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A comparison of earnings measures from longitudinal and cross‐sectional surveys: evidence from the UK

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  • Marco Francesconi
  • Holly Sutherland
  • Francesca Zantomio

Abstract

This paper compares earnings data from the BHPS with those collected in the FRS, contrasting two different points in time (1995/96 and 2003/04), allowing us to assess the possible extent of differential attrition in the BHPS data. We perform non-parametric tests of equality at the centre of the distributions and over the whole earnings distributions. We then apply multivariate regression methods to establish whether the earnings data yield different results in relation to three typical uses of earnings data. The two surveys have fairly similar earnings data in the first comparison year, while sizable differences emerge in the later comparison. This finding suggests the important role played by attrition and ‘vintage’ effects.
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  • Marco Francesconi & Holly Sutherland & Francesca Zantomio, 2011. "A comparison of earnings measures from longitudinal and cross‐sectional surveys: evidence from the UK," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(2), pages 297-326, April.
    • Handle: RePEc:bla:jorssa:v:174:y:2011:i:2:p:297-326
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    1. John Micklewright & Sylke V. Schnepf, 2010. "How reliable are income data collected with a single question?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(2), pages 409-429, April.
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    5. John Ermisch & Marco Francesconi, 2000. "Educational Choice, Families, and Young People's Earnings," Journal of Human Resources, University of Wisconsin Press, vol. 35(1), pages 143-176.
    6. Marco Francesconi, 2005. "An evaluation of the childhood family structure measures from the sixth wave of the British Household Panel Survey," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(3), pages 539-566, July.
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    Cited by:

    1. Bernard Fingleton & Simonetta Longhi, 2013. "The Effects Of Agglomeration On Wages: Evidence From The Micro-Level," Journal of Regional Science, Wiley Blackwell, vol. 53(3), pages 443-463, August.
    2. Serena Pattaro & Nick Bailey & Chris Dibben, 2020. "Using Linked Longitudinal Administrative Data to Identify Social Disadvantage," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 147(3), pages 865-895, February.
    3. Richard Blundell & Ben Etheridge, 2010. "Consumption, Income and Earnings Inequality in Britain," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 13(1), pages 76-102, January.
    4. Kirstine Hansen & Dylan Kneale, 2013. "Does How You Measure Income Make a Difference to Measuring Poverty? Evidence from the UK," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 110(3), pages 1119-1140, February.
    5. Crawford, Ron, 2009. "Variations in earnings growth: evidence from earnings transitions in the NZ Linked Income Survey," ISER Working Paper Series 2009-18, Institute for Social and Economic Research.
    6. Cappellari, Lorenzo & Jenkins, Stephen P., 2013. "Earnings and Labour Market Volatility in Britain," IZA Discussion Papers 7491, Institute of Labor Economics (IZA).

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