently
advanced two-sample GMM estimator of the exponential regression model. The
article explains how to use official Stata commands to estimate the IGE of the
expectation with the first two estimators, and how to construct confidence
intervals for the partially identified IGE when their estimates are combined to
generate a set estimate. It also explains how to use the user-written Stata
command **igetwos**** **to estimate the IGE of the expectation
with the third estimator in the two-sample context.