Income Data for Policy Analysis: A Comparative Assessment of Eight Surveys. INCOME ALLOCATION, APPROXIMATION AND ROUNDING


Two ways in which respondents can diminish the effectiveness of even very well designed income questions are by providing no answers at all or, which may be worse, inaccurate answers. It is well known that income questions generate some of the highest item non-response rates in surveys generally.55 Frequently, this results in large amounts of missing income data. Unless the data producers choose to leave such missing data for their users to address, they must apply one or more methods of allocation to fill in the missing data.56 When the data producers elect to allocate their missing income data, high rates of non-response are likely to mean that large fractions of the income data that they provide to their users will have been created by the data producers rather than supplied by their respondents. This makes the quality of the income data dependent not just on the completeness and accuracy of the reported amounts but the quality of the methods used to generate allocated amounts.57

We can quantify the amount of income data that are allocated in a survey and, in so doing, measure the magnitude of non-response and its potential impact on data quality. Income allocation is the principal focus of this chapter. We examine, in successive sections, the overall frequency of income allocation across the five general population surveys, the methods of allocation used, differences in allocation across the income distribution and by source, differences by interview month, and issues in using allocation.

We cannot assess in any direct way the accuracy of survey responses to income questions. However, one way in which respondents may reduce the accuracy of their responses is to use a high level of approximation—for example, by reporting a salary of $50,000 when the true salary lies somewhere between $45,000 and $55,000. When a significant number of respondents round their responses in this way, it distorts the distribution by creating spikes at the rounded values. In fact, rounding is a commonly used technique for protecting the confidentiality of income data in public use files.58 The frequency of round responses can be quantified, and we do so for selected income sources for the five general population surveys and the PSID in the next to last section of the chapter.

Rounding does not lead to bias, but underreporting among persons who provide dollar amounts is evident from comparisons of survey aggregates and administrative totals. While allocation is widely used to compensate for non-response, underreporting is less amenable to correction because individual underreported amounts cannot be identified without additional information—such as linked administrative records.  Some agencies substitute their own administrative records for reported data, but, in general, such data cannot be released to outside users.  Other than noting such practice, we do not assess the use or effectiveness of strategies to compensate for underreporting of dollar amounts among respondents who report both recipiency and income for a given source.

After presenting our findings on rounding we discuss two issues regarding the application of allocation that have emerged from our analysis of income data. All of our estimates in this chapter are based on income for 2002, which, as we have noted, covers a calendar year except for the rolling reference period in ACS.

View full report


"report.pdf" (pdf, 4.33Mb)

Note: Documents in PDF format require the Adobe Acrobat Reader®. If you experience problems with PDF documents, please download the latest version of the Reader®