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How Reliable Are Income Data Collected with a Single Question?

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Author Info
John Micklewright () (S3RI, University of Southampton and IZA)
Sylke V. Schnepf () (S3RI, University of Southampton and IZA)

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Abstract

Income is an important correlate for numerous phenomena in the social sciences. But many surveys collect data with just a single question covering all forms of income. This raises issues of quality, and these are heightened when individuals are asked about the household total rather than own income alone. Data are typically banded, implying a loss of information. We investigate the reliability of ‘single-question’ data using the ONS Omnibus and British Social Attitudes (BSA) surveys as examples. We first compare the distributions of income in these surveys - individual income in the Omnibus and household income in the BSA - with those in two other much larger UK surveys that measure income in much greater detail. Second, we investigate an implication of restricting the single question to individual income and interviewing only one adult per household: total income in respondents’ households is unobserved. We therefore examine the relationship between individual and household income in one of the comparator surveys. Third, after imposing bands on comparator survey data, we measure the information loss from banding with Generalised Entropy indices. We then assess its impact on the use of income as a covariate. Disaggregation by gender proves fruitful in much of the analysis.

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Publisher Info
Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 3177.

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Length: 33 pages
Date of creation: Nov 2007
Date of revision:
Handle: RePEc:iza:izadps:dp3177

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Related research
Keywords: income data; banding; information loss; Omnibus survey; British Social Attitudes survey;

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Find related papers by JEL classification:
D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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