Survey mode effects on measured income inequality
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We study the effect of interview modes on estimates of economic inequality which are based on survey data. We exploit variation in interview modes in the Austrian EU-SILC panel, where between 2007 and 2008 the interview mode was switched from personal interviews to telephone interviews for some but not all participants. We combine methods from the program evaluation literature with methods from the distributional decomposition literature to obtain causal estimates of the effect of interview mode on estimated inequality. We find that the interview mode has a large effect on estimated inequality, where telephone interviews lead to a larger downward bias. The effect of the mode is much smaller for robust inequality measures such as interquantile ranges, as these are not sensitive to the tails of the distribution. The magnitude of effects we find are of a similar order as the differences in many international and intertemporal comparisons of inequality.
KeywordsIncome inequality Survey methodology Survey modes Distributional decompositions
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We would like to thank Markus Knell and Alyssa Schneebaum for valuable comments and discussion. Additional to the usual disclaimer, the opinions expressed in this work are those of the authors and do not necessarily reflect the ones of the OeNB or the Eurosystem.
- Angrist, J., Pischke, J.-S.: Mostly Harmless Econometrics. Princeton University Press, Princeton (2008)Google Scholar
- Atkeson, L.R., Adams, A.N., Alvarez, R.M.: Nonresponse and Mode Effects in Self- and Interviewer-Administered Surveys. Political Analysis (2014)Google Scholar
- de Leeuw, E.D.: Data Quality in Mail, Telephone and Face to Face Surveys. TT-Publikaties, Amsterdam (1992)Google Scholar
- Dillman, D.A., Smyth, J.D., Christian, L.M.: Internet, Phone, Mail, and Mixed-Mode Surveys: the Tailored Design Method. Wiley, New York (2014)Google Scholar
- Huber, P.J.: Robust Statistics. Wiley Series in Probability and Statistics. Wiley, New York (2003)Google Scholar
- Iacus, S.M., King, G., Porro, G.: Matching for Causal Inference without Balance Checking. Working paper series, Harvard (2008)Google Scholar
- Klausch, T., Hox, J.J., Schouten, B.: Assessing the Mode-Dependency of Sample Selectivity Across the Survey Response Process. Technical Report 2013-03, Statistics Netherlands (2013a)Google Scholar
- OECD: Divided We Stand - Why Inequality Keeps Rising (2011)Google Scholar
- Statistik Austria: Standard Dokumentation Metainformationen - Definitionen, Erlaeuterungen, Methoden, Qualitaet (2010)Google Scholar