REDI for Binned Data: A Random Empirical Distribution Imputation method for estimating continuous incomes

Abstract

Researchers often need to work with categorical income data. While the typical nonparametric (including midpoint) and parametric estimation methods used to estimate summary statistics both have advantages, they all carry assumptions which cause them to deviate in important ways from real world distributions of income. The method introduced here, Random Empirical Distribution Imputation (REDI), imputes discrete observations using binned income data, while also calcu- lating summary statistics. REDI achieves this through random cold-deck imputation from a real world reference dataset (here, the Current Population Survey ASEC). This imputation method reconciles bins between datasets or across years and handles top incomes. REDI has other ad- vantages of computing an income distribution that is nonparametric, bin consistent, area- and variance-preserving, continuous, and computationally fast. I provide proof of concept using two years of the American Community Survey.

Predictors of First-Grade Teachers’ Teaching-Related Time During COVID-19

“…Teachers reported total teaching time allocated each day to remote teaching across live synchronous instruction, prerecording instruction, planning for remote teaching, and responding to student and parent questions. Response options were: (1) “I did not do this activity”; (2) “at least once per week, but not daily”; (3) “0–0.5 hours”; (4) “0.5–1 hours”; (5) “1–2 hours”; (6) “2–4 hours”; and (7) “4–6 hours.” Categorical responses were transformed into continuous minutes by imputing a random value in the respondent’s reported categorical range, a standard practice (see King, 2020). We examined the distribution of responses across categories; because the raw categories are not skewed, when we converted these categorical responses to continuous minutes, they retain their normality and have similar properties with most teachers reporting 1 to 2 hours of time spent across all teaching/teaching-related activities.…”