  I measure the uncertainty affecting estimates of economic inequality in the
US and investigate how accounting for properly estimated standard errors can
affect the results of empirical and structural macroeconomic studies. In my
analysis, I rely upon two data sets: the Survey of Consumer Finances (SCF),
which is a triennial survey of household financial condition, and the
Individual Tax Model Public Use File (PUF), an annual sample of individual
income tax returns. While focusing on the six income and wealth shares of the
top 10 to the top 0.01 percent between 1988 and 2018, my results suggest that
ignoring uncertainties in estimated wealth and income shares can lead to
erroneous conclusions about the current state of the economy and, therefore,
lead to inaccurate predictions and ineffective policy recommendations. My
analysis suggests that for the six top-decile income shares under
consideration, the PUF estimates are considerably better than those constructed
using the SCF; for wealth shares of the top 10 to the top 0.5 percent, the SCF
estimates appear to be more reliable than the PUF estimates; finally, for the
two most granular wealth shares, the top 0.1 and 0.01 percent, both data sets
present non-trivial challenges that cannot be readily addressed.
