Binned income data

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. This R package 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).
  2. This Stata command estimates statistics from binned incomes using the robust Pareto midpoint estimator (RPME), which assigns incomes to their bin midpoints, except for the top bin, where it assigns incomes to the harmonic mean of a Pareto distribution (von Hippel, Scarpino, & Holas, 2016).
  3. The following software estimates statistics from binned incomes using the multimodel generalized beta estimator (MGBE), which fits continuous distributions from the generalized beta family (von Hippel, Scarpino, & Holas, 2016).