Articles

1. von Hippel, P.T., Hunter, D.J., & †Drown, M. (2017). “Better estimates from binned incomes: Interpolated CDFs and mean-matching.” Sociological Science 4, 641-655.
2. von Hippel, P.T., Scarpino, S.V., & Holas, I. (2016). “Robust estimation of inequality from binned incomes.” Sociological Methodology 46(1), 212-251. Also available as arXiv e-print 1402.4061.

Software

1. The binsmooth package for R estimates statistics from binned incomes by matching the empirical CDF and (if known) the mean. The resulting estimates are better than those from other methods (von Hippel, Hunter, & Drown, 2017).
   • Hunter, D.J. & Drown, M. (2017). “The binsmooth package for R.”
2. The rpme and mgbe commands for Stata estimate statistics from binned incomes using the robust Pareto midpoint estimator (RPME), which assigns incomes to their bin midpoints, and the multimodel generalized beta estimator (MGBE), which fits continuous distributions from the generalized beta family (von Hippel, Scarpino, & Holas, 2016). The MGBE method is also implemented in the binequality package for R.
   • von Hippel, P.T. & Powers, D.E. (2015). “The rpme command for Stata.”
   • Duan, Y., & von Hippel, P.T. (2016). “The mgbe command for Stata.”
   • Scarpino, S., von Hippel, P.T., & Holas, I. (2014). “The binequality package for R.”