  This paper reanalyzes Khanna (2023), which studies labor market effects of
schooling in India through regression discontinuity designs. Absent from the
data are four districts close to the discontinuity; restoring them cuts the
reduced-form impacts on schooling and log wages by 57% and 63%. Using
regression-specific optimal band-widths and a robust variance estimator
clustered at the geographic unit of treatment makes impacts statistically
indistinguishable from 0. That finding is robust to varying the identifying
threshold and the bandwidth. The estimates of general equilibrium effects and
elasticities of substitution are not unbiased and have effectively infinite
first and second moments.
