Measuring Inequality Using Censored Data: A Multiple Imputation Approach

For assessing trends in the inequality of earnings or of household income inequality in the U.S.A., the March Current Population Survey (CPS) is the premier survey data source, widely used both within and outside government. The CPS is, however, subject to an important limitation: the data are right censored (‘topcoded’). To maximize confidentiality and to minimize disclosure risk, income values for any of the 24 income sources in internal CPS data that are above their source-specific threshold are replaced in the public use data files by the threshold itself (the ‘topcode’). Thus, for example, if someone reports wage and salary earnings of a million dollars, the value researchers will see in their data set is not one million dollars, but a lower value (the topcode). Furthermore, even the internal CPS data, used by the U.S. Census Bureau to produce official income distribution statistics, are topcoded for the same reasons, albeit to a substantially lesser degree than the public use data. Topcoded data cause problems for inequality analysis because they censor the range of incomes that are observed. Inequality is underestimated because very high incomes appear as less high incomes. This problem would be less of an issue when one is looking at inequality trends over time if the nature and extent of top coding were constant. However, CPS topcodes have changed over time in